added AI support for yaml/run

connpy/_version.py

@@ -1 +1 @@
-__version__ = "6.0.0"
+__version__ = "6.0.1"

connpy/ai.py

@@ -114,6 +114,7 @@ class ai:
         self.confirm_handler = confirm_handler or self._local_confirm_handler
         self.trusted_session = trust  # Trust mode for the entire session
         self.interrupted = False
+        self.one_shot = kwargs.get("one_shot", False)
 
         
         # 1. Cargar configuración genérica con herencia/merge global
@@ -285,10 +286,13 @@ class ai:
     @property
     def architect_system_prompt(self):
         """Build architect system prompt with plugin extensions."""
+        prompt = self._architect_base_prompt
+        if getattr(self, "one_shot", False):
+            prompt += "\n\nCRITICAL 1-SHOT DIAGNOSTICS DIRECTIVE:\nYou are running in a 1-shot offline diagnostics mode. There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately and directly to the user. Do not suggest or attempt to delegate/return control to the engineer."
         if self.architect_prompt_extensions:
             extensions = "\n".join(self.architect_prompt_extensions)
-            return self._architect_base_prompt + f"\n\nPlugin Capabilities:\n{extensions}"
-        return self._architect_base_prompt
+            return prompt + f"\n\nPlugin Capabilities:\n{extensions}"
+        return prompt
 
     def register_ai_tool(self, tool_definition, handler, target="engineer", engineer_prompt=None, architect_prompt=None, status_formatter=None):
         """Register an external tool for the AI system.
@@ -880,6 +884,8 @@ class ai:
             {"type": "function", "function": {"name": "return_to_engineer", "description": "Return control to the Engineer. Use this when your strategic analysis is complete and the Engineer should handle the rest of the conversation.", "parameters": {"type": "object", "properties": {"summary": {"type": "string", "description": "Brief summary of your analysis to hand over to the Engineer."}}, "required": ["summary"]}}},
             {"type": "function", "function": {"name": "manage_memory_tool", "description": "Saves information to long-term memory. MANDATORY: Only use this if the user explicitly asks to remember or save something.", "parameters": {"type": "object", "properties": {"content": {"type": "string"}, "action": {"type": "string", "enum": ["append", "replace"]}}, "required": ["content"]}}}
         ]
+        if getattr(self, "one_shot", False):
+            base_tools = [t for t in base_tools if t["function"]["name"] not in ("delegate_to_engineer", "return_to_engineer")]
         
         all_tools = base_tools + self.external_architect_tools
         seen_names = set()
@@ -1624,3 +1630,310 @@ Node: {node_name}"""
 
     @MethodHook
     def confirm(self, user_input): return True
+
+
+PLAYBOOK_BUILDER_SYSTEM_PROMPT = """
+You are a Connpy Playbook Builder Agent, a specialist in creating structured Connpy automation playbooks in YAML format.
+Your primary mission is to help the user build, refine, and validate playbooks.
+
+You MUST follow the Connpy canonical playbook format strictly:
+The playbook MUST always use the `tasks[]` array structure as the root key, where each task is sequential and independent.
+
+Connpy YAML Playbook Canonical Schema:
+---
+tasks:
+- name: "Task Description"
+  action: 'run' # Can be 'run' or 'test'. Mandatory.
+  nodes: # List of nodes filter or regular expressions to work on. Mandatory. Can be a string or array of strings. Supports regex (e.g. 'router.*@office' to match all routers in the 'office' folder).
+  - 'router1@office'
+  - 'router.*@office' # Regex filters are fully supported to match multiple nodes dynamically.
+  - '@aws'
+  commands: # List of CLI commands to execute. Mandatory.
+  - 'show version'
+  variables: # Key-value pairs for variables replacement in commands and expected. Optional.
+    __global__: # Global variables fallback. Optional.
+      key: value
+    node_name@folder: # Node-specific variables. Optional.
+      key: value
+  output: stdout # Mandatory. Output configuration. Choices: 'stdout', 'null', or a folder path like '/path/to/folder'.
+  options: # Execution options. Optional.
+    prompt: 'regex_prompt' # Optional prompt to expect.
+    parallel: 10 # Optional number of parallel threads. Default 10.
+    timeout: 20 # Optional execution timeout in seconds. Default 20.
+
+- name: "Verification Task"
+  action: 'test'
+  nodes:
+  - 'router1@office'
+  commands:
+  - 'ping 10.100.100.1'
+  expected: '!' # Expected text pattern to search in output. Mandatory ONLY for 'test' action.
+
+Connpy Variable Templating & Usage:
+- Variables defined under the `variables` key (either globally under `__global__` or for specific nodes) are used in commands or expected output by surrounding the variable name with single curly braces: `{variable_name}`.
+- Example: If you define a variable `ip` with a value of `10.100.100.1`, you use it in commands as `'ping {ip}'`.
+- Recommendation (Important): Variables are not limited to simple words or values. You can define entire CLI commands as variables to abstract vendor-specific syntax! This is highly recommended when executing the same logical operation across different operating systems (OS) or vendors.
+  - Example: You can define `show_interface_cmd` under a specific node's variables to be `'show ip interface brief'` for Cisco, and `'show interfaces terse'` for Juniper, and then write a single generic command under `commands`:
+    `- '{show_interface_cmd}'`
+
+Guidelines:
+1. When the user requests a playbook, you should guide them and output the YAML.
+2. IMPORTANT: You have access to the `list_nodes` tool. Proactively use it to inspect the user's real inventory. This allows you to discover correct node names, folders, or device tags, and construct precise regex filters for the `nodes` field based on real assets.
+3. IMPORTANT: Before presenting the playbook, you MUST call the `validate_playbook` tool with the YAML to let the backend check for syntax and schema correctness.
+4. If `validate_playbook` returns errors, fix them in your YAML and validate again before responding to the user.
+5. When the playbook is complete, validated, and the user approves it, you MUST call the `return_playbook` tool to return the final YAML.
+6. All text responses must be in the same language the user uses in their prompt.
+"""
+
+PLAYBOOK_BUILDER_TOOLS = [
+    {
+        "type": "function",
+        "function": {
+            "name": "list_nodes",
+            "description": "[Universal Platform] Lists available nodes in the inventory. Use this to discover device names, folders, or operating systems to build proper regex filters.",
+            "parameters": {
+                "type": "OBJECT",
+                "properties": {
+                    "filter_pattern": {
+                        "type": "STRING",
+                        "description": "Regex or pattern to filter nodes (e.g. '.*', 'border.*', '@office')."
+                    }
+                }
+            }
+        }
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "validate_playbook",
+            "description": "Validates the Connpy YAML playbook structure, syntax, and schema correctness with the backend.",
+            "parameters": {
+                "type": "OBJECT",
+                "properties": {
+                    "playbook_yaml": {
+                        "type": "STRING",
+                        "description": "The YAML content of the playbook to validate."
+                    }
+                },
+                "required": ["playbook_yaml"]
+            }
+        }
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "return_playbook",
+            "description": "Returns the final validated YAML playbook to the calling application when the user is satisfied.",
+            "parameters": {
+                "type": "OBJECT",
+                "properties": {
+                    "playbook_yaml": {
+                        "type": "STRING",
+                        "description": "The final YAML content of the playbook."
+                    }
+                },
+                "required": ["playbook_yaml"]
+            }
+        }
+    }
+]
+
+class PlaybookBuilderAgent:
+    """Specialized AI agent for building, validating, and generating Connpy YAML playbooks."""
+
+    def __init__(self, config, console=None, confirm_handler=None, trust=False, **kwargs):
+        self.config = config
+        self.console = console or printer.console
+        self.interrupted = False
+        
+        # Load AI configuration
+        if hasattr(self.config, "get_effective_setting"):
+            aiconfig = self.config.get_effective_setting("ai", {})
+        else:
+            aiconfig = self.config.config.get("ai", {}) if hasattr(self.config, "config") else {}
+
+        # Default model for technical tasks
+        self.model = kwargs.get("engineer_model") or aiconfig.get("engineer_model") or "gemini/gemini-3.1-flash-lite"
+        self.key = kwargs.get("engineer_api_key") or aiconfig.get("engineer_api_key")
+        self.auth = kwargs.get("engineer_auth") or aiconfig.get("engineer_auth") or {}
+        if self.key and "api_key" not in self.auth:
+            self.auth = self.auth.copy()
+            self.auth["api_key"] = self.key
+
+    def validate_playbook(self, playbook_yaml: str) -> dict:
+        """Sintactical and schema validation of Connpy Playbook YAML."""
+        import yaml
+        try:
+            # 1. Parse YAML
+            data = yaml.load(playbook_yaml, Loader=yaml.FullLoader)
+        except Exception as e:
+            return {"valid": False, "error": f"YAML Syntax Error: {e}"}
+
+        # 2. Check structure
+        if not isinstance(data, dict):
+            return {"valid": False, "error": "Playbook must be a YAML dictionary."}
+        
+        if "tasks" not in data:
+            return {"valid": False, "error": "Playbook missing mandatory root 'tasks' key."}
+            
+        tasks = data["tasks"]
+        if not isinstance(tasks, list):
+            return {"valid": False, "error": "'tasks' must be a list of tasks."}
+
+        # 3. Check individual tasks
+        for idx, task in enumerate(tasks):
+            if not isinstance(task, dict):
+                return {"valid": False, "error": f"Task index {idx} must be a dictionary."}
+            
+            name = task.get("name", f"Task {idx}")
+            
+            # Mandatory fields
+            mandatory = ["name", "action", "nodes", "commands", "output"]
+            missing = [field for field in mandatory if field not in task]
+            if missing:
+                return {"valid": False, "error": f"Task '{name}' (index {idx}) is missing mandatory fields: {missing}"}
+
+            # Validate nodes field type (supports string regexes or array of string regexes)
+            nodes = task["nodes"]
+            if not isinstance(nodes, (str, list)):
+                return {"valid": False, "error": f"Task '{name}' (index {idx}) 'nodes' must be a string (regex) or a list of strings (regexes)."}
+            
+            if isinstance(nodes, list):
+                for n_idx, node_item in enumerate(nodes):
+                    if not isinstance(node_item, str):
+                        return {"valid": False, "error": f"Task '{name}' (index {idx}) 'nodes' list contains a non-string value at index {n_idx}: {node_item}"}
+
+            action = task["action"]
+            if action not in ["run", "test"]:
+                return {"valid": False, "error": f"Task '{name}' (index {idx}) has invalid action '{action}'. Choices are: 'run', 'test'."}
+
+            if action == "test" and "expected" not in task:
+                return {"valid": False, "error": f"Task '{name}' (index {idx}) has action 'test' but is missing the mandatory 'expected' key."}
+
+            output = task["output"]
+            if output not in [None, "stdout"] and not output.startswith("/"):
+                return {"valid": False, "error": f"Task '{name}' (index {idx}) output '{output}' is invalid. Must be 'stdout', 'null' or an absolute path."}
+
+        return {"valid": True, "message": "Playbook schema and syntax is valid."}
+
+    def ask(self, user_input, chat_history=None, status=None, debug=False, chunk_callback=None):
+        """Standard conversation step with tool loop for PlaybookBuilderAgent."""
+        if chat_history is None:
+            chat_history = []
+
+        # System prompt and tool definition
+        system_prompt = PLAYBOOK_BUILDER_SYSTEM_PROMPT
+        tools = PLAYBOOK_BUILDER_TOOLS
+        messages = [{"role": "system", "content": system_prompt}]
+
+        for msg in chat_history:
+            m = msg if isinstance(msg, dict) else msg.copy()
+            if m.get('role') == 'assistant' and m.get('tool_calls') and m.get('content') == "":
+                m['content'] = None
+            messages.append(m)
+
+        messages.append({"role": "user", "content": user_input})
+
+        final_playbook_yaml = None
+        iteration = 0
+        max_iterations = 10
+
+        while iteration < max_iterations:
+            iteration += 1
+
+            if status:
+                status.update(f"Playbook Agent is thinking... (step {iteration})")
+
+            # Call LiteLLM completion
+            from connpy.ai import completion
+            try:
+                response = completion(
+                    model=self.model,
+                    messages=messages,
+                    tools=tools,
+                    num_retries=3,
+                    **self.auth
+                )
+            except Exception as e:
+                return {"response": f"Playbook Agent failed: {str(e)}", "chat_history": messages[1:]}
+
+            resp_msg = response.choices[0].message
+            msg_dict = resp_msg.model_dump(exclude_none=True)
+            if msg_dict.get("tool_calls") and msg_dict.get("content") == "":
+                msg_dict["content"] = None
+            
+            messages.append(msg_dict)
+
+            # If the model sends content, stream or yield it
+            if resp_msg.content:
+                if chunk_callback:
+                    chunk_callback(resp_msg.content)
+                elif not resp_msg.tool_calls:
+                    # In direct non-streaming output, print markdown
+                    self.console.print(Markdown(resp_msg.content))
+
+            if not resp_msg.tool_calls:
+                break
+
+            for tc in resp_msg.tool_calls:
+                fn = tc.function.name
+                args = json.loads(tc.function.arguments)
+
+                if fn == "list_nodes":
+                    filter_pattern = args.get("filter_pattern", ".*")
+                    try:
+                        matched_names = self.config._getallnodes(filter_pattern)
+                        if not matched_names:
+                            obs = "No nodes found matching the filter."
+                        else:
+                            if len(matched_names) <= 5:
+                                matched_data = self.config.getitems(matched_names, extract=True)
+                                res = {}
+                                for name, data in matched_data.items():
+                                    os_tag = "unknown"
+                                    if isinstance(data, dict):
+                                        ts = data.get("tags")
+                                        if isinstance(ts, dict): os_tag = ts.get("os", "unknown")
+                                    res[name] = {"os": os_tag}
+                                obs = json.dumps(res)
+                            else:
+                                obs = json.dumps({
+                                    "matched_count": len(matched_names),
+                                    "message": "Too many nodes matched. Showing names only.",
+                                    "node_names": matched_names
+                                })
+                    except Exception as e:
+                        obs = f"Error listing nodes: {e}"
+                    messages.append({
+                        "tool_call_id": tc.id,
+                        "role": "tool",
+                        "name": fn,
+                        "content": obs
+                    })
+                elif fn == "validate_playbook":
+                    playbook_yaml = args.get("playbook_yaml", "")
+                    validation_res = self.validate_playbook(playbook_yaml)
+                    messages.append({
+                        "tool_call_id": tc.id,
+                        "role": "tool",
+                        "name": fn,
+                        "content": json.dumps(validation_res)
+                    })
+                elif fn == "return_playbook":
+                    final_playbook_yaml = args.get("playbook_yaml", "")
+                    messages.append({
+                        "tool_call_id": tc.id,
+                        "role": "tool",
+                        "name": fn,
+                        "content": json.dumps({"success": True, "message": "Playbook returned successfully."})
+                    })
+
+            # If return_playbook was called, we can terminate early
+            if final_playbook_yaml is not None:
+                break
+
+        return {
+            "response": resp_msg.content or "",
+            "chat_history": messages[1:],
+            "playbook_yaml": final_playbook_yaml
+        }

connpy/cli/ai_handler.py

@@ -94,7 +94,7 @@ class AIHandler:
             
     def single_question(self, args, session_id):
         query = " ".join(args.ask)
-        with console.status("[ai_status]Agent is thinking and analyzing...") as status:
+        with console.status("[ai_status]Agent is thinking and analyzing...[/ai_status]") as status:
             result = self.app.myai.ask(query, status=status, debug=args.debug, session_id=session_id, trust=args.trust, **self.ai_overrides)
         
         responder = result.get("responder", "engineer")
@@ -131,7 +131,7 @@ class AIHandler:
                 if not user_query.strip(): continue
                 if user_query.lower() in ['exit', 'quit', 'bye', 'cancel']: break
                 
-                with console.status("[ai_status]Agent is thinking...") as status:
+                with console.status("[ai_status]Agent is thinking...[/ai_status]") as status:
                     result = self.app.myai.ask(user_query, chat_history=history, status=status, debug=args.debug, trust=args.trust, session_id=session_id, **self.ai_overrides)
                 
                 new_history = result.get("chat_history")

connpy/cli/run_handler.py

@@ -15,7 +15,12 @@ class RunHandler:
     def dispatch(self, args):
         if len(args.data) > 1:
             args.action = "noderun"
-        actions = {"noderun": self.node_run, "generate": self.yaml_generate, "run": self.yaml_run}
+        actions = {
+            "noderun": self.node_run,
+            "generate": self.yaml_generate,
+            "generate_ai": self.ai_generate,
+            "run": self.yaml_run
+        }
         return actions.get(args.action)(args)
 
     def node_run(self, args):
@@ -33,6 +38,41 @@ class RunHandler:
             
         commands = [" ".join(args.data[1:])]
 
+        # Check for Preflight AI simulation
+        if getattr(args, "preflight_ai", False):
+            matched_node_names = [n.get("name") if isinstance(n, dict) else n for n in matched_nodes]
+            
+            renderer = printer.BlockMarkdownRenderer()
+            first_chunk = True
+            status_context = printer.console.status("[ai_status]Simulating execution...[/ai_status]")
+            
+            def callback(chunk):
+                nonlocal first_chunk
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title="[engineer][bold]Preflight AI Simulation[/bold][/engineer]", style="engineer"))
+                    first_chunk = False
+                renderer.feed(chunk)
+            
+            try:
+                status_context.start()
+                self.app.services.ai.predict_execution_results(
+                    matched_node_names,
+                    commands,
+                    chunk_callback=callback
+                )
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title="[engineer][bold]Preflight AI Simulation[/bold][/engineer]", style="engineer"))
+                renderer.flush()
+                printer.console.print(Rule(style="engineer"))
+            except Exception as e:
+                printer.error(f"Preflight AI simulation failed: {e}")
+                sys.exit(1)
+            sys.exit(0)
+
         try:
             header_printed = False
 
@@ -70,6 +110,40 @@ class RunHandler:
                 )
                 printer.run_summary(results)
 
+            # Analyze execution results if requested
+            if getattr(args, "analyze", None) is not None:
+                printer.console.print()
+                
+                renderer = printer.BlockMarkdownRenderer()
+                first_chunk = True
+                status_context = printer.console.status("[ai_status]Analyzing execution results...[/ai_status]")
+                
+                def callback(chunk):
+                    nonlocal first_chunk
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Analysis[/bold][/architect]", style="architect"))
+                        first_chunk = False
+                    renderer.feed(chunk)
+                
+                query = args.analyze if args.analyze else " ".join(args.data[1:])
+                try:
+                    status_context.start()
+                    self.app.services.ai.analyze_execution_results(
+                        results,
+                        query=query,
+                        chunk_callback=callback
+                    )
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Analysis[/bold][/architect]", style="architect"))
+                    renderer.flush()
+                    printer.console.print(Rule(style="architect"))
+                except Exception as e:
+                    printer.error(f"AI Analysis failed: {e}")
+
         except ConnpyError as e:
             printer.error(str(e))
             sys.exit(1)
@@ -90,8 +164,105 @@ class RunHandler:
             with open(path, "r") as f:
                 playbook = yaml.load(f, Loader=yaml.FullLoader)
 
+            # Check preflight first before any task runs
+            if getattr(args, "preflight_ai", False):
+                preflight_failed = False
                 for task in playbook.get("tasks", []):
-                self.cli_run(task)
+                    name = task.get("name", "Task")
+                    nodelist = task.get("nodes", [])
+                    commands = task.get("commands", [])
+                    
+                    # Resolve nodes to names
+                    try:
+                        if isinstance(nodelist, str):
+                            resolved_nodes = self.app.services.nodes.list_nodes(nodelist)
+                        elif isinstance(nodelist, list):
+                            resolved_nodes = []
+                            for item in nodelist:
+                                matches = self.app.services.nodes.list_nodes(item)
+                                for m in matches:
+                                    if m not in resolved_nodes:
+                                        resolved_nodes.append(m)
+                        else:
+                            resolved_nodes = []
+                    except Exception:
+                        resolved_nodes = []
+                    
+                    resolved_names = [n.get("name") if isinstance(n, dict) else n for n in resolved_nodes]
+                    printer.console.print(f"\n[bold]Task: {name}[/bold] (Preflight for {len(resolved_names)} nodes)")
+                    
+                    renderer = printer.BlockMarkdownRenderer()
+                    first_chunk = True
+                    status_context = printer.console.status("[ai_status]Simulating execution...[/ai_status]")
+                    
+                    def callback(chunk):
+                        nonlocal first_chunk
+                        if first_chunk:
+                            try: status_context.stop()
+                            except: pass
+                            printer.console.print(Rule(title=f"[engineer][bold]Preflight AI Simulation: {name}[/bold][/engineer]", style="engineer"))
+                            first_chunk = False
+                        renderer.feed(chunk)
+                    try:
+                        status_context.start()
+                        self.app.services.ai.predict_execution_results(
+                            resolved_names,
+                            commands,
+                            chunk_callback=callback
+                        )
+                        if first_chunk:
+                            try: status_context.stop()
+                            except: pass
+                            printer.console.print(Rule(title=f"[engineer][bold]Preflight AI Simulation: {name}[/bold][/engineer]", style="engineer"))
+                        renderer.flush()
+                        printer.console.print(Rule(style="engineer"))
+                    except Exception as e:
+                        printer.error(f"Preflight AI simulation failed for task {name}: {e}")
+                        preflight_failed = True
+                if preflight_failed:
+                    sys.exit(1)
+                sys.exit(0)
+
+            # Standard run
+            results_all = {}
+            for task in playbook.get("tasks", []):
+                task_res = self.cli_run(task)
+                if task_res:
+                    results_all.update(task_res)
+
+            # If analyze is enabled, run analysis on accumulated results
+            if getattr(args, "analyze", None) is not None:
+                printer.console.print()
+                
+                renderer = printer.BlockMarkdownRenderer()
+                first_chunk = True
+                status_context = printer.console.status("[ai_status]Analyzing playbook execution results...[/ai_status]")
+                
+                def callback(chunk):
+                    nonlocal first_chunk
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Playbook Analysis[/bold][/architect]", style="architect"))
+                        first_chunk = False
+                    renderer.feed(chunk)
+                
+                query = args.analyze if args.analyze else f"Playbook: {path}"
+                try:
+                    status_context.start()
+                    self.app.services.ai.analyze_execution_results(
+                        results_all,
+                        query=query,
+                        chunk_callback=callback
+                    )
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Playbook Analysis[/bold][/architect]", style="architect"))
+                    renderer.flush()
+                    printer.console.print(Rule(style="architect"))
+                except Exception as e:
+                    printer.error(f"AI Analysis failed: {e}")
 
         except Exception as e:
             printer.error(f"Failed to run playbook {path}: {e}")
@@ -136,6 +307,7 @@ class RunHandler:
 
         nodelist = resolved_nodes
 
+        results = {}
         try:
             header_printed = False
             if action == "run":
@@ -196,5 +368,117 @@ class RunHandler:
                 # ALWAYS show the aggregate summary at the end
                 printer.test_summary(results)
                 
+            return results
+
         except ConnpyError as e:
             printer.error(str(e))
+            return {}
+
+    def ai_generate(self, args):
+        from rich.prompt import Prompt
+        from rich.rule import Rule
+        from rich.panel import Panel
+        from rich.syntax import Syntax
+
+        dest_file = args.data[0]
+        if os.path.exists(dest_file):
+            printer.error(f"File '{dest_file}' already exists.")
+            sys.exit(14)
+
+        chat_history = []
+        
+        # Consistent layout opening matching global AI (engineer style)
+        from rich.markdown import Markdown
+        printer.console.print(Rule(style="engineer"))
+        printer.console.print(Markdown("**Playbook Builder AI**: Welcome! Describe the automation workflow you want to design.\nType **exit** to quit.\n"))
+        printer.console.print(Rule(style="engineer"))
+        
+        while True:
+            try:
+                user_prompt = Prompt.ask("[user_prompt]User[/user_prompt]")
+            except (KeyboardInterrupt, EOFError):
+                printer.console.print()
+                printer.warning("Operation cancelled by user.")
+                break
+                
+            if user_prompt.strip().lower() in ["exit", "quit"]:
+                printer.info("Exiting AI Assistant.")
+                break
+                
+            if not user_prompt.strip():
+                continue
+                
+            printer.console.print()
+            
+            renderer = printer.BlockMarkdownRenderer()
+            first_chunk = True
+            status_context = printer.console.status("[ai_status]Agent is thinking...[/ai_status]")
+            
+            def callback(chunk):
+                nonlocal first_chunk
+                if first_chunk:
+                    try:
+                        status_context.stop()
+                    except:
+                        pass
+                    printer.console.print(Rule(title="[engineer][bold]Playbook Builder AI[/bold][/engineer]", style="engineer"))
+                    first_chunk = False
+                renderer.feed(chunk)
+                
+            try:
+                status_context.start()
+                res = self.app.services.ai.build_playbook_chat(
+                    user_prompt,
+                    chat_history=chat_history,
+                    chunk_callback=callback
+                )
+                if first_chunk:
+                    try:
+                        status_context.stop()
+                    except:
+                        pass
+                renderer.flush()
+                if not first_chunk:
+                    printer.console.print(Rule(style="engineer"))
+                
+                # Update history
+                if res and "chat_history" in res:
+                    chat_history = res["chat_history"]
+                
+                # Check if the agent returned a validated playbook YAML
+                if res and "playbook_yaml" in res and res["playbook_yaml"]:
+                    yaml_content = res["playbook_yaml"]
+                    printer.console.print()
+                    printer.success("Playbook YAML successfully generated and validated.")
+                    
+                    # Show the YAML inside a beautiful panel matching AI style (with engineer borders)
+                    syntax = Syntax(yaml_content, "yaml", theme="ansi_dark", word_wrap=True, background_color="default")
+                    panel = Panel(syntax, title="[engineer][bold]Resulting Playbook[/bold][/engineer]", border_style="engineer", expand=False)
+                    printer.console.print(panel)
+                    
+                    # Ask if the user wants to save it
+                    try:
+                        save_confirm = Prompt.ask(
+                            f"\nDo you want to save this playbook to '{dest_file}'?",
+                            choices=["y", "n", "run"],
+                            default="y"
+                        )
+                    except (KeyboardInterrupt, EOFError):
+                        printer.console.print()
+                        printer.warning("Saving skipped.")
+                        break
+                        
+                    choice = save_confirm.strip().lower()
+                    if choice in ["y", "yes", "run"]:
+                        with open(dest_file, "w") as f:
+                            f.write(yaml_content)
+                        printer.success(f"Playbook saved successfully to '{dest_file}'")
+                        if choice == "run":
+                            printer.console.print()
+                            printer.info("Executing the saved playbook...")
+                            self.yaml_run(args)
+                        break
+                    else:
+                        printer.warning("Playbook not saved. You can continue describing changes or exit.")
+            except Exception as e:
+                printer.error(f"Error in AI chat: {e}")

connpy/completion.py

@@ -169,12 +169,17 @@ def _build_tree(nodes, folders, profiles, plugins, configdir):
     run_after_node.update({
         "--test": {"*": run_after_node},
         "-t": {"*": run_after_node},
+        "--analyze": {"*": run_after_node},
+        "--preflight-ai": run_after_node,
         "*": run_after_node  # Consume commands
     })
 
     run_dict = {
         "--generate": {"__extra__": lambda w: get_cwd(w, "--generate")},
         "-g": {"__extra__": lambda w: get_cwd(w, "-g")},
+        "--generate-ai": {"__extra__": lambda w: get_cwd(w, "--generate-ai")},
+        "--analyze": {"*": run_after_node},
+        "--preflight-ai": run_after_node,
         "--test": {"*": None},
         "-t": {"*": None},
         "--help": None,

connpy/connapp.py

@@ -303,6 +303,9 @@ class connapp:
         runparser.add_argument("run", nargs='+', action=self._store_type, help=get_help("run"), default="run").completer = nodes_completer
         runparser.add_argument("-t", "--test", dest="test_expected", nargs='+', help="Expected text(s) to validate in output. Converts the action from 'run' to 'test'")
         runparser.add_argument("-g","--generate", dest="action", action="store_const", help="Generate yaml file template", const="generate", default="run")
+        runparser.add_argument("--generate-ai", dest="action", action="store_const", help="Generate a playbook interactively with AI assistance", const="generate_ai")
+        runparser.add_argument("--analyze", nargs='?', const="", help="Analyze actual command execution results using AI")
+        runparser.add_argument("--preflight-ai", action="store_true", help="Simulate and predict command execution on devices using AI preventively")
         runparser.set_defaults(func=self._run.dispatch)
         #APIPARSER
         apiparser = subparsers.add_parser("api", help="Start and stop connpy API", description="Start and stop connpy API", formatter_class=RichHelpFormatter) 

connpy/grpc_layer/connpy_pb2_grpc.py

@@ -1542,11 +1542,6 @@ class ExecutionServiceStub(object):
                 request_serializer=connpy__pb2.ScriptRequest.SerializeToString,
                 response_deserializer=connpy__pb2.StructResponse.FromString,
                 _registered_method=True)
-        self.run_yaml_playbook = channel.unary_unary(
-                '/connpy.ExecutionService/run_yaml_playbook',
-                request_serializer=connpy__pb2.ScriptRequest.SerializeToString,
-                response_deserializer=connpy__pb2.StructResponse.FromString,
-                _registered_method=True)
 
 
 class ExecutionServiceServicer(object):
@@ -1570,12 +1565,6 @@ class ExecutionServiceServicer(object):
         context.set_details('Method not implemented!')
         raise NotImplementedError('Method not implemented!')
 
-    def run_yaml_playbook(self, request, context):
-        """Missing associated documentation comment in .proto file."""
-        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
-        context.set_details('Method not implemented!')
-        raise NotImplementedError('Method not implemented!')
-
 
 def add_ExecutionServiceServicer_to_server(servicer, server):
     rpc_method_handlers = {
@@ -1594,11 +1583,6 @@ def add_ExecutionServiceServicer_to_server(servicer, server):
                     request_deserializer=connpy__pb2.ScriptRequest.FromString,
                     response_serializer=connpy__pb2.StructResponse.SerializeToString,
             ),
-            'run_yaml_playbook': grpc.unary_unary_rpc_method_handler(
-                    servicer.run_yaml_playbook,
-                    request_deserializer=connpy__pb2.ScriptRequest.FromString,
-                    response_serializer=connpy__pb2.StructResponse.SerializeToString,
-            ),
     }
     generic_handler = grpc.method_handlers_generic_handler(
             'connpy.ExecutionService', rpc_method_handlers)
@@ -1691,33 +1675,6 @@ class ExecutionService(object):
             metadata,
             _registered_method=True)
 
-    @staticmethod
-    def run_yaml_playbook(request,
-            target,
-            options=(),
-            channel_credentials=None,
-            call_credentials=None,
-            insecure=False,
-            compression=None,
-            wait_for_ready=None,
-            timeout=None,
-            metadata=None):
-        return grpc.experimental.unary_unary(
-            request,
-            target,
-            '/connpy.ExecutionService/run_yaml_playbook',
-            connpy__pb2.ScriptRequest.SerializeToString,
-            connpy__pb2.StructResponse.FromString,
-            options,
-            channel_credentials,
-            insecure,
-            call_credentials,
-            compression,
-            wait_for_ready,
-            timeout,
-            metadata,
-            _registered_method=True)
-
 
 class ImportExportServiceStub(object):
     """Missing associated documentation comment in .proto file."""
@@ -1931,6 +1888,21 @@ class AIServiceStub(object):
                 request_serializer=connpy__pb2.StringRequest.SerializeToString,
                 response_deserializer=connpy__pb2.StructResponse.FromString,
                 _registered_method=True)
+        self.build_playbook_chat = channel.stream_stream(
+                '/connpy.AIService/build_playbook_chat',
+                request_serializer=connpy__pb2.AskRequest.SerializeToString,
+                response_deserializer=connpy__pb2.AIResponse.FromString,
+                _registered_method=True)
+        self.analyze_execution_results = channel.unary_stream(
+                '/connpy.AIService/analyze_execution_results',
+                request_serializer=connpy__pb2.AnalyzeRequest.SerializeToString,
+                response_deserializer=connpy__pb2.AIResponse.FromString,
+                _registered_method=True)
+        self.predict_execution_results = channel.unary_stream(
+                '/connpy.AIService/predict_execution_results',
+                request_serializer=connpy__pb2.PreflightRequest.SerializeToString,
+                response_deserializer=connpy__pb2.AIResponse.FromString,
+                _registered_method=True)
 
 
 class AIServiceServicer(object):
@@ -1990,6 +1962,24 @@ class AIServiceServicer(object):
         context.set_details('Method not implemented!')
         raise NotImplementedError('Method not implemented!')
 
+    def build_playbook_chat(self, request_iterator, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def analyze_execution_results(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def predict_execution_results(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
 
 def add_AIServiceServicer_to_server(servicer, server):
     rpc_method_handlers = {
@@ -2038,6 +2028,21 @@ def add_AIServiceServicer_to_server(servicer, server):
                     request_deserializer=connpy__pb2.StringRequest.FromString,
                     response_serializer=connpy__pb2.StructResponse.SerializeToString,
             ),
+            'build_playbook_chat': grpc.stream_stream_rpc_method_handler(
+                    servicer.build_playbook_chat,
+                    request_deserializer=connpy__pb2.AskRequest.FromString,
+                    response_serializer=connpy__pb2.AIResponse.SerializeToString,
+            ),
+            'analyze_execution_results': grpc.unary_stream_rpc_method_handler(
+                    servicer.analyze_execution_results,
+                    request_deserializer=connpy__pb2.AnalyzeRequest.FromString,
+                    response_serializer=connpy__pb2.AIResponse.SerializeToString,
+            ),
+            'predict_execution_results': grpc.unary_stream_rpc_method_handler(
+                    servicer.predict_execution_results,
+                    request_deserializer=connpy__pb2.PreflightRequest.FromString,
+                    response_serializer=connpy__pb2.AIResponse.SerializeToString,
+            ),
     }
     generic_handler = grpc.method_handlers_generic_handler(
             'connpy.AIService', rpc_method_handlers)
@@ -2292,6 +2297,87 @@ class AIService(object):
             metadata,
             _registered_method=True)
 
+    @staticmethod
+    def build_playbook_chat(request_iterator,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.stream_stream(
+            request_iterator,
+            target,
+            '/connpy.AIService/build_playbook_chat',
+            connpy__pb2.AskRequest.SerializeToString,
+            connpy__pb2.AIResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def analyze_execution_results(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(
+            request,
+            target,
+            '/connpy.AIService/analyze_execution_results',
+            connpy__pb2.AnalyzeRequest.SerializeToString,
+            connpy__pb2.AIResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def predict_execution_results(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(
+            request,
+            target,
+            '/connpy.AIService/predict_execution_results',
+            connpy__pb2.PreflightRequest.SerializeToString,
+            connpy__pb2.AIResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
 
 class SystemServiceStub(object):
     """Missing associated documentation comment in .proto file."""

connpy/grpc_layer/server.py

@@ -791,11 +791,6 @@ class ExecutionServicer(connpy_pb2_grpc.ExecutionServiceServicer):
         res = self.service.run_cli_script(request.param1, request.param2, request.parallel)
         return connpy_pb2.StructResponse(data=to_struct(res))
 
-    @handle_errors
-    def run_yaml_playbook(self, request, context):
-        res = self.service.run_yaml_playbook(request.param1, request.parallel)
-        return connpy_pb2.StructResponse(data=to_struct(res))
-
 class ImportExportServicer(connpy_pb2_grpc.ImportExportServiceServicer):
     def __init__(self, provider, registry=None):
         if not hasattr(provider, "mode"):
@@ -955,12 +950,10 @@ class AIServicer(connpy_pb2_grpc.AIServiceServicer):
     def service(self):
         return self._get_provider().ai
 
-    @handle_errors
-    def ask(self, request_iterator, context):
+    def _handle_chat_stream(self, request_iterator, context, service_method):
         import queue
         import threading
 
-        ai_service = self.service
         chunk_queue = queue.Queue()
         request_queue = queue.Queue()
         bridge = None
@@ -978,13 +971,20 @@ class AIServicer(connpy_pb2_grpc.AIServiceServicer):
             nonlocal history, bridge, agent_instance
             try:
                 # Run the AI interaction (this blocks this specific thread)
-                res = ai_service.ask(
+                if getattr(service_method, "__name__", None) == "build_playbook_chat":
+                    res = service_method(
+                        input_text,
+                        chat_history=history if history else None,
+                        status=bridge,
+                        chunk_callback=callback
+                    )
+                else:
+                    res = service_method(
                         input_text,
                         chat_history=history if history else None,
                         session_id=session_id,
                         debug=debug,
                         status=bridge,
-                    console=bridge,
                         confirm_handler=bridge.confirm,
                         chunk_callback=callback,
                         trust=trust,
@@ -992,7 +992,7 @@ class AIServicer(connpy_pb2_grpc.AIServiceServicer):
                     )
 
                 # Update history for next message
-                if "chat_history" in res:
+                if res and "chat_history" in res:
                     history = res["chat_history"]
 
                 # Send final chunk marker
@@ -1086,6 +1086,71 @@ class AIServicer(connpy_pb2_grpc.AIServiceServicer):
             elif msg_type == "final_mark":
                 yield connpy_pb2.AIResponse(is_final=True, full_result=to_struct(val))
 
+    def _handle_unary_stream(self, service_method, *args, **kwargs):
+        import queue
+        import threading
+        
+        chunk_queue = queue.Queue()
+        bridge = StatusBridge(chunk_queue, is_web=False)
+        
+        def callback(chunk):
+            chunk_queue.put(("text", chunk))
+            
+        def _worker():
+            try:
+                res = service_method(*args, chunk_callback=callback, status=bridge, **kwargs)
+                chunk_queue.put(("final_mark", res))
+            except Exception as e:
+                import traceback
+                print(f"gRPC Unary Stream error: {e}")
+                traceback.print_exc()
+                chunk_queue.put(("status", f"Error: {str(e)}"))
+                chunk_queue.put(("final_mark", {"response": f"Error: {str(e)}", "error": True}))
+            finally:
+                chunk_queue.put((None, None))
+                
+        threading.Thread(target=_worker, daemon=True).start()
+        
+        while True:
+            item = chunk_queue.get()
+            if item == (None, None):
+                break
+                
+            msg_type, val = item
+            if msg_type == "text":
+                yield connpy_pb2.AIResponse(text_chunk=val, is_final=False)
+            elif msg_type == "status":
+                clean_val = val.replace("[ai_status]", "").replace("[/ai_status]", "")
+                yield connpy_pb2.AIResponse(status_update=clean_val, is_final=False)
+            elif msg_type == "debug":
+                yield connpy_pb2.AIResponse(debug_message=val, is_final=False)
+            elif msg_type == "important":
+                yield connpy_pb2.AIResponse(important_message=val, is_final=False)
+            elif msg_type == "confirm":
+                yield connpy_pb2.AIResponse(status_update=val, requires_confirmation=True, is_final=False)
+            elif msg_type == "final_mark":
+                yield connpy_pb2.AIResponse(is_final=True, full_result=to_struct(val))
+
+    @handle_errors
+    def ask(self, request_iterator, context):
+        yield from self._handle_chat_stream(request_iterator, context, self.service.ask)
+
+    @handle_errors
+    def build_playbook_chat(self, request_iterator, context):
+        yield from self._handle_chat_stream(request_iterator, context, self.service.build_playbook_chat)
+
+    @handle_errors
+    def analyze_execution_results(self, request, context):
+        results = from_struct(request.results)
+        query = request.query if request.query else None
+        yield from self._handle_unary_stream(self.service.analyze_execution_results, results, query=query)
+
+    @handle_errors
+    def predict_execution_results(self, request, context):
+        target_nodes = list(request.target_nodes)
+        commands = list(request.commands)
+        yield from self._handle_unary_stream(self.service.predict_execution_results, target_nodes, commands)
+
     @handle_errors
     def confirm(self, request, context):
         res = self.service.confirm(request.value)

connpy/grpc_layer/stubs.py

@@ -692,11 +692,6 @@ class ExecutionStub:
         req = connpy_pb2.ScriptRequest(param1=nodes_filter, param2=script_path, parallel=parallel)
         return from_struct(self.stub.run_cli_script(req).data)
 
-    @handle_errors
-    def run_yaml_playbook(self, playbook_path, parallel=10):
-        req = connpy_pb2.ScriptRequest(param1=playbook_path, parallel=parallel)
-        return from_struct(self.stub.run_yaml_playbook(req).data)
-
 class ImportExportStub:
     def __init__(self, channel, remote_host):
         self.stub = connpy_pb2_grpc.ImportExportServiceStub(channel)
@@ -724,8 +719,7 @@ class AIStub:
         self.stub = connpy_pb2_grpc.AIServiceStub(channel)
         self.remote_host = remote_host
 
-    @handle_errors
-    def ask(self, input_text, dryrun=False, chat_history=None, session_id=None, debug=False, status=None, **overrides):
+    def _ai_chat_stream(self, stub_method, input_text, dryrun=False, chat_history=None, session_id=None, debug=False, status=None, chunk_callback=None, **overrides):
         import queue
         from rich.prompt import Prompt
         from rich.text import Text
@@ -760,7 +754,7 @@ class AIStub:
                 if req is None: break
                 yield req
 
-        responses = self.stub.ask(request_generator())
+        responses = stub_method(request_generator())
         
         full_content = ""
         header_printed = False
@@ -859,6 +853,9 @@ class AIStub:
                                 try: status.stop()
                                 except: pass
                             
+                            if chunk_callback:
+                                header_printed = True
+                            else:
                                 from rich.console import Console as RichConsole
                                 from rich.rule import Rule
                                 from ..printer import connpy_theme, get_original_stdout, IncrementalMarkdownParser
@@ -874,11 +871,14 @@ class AIStub:
                                 md_parser = IncrementalMarkdownParser(console=stable_console)
                         
                         full_content += response.text_chunk
+                        if chunk_callback:
+                            chunk_callback(response.text_chunk)
+                        elif md_parser:
                             md_parser.feed(response.text_chunk)
                     continue
                 
                 if response.is_final:
-                    if header_printed:
+                    if not chunk_callback and header_printed:
                         from rich.rule import Rule
                         md_parser.flush()
                         
@@ -887,12 +887,8 @@ class AIStub:
                         except: pass
 
                     final_result = from_struct(response.full_result)
-                    responder = final_result.get("responder", "engineer")
-                    alias = "architect" if responder == "architect" else "engineer"
-                    role_label = "Network Architect" if responder == "architect" else "Network Engineer"
-                    title = f"[bold {alias}]{role_label}[/bold {alias}]"
                     
-                    if header_printed:
+                    if not chunk_callback and header_printed:
                         from rich.console import Console as RichConsole
                         from ..printer import connpy_theme, get_original_stdout
                         stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
@@ -911,6 +907,104 @@ class AIStub:
             
         return final_result
 
+    @handle_errors
+    def ask(self, input_text, dryrun=False, chat_history=None, session_id=None, debug=False, status=None, **overrides):
+        return self._ai_chat_stream(self.stub.ask, input_text, dryrun=dryrun, chat_history=chat_history, session_id=session_id, debug=debug, status=status, **overrides)
+
+    @handle_errors
+    def build_playbook_chat(self, user_input, chat_history=None, status=None, chunk_callback=None):
+        return self._ai_chat_stream(self.stub.build_playbook_chat, user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)
+
+    def _process_unary_stream(self, responses, status=None, chunk_callback=None):
+        full_content = ""
+        header_printed = False
+        final_result = {"response": "", "chat_history": []}
+        md_parser = None
+
+        try:
+            for response in responses:
+                if response.status_update:
+                    if status:
+                        status.update(response.status_update)
+                    continue
+                
+                if response.important_message:
+                    if status:
+                        try: status.stop()
+                        except: pass
+                    printer.console.print(Text.from_ansi(response.important_message))
+                    if status:
+                        try: status.start()
+                        except: pass
+                    continue
+
+                if not response.is_final:
+                    if response.text_chunk:
+                        if not header_printed:
+                            if status:
+                                try: status.stop()
+                                except: pass
+                            
+                            if chunk_callback:
+                                header_printed = True
+                            else:
+                                from rich.console import Console as RichConsole
+                                from rich.rule import Rule
+                                from ..printer import connpy_theme, get_original_stdout, IncrementalMarkdownParser
+                                stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
+                                
+                                # Print default header
+                                stable_console.print(Rule("[bold engineer]AI Analysis[/bold engineer]", style="engineer"))
+                                header_printed = True
+                                md_parser = IncrementalMarkdownParser(console=stable_console)
+                        
+                        full_content += response.text_chunk
+                        if chunk_callback:
+                            chunk_callback(response.text_chunk)
+                        elif md_parser:
+                            md_parser.feed(response.text_chunk)
+                    continue
+                
+                if response.is_final:
+                    if md_parser:
+                        md_parser.flush()
+                        
+                    if status:
+                        try: status.stop()
+                        except: pass
+
+                    final_result = from_struct(response.full_result)
+                    
+                    if md_parser:
+                        from rich.console import Console as RichConsole
+                        from rich.rule import Rule
+                        from ..printer import connpy_theme, get_original_stdout
+                        stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
+                        stable_console.print(Rule(style="engineer"))
+                    break
+        except Exception as e:
+            if isinstance(e, grpc.RpcError):
+                raise
+            printer.warning(f"Stream interrupted: {e}")
+            
+        if full_content:
+            final_result["streamed"] = True
+            
+        return final_result
+
+    @handle_errors
+    def analyze_execution_results(self, results, query=None, status=None, chunk_callback=None):
+        req = connpy_pb2.AnalyzeRequest(query=query or "")
+        req.results.CopyFrom(to_struct(results))
+        responses = self.stub.analyze_execution_results(req)
+        return self._process_unary_stream(responses, status, chunk_callback)
+
+    @handle_errors
+    def predict_execution_results(self, target_nodes, commands, status=None, chunk_callback=None):
+        req = connpy_pb2.PreflightRequest(target_nodes=target_nodes, commands=commands)
+        responses = self.stub.predict_execution_results(req)
+        return self._process_unary_stream(responses, status, chunk_callback)
+
     @handle_errors
     def confirm(self, input_text, console=None):
         return self.stub.confirm(connpy_pb2.StringRequest(value=input_text)).value

connpy/printer.py

@@ -573,7 +573,7 @@ class BlockMarkdownRenderer:
         if not block_text:
             return
         from rich.markdown import Markdown
-        self._console.print(Markdown(block_text))
+        self._console.print(Markdown(block_text, code_theme="ansi_dark"))
 
 # Alias for backward compatibility
 IncrementalMarkdownParser = BlockMarkdownRenderer

connpy/proto/connpy.proto

@@ -53,7 +53,6 @@ service ExecutionService {
     rpc run_commands (RunRequest) returns (stream NodeRunResult) {}
     rpc test_commands (TestRequest) returns (stream NodeRunResult) {}
     rpc run_cli_script (ScriptRequest) returns (StructResponse) {}
-    rpc run_yaml_playbook (ScriptRequest) returns (StructResponse) {}
 }
 
 service ImportExportService {
@@ -72,6 +71,9 @@ service AIService {
     rpc configure_mcp (MCPRequest) returns (google.protobuf.Empty) {}
     rpc list_mcp_servers (google.protobuf.Empty) returns (ValueResponse) {}
     rpc load_session_data (StringRequest) returns (StructResponse) {}
+    rpc build_playbook_chat (stream AskRequest) returns (stream AIResponse) {}
+    rpc analyze_execution_results (AnalyzeRequest) returns (stream AIResponse) {}
+    rpc predict_execution_results (PreflightRequest) returns (stream AIResponse) {}
 }
 
 service SystemService {
@@ -317,3 +319,13 @@ message ChangePasswordRequest {
     string old_password = 1;
     string new_password = 2;
 }
+
+message AnalyzeRequest {
+    google.protobuf.Struct results = 1;
+    string query = 2;
+}
+
+message PreflightRequest {
+    repeated string target_nodes = 1;
+    repeated string commands = 2;
+}

connpy/services/ai_service.py

@@ -319,3 +319,37 @@ class AIService(BaseService):
         agent = ai(self.config)
         return agent.load_session_data(session_id)
 
+    def build_playbook_chat(self, user_input: str, chat_history: list = None, status=None, chunk_callback=None):
+        """Interact with the specialized Playbook Builder Agent."""
+        from connpy.ai import PlaybookBuilderAgent
+        agent = PlaybookBuilderAgent(self.config)
+        return agent.ask(user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)
+
+    def analyze_execution_results(self, results: dict, query: str = None, status=None, chunk_callback=None):
+        """Analyze actual command execution results using Network Architect 1-shot."""
+        import json
+        results_str = json.dumps(results, indent=2)
+        
+        prompt = f"@architect: Please analyze the following actual execution results. Diagnose any issues, highlight successful actions, and suggest strategic remediation steps if needed."
+        if query:
+            prompt += f"\nSpecific user request: {query}"
+        prompt += f"\n\nResults Data:\n{results_str}"
+        prompt += "\n\nCRITICAL DIRECTIVE: You are running in a strictly 1-shot offline diagnostics mode (--analyze). There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately. DO NOT suggest, mention, or attempt to delegate the session back to the engineer."
+        
+        # Delegate to self.ask, setting stream=True and forwarding callback/status.
+        # This will invoke standard ai.ask with '@architect:' prefix, forcing 1-shot architect brain.
+        return self.ask(prompt, status=status, chunk_callback=chunk_callback, one_shot=True)
+
+    def predict_execution_results(self, target_nodes: list, commands: list, status=None, chunk_callback=None):
+        """Predict and simulate execution results preventively using the Preflight Simulation Agent (1-shot)."""
+        nodes_str = ", ".join(target_nodes)
+        commands_str = "\n".join(f"- {cmd}" for cmd in commands)
+        
+        prompt = f"@engineer: Act as a Preflight Simulation Agent. Simulate and predict the expected outputs and behaviors of the following commands on the target nodes. Alert about potential safety or configuration risks based on node profiles."
+        prompt += f"\n\nTarget Nodes: {nodes_str}"
+        prompt += f"\nCommands to simulate:\n{commands_str}"
+        prompt += "\n\nCRITICAL SCALABILITY DIRECTIVE: If there are many target nodes, DO NOT list predictions node-by-node. Instead, group them by Operating System, vendor, or platform, and provide a highly concise Executive Summary. Detail individual risks only for nodes that present specific anomalies or security concerns. Focus on overall impact."
+        
+        # Delegate to self.ask, using the standard engineer brain but with the simulated preflight prompt.
+        return self.ask(prompt, status=status, chunk_callback=chunk_callback)
+

connpy/services/execution_service.py

@@ -1,6 +1,5 @@
 from typing import List, Dict, Any, Callable, Optional
 import os
-import yaml
 from .base import BaseService
 from connpy.core import nodes as Nodes
 from .exceptions import ConnpyError
@@ -108,52 +107,3 @@ class ExecutionService(BaseService):
             
         return self.run_commands(nodes_filter, commands, parallel=parallel)
 
-    def run_yaml_playbook(self, playbook_data: str, parallel: int = 10) -> Dict[str, Any]:
-        """Run a structured Connpy YAML automation playbook (from path or content)."""
-        playbook = None
-        if playbook_data.startswith("---YAML---\n"):
-            try:
-                content = playbook_data[len("---YAML---\n"):]
-                playbook = yaml.load(content, Loader=yaml.FullLoader)
-            except Exception as e:
-                raise ConnpyError(f"Failed to parse YAML content: {e}")
-        else:
-            if not os.path.exists(playbook_data):
-                raise ConnpyError(f"Playbook file not found: {playbook_data}")
-            try:
-                with open(playbook_data, "r") as f:
-                    playbook = yaml.load(f, Loader=yaml.FullLoader)
-            except Exception as e:
-                raise ConnpyError(f"Failed to load playbook {playbook_data}: {e}")
-            
-        # Basic validation
-        if not isinstance(playbook, dict) or "nodes" not in playbook or "commands" not in playbook:
-            raise ConnpyError("Invalid playbook format: missing 'nodes' or 'commands' keys.")
-            
-        action = playbook.get("action", "run")
-        options = playbook.get("options", {})
-        
-        # Extract all fields similar to RunHandler.cli_run
-        exec_args = {
-            "nodes_filter": playbook["nodes"],
-            "commands": playbook["commands"],
-            "variables": playbook.get("variables"),
-            "parallel": options.get("parallel", parallel),
-            "timeout": playbook.get("timeout", options.get("timeout", 20)),
-            "prompt": options.get("prompt"),
-            "name": playbook.get("name", "Task")
-        }
-
-        # Map 'output' field to folder path if it's not stdout/null
-        output_cfg = playbook.get("output")
-        if output_cfg not in [None, "stdout"]:
-            exec_args["folder"] = output_cfg
-
-        if action == "run":
-            return self.run_commands(**exec_args)
-        elif action == "test":
-            exec_args["expected"] = playbook.get("expected", [])
-            return self.test_commands(**exec_args)
-        else:
-            raise ConnpyError(f"Unsupported playbook action: {action}")
-

connpy/tests/test_ai.py

@@ -480,6 +480,15 @@ class TestToolDefinitions:
         names = [t["function"]["name"] for t in tools]
         assert "arch_tool" in names
 
+    def test_architect_tools_one_shot(self, ai_config):
+        from connpy.ai import ai
+        one_shot_ai = ai(ai_config, one_shot=True)
+        tools = one_shot_ai._get_architect_tools()
+        names = [t["function"]["name"] for t in tools]
+        assert "delegate_to_engineer" not in names
+        assert "return_to_engineer" not in names
+        assert "manage_memory_tool" in names
+
 
 # =========================================================================
 # AI Session Management tests

connpy/tests/test_cli_run_ai.py

@@ -0,0 +1,136 @@
+import pytest
+from unittest.mock import patch, MagicMock, ANY
+from connpy.connapp import connapp
+import os
+
+@pytest.fixture
+def app(populated_config):
+    """Returns an instance of connapp initialized with mock config."""
+    return connapp(populated_config)
+
+def test_run_generate_ai_dispatch(app):
+    """Test that connpy run --generate-ai parses and calls ai_generate."""
+    with patch("connpy.cli.run_handler.RunHandler.ai_generate") as mock_ai_gen:
+        app.start(["run", "--generate-ai", "new_playbook.yaml"])
+        mock_ai_gen.assert_called_once()
+        args = mock_ai_gen.call_args[0][0]
+        assert args.data == ["new_playbook.yaml"]
+        assert args.action == "generate_ai"
+
+def test_run_preflight_ai_node(app):
+    """Test that connpy run --preflight-ai calls predict_execution_results and exits."""
+    with patch("connpy.services.node_service.NodeService.list_nodes", return_value=["router1"]):
+        with patch("connpy.services.ai_service.AIService.predict_execution_results") as mock_predict:
+            with pytest.raises(SystemExit) as exc:
+                app.start(["run", "router1", "show version", "--preflight-ai"])
+            
+            assert exc.value.code == 0
+            mock_predict.assert_called_once_with(["router1"], ["show version"], chunk_callback=ANY)
+
+def test_run_analyze_node(app):
+    """Test that connpy run --analyze calls analyze_execution_results after execution."""
+    mock_run = MagicMock(return_value={"router1": {"status": 0, "output": "success"}})
+    
+    with patch("connpy.services.node_service.NodeService.list_nodes", return_value=["router1"]):
+        with patch("connpy.services.execution_service.ExecutionService.run_commands", mock_run):
+            with patch("connpy.services.ai_service.AIService.analyze_execution_results") as mock_analyze:
+                app.start(["run", "router1", "show version", "--analyze"])
+                mock_run.assert_called_once()
+                mock_analyze.assert_called_once_with(
+                    {"router1": {"status": 0, "output": "success"}},
+                    query="show version",
+                    chunk_callback=ANY
+                )
+
+def test_run_preflight_ai_playbook(app, tmp_path):
+    """Test that running a playbook with --preflight-ai predicts results per task."""
+    playbook_path = tmp_path / "test_playbook.yaml"
+    playbook_content = """
+tasks:
+  - name: test-task
+    action: run
+    nodes: "router1"
+    commands: ["show ip interface brief"]
+    output: stdout
+"""
+    playbook_path.write_text(playbook_content)
+    
+    with patch("connpy.services.node_service.NodeService.list_nodes", return_value=["router1"]):
+        with patch("connpy.services.ai_service.AIService.predict_execution_results") as mock_predict:
+            with pytest.raises(SystemExit) as exc:
+                app.start(["run", str(playbook_path), "--preflight-ai"])
+            
+            assert exc.value.code == 0
+            mock_predict.assert_called_once_with(["router1"], ["show ip interface brief"], chunk_callback=ANY)
+
+def test_run_analyze_playbook(app, tmp_path):
+    """Test that running a playbook with --analyze triggers strategic analysis on all task outcomes."""
+    playbook_path = tmp_path / "test_playbook.yaml"
+    playbook_content = """
+tasks:
+  - name: test-task
+    action: run
+    nodes: "router1"
+    commands: ["show ip interface brief"]
+    output: stdout
+"""
+    playbook_path.write_text(playbook_content)
+    
+    mock_run = MagicMock(return_value={"router1": {"status": 0, "output": "ok"}})
+    
+    with patch("connpy.services.node_service.NodeService.list_nodes", return_value=["router1"]):
+        with patch("connpy.services.execution_service.ExecutionService.run_commands", mock_run):
+            with patch("connpy.services.ai_service.AIService.analyze_execution_results") as mock_analyze:
+                app.start(["run", str(playbook_path), "--analyze"])
+                mock_run.assert_called_once()
+                mock_analyze.assert_called_once_with(
+                    {"router1": {"status": 0, "output": "ok"}},
+                    query=f"Playbook: {str(playbook_path)}",
+                    chunk_callback=ANY
+                )
+
+def test_ai_generate_wizard_save(app, tmp_path):
+    """Test that ai_generate wizard runs interactive chat loop, asks for validation and saves YAML."""
+    dest_yaml = tmp_path / "playbook.yaml"
+    
+    mock_chat = MagicMock(return_value={
+        "response": "Here is your playbook.",
+        "chat_history": [],
+        "playbook_yaml": "tasks:\n  - name: mytask"
+    })
+    app.services.ai.build_playbook_chat = mock_chat
+    
+    # Mock rich.prompt.Prompt.ask to simulate User inputting prompt and then 'y' to save
+    with patch("rich.prompt.Prompt.ask", side_effect=["create a basic task", "y"]):
+        app.start(["run", "--generate-ai", str(dest_yaml)])
+        
+        mock_chat.assert_called_once_with("create a basic task", chat_history=[], chunk_callback=ANY)
+        assert os.path.exists(dest_yaml)
+        with open(dest_yaml) as f:
+            content = f.read()
+            assert "tasks:" in content
+
+def test_ai_generate_wizard_run(app, tmp_path):
+    """Test that ai_generate wizard runs, saves the playbook and executes it when choosing 'run'."""
+    dest_yaml = tmp_path / "playbook_run.yaml"
+    
+    mock_chat = MagicMock(return_value={
+        "response": "Here is your playbook.",
+        "chat_history": [],
+        "playbook_yaml": "tasks:\n  - name: mytask\n    action: run\n    nodes: '*'\n    commands: ['show version']\n    output: stdout"
+    })
+    app.services.ai.build_playbook_chat = mock_chat
+    
+    with patch("rich.prompt.Prompt.ask", side_effect=["create task", "run"]):
+        with patch("connpy.cli.run_handler.RunHandler.yaml_run") as mock_yaml_run:
+            app.start(["run", "--generate-ai", str(dest_yaml)])
+            
+            mock_chat.assert_called_once_with("create task", chat_history=[], chunk_callback=ANY)
+            assert os.path.exists(dest_yaml)
+            with open(dest_yaml) as f:
+                content = f.read()
+                assert "tasks:" in content
+            
+            mock_yaml_run.assert_called_once()
+            args = mock_yaml_run.call_args[0][0]
+            assert args.data == [str(dest_yaml)]

connpy/tests/test_run_ai.py

@@ -0,0 +1,296 @@
+import pytest
+import json
+from unittest.mock import patch, MagicMock
+from connpy.ai import PlaybookBuilderAgent
+from connpy.services.ai_service import AIService
+
+# =========================================================================
+# PlaybookBuilderAgent validation tests
+# =========================================================================
+
+def test_validate_playbook_valid(ai_config):
+    """Verifies that a valid canonical tasks[] playbook passes validation."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    valid_yaml = """
+    tasks:
+    - name: "Apply standard config"
+      action: "run"
+      nodes: "router1"
+      commands:
+      - "conf t"
+      - "end"
+      output: "stdout"
+    - name: "Verify connectivity"
+      action: "test"
+      nodes: "router1"
+      commands:
+      - "ping 10.0.0.1"
+      expected: "!"
+      output: "stdout"
+    """
+    
+    res = agent.validate_playbook(valid_yaml)
+    assert res["valid"] is True
+    assert "valid" in res["message"].lower()
+
+def test_validate_playbook_invalid_yaml(ai_config):
+    """Verifies that syntax errors in YAML are caught and reported."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    invalid_yaml = """
+    tasks:
+    - name: "Broken task"
+      action: "run
+      nodes: "router1"
+    """
+    
+    res = agent.validate_playbook(invalid_yaml)
+    assert res["valid"] is False
+    assert "syntax error" in res["error"].lower()
+
+def test_validate_playbook_missing_tasks_key(ai_config):
+    """Verifies that a playbook without tasks root key is invalid."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    invalid_yaml = """
+    not_tasks:
+    - name: "Apply standard config"
+      action: "run"
+      nodes: "router1"
+      commands:
+      - "conf t"
+      output: "stdout"
+    """
+    
+    res = agent.validate_playbook(invalid_yaml)
+    assert res["valid"] is False
+    assert "missing mandatory root 'tasks' key" in res["error"].lower()
+
+def test_validate_playbook_missing_mandatory_fields(ai_config):
+    """Verifies that missing name, action, nodes, commands, or output triggers a validation failure."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    # Missing nodes
+    invalid_yaml = """
+    tasks:
+    - name: "Apply standard config"
+      action: "run"
+      commands:
+      - "conf t"
+      output: "stdout"
+    """
+    res = agent.validate_playbook(invalid_yaml)
+    assert res["valid"] is False
+    assert "missing mandatory fields" in res["error"].lower()
+    assert "nodes" in res["error"]
+
+def test_validate_playbook_invalid_action(ai_config):
+    """Verifies that an unsupported action type is caught."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    invalid_yaml = """
+    tasks:
+    - name: "Apply standard config"
+      action: "delete_everything"
+      nodes: "router1"
+      commands:
+      - "conf t"
+      output: "stdout"
+    """
+    res = agent.validate_playbook(invalid_yaml)
+    assert res["valid"] is False
+    assert "invalid action" in res["error"].lower()
+
+def test_validate_playbook_missing_expected_in_test(ai_config):
+    """Verifies that action 'test' requires the expected field."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    invalid_yaml = """
+    tasks:
+    - name: "Apply standard config"
+      action: "test"
+      nodes: "router1"
+      commands:
+      - "ping 10.0.0.1"
+      output: "stdout"
+    """
+    res = agent.validate_playbook(invalid_yaml)
+    assert res["valid"] is False
+    assert "missing the mandatory 'expected' key" in res["error"].lower()
+
+def test_validate_playbook_invalid_nodes_type(ai_config):
+    """Verifies that nodes of invalid type (e.g. integer) is caught."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    invalid_yaml = """
+    tasks:
+    - name: "Apply config"
+      action: "run"
+      nodes: 12345
+      commands:
+      - "conf t"
+      output: "stdout"
+    """
+    res = agent.validate_playbook(invalid_yaml)
+    assert res["valid"] is False
+    assert "nodes' must be a string (regex) or a list of strings (regexes)" in res["error"]
+
+def test_validate_playbook_invalid_nodes_list_item(ai_config):
+    """Verifies that nodes list containing non-string items is caught."""
+    agent = PlaybookBuilderAgent(ai_config)
+    
+    invalid_yaml = """
+    tasks:
+    - name: "Apply config"
+      action: "run"
+      nodes:
+      - "router1"
+      - 9999
+      commands:
+      - "conf t"
+      output: "stdout"
+    """
+    res = agent.validate_playbook(invalid_yaml)
+    assert res["valid"] is False
+    assert "list contains a non-string value" in res["error"]
+
+
+# =========================================================================
+# AIService new methods delegation tests
+# =========================================================================
+
+def test_build_playbook_chat_delegation(ai_config):
+    """Verifies that build_playbook_chat instantiates PlaybookBuilderAgent and delegates ask."""
+    service = AIService(ai_config)
+    
+    with patch("connpy.ai.PlaybookBuilderAgent") as MockAgentClass:
+        mock_agent = MockAgentClass.return_value
+        mock_agent.ask.return_value = {"response": "Mock response", "chat_history": []}
+        
+        history = [{"role": "user", "content": "build playbook"}]
+        res = service.build_playbook_chat("help me", chat_history=history)
+        
+        MockAgentClass.assert_called_once_with(ai_config)
+        mock_agent.ask.assert_called_once_with("help me", chat_history=history, status=None, chunk_callback=None)
+        assert res["response"] == "Mock response"
+
+def test_analyze_execution_results_delegation(ai_config):
+    """Verifies that analyze_execution_results formats prompt with @architect and delegates to self.ask."""
+    service = AIService(ai_config)
+    service.ask = MagicMock()
+    
+    results = {"router1": {"output": "success", "status": 0}}
+    service.analyze_execution_results(results, query="diagnose border")
+    
+    service.ask.assert_called_once()
+    args, kwargs = service.ask.call_args
+    prompt = args[0]
+    
+    assert prompt.startswith("@architect:")
+    assert "diagnose border" in prompt
+    assert "Results Data:" in prompt
+    assert "router1" in prompt
+    assert kwargs.get("one_shot") is True
+
+def test_predict_execution_results_delegation(ai_config):
+    """Verifies that predict_execution_results formats prompt with @engineer and delegates to self.ask."""
+    service = AIService(ai_config)
+    service.ask = MagicMock()
+    
+    nodes = ["router1", "router2"]
+    commands = ["conf t", "interface lo0"]
+    service.predict_execution_results(nodes, commands)
+    
+    service.ask.assert_called_once()
+    args, kwargs = service.ask.call_args
+    prompt = args[0]
+    
+    assert prompt.startswith("@engineer:")
+    assert "Preflight Simulation Agent" in prompt
+    assert "router1, router2" in prompt
+    assert "conf t" in prompt
+    assert "interface lo0" in prompt
+
+
+# =========================================================================
+# gRPC Integration Tests for AIService
+# =========================================================================
+
+import grpc
+from concurrent import futures
+from connpy.grpc_layer import server, connpy_pb2, connpy_pb2_grpc, stubs
+
+class TestGRPCAIIntegration:
+    @pytest.fixture
+    def grpc_server(self, populated_config):
+        """Starts a local gRPC server for IA integration testing."""
+        srv = grpc.server(futures.ThreadPoolExecutor(max_workers=5))
+        connpy_pb2_grpc.add_AIServiceServicer_to_server(server.ServerServicer(populated_config).ai if hasattr(server, 'ServerServicer') else server.AIServicer(populated_config), srv)
+        port = srv.add_insecure_port('127.0.0.1:0')
+        srv.start()
+        yield f"127.0.0.1:{port}"
+        srv.stop(0)
+
+    @pytest.fixture
+    def channel(self, grpc_server):
+        with grpc.insecure_channel(grpc_server) as channel:
+            yield channel
+
+    @pytest.fixture
+    def ai_stub(self, channel):
+        return stubs.AIStub(channel, "localhost")
+
+    def test_build_playbook_chat_grpc(self, ai_stub, populated_config):
+        """Verifies that build_playbook_chat gRPC stream functions correctly."""
+        # Mock PlaybookBuilderAgent.ask to simulate agent response stream
+        def mock_ask(user_input, chat_history=None, status=None, debug=False, chunk_callback=None):
+            if chunk_callback:
+                chunk_callback("Generated Tasks:\n- name: config")
+            return {"response": "Done", "playbook_yaml": "tasks:\n- name: config"}
+
+        with patch("connpy.ai.PlaybookBuilderAgent.ask", side_effect=mock_ask):
+            chunks = []
+            def callback(chunk):
+                chunks.append(chunk)
+
+            res = ai_stub.build_playbook_chat("make playbook", chunk_callback=callback)
+            assert "tasks:" in res["playbook_yaml"]
+            assert len(chunks) > 0
+            assert "Generated Tasks:" in chunks[0]
+
+    def test_analyze_execution_results_grpc(self, ai_stub, populated_config):
+        """Verifies that analyze_execution_results gRPC stream functions correctly."""
+        # Mock AIService.ask to simulate response stream
+        def mock_ask(prompt, status=None, debug=False, chunk_callback=None, **kwargs):
+            if chunk_callback:
+                chunk_callback("Results are optimal.")
+            return {"response": "Done"}
+
+        with patch.object(AIService, "ask", side_effect=mock_ask):
+            chunks = []
+            def callback(chunk):
+                chunks.append(chunk)
+
+            res = ai_stub.analyze_execution_results({"r1": "ok"}, query="test query", chunk_callback=callback)
+            assert res is not None
+            assert len(chunks) > 0
+            assert "optimal" in chunks[0]
+
+    def test_predict_execution_results_grpc(self, ai_stub, populated_config):
+        """Verifies that predict_execution_results gRPC stream functions correctly."""
+        # Mock AIService.ask to simulate response stream
+        def mock_ask(prompt, status=None, debug=False, chunk_callback=None, **kwargs):
+            if chunk_callback:
+                chunk_callback("Commands are safe.")
+            return {"response": "Done"}
+
+        with patch.object(AIService, "ask", side_effect=mock_ask):
+            chunks = []
+            def callback(chunk):
+                chunks.append(chunk)
+
+            res = ai_stub.predict_execution_results(["r1"], ["show version"], chunk_callback=callback)
+            assert res is not None
+            assert len(chunks) > 0
+            assert "safe" in chunks[0]

docs/connpy/cli/ai_handler.html

@@ -140,7 +140,7 @@ el.replaceWith(d);
             
     def single_question(self, args, session_id):
         query = " ".join(args.ask)
-        with console.status("[ai_status]Agent is thinking and analyzing...") as status:
+        with console.status("[ai_status]Agent is thinking and analyzing...[/ai_status]") as status:
             result = self.app.myai.ask(query, status=status, debug=args.debug, session_id=session_id, trust=args.trust, **self.ai_overrides)
         
         responder = result.get("responder", "engineer")
@@ -177,7 +177,7 @@ el.replaceWith(d);
                 if not user_query.strip(): continue
                 if user_query.lower() in ['exit', 'quit', 'bye', 'cancel']: break
                 
-                with console.status("[ai_status]Agent is thinking...") as status:
+                with console.status("[ai_status]Agent is thinking...[/ai_status]") as status:
                     result = self.app.myai.ask(user_query, chat_history=history, status=status, debug=args.debug, trust=args.trust, session_id=session_id, **self.ai_overrides)
                 
                 new_history = result.get("chat_history")
@@ -583,7 +583,7 @@ el.replaceWith(d);
             if not user_query.strip(): continue
             if user_query.lower() in ['exit', 'quit', 'bye', 'cancel']: break
             
-            with console.status("[ai_status]Agent is thinking...") as status:
+            with console.status("[ai_status]Agent is thinking...[/ai_status]") as status:
                 result = self.app.myai.ask(user_query, chat_history=history, status=status, debug=args.debug, trust=args.trust, session_id=session_id, **self.ai_overrides)
             
             new_history = result.get("chat_history")
@@ -618,7 +618,7 @@ el.replaceWith(d);
 </summary>
 <pre><code class="python">def single_question(self, args, session_id):
     query = &#34; &#34;.join(args.ask)
-    with console.status(&#34;[ai_status]Agent is thinking and analyzing...&#34;) as status:
+    with console.status(&#34;[ai_status]Agent is thinking and analyzing...[/ai_status]&#34;) as status:
         result = self.app.myai.ask(query, status=status, debug=args.debug, session_id=session_id, trust=args.trust, **self.ai_overrides)
     
     responder = result.get(&#34;responder&#34;, &#34;engineer&#34;)

docs/connpy/cli/run_handler.html

@@ -63,7 +63,12 @@ el.replaceWith(d);
     def dispatch(self, args):
         if len(args.data) > 1:
             args.action = "noderun"
-        actions = {"noderun": self.node_run, "generate": self.yaml_generate, "run": self.yaml_run}
+        actions = {
+            "noderun": self.node_run,
+            "generate": self.yaml_generate,
+            "generate_ai": self.ai_generate,
+            "run": self.yaml_run
+        }
         return actions.get(args.action)(args)
 
     def node_run(self, args):
@@ -81,6 +86,41 @@ el.replaceWith(d);
             
         commands = [" ".join(args.data[1:])]
 
+        # Check for Preflight AI simulation
+        if getattr(args, "preflight_ai", False):
+            matched_node_names = [n.get("name") if isinstance(n, dict) else n for n in matched_nodes]
+            
+            renderer = printer.BlockMarkdownRenderer()
+            first_chunk = True
+            status_context = printer.console.status("[ai_status]Simulating execution...[/ai_status]")
+            
+            def callback(chunk):
+                nonlocal first_chunk
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title="[engineer][bold]Preflight AI Simulation[/bold][/engineer]", style="engineer"))
+                    first_chunk = False
+                renderer.feed(chunk)
+            
+            try:
+                status_context.start()
+                self.app.services.ai.predict_execution_results(
+                    matched_node_names,
+                    commands,
+                    chunk_callback=callback
+                )
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title="[engineer][bold]Preflight AI Simulation[/bold][/engineer]", style="engineer"))
+                renderer.flush()
+                printer.console.print(Rule(style="engineer"))
+            except Exception as e:
+                printer.error(f"Preflight AI simulation failed: {e}")
+                sys.exit(1)
+            sys.exit(0)
+
         try:
             header_printed = False
 
@@ -118,6 +158,40 @@ el.replaceWith(d);
                 )
                 printer.run_summary(results)
 
+            # Analyze execution results if requested
+            if getattr(args, "analyze", None) is not None:
+                printer.console.print()
+                
+                renderer = printer.BlockMarkdownRenderer()
+                first_chunk = True
+                status_context = printer.console.status("[ai_status]Analyzing execution results...[/ai_status]")
+                
+                def callback(chunk):
+                    nonlocal first_chunk
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Analysis[/bold][/architect]", style="architect"))
+                        first_chunk = False
+                    renderer.feed(chunk)
+                
+                query = args.analyze if args.analyze else " ".join(args.data[1:])
+                try:
+                    status_context.start()
+                    self.app.services.ai.analyze_execution_results(
+                        results,
+                        query=query,
+                        chunk_callback=callback
+                    )
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Analysis[/bold][/architect]", style="architect"))
+                    renderer.flush()
+                    printer.console.print(Rule(style="architect"))
+                except Exception as e:
+                    printer.error(f"AI Analysis failed: {e}")
+
         except ConnpyError as e:
             printer.error(str(e))
             sys.exit(1)
@@ -138,8 +212,105 @@ el.replaceWith(d);
             with open(path, "r") as f:
                 playbook = yaml.load(f, Loader=yaml.FullLoader)
 
+            # Check preflight first before any task runs
+            if getattr(args, "preflight_ai", False):
+                preflight_failed = False
                 for task in playbook.get("tasks", []):
-                self.cli_run(task)
+                    name = task.get("name", "Task")
+                    nodelist = task.get("nodes", [])
+                    commands = task.get("commands", [])
+                    
+                    # Resolve nodes to names
+                    try:
+                        if isinstance(nodelist, str):
+                            resolved_nodes = self.app.services.nodes.list_nodes(nodelist)
+                        elif isinstance(nodelist, list):
+                            resolved_nodes = []
+                            for item in nodelist:
+                                matches = self.app.services.nodes.list_nodes(item)
+                                for m in matches:
+                                    if m not in resolved_nodes:
+                                        resolved_nodes.append(m)
+                        else:
+                            resolved_nodes = []
+                    except Exception:
+                        resolved_nodes = []
+                    
+                    resolved_names = [n.get("name") if isinstance(n, dict) else n for n in resolved_nodes]
+                    printer.console.print(f"\n[bold]Task: {name}[/bold] (Preflight for {len(resolved_names)} nodes)")
+                    
+                    renderer = printer.BlockMarkdownRenderer()
+                    first_chunk = True
+                    status_context = printer.console.status("[ai_status]Simulating execution...[/ai_status]")
+                    
+                    def callback(chunk):
+                        nonlocal first_chunk
+                        if first_chunk:
+                            try: status_context.stop()
+                            except: pass
+                            printer.console.print(Rule(title=f"[engineer][bold]Preflight AI Simulation: {name}[/bold][/engineer]", style="engineer"))
+                            first_chunk = False
+                        renderer.feed(chunk)
+                    try:
+                        status_context.start()
+                        self.app.services.ai.predict_execution_results(
+                            resolved_names,
+                            commands,
+                            chunk_callback=callback
+                        )
+                        if first_chunk:
+                            try: status_context.stop()
+                            except: pass
+                            printer.console.print(Rule(title=f"[engineer][bold]Preflight AI Simulation: {name}[/bold][/engineer]", style="engineer"))
+                        renderer.flush()
+                        printer.console.print(Rule(style="engineer"))
+                    except Exception as e:
+                        printer.error(f"Preflight AI simulation failed for task {name}: {e}")
+                        preflight_failed = True
+                if preflight_failed:
+                    sys.exit(1)
+                sys.exit(0)
+
+            # Standard run
+            results_all = {}
+            for task in playbook.get("tasks", []):
+                task_res = self.cli_run(task)
+                if task_res:
+                    results_all.update(task_res)
+
+            # If analyze is enabled, run analysis on accumulated results
+            if getattr(args, "analyze", None) is not None:
+                printer.console.print()
+                
+                renderer = printer.BlockMarkdownRenderer()
+                first_chunk = True
+                status_context = printer.console.status("[ai_status]Analyzing playbook execution results...[/ai_status]")
+                
+                def callback(chunk):
+                    nonlocal first_chunk
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Playbook Analysis[/bold][/architect]", style="architect"))
+                        first_chunk = False
+                    renderer.feed(chunk)
+                
+                query = args.analyze if args.analyze else f"Playbook: {path}"
+                try:
+                    status_context.start()
+                    self.app.services.ai.analyze_execution_results(
+                        results_all,
+                        query=query,
+                        chunk_callback=callback
+                    )
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title="[architect][bold]Network Architect AI Playbook Analysis[/bold][/architect]", style="architect"))
+                    renderer.flush()
+                    printer.console.print(Rule(style="architect"))
+                except Exception as e:
+                    printer.error(f"AI Analysis failed: {e}")
 
         except Exception as e:
             printer.error(f"Failed to run playbook {path}: {e}")
@@ -184,6 +355,7 @@ el.replaceWith(d);
 
         nodelist = resolved_nodes
 
+        results = {}
         try:
             header_printed = False
             if action == "run":
@@ -244,12 +416,243 @@ el.replaceWith(d);
                 # ALWAYS show the aggregate summary at the end
                 printer.test_summary(results)
                 
+            return results
+
         except ConnpyError as e:
-            printer.error(str(e))</code></pre>
+            printer.error(str(e))
+            return {}
+
+    def ai_generate(self, args):
+        from rich.prompt import Prompt
+        from rich.rule import Rule
+        from rich.panel import Panel
+        from rich.syntax import Syntax
+
+        dest_file = args.data[0]
+        if os.path.exists(dest_file):
+            printer.error(f&#34;File &#39;{dest_file}&#39; already exists.&#34;)
+            sys.exit(14)
+
+        chat_history = []
+        
+        # Consistent layout opening matching global AI (engineer style)
+        from rich.markdown import Markdown
+        printer.console.print(Rule(style=&#34;engineer&#34;))
+        printer.console.print(Markdown(&#34;**Playbook Builder AI**: Welcome! Describe the automation workflow you want to design.\nType **exit** to quit.\n&#34;))
+        printer.console.print(Rule(style=&#34;engineer&#34;))
+        
+        while True:
+            try:
+                user_prompt = Prompt.ask(&#34;[user_prompt]User[/user_prompt]&#34;)
+            except (KeyboardInterrupt, EOFError):
+                printer.console.print()
+                printer.warning(&#34;Operation cancelled by user.&#34;)
+                break
+                
+            if user_prompt.strip().lower() in [&#34;exit&#34;, &#34;quit&#34;]:
+                printer.info(&#34;Exiting AI Assistant.&#34;)
+                break
+                
+            if not user_prompt.strip():
+                continue
+                
+            printer.console.print()
+            
+            renderer = printer.BlockMarkdownRenderer()
+            first_chunk = True
+            status_context = printer.console.status(&#34;[ai_status]Agent is thinking...[/ai_status]&#34;)
+            
+            def callback(chunk):
+                nonlocal first_chunk
+                if first_chunk:
+                    try:
+                        status_context.stop()
+                    except:
+                        pass
+                    printer.console.print(Rule(title=&#34;[engineer][bold]Playbook Builder AI[/bold][/engineer]&#34;, style=&#34;engineer&#34;))
+                    first_chunk = False
+                renderer.feed(chunk)
+                
+            try:
+                status_context.start()
+                res = self.app.services.ai.build_playbook_chat(
+                    user_prompt,
+                    chat_history=chat_history,
+                    chunk_callback=callback
+                )
+                if first_chunk:
+                    try:
+                        status_context.stop()
+                    except:
+                        pass
+                renderer.flush()
+                if not first_chunk:
+                    printer.console.print(Rule(style=&#34;engineer&#34;))
+                
+                # Update history
+                if res and &#34;chat_history&#34; in res:
+                    chat_history = res[&#34;chat_history&#34;]
+                
+                # Check if the agent returned a validated playbook YAML
+                if res and &#34;playbook_yaml&#34; in res and res[&#34;playbook_yaml&#34;]:
+                    yaml_content = res[&#34;playbook_yaml&#34;]
+                    printer.console.print()
+                    printer.success(&#34;Playbook YAML successfully generated and validated.&#34;)
+                    
+                    # Show the YAML inside a beautiful panel matching AI style (with engineer borders)
+                    syntax = Syntax(yaml_content, &#34;yaml&#34;, theme=&#34;ansi_dark&#34;, word_wrap=True, background_color=&#34;default&#34;)
+                    panel = Panel(syntax, title=&#34;[engineer][bold]Resulting Playbook[/bold][/engineer]&#34;, border_style=&#34;engineer&#34;, expand=False)
+                    printer.console.print(panel)
+                    
+                    # Ask if the user wants to save it
+                    try:
+                        save_confirm = Prompt.ask(
+                            f&#34;\nDo you want to save this playbook to &#39;{dest_file}&#39;?&#34;,
+                            choices=[&#34;y&#34;, &#34;n&#34;, &#34;run&#34;],
+                            default=&#34;y&#34;
+                        )
+                    except (KeyboardInterrupt, EOFError):
+                        printer.console.print()
+                        printer.warning(&#34;Saving skipped.&#34;)
+                        break
+                        
+                    choice = save_confirm.strip().lower()
+                    if choice in [&#34;y&#34;, &#34;yes&#34;, &#34;run&#34;]:
+                        with open(dest_file, &#34;w&#34;) as f:
+                            f.write(yaml_content)
+                        printer.success(f&#34;Playbook saved successfully to &#39;{dest_file}&#39;&#34;)
+                        if choice == &#34;run&#34;:
+                            printer.console.print()
+                            printer.info(&#34;Executing the saved playbook...&#34;)
+                            self.yaml_run(args)
+                        break
+                    else:
+                        printer.warning(&#34;Playbook not saved. You can continue describing changes or exit.&#34;)
+            except Exception as e:
+                printer.error(f&#34;Error in AI chat: {e}&#34;)</code></pre>
 </details>
 <div class="desc"></div>
 <h3>Methods</h3>
 <dl>
+<dt id="connpy.cli.run_handler.RunHandler.ai_generate"><code class="name flex">
+<span>def <span class="ident">ai_generate</span></span>(<span>self, args)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def ai_generate(self, args):
+    from rich.prompt import Prompt
+    from rich.rule import Rule
+    from rich.panel import Panel
+    from rich.syntax import Syntax
+
+    dest_file = args.data[0]
+    if os.path.exists(dest_file):
+        printer.error(f&#34;File &#39;{dest_file}&#39; already exists.&#34;)
+        sys.exit(14)
+
+    chat_history = []
+    
+    # Consistent layout opening matching global AI (engineer style)
+    from rich.markdown import Markdown
+    printer.console.print(Rule(style=&#34;engineer&#34;))
+    printer.console.print(Markdown(&#34;**Playbook Builder AI**: Welcome! Describe the automation workflow you want to design.\nType **exit** to quit.\n&#34;))
+    printer.console.print(Rule(style=&#34;engineer&#34;))
+    
+    while True:
+        try:
+            user_prompt = Prompt.ask(&#34;[user_prompt]User[/user_prompt]&#34;)
+        except (KeyboardInterrupt, EOFError):
+            printer.console.print()
+            printer.warning(&#34;Operation cancelled by user.&#34;)
+            break
+            
+        if user_prompt.strip().lower() in [&#34;exit&#34;, &#34;quit&#34;]:
+            printer.info(&#34;Exiting AI Assistant.&#34;)
+            break
+            
+        if not user_prompt.strip():
+            continue
+            
+        printer.console.print()
+        
+        renderer = printer.BlockMarkdownRenderer()
+        first_chunk = True
+        status_context = printer.console.status(&#34;[ai_status]Agent is thinking...[/ai_status]&#34;)
+        
+        def callback(chunk):
+            nonlocal first_chunk
+            if first_chunk:
+                try:
+                    status_context.stop()
+                except:
+                    pass
+                printer.console.print(Rule(title=&#34;[engineer][bold]Playbook Builder AI[/bold][/engineer]&#34;, style=&#34;engineer&#34;))
+                first_chunk = False
+            renderer.feed(chunk)
+            
+        try:
+            status_context.start()
+            res = self.app.services.ai.build_playbook_chat(
+                user_prompt,
+                chat_history=chat_history,
+                chunk_callback=callback
+            )
+            if first_chunk:
+                try:
+                    status_context.stop()
+                except:
+                    pass
+            renderer.flush()
+            if not first_chunk:
+                printer.console.print(Rule(style=&#34;engineer&#34;))
+            
+            # Update history
+            if res and &#34;chat_history&#34; in res:
+                chat_history = res[&#34;chat_history&#34;]
+            
+            # Check if the agent returned a validated playbook YAML
+            if res and &#34;playbook_yaml&#34; in res and res[&#34;playbook_yaml&#34;]:
+                yaml_content = res[&#34;playbook_yaml&#34;]
+                printer.console.print()
+                printer.success(&#34;Playbook YAML successfully generated and validated.&#34;)
+                
+                # Show the YAML inside a beautiful panel matching AI style (with engineer borders)
+                syntax = Syntax(yaml_content, &#34;yaml&#34;, theme=&#34;ansi_dark&#34;, word_wrap=True, background_color=&#34;default&#34;)
+                panel = Panel(syntax, title=&#34;[engineer][bold]Resulting Playbook[/bold][/engineer]&#34;, border_style=&#34;engineer&#34;, expand=False)
+                printer.console.print(panel)
+                
+                # Ask if the user wants to save it
+                try:
+                    save_confirm = Prompt.ask(
+                        f&#34;\nDo you want to save this playbook to &#39;{dest_file}&#39;?&#34;,
+                        choices=[&#34;y&#34;, &#34;n&#34;, &#34;run&#34;],
+                        default=&#34;y&#34;
+                    )
+                except (KeyboardInterrupt, EOFError):
+                    printer.console.print()
+                    printer.warning(&#34;Saving skipped.&#34;)
+                    break
+                    
+                choice = save_confirm.strip().lower()
+                if choice in [&#34;y&#34;, &#34;yes&#34;, &#34;run&#34;]:
+                    with open(dest_file, &#34;w&#34;) as f:
+                        f.write(yaml_content)
+                    printer.success(f&#34;Playbook saved successfully to &#39;{dest_file}&#39;&#34;)
+                    if choice == &#34;run&#34;:
+                        printer.console.print()
+                        printer.info(&#34;Executing the saved playbook...&#34;)
+                        self.yaml_run(args)
+                    break
+                else:
+                    printer.warning(&#34;Playbook not saved. You can continue describing changes or exit.&#34;)
+        except Exception as e:
+            printer.error(f&#34;Error in AI chat: {e}&#34;)</code></pre>
+</details>
+<div class="desc"></div>
+</dd>
 <dt id="connpy.cli.run_handler.RunHandler.cli_run"><code class="name flex">
 <span>def <span class="ident">cli_run</span></span>(<span>self, script)</span>
 </code></dt>
@@ -297,6 +700,7 @@ el.replaceWith(d);
 
     nodelist = resolved_nodes
 
+    results = {}
     try:
         header_printed = False
         if action == &#34;run&#34;:
@@ -357,8 +761,11 @@ el.replaceWith(d);
             # ALWAYS show the aggregate summary at the end
             printer.test_summary(results)
             
+        return results
+
     except ConnpyError as e:
-        printer.error(str(e))</code></pre>
+        printer.error(str(e))
+        return {}</code></pre>
 </details>
 <div class="desc"></div>
 </dd>
@@ -373,7 +780,12 @@ el.replaceWith(d);
 <pre><code class="python">def dispatch(self, args):
     if len(args.data) &gt; 1:
         args.action = &#34;noderun&#34;
-    actions = {&#34;noderun&#34;: self.node_run, &#34;generate&#34;: self.yaml_generate, &#34;run&#34;: self.yaml_run}
+    actions = {
+        &#34;noderun&#34;: self.node_run,
+        &#34;generate&#34;: self.yaml_generate,
+        &#34;generate_ai&#34;: self.ai_generate,
+        &#34;run&#34;: self.yaml_run
+    }
     return actions.get(args.action)(args)</code></pre>
 </details>
 <div class="desc"></div>
@@ -401,6 +813,41 @@ el.replaceWith(d);
         
     commands = [&#34; &#34;.join(args.data[1:])]
 
+    # Check for Preflight AI simulation
+    if getattr(args, &#34;preflight_ai&#34;, False):
+        matched_node_names = [n.get(&#34;name&#34;) if isinstance(n, dict) else n for n in matched_nodes]
+        
+        renderer = printer.BlockMarkdownRenderer()
+        first_chunk = True
+        status_context = printer.console.status(&#34;[ai_status]Simulating execution...[/ai_status]&#34;)
+        
+        def callback(chunk):
+            nonlocal first_chunk
+            if first_chunk:
+                try: status_context.stop()
+                except: pass
+                printer.console.print(Rule(title=&#34;[engineer][bold]Preflight AI Simulation[/bold][/engineer]&#34;, style=&#34;engineer&#34;))
+                first_chunk = False
+            renderer.feed(chunk)
+        
+        try:
+            status_context.start()
+            self.app.services.ai.predict_execution_results(
+                matched_node_names,
+                commands,
+                chunk_callback=callback
+            )
+            if first_chunk:
+                try: status_context.stop()
+                except: pass
+                printer.console.print(Rule(title=&#34;[engineer][bold]Preflight AI Simulation[/bold][/engineer]&#34;, style=&#34;engineer&#34;))
+            renderer.flush()
+            printer.console.print(Rule(style=&#34;engineer&#34;))
+        except Exception as e:
+            printer.error(f&#34;Preflight AI simulation failed: {e}&#34;)
+            sys.exit(1)
+        sys.exit(0)
+
     try:
         header_printed = False
 
@@ -438,6 +885,40 @@ el.replaceWith(d);
             )
             printer.run_summary(results)
 
+        # Analyze execution results if requested
+        if getattr(args, &#34;analyze&#34;, None) is not None:
+            printer.console.print()
+            
+            renderer = printer.BlockMarkdownRenderer()
+            first_chunk = True
+            status_context = printer.console.status(&#34;[ai_status]Analyzing execution results...[/ai_status]&#34;)
+            
+            def callback(chunk):
+                nonlocal first_chunk
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title=&#34;[architect][bold]Network Architect AI Analysis[/bold][/architect]&#34;, style=&#34;architect&#34;))
+                    first_chunk = False
+                renderer.feed(chunk)
+            
+            query = args.analyze if args.analyze else &#34; &#34;.join(args.data[1:])
+            try:
+                status_context.start()
+                self.app.services.ai.analyze_execution_results(
+                    results,
+                    query=query,
+                    chunk_callback=callback
+                )
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title=&#34;[architect][bold]Network Architect AI Analysis[/bold][/architect]&#34;, style=&#34;architect&#34;))
+                renderer.flush()
+                printer.console.print(Rule(style=&#34;architect&#34;))
+            except Exception as e:
+                printer.error(f&#34;AI Analysis failed: {e}&#34;)
+
     except ConnpyError as e:
         printer.error(str(e))
         sys.exit(1)</code></pre>
@@ -478,8 +959,105 @@ el.replaceWith(d);
         with open(path, &#34;r&#34;) as f:
             playbook = yaml.load(f, Loader=yaml.FullLoader)
 
+        # Check preflight first before any task runs
+        if getattr(args, &#34;preflight_ai&#34;, False):
+            preflight_failed = False
             for task in playbook.get(&#34;tasks&#34;, []):
-            self.cli_run(task)
+                name = task.get(&#34;name&#34;, &#34;Task&#34;)
+                nodelist = task.get(&#34;nodes&#34;, [])
+                commands = task.get(&#34;commands&#34;, [])
+                
+                # Resolve nodes to names
+                try:
+                    if isinstance(nodelist, str):
+                        resolved_nodes = self.app.services.nodes.list_nodes(nodelist)
+                    elif isinstance(nodelist, list):
+                        resolved_nodes = []
+                        for item in nodelist:
+                            matches = self.app.services.nodes.list_nodes(item)
+                            for m in matches:
+                                if m not in resolved_nodes:
+                                    resolved_nodes.append(m)
+                    else:
+                        resolved_nodes = []
+                except Exception:
+                    resolved_nodes = []
+                
+                resolved_names = [n.get(&#34;name&#34;) if isinstance(n, dict) else n for n in resolved_nodes]
+                printer.console.print(f&#34;\n[bold]Task: {name}[/bold] (Preflight for {len(resolved_names)} nodes)&#34;)
+                
+                renderer = printer.BlockMarkdownRenderer()
+                first_chunk = True
+                status_context = printer.console.status(&#34;[ai_status]Simulating execution...[/ai_status]&#34;)
+                
+                def callback(chunk):
+                    nonlocal first_chunk
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title=f&#34;[engineer][bold]Preflight AI Simulation: {name}[/bold][/engineer]&#34;, style=&#34;engineer&#34;))
+                        first_chunk = False
+                    renderer.feed(chunk)
+                try:
+                    status_context.start()
+                    self.app.services.ai.predict_execution_results(
+                        resolved_names,
+                        commands,
+                        chunk_callback=callback
+                    )
+                    if first_chunk:
+                        try: status_context.stop()
+                        except: pass
+                        printer.console.print(Rule(title=f&#34;[engineer][bold]Preflight AI Simulation: {name}[/bold][/engineer]&#34;, style=&#34;engineer&#34;))
+                    renderer.flush()
+                    printer.console.print(Rule(style=&#34;engineer&#34;))
+                except Exception as e:
+                    printer.error(f&#34;Preflight AI simulation failed for task {name}: {e}&#34;)
+                    preflight_failed = True
+            if preflight_failed:
+                sys.exit(1)
+            sys.exit(0)
+
+        # Standard run
+        results_all = {}
+        for task in playbook.get(&#34;tasks&#34;, []):
+            task_res = self.cli_run(task)
+            if task_res:
+                results_all.update(task_res)
+
+        # If analyze is enabled, run analysis on accumulated results
+        if getattr(args, &#34;analyze&#34;, None) is not None:
+            printer.console.print()
+            
+            renderer = printer.BlockMarkdownRenderer()
+            first_chunk = True
+            status_context = printer.console.status(&#34;[ai_status]Analyzing playbook execution results...[/ai_status]&#34;)
+            
+            def callback(chunk):
+                nonlocal first_chunk
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title=&#34;[architect][bold]Network Architect AI Playbook Analysis[/bold][/architect]&#34;, style=&#34;architect&#34;))
+                    first_chunk = False
+                renderer.feed(chunk)
+            
+            query = args.analyze if args.analyze else f&#34;Playbook: {path}&#34;
+            try:
+                status_context.start()
+                self.app.services.ai.analyze_execution_results(
+                    results_all,
+                    query=query,
+                    chunk_callback=callback
+                )
+                if first_chunk:
+                    try: status_context.stop()
+                    except: pass
+                    printer.console.print(Rule(title=&#34;[architect][bold]Network Architect AI Playbook Analysis[/bold][/architect]&#34;, style=&#34;architect&#34;))
+                renderer.flush()
+                printer.console.print(Rule(style=&#34;architect&#34;))
+            except Exception as e:
+                printer.error(f&#34;AI Analysis failed: {e}&#34;)
 
     except Exception as e:
         printer.error(f&#34;Failed to run playbook {path}: {e}&#34;)
@@ -506,7 +1084,8 @@ el.replaceWith(d);
 <ul>
 <li>
 <h4><code><a title="connpy.cli.run_handler.RunHandler" href="#connpy.cli.run_handler.RunHandler">RunHandler</a></code></h4>
-<ul class="">
+<ul class="two-column">
+<li><code><a title="connpy.cli.run_handler.RunHandler.ai_generate" href="#connpy.cli.run_handler.RunHandler.ai_generate">ai_generate</a></code></li>
 <li><code><a title="connpy.cli.run_handler.RunHandler.cli_run" href="#connpy.cli.run_handler.RunHandler.cli_run">cli_run</a></code></li>
 <li><code><a title="connpy.cli.run_handler.RunHandler.dispatch" href="#connpy.cli.run_handler.RunHandler.dispatch">dispatch</a></code></li>
 <li><code><a title="connpy.cli.run_handler.RunHandler.node_run" href="#connpy.cli.run_handler.RunHandler.node_run">node_run</a></code></li>

docs/connpy/grpc_layer/connpy_pb2_grpc.html

@@ -100,6 +100,21 @@ el.replaceWith(d);
                     request_deserializer=connpy__pb2.StringRequest.FromString,
                     response_serializer=connpy__pb2.StructResponse.SerializeToString,
             ),
+            'build_playbook_chat': grpc.stream_stream_rpc_method_handler(
+                    servicer.build_playbook_chat,
+                    request_deserializer=connpy__pb2.AskRequest.FromString,
+                    response_serializer=connpy__pb2.AIResponse.SerializeToString,
+            ),
+            'analyze_execution_results': grpc.unary_stream_rpc_method_handler(
+                    servicer.analyze_execution_results,
+                    request_deserializer=connpy__pb2.AnalyzeRequest.FromString,
+                    response_serializer=connpy__pb2.AIResponse.SerializeToString,
+            ),
+            'predict_execution_results': grpc.unary_stream_rpc_method_handler(
+                    servicer.predict_execution_results,
+                    request_deserializer=connpy__pb2.PreflightRequest.FromString,
+                    response_serializer=connpy__pb2.AIResponse.SerializeToString,
+            ),
     }
     generic_handler = grpc.method_handlers_generic_handler(
             'connpy.AIService', rpc_method_handlers)
@@ -209,11 +224,6 @@ el.replaceWith(d);
                     request_deserializer=connpy__pb2.ScriptRequest.FromString,
                     response_serializer=connpy__pb2.StructResponse.SerializeToString,
             ),
-            'run_yaml_playbook': grpc.unary_unary_rpc_method_handler(
-                    servicer.run_yaml_playbook,
-                    request_deserializer=connpy__pb2.ScriptRequest.FromString,
-                    response_serializer=connpy__pb2.StructResponse.SerializeToString,
-            ),
     }
     generic_handler = grpc.method_handlers_generic_handler(
             'connpy.ExecutionService', rpc_method_handlers)
@@ -739,11 +749,129 @@ el.replaceWith(d);
             wait_for_ready,
             timeout,
             metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def build_playbook_chat(request_iterator,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.stream_stream(
+            request_iterator,
+            target,
+            '/connpy.AIService/build_playbook_chat',
+            connpy__pb2.AskRequest.SerializeToString,
+            connpy__pb2.AIResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def analyze_execution_results(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(
+            request,
+            target,
+            '/connpy.AIService/analyze_execution_results',
+            connpy__pb2.AnalyzeRequest.SerializeToString,
+            connpy__pb2.AIResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)
+
+    @staticmethod
+    def predict_execution_results(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(
+            request,
+            target,
+            '/connpy.AIService/predict_execution_results',
+            connpy__pb2.PreflightRequest.SerializeToString,
+            connpy__pb2.AIResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
             _registered_method=True)</code></pre>
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
 <h3>Static methods</h3>
 <dl>
+<dt id="connpy.grpc_layer.connpy_pb2_grpc.AIService.analyze_execution_results"><code class="name flex">
+<span>def <span class="ident">analyze_execution_results</span></span>(<span>request,<br>target,<br>options=(),<br>channel_credentials=None,<br>call_credentials=None,<br>insecure=False,<br>compression=None,<br>wait_for_ready=None,<br>timeout=None,<br>metadata=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">@staticmethod
+def analyze_execution_results(request,
+        target,
+        options=(),
+        channel_credentials=None,
+        call_credentials=None,
+        insecure=False,
+        compression=None,
+        wait_for_ready=None,
+        timeout=None,
+        metadata=None):
+    return grpc.experimental.unary_stream(
+        request,
+        target,
+        &#39;/connpy.AIService/analyze_execution_results&#39;,
+        connpy__pb2.AnalyzeRequest.SerializeToString,
+        connpy__pb2.AIResponse.FromString,
+        options,
+        channel_credentials,
+        insecure,
+        call_credentials,
+        compression,
+        wait_for_ready,
+        timeout,
+        metadata,
+        _registered_method=True)</code></pre>
+</details>
+<div class="desc"></div>
+</dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.AIService.ask"><code class="name flex">
 <span>def <span class="ident">ask</span></span>(<span>request_iterator,<br>target,<br>options=(),<br>channel_credentials=None,<br>call_credentials=None,<br>insecure=False,<br>compression=None,<br>wait_for_ready=None,<br>timeout=None,<br>metadata=None)</span>
 </code></dt>
@@ -818,6 +946,43 @@ def ask_copilot(request,
 </details>
 <div class="desc"></div>
 </dd>
+<dt id="connpy.grpc_layer.connpy_pb2_grpc.AIService.build_playbook_chat"><code class="name flex">
+<span>def <span class="ident">build_playbook_chat</span></span>(<span>request_iterator,<br>target,<br>options=(),<br>channel_credentials=None,<br>call_credentials=None,<br>insecure=False,<br>compression=None,<br>wait_for_ready=None,<br>timeout=None,<br>metadata=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">@staticmethod
+def build_playbook_chat(request_iterator,
+        target,
+        options=(),
+        channel_credentials=None,
+        call_credentials=None,
+        insecure=False,
+        compression=None,
+        wait_for_ready=None,
+        timeout=None,
+        metadata=None):
+    return grpc.experimental.stream_stream(
+        request_iterator,
+        target,
+        &#39;/connpy.AIService/build_playbook_chat&#39;,
+        connpy__pb2.AskRequest.SerializeToString,
+        connpy__pb2.AIResponse.FromString,
+        options,
+        channel_credentials,
+        insecure,
+        call_credentials,
+        compression,
+        wait_for_ready,
+        timeout,
+        metadata,
+        _registered_method=True)</code></pre>
+</details>
+<div class="desc"></div>
+</dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.AIService.configure_mcp"><code class="name flex">
 <span>def <span class="ident">configure_mcp</span></span>(<span>request,<br>target,<br>options=(),<br>channel_credentials=None,<br>call_credentials=None,<br>insecure=False,<br>compression=None,<br>wait_for_ready=None,<br>timeout=None,<br>metadata=None)</span>
 </code></dt>
@@ -1077,6 +1242,43 @@ def load_session_data(request,
 </details>
 <div class="desc"></div>
 </dd>
+<dt id="connpy.grpc_layer.connpy_pb2_grpc.AIService.predict_execution_results"><code class="name flex">
+<span>def <span class="ident">predict_execution_results</span></span>(<span>request,<br>target,<br>options=(),<br>channel_credentials=None,<br>call_credentials=None,<br>insecure=False,<br>compression=None,<br>wait_for_ready=None,<br>timeout=None,<br>metadata=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">@staticmethod
+def predict_execution_results(request,
+        target,
+        options=(),
+        channel_credentials=None,
+        call_credentials=None,
+        insecure=False,
+        compression=None,
+        wait_for_ready=None,
+        timeout=None,
+        metadata=None):
+    return grpc.experimental.unary_stream(
+        request,
+        target,
+        &#39;/connpy.AIService/predict_execution_results&#39;,
+        connpy__pb2.PreflightRequest.SerializeToString,
+        connpy__pb2.AIResponse.FromString,
+        options,
+        channel_credentials,
+        insecure,
+        call_credentials,
+        compression,
+        wait_for_ready,
+        timeout,
+        metadata,
+        _registered_method=True)</code></pre>
+</details>
+<div class="desc"></div>
+</dd>
 </dl>
 </dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer"><code class="flex name class">
@@ -1139,6 +1341,24 @@ def load_session_data(request,
         raise NotImplementedError(&#39;Method not implemented!&#39;)
 
     def load_session_data(self, request, context):
+        &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details(&#39;Method not implemented!&#39;)
+        raise NotImplementedError(&#39;Method not implemented!&#39;)
+
+    def build_playbook_chat(self, request_iterator, context):
+        &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details(&#39;Method not implemented!&#39;)
+        raise NotImplementedError(&#39;Method not implemented!&#39;)
+
+    def analyze_execution_results(self, request, context):
+        &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details(&#39;Method not implemented!&#39;)
+        raise NotImplementedError(&#39;Method not implemented!&#39;)
+
+    def predict_execution_results(self, request, context):
         &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
         context.set_code(grpc.StatusCode.UNIMPLEMENTED)
         context.set_details(&#39;Method not implemented!&#39;)
@@ -1151,6 +1371,22 @@ def load_session_data(request,
 </ul>
 <h3>Methods</h3>
 <dl>
+<dt id="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.analyze_execution_results"><code class="name flex">
+<span>def <span class="ident">analyze_execution_results</span></span>(<span>self, request, context)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def analyze_execution_results(self, request, context):
+    &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
+    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+    context.set_details(&#39;Method not implemented!&#39;)
+    raise NotImplementedError(&#39;Method not implemented!&#39;)</code></pre>
+</details>
+<div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
+</dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask"><code class="name flex">
 <span>def <span class="ident">ask</span></span>(<span>self, request_iterator, context)</span>
 </code></dt>
@@ -1183,6 +1419,22 @@ def load_session_data(request,
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
 </dd>
+<dt id="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.build_playbook_chat"><code class="name flex">
+<span>def <span class="ident">build_playbook_chat</span></span>(<span>self, request_iterator, context)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def build_playbook_chat(self, request_iterator, context):
+    &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
+    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+    context.set_details(&#39;Method not implemented!&#39;)
+    raise NotImplementedError(&#39;Method not implemented!&#39;)</code></pre>
+</details>
+<div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
+</dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_mcp"><code class="name flex">
 <span>def <span class="ident">configure_mcp</span></span>(<span>self, request, context)</span>
 </code></dt>
@@ -1295,6 +1547,22 @@ def load_session_data(request,
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
 </dd>
+<dt id="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.predict_execution_results"><code class="name flex">
+<span>def <span class="ident">predict_execution_results</span></span>(<span>self, request, context)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def predict_execution_results(self, request, context):
+    &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
+    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+    context.set_details(&#39;Method not implemented!&#39;)
+    raise NotImplementedError(&#39;Method not implemented!&#39;)</code></pre>
+</details>
+<div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
+</dd>
 </dl>
 </dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.AIServiceStub"><code class="flex name class">
@@ -1359,6 +1627,21 @@ def load_session_data(request,
                 &#39;/connpy.AIService/load_session_data&#39;,
                 request_serializer=connpy__pb2.StringRequest.SerializeToString,
                 response_deserializer=connpy__pb2.StructResponse.FromString,
+                _registered_method=True)
+        self.build_playbook_chat = channel.stream_stream(
+                &#39;/connpy.AIService/build_playbook_chat&#39;,
+                request_serializer=connpy__pb2.AskRequest.SerializeToString,
+                response_deserializer=connpy__pb2.AIResponse.FromString,
+                _registered_method=True)
+        self.analyze_execution_results = channel.unary_stream(
+                &#39;/connpy.AIService/analyze_execution_results&#39;,
+                request_serializer=connpy__pb2.AnalyzeRequest.SerializeToString,
+                response_deserializer=connpy__pb2.AIResponse.FromString,
+                _registered_method=True)
+        self.predict_execution_results = channel.unary_stream(
+                &#39;/connpy.AIService/predict_execution_results&#39;,
+                request_serializer=connpy__pb2.PreflightRequest.SerializeToString,
+                response_deserializer=connpy__pb2.AIResponse.FromString,
                 _registered_method=True)</code></pre>
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p>
@@ -2313,33 +2596,6 @@ def update_setting(request,
             wait_for_ready,
             timeout,
             metadata,
-            _registered_method=True)
-
-    @staticmethod
-    def run_yaml_playbook(request,
-            target,
-            options=(),
-            channel_credentials=None,
-            call_credentials=None,
-            insecure=False,
-            compression=None,
-            wait_for_ready=None,
-            timeout=None,
-            metadata=None):
-        return grpc.experimental.unary_unary(
-            request,
-            target,
-            &#39;/connpy.ExecutionService/run_yaml_playbook&#39;,
-            connpy__pb2.ScriptRequest.SerializeToString,
-            connpy__pb2.StructResponse.FromString,
-            options,
-            channel_credentials,
-            insecure,
-            call_credentials,
-            compression,
-            wait_for_ready,
-            timeout,
-            metadata,
             _registered_method=True)</code></pre>
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
@@ -2419,43 +2675,6 @@ def run_commands(request,
 </details>
 <div class="desc"></div>
 </dd>
-<dt id="connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.run_yaml_playbook"><code class="name flex">
-<span>def <span class="ident">run_yaml_playbook</span></span>(<span>request,<br>target,<br>options=(),<br>channel_credentials=None,<br>call_credentials=None,<br>insecure=False,<br>compression=None,<br>wait_for_ready=None,<br>timeout=None,<br>metadata=None)</span>
-</code></dt>
-<dd>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">@staticmethod
-def run_yaml_playbook(request,
-        target,
-        options=(),
-        channel_credentials=None,
-        call_credentials=None,
-        insecure=False,
-        compression=None,
-        wait_for_ready=None,
-        timeout=None,
-        metadata=None):
-    return grpc.experimental.unary_unary(
-        request,
-        target,
-        &#39;/connpy.ExecutionService/run_yaml_playbook&#39;,
-        connpy__pb2.ScriptRequest.SerializeToString,
-        connpy__pb2.StructResponse.FromString,
-        options,
-        channel_credentials,
-        insecure,
-        call_credentials,
-        compression,
-        wait_for_ready,
-        timeout,
-        metadata,
-        _registered_method=True)</code></pre>
-</details>
-<div class="desc"></div>
-</dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.test_commands"><code class="name flex">
 <span>def <span class="ident">test_commands</span></span>(<span>request,<br>target,<br>options=(),<br>channel_credentials=None,<br>call_credentials=None,<br>insecure=False,<br>compression=None,<br>wait_for_ready=None,<br>timeout=None,<br>metadata=None)</span>
 </code></dt>
@@ -2519,12 +2738,6 @@ def test_commands(request,
         raise NotImplementedError(&#39;Method not implemented!&#39;)
 
     def run_cli_script(self, request, context):
-        &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
-        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
-        context.set_details(&#39;Method not implemented!&#39;)
-        raise NotImplementedError(&#39;Method not implemented!&#39;)
-
-    def run_yaml_playbook(self, request, context):
         &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
         context.set_code(grpc.StatusCode.UNIMPLEMENTED)
         context.set_details(&#39;Method not implemented!&#39;)
@@ -2569,22 +2782,6 @@ def test_commands(request,
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
 </dd>
-<dt id="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_yaml_playbook"><code class="name flex">
-<span>def <span class="ident">run_yaml_playbook</span></span>(<span>self, request, context)</span>
-</code></dt>
-<dd>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def run_yaml_playbook(self, request, context):
-    &#34;&#34;&#34;Missing associated documentation comment in .proto file.&#34;&#34;&#34;
-    context.set_code(grpc.StatusCode.UNIMPLEMENTED)
-    context.set_details(&#39;Method not implemented!&#39;)
-    raise NotImplementedError(&#39;Method not implemented!&#39;)</code></pre>
-</details>
-<div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
-</dd>
 <dt id="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.test_commands"><code class="name flex">
 <span>def <span class="ident">test_commands</span></span>(<span>self, request, context)</span>
 </code></dt>
@@ -2635,11 +2832,6 @@ def test_commands(request,
                 &#39;/connpy.ExecutionService/run_cli_script&#39;,
                 request_serializer=connpy__pb2.ScriptRequest.SerializeToString,
                 response_deserializer=connpy__pb2.StructResponse.FromString,
-                _registered_method=True)
-        self.run_yaml_playbook = channel.unary_unary(
-                &#39;/connpy.ExecutionService/run_yaml_playbook&#39;,
-                request_serializer=connpy__pb2.ScriptRequest.SerializeToString,
-                response_deserializer=connpy__pb2.StructResponse.FromString,
                 _registered_method=True)</code></pre>
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p>
@@ -6089,9 +6281,11 @@ def stop_api(request,
 <ul>
 <li>
 <h4><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService">AIService</a></code></h4>
-<ul class="two-column">
+<ul class="">
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.analyze_execution_results" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.analyze_execution_results">analyze_execution_results</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.ask" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.ask">ask</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.ask_copilot" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.ask_copilot">ask_copilot</a></code></li>
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.build_playbook_chat" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.build_playbook_chat">build_playbook_chat</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.configure_mcp" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.configure_mcp">configure_mcp</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.configure_provider" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.configure_provider">configure_provider</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.confirm" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.confirm">confirm</a></code></li>
@@ -6099,13 +6293,16 @@ def stop_api(request,
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.list_mcp_servers" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.list_mcp_servers">list_mcp_servers</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.list_sessions" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.list_sessions">list_sessions</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.load_session_data" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.load_session_data">load_session_data</a></code></li>
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIService.predict_execution_results" href="#connpy.grpc_layer.connpy_pb2_grpc.AIService.predict_execution_results">predict_execution_results</a></code></li>
 </ul>
 </li>
 <li>
 <h4><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer">AIServiceServicer</a></code></h4>
-<ul class="two-column">
+<ul class="">
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.analyze_execution_results" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.analyze_execution_results">analyze_execution_results</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask">ask</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask_copilot" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask_copilot">ask_copilot</a></code></li>
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.build_playbook_chat" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.build_playbook_chat">build_playbook_chat</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_mcp" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_mcp">configure_mcp</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_provider" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_provider">configure_provider</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.confirm" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.confirm">confirm</a></code></li>
@@ -6113,6 +6310,7 @@ def stop_api(request,
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_mcp_servers" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_mcp_servers">list_mcp_servers</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_sessions" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_sessions">list_sessions</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.load_session_data" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.load_session_data">load_session_data</a></code></li>
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.predict_execution_results" href="#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.predict_execution_results">predict_execution_results</a></code></li>
 </ul>
 </li>
 <li>
@@ -6165,7 +6363,6 @@ def stop_api(request,
 <ul class="">
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.run_cli_script" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.run_cli_script">run_cli_script</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.run_commands" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.run_commands">run_commands</a></code></li>
-<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.run_yaml_playbook" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.run_yaml_playbook">run_yaml_playbook</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.test_commands" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionService.test_commands">test_commands</a></code></li>
 </ul>
 </li>
@@ -6174,7 +6371,6 @@ def stop_api(request,
 <ul class="">
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_cli_script" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_cli_script">run_cli_script</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_commands" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_commands">run_commands</a></code></li>
-<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_yaml_playbook" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_yaml_playbook">run_yaml_playbook</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.test_commands" href="#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.test_commands">test_commands</a></code></li>
 </ul>
 </li>

docs/connpy/grpc_layer/server.html

@@ -174,12 +174,10 @@ el.replaceWith(d);
     def service(self):
         return self._get_provider().ai
 
-    @handle_errors
-    def ask(self, request_iterator, context):
+    def _handle_chat_stream(self, request_iterator, context, service_method):
         import queue
         import threading
 
-        ai_service = self.service
         chunk_queue = queue.Queue()
         request_queue = queue.Queue()
         bridge = None
@@ -197,13 +195,20 @@ el.replaceWith(d);
             nonlocal history, bridge, agent_instance
             try:
                 # Run the AI interaction (this blocks this specific thread)
-                res = ai_service.ask(
+                if getattr(service_method, "__name__", None) == "build_playbook_chat":
+                    res = service_method(
+                        input_text,
+                        chat_history=history if history else None,
+                        status=bridge,
+                        chunk_callback=callback
+                    )
+                else:
+                    res = service_method(
                         input_text,
                         chat_history=history if history else None,
                         session_id=session_id,
                         debug=debug,
                         status=bridge,
-                    console=bridge,
                         confirm_handler=bridge.confirm,
                         chunk_callback=callback,
                         trust=trust,
@@ -211,7 +216,7 @@ el.replaceWith(d);
                     )
 
                 # Update history for next message
-                if "chat_history" in res:
+                if res and "chat_history" in res:
                     history = res["chat_history"]
 
                 # Send final chunk marker
@@ -305,6 +310,71 @@ el.replaceWith(d);
             elif msg_type == "final_mark":
                 yield connpy_pb2.AIResponse(is_final=True, full_result=to_struct(val))
 
+    def _handle_unary_stream(self, service_method, *args, **kwargs):
+        import queue
+        import threading
+        
+        chunk_queue = queue.Queue()
+        bridge = StatusBridge(chunk_queue, is_web=False)
+        
+        def callback(chunk):
+            chunk_queue.put(("text", chunk))
+            
+        def _worker():
+            try:
+                res = service_method(*args, chunk_callback=callback, status=bridge, **kwargs)
+                chunk_queue.put(("final_mark", res))
+            except Exception as e:
+                import traceback
+                print(f"gRPC Unary Stream error: {e}")
+                traceback.print_exc()
+                chunk_queue.put(("status", f"Error: {str(e)}"))
+                chunk_queue.put(("final_mark", {"response": f"Error: {str(e)}", "error": True}))
+            finally:
+                chunk_queue.put((None, None))
+                
+        threading.Thread(target=_worker, daemon=True).start()
+        
+        while True:
+            item = chunk_queue.get()
+            if item == (None, None):
+                break
+                
+            msg_type, val = item
+            if msg_type == "text":
+                yield connpy_pb2.AIResponse(text_chunk=val, is_final=False)
+            elif msg_type == "status":
+                clean_val = val.replace("[ai_status]", "").replace("[/ai_status]", "")
+                yield connpy_pb2.AIResponse(status_update=clean_val, is_final=False)
+            elif msg_type == "debug":
+                yield connpy_pb2.AIResponse(debug_message=val, is_final=False)
+            elif msg_type == "important":
+                yield connpy_pb2.AIResponse(important_message=val, is_final=False)
+            elif msg_type == "confirm":
+                yield connpy_pb2.AIResponse(status_update=val, requires_confirmation=True, is_final=False)
+            elif msg_type == "final_mark":
+                yield connpy_pb2.AIResponse(is_final=True, full_result=to_struct(val))
+
+    @handle_errors
+    def ask(self, request_iterator, context):
+        yield from self._handle_chat_stream(request_iterator, context, self.service.ask)
+
+    @handle_errors
+    def build_playbook_chat(self, request_iterator, context):
+        yield from self._handle_chat_stream(request_iterator, context, self.service.build_playbook_chat)
+
+    @handle_errors
+    def analyze_execution_results(self, request, context):
+        results = from_struct(request.results)
+        query = request.query if request.query else None
+        yield from self._handle_unary_stream(self.service.analyze_execution_results, results, query=query)
+
+    @handle_errors
+    def predict_execution_results(self, request, context):
+        target_nodes = list(request.target_nodes)
+        commands = list(request.commands)
+        yield from self._handle_unary_stream(self.service.predict_execution_results, target_nodes, commands)
+
     @handle_errors
     def confirm(self, request, context):
         res = self.service.confirm(request.value)
@@ -386,8 +456,10 @@ def service(self):
 <ul class="hlist">
 <li><code><b><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer">AIServiceServicer</a></b></code>:
 <ul class="hlist">
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.analyze_execution_results" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.analyze_execution_results">analyze_execution_results</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask">ask</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask_copilot" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.ask_copilot">ask_copilot</a></code></li>
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.build_playbook_chat" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.build_playbook_chat">build_playbook_chat</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_mcp" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_mcp">configure_mcp</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_provider" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.configure_provider">configure_provider</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.confirm" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.confirm">confirm</a></code></li>
@@ -395,6 +467,7 @@ def service(self):
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_mcp_servers" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_mcp_servers">list_mcp_servers</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_sessions" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.list_sessions">list_sessions</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.load_session_data" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.load_session_data">load_session_data</a></code></li>
+<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.predict_execution_results" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.AIServiceServicer.predict_execution_results">predict_execution_results</a></code></li>
 </ul>
 </li>
 </ul>
@@ -855,11 +928,6 @@ def service(self):
     @handle_errors
     def run_cli_script(self, request, context):
         res = self.service.run_cli_script(request.param1, request.param2, request.parallel)
-        return connpy_pb2.StructResponse(data=to_struct(res))
-
-    @handle_errors
-    def run_yaml_playbook(self, request, context):
-        res = self.service.run_yaml_playbook(request.param1, request.parallel)
         return connpy_pb2.StructResponse(data=to_struct(res))</code></pre>
 </details>
 <div class="desc"><p>Missing associated documentation comment in .proto file.</p></div>
@@ -888,7 +956,6 @@ def service(self):
 <ul class="hlist">
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_cli_script" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_cli_script">run_cli_script</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_commands" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_commands">run_commands</a></code></li>
-<li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_yaml_playbook" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.run_yaml_playbook">run_yaml_playbook</a></code></li>
 <li><code><a title="connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.test_commands" href="connpy_pb2_grpc.html#connpy.grpc_layer.connpy_pb2_grpc.ExecutionServiceServicer.test_commands">test_commands</a></code></li>
 </ul>
 </li>

docs/connpy/grpc_layer/stubs.html

@@ -99,8 +99,7 @@ el.replaceWith(d);
         self.stub = connpy_pb2_grpc.AIServiceStub(channel)
         self.remote_host = remote_host
 
-    @handle_errors
-    def ask(self, input_text, dryrun=False, chat_history=None, session_id=None, debug=False, status=None, **overrides):
+    def _ai_chat_stream(self, stub_method, input_text, dryrun=False, chat_history=None, session_id=None, debug=False, status=None, chunk_callback=None, **overrides):
         import queue
         from rich.prompt import Prompt
         from rich.text import Text
@@ -135,7 +134,7 @@ el.replaceWith(d);
                 if req is None: break
                 yield req
 
-        responses = self.stub.ask(request_generator())
+        responses = stub_method(request_generator())
         
         full_content = ""
         header_printed = False
@@ -234,6 +233,9 @@ el.replaceWith(d);
                                 try: status.stop()
                                 except: pass
                             
+                            if chunk_callback:
+                                header_printed = True
+                            else:
                                 from rich.console import Console as RichConsole
                                 from rich.rule import Rule
                                 from ..printer import connpy_theme, get_original_stdout, IncrementalMarkdownParser
@@ -249,11 +251,14 @@ el.replaceWith(d);
                                 md_parser = IncrementalMarkdownParser(console=stable_console)
                         
                         full_content += response.text_chunk
+                        if chunk_callback:
+                            chunk_callback(response.text_chunk)
+                        elif md_parser:
                             md_parser.feed(response.text_chunk)
                     continue
                 
                 if response.is_final:
-                    if header_printed:
+                    if not chunk_callback and header_printed:
                         from rich.rule import Rule
                         md_parser.flush()
                         
@@ -262,12 +267,8 @@ el.replaceWith(d);
                         except: pass
 
                     final_result = from_struct(response.full_result)
-                    responder = final_result.get("responder", "engineer")
-                    alias = "architect" if responder == "architect" else "engineer"
-                    role_label = "Network Architect" if responder == "architect" else "Network Engineer"
-                    title = f"[bold {alias}]{role_label}[/bold {alias}]"
                     
-                    if header_printed:
+                    if not chunk_callback and header_printed:
                         from rich.console import Console as RichConsole
                         from ..printer import connpy_theme, get_original_stdout
                         stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
@@ -286,6 +287,104 @@ el.replaceWith(d);
             
         return final_result
 
+    @handle_errors
+    def ask(self, input_text, dryrun=False, chat_history=None, session_id=None, debug=False, status=None, **overrides):
+        return self._ai_chat_stream(self.stub.ask, input_text, dryrun=dryrun, chat_history=chat_history, session_id=session_id, debug=debug, status=status, **overrides)
+
+    @handle_errors
+    def build_playbook_chat(self, user_input, chat_history=None, status=None, chunk_callback=None):
+        return self._ai_chat_stream(self.stub.build_playbook_chat, user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)
+
+    def _process_unary_stream(self, responses, status=None, chunk_callback=None):
+        full_content = ""
+        header_printed = False
+        final_result = {"response": "", "chat_history": []}
+        md_parser = None
+
+        try:
+            for response in responses:
+                if response.status_update:
+                    if status:
+                        status.update(response.status_update)
+                    continue
+                
+                if response.important_message:
+                    if status:
+                        try: status.stop()
+                        except: pass
+                    printer.console.print(Text.from_ansi(response.important_message))
+                    if status:
+                        try: status.start()
+                        except: pass
+                    continue
+
+                if not response.is_final:
+                    if response.text_chunk:
+                        if not header_printed:
+                            if status:
+                                try: status.stop()
+                                except: pass
+                            
+                            if chunk_callback:
+                                header_printed = True
+                            else:
+                                from rich.console import Console as RichConsole
+                                from rich.rule import Rule
+                                from ..printer import connpy_theme, get_original_stdout, IncrementalMarkdownParser
+                                stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
+                                
+                                # Print default header
+                                stable_console.print(Rule("[bold engineer]AI Analysis[/bold engineer]", style="engineer"))
+                                header_printed = True
+                                md_parser = IncrementalMarkdownParser(console=stable_console)
+                        
+                        full_content += response.text_chunk
+                        if chunk_callback:
+                            chunk_callback(response.text_chunk)
+                        elif md_parser:
+                            md_parser.feed(response.text_chunk)
+                    continue
+                
+                if response.is_final:
+                    if md_parser:
+                        md_parser.flush()
+                        
+                    if status:
+                        try: status.stop()
+                        except: pass
+
+                    final_result = from_struct(response.full_result)
+                    
+                    if md_parser:
+                        from rich.console import Console as RichConsole
+                        from rich.rule import Rule
+                        from ..printer import connpy_theme, get_original_stdout
+                        stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
+                        stable_console.print(Rule(style="engineer"))
+                    break
+        except Exception as e:
+            if isinstance(e, grpc.RpcError):
+                raise
+            printer.warning(f"Stream interrupted: {e}")
+            
+        if full_content:
+            final_result["streamed"] = True
+            
+        return final_result
+
+    @handle_errors
+    def analyze_execution_results(self, results, query=None, status=None, chunk_callback=None):
+        req = connpy_pb2.AnalyzeRequest(query=query or "")
+        req.results.CopyFrom(to_struct(results))
+        responses = self.stub.analyze_execution_results(req)
+        return self._process_unary_stream(responses, status, chunk_callback)
+
+    @handle_errors
+    def predict_execution_results(self, target_nodes, commands, status=None, chunk_callback=None):
+        req = connpy_pb2.PreflightRequest(target_nodes=target_nodes, commands=commands)
+        responses = self.stub.predict_execution_results(req)
+        return self._process_unary_stream(responses, status, chunk_callback)
+
     @handle_errors
     def confirm(self, input_text, console=None):
         return self.stub.confirm(connpy_pb2.StringRequest(value=input_text)).value
@@ -333,6 +432,23 @@ el.replaceWith(d);
 <div class="desc"></div>
 <h3>Methods</h3>
 <dl>
+<dt id="connpy.grpc_layer.stubs.AIStub.analyze_execution_results"><code class="name flex">
+<span>def <span class="ident">analyze_execution_results</span></span>(<span>self, results, query=None, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">@handle_errors
+def analyze_execution_results(self, results, query=None, status=None, chunk_callback=None):
+    req = connpy_pb2.AnalyzeRequest(query=query or &#34;&#34;)
+    req.results.CopyFrom(to_struct(results))
+    responses = self.stub.analyze_execution_results(req)
+    return self._process_unary_stream(responses, status, chunk_callback)</code></pre>
+</details>
+<div class="desc"></div>
+</dd>
 <dt id="connpy.grpc_layer.stubs.AIStub.ask"><code class="name flex">
 <span>def <span class="ident">ask</span></span>(<span>self,<br>input_text,<br>dryrun=False,<br>chat_history=None,<br>session_id=None,<br>debug=False,<br>status=None,<br>**overrides)</span>
 </code></dt>
@@ -343,190 +459,21 @@ el.replaceWith(d);
 </summary>
 <pre><code class="python">@handle_errors
 def ask(self, input_text, dryrun=False, chat_history=None, session_id=None, debug=False, status=None, **overrides):
-    import queue
-    from rich.prompt import Prompt
-    from rich.text import Text
-    from rich.panel import Panel
-    from rich.markdown import Markdown
-    
-    req_queue = queue.Queue()
-    
-    initial_req = connpy_pb2.AskRequest(
-        input_text=input_text,
-        dryrun=dryrun,
-        session_id=session_id or &#34;&#34;,
-        debug=debug,
-        engineer_model=overrides.get(&#34;engineer_model&#34;, &#34;&#34;),
-        engineer_api_key=overrides.get(&#34;engineer_api_key&#34;, &#34;&#34;),
-        architect_model=overrides.get(&#34;architect_model&#34;, &#34;&#34;),
-        architect_api_key=overrides.get(&#34;architect_api_key&#34;, &#34;&#34;),
-        trust=overrides.get(&#34;trust&#34;, False)
-    )
-    if chat_history is not None:
-        initial_req.chat_history.CopyFrom(to_value(chat_history))
-    if &#34;engineer_auth&#34; in overrides and overrides[&#34;engineer_auth&#34;]:
-        initial_req.engineer_auth.CopyFrom(to_struct(overrides[&#34;engineer_auth&#34;]))
-    if &#34;architect_auth&#34; in overrides and overrides[&#34;architect_auth&#34;]:
-        initial_req.architect_auth.CopyFrom(to_struct(overrides[&#34;architect_auth&#34;]))
-        
-    req_queue.put(initial_req)
-
-    def request_generator():
-        while True:
-            req = req_queue.get()
-            if req is None: break
-            yield req
-
-    responses = self.stub.ask(request_generator())
-    
-    full_content = &#34;&#34;
-    header_printed = False
-    current_responder = &#34;engineer&#34;
-    final_result = {&#34;response&#34;: &#34;&#34;, &#34;chat_history&#34;: []}
-
-    # Background thread to pull responses from gRPC into a local queue
-    # This prevents KeyboardInterrupt from corrupting the gRPC iterator state
-    response_queue = queue.Queue()
-    
-    def pull_responses():
-        try:
-            for response in responses:
-                response_queue.put((&#34;data&#34;, response))
-        except Exception as e:
-            response_queue.put((&#34;error&#34;, e))
-        finally:
-            response_queue.put((None, None))
-
-    threading.Thread(target=pull_responses, daemon=True).start()
-
-    try:
-        while True:
-            try:
-                # BLOCKING GET from local queue (interruptible by signal)
-                msg_type, response = response_queue.get()
-            except KeyboardInterrupt:
-                # Signal interruption to the server
-                if status:
-                    status.update(&#34;[error]Interrupted! Closing pending tasks...&#34;)
-                
-                # Send the interrupt signal to the server
-                req_queue.put(connpy_pb2.AskRequest(interrupt=True))
-                
-                # CONTINUE the loop to receive remaining data and summary from the queue
-                continue
-            
-            if msg_type is None: # Sentinel
-                break
-            
-            if msg_type == &#34;error&#34;:
-                # Re-raise or handle gRPC error from background thread
-                if isinstance(response, grpc.RpcError):
-                    raise response
-                printer.warning(f&#34;Stream interrupted: {response}&#34;)
-                break
-
-            if response.status_update:
-                if response.status_update.startswith(&#34;__RESPONDER__:&#34;):
-                    current_responder = response.status_update.split(&#34;:&#34;)[1].lower()
-                    continue
-                    
-                if response.requires_confirmation:
-                    if status: status.stop()
-                    
-                    # Show prompt and wait for answer
-                    prompt_text = Text.from_ansi(response.status_update)
-                    ans = Prompt.ask(prompt_text)
-                    
-                    if status: 
-                        status.update(&#34;[ai_status]Agent: Resuming...&#34;)
-                        status.start()
-                    
-                    req_queue.put(connpy_pb2.AskRequest(confirmation_answer=ans))
-                    continue
-                    
-                if status:
-                    status.update(response.status_update)
-                continue
-            
-            if response.debug_message:
-                if debug:
-                    if status:
-                        try: status.stop()
-                        except: pass
-                    printer.console.print(Text.from_ansi(response.debug_message))
-                    if status:
-                        try: status.start()
-                        except: pass
-                continue
-            
-            if response.important_message:
-                if status:
-                    try: status.stop()
-                    except: pass
-                printer.console.print(Text.from_ansi(response.important_message))
-                if status:
-                    try: status.start()
-                    except: pass
-                continue
-
-            if not response.is_final:
-                if response.text_chunk:
-                    if not header_printed:
-                        if status:
-                            try: status.stop()
-                            except: pass
-                        
-                        from rich.console import Console as RichConsole
-                        from rich.rule import Rule
-                        from ..printer import connpy_theme, get_original_stdout, IncrementalMarkdownParser
-                        stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
-                        
-                        # Print header on first chunk
-                        alias = &#34;architect&#34; if current_responder == &#34;architect&#34; else &#34;engineer&#34;
-                        role_label = &#34;Network Architect&#34; if current_responder == &#34;architect&#34; else &#34;Network Engineer&#34;
-                        stable_console.print(Rule(f&#34;[bold {alias}]{role_label}[/bold {alias}]&#34;, style=alias))
-                        header_printed = True
-                        
-                        # Initialize parser
-                        md_parser = IncrementalMarkdownParser(console=stable_console)
-                    
-                    full_content += response.text_chunk
-                    md_parser.feed(response.text_chunk)
-                continue
-            
-            if response.is_final:
-                if header_printed:
-                    from rich.rule import Rule
-                    md_parser.flush()
-                    
-                if status:
-                    try: status.stop()
-                    except: pass
-
-                final_result = from_struct(response.full_result)
-                responder = final_result.get(&#34;responder&#34;, &#34;engineer&#34;)
-                alias = &#34;architect&#34; if responder == &#34;architect&#34; else &#34;engineer&#34;
-                role_label = &#34;Network Architect&#34; if responder == &#34;architect&#34; else &#34;Network Engineer&#34;
-                title = f&#34;[bold {alias}]{role_label}[/bold {alias}]&#34;
-                
-                if header_printed:
-                    from rich.console import Console as RichConsole
-                    from ..printer import connpy_theme, get_original_stdout
-                    stable_console = RichConsole(theme=connpy_theme, file=get_original_stdout())
-                    stable_console.print(Rule(style=alias))
-                break
-    except Exception as e:
-        # Check if it was a gRPC error that we should let handle_errors catch
-        if isinstance(e, grpc.RpcError):
-            raise
-        printer.warning(f&#34;Stream interrupted: {e}&#34;)
-    finally:
-        req_queue.put(None)
-    
-    if full_content:
-        final_result[&#34;streamed&#34;] = True
-        
-    return final_result</code></pre>
+    return self._ai_chat_stream(self.stub.ask, input_text, dryrun=dryrun, chat_history=chat_history, session_id=session_id, debug=debug, status=status, **overrides)</code></pre>
+</details>
+<div class="desc"></div>
+</dd>
+<dt id="connpy.grpc_layer.stubs.AIStub.build_playbook_chat"><code class="name flex">
+<span>def <span class="ident">build_playbook_chat</span></span>(<span>self, user_input, chat_history=None, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">@handle_errors
+def build_playbook_chat(self, user_input, chat_history=None, status=None, chunk_callback=None):
+    return self._ai_chat_stream(self.stub.build_playbook_chat, user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)</code></pre>
 </details>
 <div class="desc"></div>
 </dd>
@@ -644,6 +591,22 @@ def load_session_data(self, session_id):
 </details>
 <div class="desc"></div>
 </dd>
+<dt id="connpy.grpc_layer.stubs.AIStub.predict_execution_results"><code class="name flex">
+<span>def <span class="ident">predict_execution_results</span></span>(<span>self, target_nodes, commands, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">@handle_errors
+def predict_execution_results(self, target_nodes, commands, status=None, chunk_callback=None):
+    req = connpy_pb2.PreflightRequest(target_nodes=target_nodes, commands=commands)
+    responses = self.stub.predict_execution_results(req)
+    return self._process_unary_stream(responses, status, chunk_callback)</code></pre>
+</details>
+<div class="desc"></div>
+</dd>
 </dl>
 </dd>
 <dt id="connpy.grpc_layer.stubs.AuthClientInterceptor"><code class="flex name class">
@@ -1124,12 +1087,7 @@ def update_setting(self, key, value):
     @handle_errors
     def run_cli_script(self, nodes_filter, script_path, parallel=10):
         req = connpy_pb2.ScriptRequest(param1=nodes_filter, param2=script_path, parallel=parallel)
-        return from_struct(self.stub.run_cli_script(req).data)
-
-    @handle_errors
-    def run_yaml_playbook(self, playbook_path, parallel=10):
-        req = connpy_pb2.ScriptRequest(param1=playbook_path, parallel=parallel)
-        return from_struct(self.stub.run_yaml_playbook(req).data)</code></pre>
+        return from_struct(self.stub.run_cli_script(req).data)</code></pre>
 </details>
 <div class="desc"></div>
 <h3>Methods</h3>
@@ -1187,21 +1145,6 @@ def run_commands(self, nodes_filter, commands, variables=None, parallel=10, time
 </details>
 <div class="desc"></div>
 </dd>
-<dt id="connpy.grpc_layer.stubs.ExecutionStub.run_yaml_playbook"><code class="name flex">
-<span>def <span class="ident">run_yaml_playbook</span></span>(<span>self, playbook_path, parallel=10)</span>
-</code></dt>
-<dd>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">@handle_errors
-def run_yaml_playbook(self, playbook_path, parallel=10):
-    req = connpy_pb2.ScriptRequest(param1=playbook_path, parallel=parallel)
-    return from_struct(self.stub.run_yaml_playbook(req).data)</code></pre>
-</details>
-<div class="desc"></div>
-</dd>
 <dt id="connpy.grpc_layer.stubs.ExecutionStub.test_commands"><code class="name flex">
 <span>def <span class="ident">test_commands</span></span>(<span>self,<br>nodes_filter,<br>commands,<br>expected,<br>variables=None,<br>parallel=10,<br>timeout=10,<br>prompt=None,<br>**kwargs)</span>
 </code></dt>
@@ -2815,8 +2758,10 @@ def stop_api(self):
 <ul>
 <li>
 <h4><code><a title="connpy.grpc_layer.stubs.AIStub" href="#connpy.grpc_layer.stubs.AIStub">AIStub</a></code></h4>
-<ul class="two-column">
+<ul class="">
+<li><code><a title="connpy.grpc_layer.stubs.AIStub.analyze_execution_results" href="#connpy.grpc_layer.stubs.AIStub.analyze_execution_results">analyze_execution_results</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.AIStub.ask" href="#connpy.grpc_layer.stubs.AIStub.ask">ask</a></code></li>
+<li><code><a title="connpy.grpc_layer.stubs.AIStub.build_playbook_chat" href="#connpy.grpc_layer.stubs.AIStub.build_playbook_chat">build_playbook_chat</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.AIStub.configure_mcp" href="#connpy.grpc_layer.stubs.AIStub.configure_mcp">configure_mcp</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.AIStub.configure_provider" href="#connpy.grpc_layer.stubs.AIStub.configure_provider">configure_provider</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.AIStub.confirm" href="#connpy.grpc_layer.stubs.AIStub.confirm">confirm</a></code></li>
@@ -2824,6 +2769,7 @@ def stop_api(self):
 <li><code><a title="connpy.grpc_layer.stubs.AIStub.list_mcp_servers" href="#connpy.grpc_layer.stubs.AIStub.list_mcp_servers">list_mcp_servers</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.AIStub.list_sessions" href="#connpy.grpc_layer.stubs.AIStub.list_sessions">list_sessions</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.AIStub.load_session_data" href="#connpy.grpc_layer.stubs.AIStub.load_session_data">load_session_data</a></code></li>
+<li><code><a title="connpy.grpc_layer.stubs.AIStub.predict_execution_results" href="#connpy.grpc_layer.stubs.AIStub.predict_execution_results">predict_execution_results</a></code></li>
 </ul>
 </li>
 <li>
@@ -2857,7 +2803,6 @@ def stop_api(self):
 <ul class="">
 <li><code><a title="connpy.grpc_layer.stubs.ExecutionStub.run_cli_script" href="#connpy.grpc_layer.stubs.ExecutionStub.run_cli_script">run_cli_script</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.ExecutionStub.run_commands" href="#connpy.grpc_layer.stubs.ExecutionStub.run_commands">run_commands</a></code></li>
-<li><code><a title="connpy.grpc_layer.stubs.ExecutionStub.run_yaml_playbook" href="#connpy.grpc_layer.stubs.ExecutionStub.run_yaml_playbook">run_yaml_playbook</a></code></li>
 <li><code><a title="connpy.grpc_layer.stubs.ExecutionStub.test_commands" href="#connpy.grpc_layer.stubs.ExecutionStub.test_commands">test_commands</a></code></li>
 </ul>
 </li>

docs/connpy/index.html

@@ -185,6 +185,8 @@ response = myai.ask("What is the status of the BGP neighbors in the office?
 </code></pre>
 <hr>
 <p><em>For detailed developer notes and plugin hooks documentation, see the <a href="https://fluzzi.github.io/connpy/">Documentation</a>.</em></p>
+<h2 id="license">📜 License</h2>
+<p><a href="LICENSE">PolyForm Noncommercial 1.0.0</a></p>
 </section>
 <section>
 <h2 class="section-title" id="header-submodules">Sub-modules</h2>
@@ -644,6 +646,7 @@ class ai:
         self.confirm_handler = confirm_handler or self._local_confirm_handler
         self.trusted_session = trust  # Trust mode for the entire session
         self.interrupted = False
+        self.one_shot = kwargs.get(&#34;one_shot&#34;, False)
 
         
         # 1. Cargar configuración genérica con herencia/merge global
@@ -815,10 +818,13 @@ class ai:
     @property
     def architect_system_prompt(self):
         &#34;&#34;&#34;Build architect system prompt with plugin extensions.&#34;&#34;&#34;
+        prompt = self._architect_base_prompt
+        if getattr(self, &#34;one_shot&#34;, False):
+            prompt += &#34;\n\nCRITICAL 1-SHOT DIAGNOSTICS DIRECTIVE:\nYou are running in a 1-shot offline diagnostics mode. There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately and directly to the user. Do not suggest or attempt to delegate/return control to the engineer.&#34;
         if self.architect_prompt_extensions:
             extensions = &#34;\n&#34;.join(self.architect_prompt_extensions)
-            return self._architect_base_prompt + f&#34;\n\nPlugin Capabilities:\n{extensions}&#34;
-        return self._architect_base_prompt
+            return prompt + f&#34;\n\nPlugin Capabilities:\n{extensions}&#34;
+        return prompt
 
     def register_ai_tool(self, tool_definition, handler, target=&#34;engineer&#34;, engineer_prompt=None, architect_prompt=None, status_formatter=None):
         &#34;&#34;&#34;Register an external tool for the AI system.
@@ -1295,13 +1301,11 @@ class ai:
                 if self.interrupted:
                     raise KeyboardInterrupt
                 
-                # Soft limit warning
-                if iteration == self.soft_limit_iterations and not soft_limit_warned:
-                    self.console.print(f&#34;[warning]⚠ Engineer has performed {iteration} steps. This is taking longer than expected.[/warning]&#34;)
-                    self.console.print(f&#34;[warning]  You can press Ctrl+C to interrupt and get a summary.[/warning]&#34;)
-                    soft_limit_warned = True
-                
-                if status and not chat_history: status.update(f&#34;[ai_status]Engineer: Analyzing mission... (step {iteration})&#34;)
+                if status and not chat_history:
+                    status_text = f&#34;[ai_status]Engineer: Analyzing mission... (step {iteration})&#34;
+                    if iteration &gt;= self.soft_limit_iterations:
+                        status_text += &#34; [warning]⚠ Taking longer than expected (Ctrl+C to interrupt)[/warning]&#34;
+                    status.update(status_text)
                 
                 try:
                     safe_messages = self._sanitize_messages(messages)
@@ -1326,17 +1330,23 @@ class ai:
                     
                     # Notificación en tiempo real de la tarea técnica (Only if not in Architect loop)
                     if status and not chat_history:
-                        if fn == &#34;list_nodes&#34;: status.update(f&#34;[ai_status]Engineer: [SEARCH] {args.get(&#39;filter_pattern&#39;,&#39;.*&#39;)}&#34;)
+                        s_text = &#34;&#34;
+                        if fn == &#34;list_nodes&#34;: s_text = f&#34;[ai_status]Engineer: [SEARCH] {args.get(&#39;filter_pattern&#39;,&#39;.*&#39;)}&#34;
                         elif fn == &#34;run_commands&#34;: 
                             cmds = args.get(&#39;commands&#39;, [])
                             cmd_str = cmds[0] if cmds else &#34;&#34;
-                            status.update(f&#34;[ai_status]Engineer: [CMD] {cmd_str}&#34;)
-                        elif fn == &#34;get_node_info&#34;: status.update(f&#34;[ai_status]Engineer: [INSPECT] {args.get(&#39;node_name&#39;,&#39;&#39;)}&#34;)
+                            s_text = f&#34;[ai_status]Engineer: [CMD] {cmd_str}&#34;
+                        elif fn == &#34;get_node_info&#34;: s_text = f&#34;[ai_status]Engineer: [INSPECT] {args.get(&#39;node_name&#39;,&#39;&#39;)}&#34;
                         elif fn.startswith(&#34;mcp_&#34;):
                             server = fn.split(&#34;__&#34;)[0].replace(&#34;mcp_&#34;, &#34;&#34;)
                             tool = fn.split(&#34;__&#34;)[1] if &#34;__&#34; in fn else fn
-                            status.update(f&#34;[ai_status]Engineer: [MCP:{server}] {tool}&#34;)
-                        elif fn in self.tool_status_formatters: status.update(self.tool_status_formatters[fn](args))
+                            s_text = f&#34;[ai_status]Engineer: [MCP:{server}] {tool}&#34;
+                        elif fn in self.tool_status_formatters: s_text = self.tool_status_formatters[fn](args)
+                        
+                        if s_text:
+                            if iteration &gt;= self.soft_limit_iterations:
+                                s_text += &#34; [warning]⚠ Taking longer than expected (Ctrl+C to interrupt)[/warning]&#34;
+                            status.update(s_text)
 
                     if debug:
                         self._print_debug_observation(f&#34;Decision: {fn}&#34;, args, status=status)
@@ -1406,6 +1416,8 @@ class ai:
             {&#34;type&#34;: &#34;function&#34;, &#34;function&#34;: {&#34;name&#34;: &#34;return_to_engineer&#34;, &#34;description&#34;: &#34;Return control to the Engineer. Use this when your strategic analysis is complete and the Engineer should handle the rest of the conversation.&#34;, &#34;parameters&#34;: {&#34;type&#34;: &#34;object&#34;, &#34;properties&#34;: {&#34;summary&#34;: {&#34;type&#34;: &#34;string&#34;, &#34;description&#34;: &#34;Brief summary of your analysis to hand over to the Engineer.&#34;}}, &#34;required&#34;: [&#34;summary&#34;]}}},
             {&#34;type&#34;: &#34;function&#34;, &#34;function&#34;: {&#34;name&#34;: &#34;manage_memory_tool&#34;, &#34;description&#34;: &#34;Saves information to long-term memory. MANDATORY: Only use this if the user explicitly asks to remember or save something.&#34;, &#34;parameters&#34;: {&#34;type&#34;: &#34;object&#34;, &#34;properties&#34;: {&#34;content&#34;: {&#34;type&#34;: &#34;string&#34;}, &#34;action&#34;: {&#34;type&#34;: &#34;string&#34;, &#34;enum&#34;: [&#34;append&#34;, &#34;replace&#34;]}}, &#34;required&#34;: [&#34;content&#34;]}}}
         ]
+        if getattr(self, &#34;one_shot&#34;, False):
+            base_tools = [t for t in base_tools if t[&#34;function&#34;][&#34;name&#34;] not in (&#34;delegate_to_engineer&#34;, &#34;return_to_engineer&#34;)]
         
         all_tools = base_tools + self.external_architect_tools
         seen_names = set()
@@ -1541,11 +1553,18 @@ class ai:
 
     @MethodHook
     def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=False, stream=True, session_id=None, chunk_callback=None):
-        soft_limit_warned = False
         is_engineer_keyless = &#34;vertex&#34; in self.engineer_model.lower() or &#34;ollama&#34; in self.engineer_model.lower() or &#34;local&#34; in self.engineer_model.lower()
         if not self.engineer_key and not self.engineer_auth and not is_engineer_keyless:
             raise ValueError(&#34;Engineer API key or authentication not configured. Use &#39;connpy config --engineer-auth &lt;auth&gt;&#39; to set it.&#34;)
 
+        def update_status(text):
+            if not status:
+                return
+            if iteration &gt;= self.soft_limit_iterations:
+                warning_suffix = &#34; [warning]⚠ Taking longer than expected (Ctrl+C to interrupt)[/warning]&#34;
+                if warning_suffix not in text:
+                    text += warning_suffix
+            status.update(text)
             
         if chat_history is None: chat_history = []
         
@@ -1636,18 +1655,14 @@ class ai:
                 if self.interrupted:
                     raise KeyboardInterrupt
                 
-                # Soft limit warning
-                if iteration == self.soft_limit_iterations and not soft_limit_warned:
-                    self.console.print(f&#34;[warning]⚠ Agent has performed {iteration} steps. This is taking longer than expected.[/warning]&#34;)
-                    self.console.print(f&#34;[warning]  You can press Ctrl+C to interrupt and get a summary of progress.[/warning]&#34;)
-                    soft_limit_warned = True
+                # Soft limit warning - handled inline within update_status
                 
                 label = &#34;[architect][bold]Architect[/bold][/architect]&#34; if current_brain == &#34;architect&#34; else &#34;[engineer][bold]Engineer[/bold][/engineer]&#34;
                 if status: 
                     # Notify responder identity for web/remote clients
                     if getattr(status, &#34;is_web&#34;, False) or getattr(status, &#34;is_remote&#34;, False):
                         status.update(f&#34;__RESPONDER__:{current_brain}&#34;)
-                    status.update(f&#34;{label} is thinking... (step {iteration})&#34;)
+                    update_status(f&#34;{label} is thinking... (step {iteration})&#34;)
                 
                 streamed_response = False
                 try:
@@ -1662,7 +1677,7 @@ class ai:
                         response = completion(model=model, messages=safe_messages, tools=tools, num_retries=3, **current_auth)
                 except Exception as e:
                     if current_brain == &#34;architect&#34;:
-                        if status: status.update(&#34;[unavailable]Architect unavailable! Falling back to Engineer...&#34;)
+                        if status: update_status(&#34;[unavailable]Architect unavailable! Falling back to Engineer...&#34;)
                         # Preserve context when falling back - use clean_input directly
                         current_brain = &#34;engineer&#34;
                         model = self.engineer_model
@@ -1719,8 +1734,8 @@ class ai:
                         continue
                     
                     if status:
-                        if fn == &#34;delegate_to_engineer&#34;: status.update(f&#34;[architect]Architect: [DELEGATING MISSION] {args.get(&#39;task&#39;,&#39;&#39;)[:40]}...&#34;)
-                        elif fn == &#34;manage_memory_tool&#34;: status.update(f&#34;[architect]Architect: [UPDATING MEMORY]&#34;)
+                        if fn == &#34;delegate_to_engineer&#34;: update_status(f&#34;[architect]Architect: [DELEGATING MISSION] {args.get(&#39;task&#39;,&#39;&#39;)[:40]}...&#34;)
+                        elif fn == &#34;manage_memory_tool&#34;: update_status(f&#34;[architect]Architect: [UPDATING MEMORY]&#34;)
 
                     if debug:
                         self._print_debug_observation(f&#34;Decision: {fn}&#34;, args, status=status)
@@ -1729,7 +1744,7 @@ class ai:
                         obs, eng_usage = self._engineer_loop(args[&#34;task&#34;], status=status, debug=debug, chat_history=messages[:-1])
                         usage[&#34;input&#34;] += eng_usage[&#34;input&#34;]; usage[&#34;output&#34;] += eng_usage[&#34;output&#34;]; usage[&#34;total&#34;] += eng_usage[&#34;total&#34;]
                     elif fn == &#34;consult_architect&#34;:
-                        if status: status.update(&#34;[architect]Engineer consulting Architect...&#34;)
+                        if status: update_status(&#34;[architect]Engineer consulting Architect...&#34;)
                         try:
                             # Consultation only - Engineer stays in control
                             claude_resp = completion(
@@ -1751,11 +1766,11 @@ class ai:
                                     try: status.start()
                                     except: pass
                         except Exception as e:
-                            if status: status.update(&#34;[unavailable]Architect unavailable! Engineer continuing alone...&#34;)
+                            if status: update_status(&#34;[unavailable]Architect unavailable! Engineer continuing alone...&#34;)
                             obs = f&#34;Architect unavailable ({str(e)}). Proceeding with your best technical judgment.&#34;
                     
                     elif fn == &#34;escalate_to_architect&#34;:
-                        if status: status.update(&#34;[architect]Transferring control to Architect...&#34;)
+                        if status: update_status(&#34;[architect]Transferring control to Architect...&#34;)
                         # Full escalation - Architect takes over
                         current_brain = &#34;architect&#34;
                         model = self.architect_model
@@ -1777,7 +1792,7 @@ class ai:
                                 except: pass
                     
                     elif fn == &#34;return_to_engineer&#34;:
-                        if status: status.update(&#34;[engineer]Transferring control back to Engineer...&#34;)
+                        if status: update_status(&#34;[engineer]Transferring control back to Engineer...&#34;)
                         # Architect returns control to Engineer
                         current_brain = &#34;engineer&#34;
                         model = self.engineer_model
@@ -1830,7 +1845,7 @@ class ai:
                         messages.append(resp_msg.model_dump(exclude_none=True))
                     except Exception as e:
                         if status:
-                            status.update(f&#34;[error]Error fetching summary: {e}[/error]&#34;)
+                            update_status(f&#34;[error]Error fetching summary: {e}[/error]&#34;)
                         printer.warning(f&#34;Failed to fetch final summary from LLM: {e}&#34;)
         except KeyboardInterrupt:
             if status: status.update(&#34;[error]Interrupted! Closing pending tasks...&#34;)
@@ -2167,10 +2182,13 @@ Node: {node_name}&#34;&#34;&#34;
 <pre><code class="python">@property
 def architect_system_prompt(self):
     &#34;&#34;&#34;Build architect system prompt with plugin extensions.&#34;&#34;&#34;
+    prompt = self._architect_base_prompt
+    if getattr(self, &#34;one_shot&#34;, False):
+        prompt += &#34;\n\nCRITICAL 1-SHOT DIAGNOSTICS DIRECTIVE:\nYou are running in a 1-shot offline diagnostics mode. There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately and directly to the user. Do not suggest or attempt to delegate/return control to the engineer.&#34;
     if self.architect_prompt_extensions:
         extensions = &#34;\n&#34;.join(self.architect_prompt_extensions)
-        return self._architect_base_prompt + f&#34;\n\nPlugin Capabilities:\n{extensions}&#34;
-    return self._architect_base_prompt</code></pre>
+        return prompt + f&#34;\n\nPlugin Capabilities:\n{extensions}&#34;
+    return prompt</code></pre>
 </details>
 <div class="desc"><p>Build architect system prompt with plugin extensions.</p></div>
 </dd>
@@ -2488,11 +2506,18 @@ Node: {node_name}&#34;&#34;&#34;
 </summary>
 <pre><code class="python">@MethodHook
 def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=False, stream=True, session_id=None, chunk_callback=None):
-    soft_limit_warned = False
     is_engineer_keyless = &#34;vertex&#34; in self.engineer_model.lower() or &#34;ollama&#34; in self.engineer_model.lower() or &#34;local&#34; in self.engineer_model.lower()
     if not self.engineer_key and not self.engineer_auth and not is_engineer_keyless:
         raise ValueError(&#34;Engineer API key or authentication not configured. Use &#39;connpy config --engineer-auth &lt;auth&gt;&#39; to set it.&#34;)
 
+    def update_status(text):
+        if not status:
+            return
+        if iteration &gt;= self.soft_limit_iterations:
+            warning_suffix = &#34; [warning]⚠ Taking longer than expected (Ctrl+C to interrupt)[/warning]&#34;
+            if warning_suffix not in text:
+                text += warning_suffix
+        status.update(text)
         
     if chat_history is None: chat_history = []
     
@@ -2583,18 +2608,14 @@ def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=Fa
             if self.interrupted:
                 raise KeyboardInterrupt
             
-            # Soft limit warning
-            if iteration == self.soft_limit_iterations and not soft_limit_warned:
-                self.console.print(f&#34;[warning]⚠ Agent has performed {iteration} steps. This is taking longer than expected.[/warning]&#34;)
-                self.console.print(f&#34;[warning]  You can press Ctrl+C to interrupt and get a summary of progress.[/warning]&#34;)
-                soft_limit_warned = True
+            # Soft limit warning - handled inline within update_status
             
             label = &#34;[architect][bold]Architect[/bold][/architect]&#34; if current_brain == &#34;architect&#34; else &#34;[engineer][bold]Engineer[/bold][/engineer]&#34;
             if status: 
                 # Notify responder identity for web/remote clients
                 if getattr(status, &#34;is_web&#34;, False) or getattr(status, &#34;is_remote&#34;, False):
                     status.update(f&#34;__RESPONDER__:{current_brain}&#34;)
-                status.update(f&#34;{label} is thinking... (step {iteration})&#34;)
+                update_status(f&#34;{label} is thinking... (step {iteration})&#34;)
             
             streamed_response = False
             try:
@@ -2609,7 +2630,7 @@ def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=Fa
                     response = completion(model=model, messages=safe_messages, tools=tools, num_retries=3, **current_auth)
             except Exception as e:
                 if current_brain == &#34;architect&#34;:
-                    if status: status.update(&#34;[unavailable]Architect unavailable! Falling back to Engineer...&#34;)
+                    if status: update_status(&#34;[unavailable]Architect unavailable! Falling back to Engineer...&#34;)
                     # Preserve context when falling back - use clean_input directly
                     current_brain = &#34;engineer&#34;
                     model = self.engineer_model
@@ -2666,8 +2687,8 @@ def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=Fa
                     continue
                 
                 if status:
-                    if fn == &#34;delegate_to_engineer&#34;: status.update(f&#34;[architect]Architect: [DELEGATING MISSION] {args.get(&#39;task&#39;,&#39;&#39;)[:40]}...&#34;)
-                    elif fn == &#34;manage_memory_tool&#34;: status.update(f&#34;[architect]Architect: [UPDATING MEMORY]&#34;)
+                    if fn == &#34;delegate_to_engineer&#34;: update_status(f&#34;[architect]Architect: [DELEGATING MISSION] {args.get(&#39;task&#39;,&#39;&#39;)[:40]}...&#34;)
+                    elif fn == &#34;manage_memory_tool&#34;: update_status(f&#34;[architect]Architect: [UPDATING MEMORY]&#34;)
 
                 if debug:
                     self._print_debug_observation(f&#34;Decision: {fn}&#34;, args, status=status)
@@ -2676,7 +2697,7 @@ def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=Fa
                     obs, eng_usage = self._engineer_loop(args[&#34;task&#34;], status=status, debug=debug, chat_history=messages[:-1])
                     usage[&#34;input&#34;] += eng_usage[&#34;input&#34;]; usage[&#34;output&#34;] += eng_usage[&#34;output&#34;]; usage[&#34;total&#34;] += eng_usage[&#34;total&#34;]
                 elif fn == &#34;consult_architect&#34;:
-                    if status: status.update(&#34;[architect]Engineer consulting Architect...&#34;)
+                    if status: update_status(&#34;[architect]Engineer consulting Architect...&#34;)
                     try:
                         # Consultation only - Engineer stays in control
                         claude_resp = completion(
@@ -2698,11 +2719,11 @@ def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=Fa
                                 try: status.start()
                                 except: pass
                     except Exception as e:
-                        if status: status.update(&#34;[unavailable]Architect unavailable! Engineer continuing alone...&#34;)
+                        if status: update_status(&#34;[unavailable]Architect unavailable! Engineer continuing alone...&#34;)
                         obs = f&#34;Architect unavailable ({str(e)}). Proceeding with your best technical judgment.&#34;
                 
                 elif fn == &#34;escalate_to_architect&#34;:
-                    if status: status.update(&#34;[architect]Transferring control to Architect...&#34;)
+                    if status: update_status(&#34;[architect]Transferring control to Architect...&#34;)
                     # Full escalation - Architect takes over
                     current_brain = &#34;architect&#34;
                     model = self.architect_model
@@ -2724,7 +2745,7 @@ def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=Fa
                             except: pass
                 
                 elif fn == &#34;return_to_engineer&#34;:
-                    if status: status.update(&#34;[engineer]Transferring control back to Engineer...&#34;)
+                    if status: update_status(&#34;[engineer]Transferring control back to Engineer...&#34;)
                     # Architect returns control to Engineer
                     current_brain = &#34;engineer&#34;
                     model = self.engineer_model
@@ -2777,7 +2798,7 @@ def ask(self, user_input, dryrun=False, chat_history=None, status=None, debug=Fa
                     messages.append(resp_msg.model_dump(exclude_none=True))
                 except Exception as e:
                     if status:
-                        status.update(f&#34;[error]Error fetching summary: {e}[/error]&#34;)
+                        update_status(f&#34;[error]Error fetching summary: {e}[/error]&#34;)
                     printer.warning(f&#34;Failed to fetch final summary from LLM: {e}&#34;)
     except KeyboardInterrupt:
         if status: status.update(&#34;[error]Interrupted! Closing pending tasks...&#34;)
@@ -6384,6 +6405,7 @@ def test(self, commands, expected, vars = None,*, folder = None, prompt = None,
 <li><a href="#ai-programmatic-use">AI Programmatic Use</a></li>
 </ul>
 </li>
+<li><a href="#license">📜 License</a></li>
 </ul>
 </li>
 </ul>

docs/connpy/services/ai_service.html

@@ -369,7 +369,41 @@ el.replaceWith(d);
         """Load a session's raw data by ID."""
         from connpy.ai import ai
         agent = ai(self.config)
-        return agent.load_session_data(session_id)</code></pre>
+        return agent.load_session_data(session_id)
+
+    def build_playbook_chat(self, user_input: str, chat_history: list = None, status=None, chunk_callback=None):
+        &#34;&#34;&#34;Interact with the specialized Playbook Builder Agent.&#34;&#34;&#34;
+        from connpy.ai import PlaybookBuilderAgent
+        agent = PlaybookBuilderAgent(self.config)
+        return agent.ask(user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)
+
+    def analyze_execution_results(self, results: dict, query: str = None, status=None, chunk_callback=None):
+        &#34;&#34;&#34;Analyze actual command execution results using Network Architect 1-shot.&#34;&#34;&#34;
+        import json
+        results_str = json.dumps(results, indent=2)
+        
+        prompt = f&#34;@architect: Please analyze the following actual execution results. Diagnose any issues, highlight successful actions, and suggest strategic remediation steps if needed.&#34;
+        if query:
+            prompt += f&#34;\nSpecific user request: {query}&#34;
+        prompt += f&#34;\n\nResults Data:\n{results_str}&#34;
+        prompt += &#34;\n\nCRITICAL DIRECTIVE: You are running in a strictly 1-shot offline diagnostics mode (--analyze). There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately. DO NOT suggest, mention, or attempt to delegate the session back to the engineer.&#34;
+        
+        # Delegate to self.ask, setting stream=True and forwarding callback/status.
+        # This will invoke standard ai.ask with &#39;@architect:&#39; prefix, forcing 1-shot architect brain.
+        return self.ask(prompt, status=status, chunk_callback=chunk_callback, one_shot=True)
+
+    def predict_execution_results(self, target_nodes: list, commands: list, status=None, chunk_callback=None):
+        &#34;&#34;&#34;Predict and simulate execution results preventively using the Preflight Simulation Agent (1-shot).&#34;&#34;&#34;
+        nodes_str = &#34;, &#34;.join(target_nodes)
+        commands_str = &#34;\n&#34;.join(f&#34;- {cmd}&#34; for cmd in commands)
+        
+        prompt = f&#34;@engineer: Act as a Preflight Simulation Agent. Simulate and predict the expected outputs and behaviors of the following commands on the target nodes. Alert about potential safety or configuration risks based on node profiles.&#34;
+        prompt += f&#34;\n\nTarget Nodes: {nodes_str}&#34;
+        prompt += f&#34;\nCommands to simulate:\n{commands_str}&#34;
+        prompt += &#34;\n\nCRITICAL SCALABILITY DIRECTIVE: If there are many target nodes, DO NOT list predictions node-by-node. Instead, group them by Operating System, vendor, or platform, and provide a highly concise Executive Summary. Detail individual risks only for nodes that present specific anomalies or security concerns. Focus on overall impact.&#34;
+        
+        # Delegate to self.ask, using the standard engineer brain but with the simulated preflight prompt.
+        return self.ask(prompt, status=status, chunk_callback=chunk_callback)</code></pre>
 </details>
 <div class="desc"><p>Business logic for interacting with AI agents and LLM configurations.</p>
 <p>Initialize the service.</p>
@@ -402,6 +436,31 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Ask the AI copilot for terminal assistance asynchronously.</p></div>
 </dd>
+<dt id="connpy.services.ai_service.AIService.analyze_execution_results"><code class="name flex">
+<span>def <span class="ident">analyze_execution_results</span></span>(<span>self, results: dict, query: str = None, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def analyze_execution_results(self, results: dict, query: str = None, status=None, chunk_callback=None):
+    &#34;&#34;&#34;Analyze actual command execution results using Network Architect 1-shot.&#34;&#34;&#34;
+    import json
+    results_str = json.dumps(results, indent=2)
+    
+    prompt = f&#34;@architect: Please analyze the following actual execution results. Diagnose any issues, highlight successful actions, and suggest strategic remediation steps if needed.&#34;
+    if query:
+        prompt += f&#34;\nSpecific user request: {query}&#34;
+    prompt += f&#34;\n\nResults Data:\n{results_str}&#34;
+    prompt += &#34;\n\nCRITICAL DIRECTIVE: You are running in a strictly 1-shot offline diagnostics mode (--analyze). There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately. DO NOT suggest, mention, or attempt to delegate the session back to the engineer.&#34;
+    
+    # Delegate to self.ask, setting stream=True and forwarding callback/status.
+    # This will invoke standard ai.ask with &#39;@architect:&#39; prefix, forcing 1-shot architect brain.
+    return self.ask(prompt, status=status, chunk_callback=chunk_callback, one_shot=True)</code></pre>
+</details>
+<div class="desc"><p>Analyze actual command execution results using Network Architect 1-shot.</p></div>
+</dd>
 <dt id="connpy.services.ai_service.AIService.ask"><code class="name flex">
 <span>def <span class="ident">ask</span></span>(<span>self,<br>input_text,<br>dryrun=False,<br>chat_history=None,<br>status=None,<br>debug=False,<br>session_id=None,<br>console=None,<br>chunk_callback=None,<br>confirm_handler=None,<br>trust=False,<br>**overrides)</span>
 </code></dt>
@@ -559,6 +618,22 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Identifies command blocks in the terminal history.</p></div>
 </dd>
+<dt id="connpy.services.ai_service.AIService.build_playbook_chat"><code class="name flex">
+<span>def <span class="ident">build_playbook_chat</span></span>(<span>self, user_input: str, chat_history: list = None, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def build_playbook_chat(self, user_input: str, chat_history: list = None, status=None, chunk_callback=None):
+    &#34;&#34;&#34;Interact with the specialized Playbook Builder Agent.&#34;&#34;&#34;
+    from connpy.ai import PlaybookBuilderAgent
+    agent = PlaybookBuilderAgent(self.config)
+    return agent.ask(user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)</code></pre>
+</details>
+<div class="desc"><p>Interact with the specialized Playbook Builder Agent.</p></div>
+</dd>
 <dt id="connpy.services.ai_service.AIService.configure_mcp"><code class="name flex">
 <span>def <span class="ident">configure_mcp</span></span>(<span>self, name, url=None, enabled=None, auto_load_on_os=None, remove=False)</span>
 </code></dt>
@@ -715,6 +790,29 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Load a session's raw data by ID.</p></div>
 </dd>
+<dt id="connpy.services.ai_service.AIService.predict_execution_results"><code class="name flex">
+<span>def <span class="ident">predict_execution_results</span></span>(<span>self, target_nodes: list, commands: list, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def predict_execution_results(self, target_nodes: list, commands: list, status=None, chunk_callback=None):
+    &#34;&#34;&#34;Predict and simulate execution results preventively using the Preflight Simulation Agent (1-shot).&#34;&#34;&#34;
+    nodes_str = &#34;, &#34;.join(target_nodes)
+    commands_str = &#34;\n&#34;.join(f&#34;- {cmd}&#34; for cmd in commands)
+    
+    prompt = f&#34;@engineer: Act as a Preflight Simulation Agent. Simulate and predict the expected outputs and behaviors of the following commands on the target nodes. Alert about potential safety or configuration risks based on node profiles.&#34;
+    prompt += f&#34;\n\nTarget Nodes: {nodes_str}&#34;
+    prompt += f&#34;\nCommands to simulate:\n{commands_str}&#34;
+    prompt += &#34;\n\nCRITICAL SCALABILITY DIRECTIVE: If there are many target nodes, DO NOT list predictions node-by-node. Instead, group them by Operating System, vendor, or platform, and provide a highly concise Executive Summary. Detail individual risks only for nodes that present specific anomalies or security concerns. Focus on overall impact.&#34;
+    
+    # Delegate to self.ask, using the standard engineer brain but with the simulated preflight prompt.
+    return self.ask(prompt, status=status, chunk_callback=chunk_callback)</code></pre>
+</details>
+<div class="desc"><p>Predict and simulate execution results preventively using the Preflight Simulation Agent (1-shot).</p></div>
+</dd>
 <dt id="connpy.services.ai_service.AIService.process_copilot_input"><code class="name flex">
 <span>def <span class="ident">process_copilot_input</span></span>(<span>self, input_text: str, session_state: dict) ‑> dict</span>
 </code></dt>
@@ -813,9 +911,11 @@ el.replaceWith(d);
 <h4><code><a title="connpy.services.ai_service.AIService" href="#connpy.services.ai_service.AIService">AIService</a></code></h4>
 <ul class="">
 <li><code><a title="connpy.services.ai_service.AIService.aask_copilot" href="#connpy.services.ai_service.AIService.aask_copilot">aask_copilot</a></code></li>
+<li><code><a title="connpy.services.ai_service.AIService.analyze_execution_results" href="#connpy.services.ai_service.AIService.analyze_execution_results">analyze_execution_results</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.ask" href="#connpy.services.ai_service.AIService.ask">ask</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.ask_copilot" href="#connpy.services.ai_service.AIService.ask_copilot">ask_copilot</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.build_context_blocks" href="#connpy.services.ai_service.AIService.build_context_blocks">build_context_blocks</a></code></li>
+<li><code><a title="connpy.services.ai_service.AIService.build_playbook_chat" href="#connpy.services.ai_service.AIService.build_playbook_chat">build_playbook_chat</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.configure_mcp" href="#connpy.services.ai_service.AIService.configure_mcp">configure_mcp</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.configure_provider" href="#connpy.services.ai_service.AIService.configure_provider">configure_provider</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.confirm" href="#connpy.services.ai_service.AIService.confirm">confirm</a></code></li>
@@ -823,6 +923,7 @@ el.replaceWith(d);
 <li><code><a title="connpy.services.ai_service.AIService.list_mcp_servers" href="#connpy.services.ai_service.AIService.list_mcp_servers">list_mcp_servers</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.list_sessions" href="#connpy.services.ai_service.AIService.list_sessions">list_sessions</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.load_session_data" href="#connpy.services.ai_service.AIService.load_session_data">load_session_data</a></code></li>
+<li><code><a title="connpy.services.ai_service.AIService.predict_execution_results" href="#connpy.services.ai_service.AIService.predict_execution_results">predict_execution_results</a></code></li>
 <li><code><a title="connpy.services.ai_service.AIService.process_copilot_input" href="#connpy.services.ai_service.AIService.process_copilot_input">process_copilot_input</a></code></li>
 </ul>
 </li>

docs/connpy/services/execution_service.html

@@ -156,56 +156,7 @@ el.replaceWith(d);
         except Exception as e:
             raise ConnpyError(f"Failed to read script {script_path}: {e}")
             
-        return self.run_commands(nodes_filter, commands, parallel=parallel)
-
-    def run_yaml_playbook(self, playbook_data: str, parallel: int = 10) -> Dict[str, Any]:
-        """Run a structured Connpy YAML automation playbook (from path or content)."""
-        playbook = None
-        if playbook_data.startswith("---YAML---\n"):
-            try:
-                content = playbook_data[len("---YAML---\n"):]
-                playbook = yaml.load(content, Loader=yaml.FullLoader)
-            except Exception as e:
-                raise ConnpyError(f"Failed to parse YAML content: {e}")
-        else:
-            if not os.path.exists(playbook_data):
-                raise ConnpyError(f"Playbook file not found: {playbook_data}")
-            try:
-                with open(playbook_data, "r") as f:
-                    playbook = yaml.load(f, Loader=yaml.FullLoader)
-            except Exception as e:
-                raise ConnpyError(f"Failed to load playbook {playbook_data}: {e}")
-            
-        # Basic validation
-        if not isinstance(playbook, dict) or "nodes" not in playbook or "commands" not in playbook:
-            raise ConnpyError("Invalid playbook format: missing 'nodes' or 'commands' keys.")
-            
-        action = playbook.get("action", "run")
-        options = playbook.get("options", {})
-        
-        # Extract all fields similar to RunHandler.cli_run
-        exec_args = {
-            "nodes_filter": playbook["nodes"],
-            "commands": playbook["commands"],
-            "variables": playbook.get("variables"),
-            "parallel": options.get("parallel", parallel),
-            "timeout": playbook.get("timeout", options.get("timeout", 20)),
-            "prompt": options.get("prompt"),
-            "name": playbook.get("name", "Task")
-        }
-
-        # Map 'output' field to folder path if it's not stdout/null
-        output_cfg = playbook.get("output")
-        if output_cfg not in [None, "stdout"]:
-            exec_args["folder"] = output_cfg
-
-        if action == "run":
-            return self.run_commands(**exec_args)
-        elif action == "test":
-            exec_args["expected"] = playbook.get("expected", [])
-            return self.test_commands(**exec_args)
-        else:
-            raise ConnpyError(f&#34;Unsupported playbook action: {action}&#34;)</code></pre>
+        return self.run_commands(nodes_filter, commands, parallel=parallel)</code></pre>
 </details>
 <div class="desc"><p>Business logic for executing commands on nodes and running automation scripts.</p>
 <p>Initialize the service.</p>
@@ -300,65 +251,6 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Execute commands on a set of nodes.</p></div>
 </dd>
-<dt id="connpy.services.execution_service.ExecutionService.run_yaml_playbook"><code class="name flex">
-<span>def <span class="ident">run_yaml_playbook</span></span>(<span>self, playbook_data: str, parallel: int = 10) ‑> Dict[str, Any]</span>
-</code></dt>
-<dd>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def run_yaml_playbook(self, playbook_data: str, parallel: int = 10) -&gt; Dict[str, Any]:
-    &#34;&#34;&#34;Run a structured Connpy YAML automation playbook (from path or content).&#34;&#34;&#34;
-    playbook = None
-    if playbook_data.startswith(&#34;---YAML---\n&#34;):
-        try:
-            content = playbook_data[len(&#34;---YAML---\n&#34;):]
-            playbook = yaml.load(content, Loader=yaml.FullLoader)
-        except Exception as e:
-            raise ConnpyError(f&#34;Failed to parse YAML content: {e}&#34;)
-    else:
-        if not os.path.exists(playbook_data):
-            raise ConnpyError(f&#34;Playbook file not found: {playbook_data}&#34;)
-        try:
-            with open(playbook_data, &#34;r&#34;) as f:
-                playbook = yaml.load(f, Loader=yaml.FullLoader)
-        except Exception as e:
-            raise ConnpyError(f&#34;Failed to load playbook {playbook_data}: {e}&#34;)
-        
-    # Basic validation
-    if not isinstance(playbook, dict) or &#34;nodes&#34; not in playbook or &#34;commands&#34; not in playbook:
-        raise ConnpyError(&#34;Invalid playbook format: missing &#39;nodes&#39; or &#39;commands&#39; keys.&#34;)
-        
-    action = playbook.get(&#34;action&#34;, &#34;run&#34;)
-    options = playbook.get(&#34;options&#34;, {})
-    
-    # Extract all fields similar to RunHandler.cli_run
-    exec_args = {
-        &#34;nodes_filter&#34;: playbook[&#34;nodes&#34;],
-        &#34;commands&#34;: playbook[&#34;commands&#34;],
-        &#34;variables&#34;: playbook.get(&#34;variables&#34;),
-        &#34;parallel&#34;: options.get(&#34;parallel&#34;, parallel),
-        &#34;timeout&#34;: playbook.get(&#34;timeout&#34;, options.get(&#34;timeout&#34;, 20)),
-        &#34;prompt&#34;: options.get(&#34;prompt&#34;),
-        &#34;name&#34;: playbook.get(&#34;name&#34;, &#34;Task&#34;)
-    }
-
-    # Map &#39;output&#39; field to folder path if it&#39;s not stdout/null
-    output_cfg = playbook.get(&#34;output&#34;)
-    if output_cfg not in [None, &#34;stdout&#34;]:
-        exec_args[&#34;folder&#34;] = output_cfg
-
-    if action == &#34;run&#34;:
-        return self.run_commands(**exec_args)
-    elif action == &#34;test&#34;:
-        exec_args[&#34;expected&#34;] = playbook.get(&#34;expected&#34;, [])
-        return self.test_commands(**exec_args)
-    else:
-        raise ConnpyError(f&#34;Unsupported playbook action: {action}&#34;)</code></pre>
-</details>
-<div class="desc"><p>Run a structured Connpy YAML automation playbook (from path or content).</p></div>
-</dd>
 <dt id="connpy.services.execution_service.ExecutionService.test_commands"><code class="name flex">
 <span>def <span class="ident">test_commands</span></span>(<span>self,<br>nodes_filter: str,<br>commands: List[str],<br>expected: List[str],<br>variables: Dict[str, Any] | None = None,<br>parallel: int = 10,<br>timeout: int = 20,<br>folder: str | None = None,<br>prompt: str | None = None,<br>on_node_complete: Callable | None = None,<br>logger: Callable | None = None,<br>name: str | None = None) ‑> Dict[str, Dict[str, bool]]</span>
 </code></dt>
@@ -439,7 +331,6 @@ el.replaceWith(d);
 <ul class="">
 <li><code><a title="connpy.services.execution_service.ExecutionService.run_cli_script" href="#connpy.services.execution_service.ExecutionService.run_cli_script">run_cli_script</a></code></li>
 <li><code><a title="connpy.services.execution_service.ExecutionService.run_commands" href="#connpy.services.execution_service.ExecutionService.run_commands">run_commands</a></code></li>
-<li><code><a title="connpy.services.execution_service.ExecutionService.run_yaml_playbook" href="#connpy.services.execution_service.ExecutionService.run_yaml_playbook">run_yaml_playbook</a></code></li>
 <li><code><a title="connpy.services.execution_service.ExecutionService.test_commands" href="#connpy.services.execution_service.ExecutionService.test_commands">test_commands</a></code></li>
 </ul>
 </li>

docs/connpy/services/index.html

@@ -428,7 +428,41 @@ el.replaceWith(d);
         """Load a session's raw data by ID."""
         from connpy.ai import ai
         agent = ai(self.config)
-        return agent.load_session_data(session_id)</code></pre>
+        return agent.load_session_data(session_id)
+
+    def build_playbook_chat(self, user_input: str, chat_history: list = None, status=None, chunk_callback=None):
+        &#34;&#34;&#34;Interact with the specialized Playbook Builder Agent.&#34;&#34;&#34;
+        from connpy.ai import PlaybookBuilderAgent
+        agent = PlaybookBuilderAgent(self.config)
+        return agent.ask(user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)
+
+    def analyze_execution_results(self, results: dict, query: str = None, status=None, chunk_callback=None):
+        &#34;&#34;&#34;Analyze actual command execution results using Network Architect 1-shot.&#34;&#34;&#34;
+        import json
+        results_str = json.dumps(results, indent=2)
+        
+        prompt = f&#34;@architect: Please analyze the following actual execution results. Diagnose any issues, highlight successful actions, and suggest strategic remediation steps if needed.&#34;
+        if query:
+            prompt += f&#34;\nSpecific user request: {query}&#34;
+        prompt += f&#34;\n\nResults Data:\n{results_str}&#34;
+        prompt += &#34;\n\nCRITICAL DIRECTIVE: You are running in a strictly 1-shot offline diagnostics mode (--analyze). There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately. DO NOT suggest, mention, or attempt to delegate the session back to the engineer.&#34;
+        
+        # Delegate to self.ask, setting stream=True and forwarding callback/status.
+        # This will invoke standard ai.ask with &#39;@architect:&#39; prefix, forcing 1-shot architect brain.
+        return self.ask(prompt, status=status, chunk_callback=chunk_callback, one_shot=True)
+
+    def predict_execution_results(self, target_nodes: list, commands: list, status=None, chunk_callback=None):
+        &#34;&#34;&#34;Predict and simulate execution results preventively using the Preflight Simulation Agent (1-shot).&#34;&#34;&#34;
+        nodes_str = &#34;, &#34;.join(target_nodes)
+        commands_str = &#34;\n&#34;.join(f&#34;- {cmd}&#34; for cmd in commands)
+        
+        prompt = f&#34;@engineer: Act as a Preflight Simulation Agent. Simulate and predict the expected outputs and behaviors of the following commands on the target nodes. Alert about potential safety or configuration risks based on node profiles.&#34;
+        prompt += f&#34;\n\nTarget Nodes: {nodes_str}&#34;
+        prompt += f&#34;\nCommands to simulate:\n{commands_str}&#34;
+        prompt += &#34;\n\nCRITICAL SCALABILITY DIRECTIVE: If there are many target nodes, DO NOT list predictions node-by-node. Instead, group them by Operating System, vendor, or platform, and provide a highly concise Executive Summary. Detail individual risks only for nodes that present specific anomalies or security concerns. Focus on overall impact.&#34;
+        
+        # Delegate to self.ask, using the standard engineer brain but with the simulated preflight prompt.
+        return self.ask(prompt, status=status, chunk_callback=chunk_callback)</code></pre>
 </details>
 <div class="desc"><p>Business logic for interacting with AI agents and LLM configurations.</p>
 <p>Initialize the service.</p>
@@ -461,6 +495,31 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Ask the AI copilot for terminal assistance asynchronously.</p></div>
 </dd>
+<dt id="connpy.services.AIService.analyze_execution_results"><code class="name flex">
+<span>def <span class="ident">analyze_execution_results</span></span>(<span>self, results: dict, query: str = None, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def analyze_execution_results(self, results: dict, query: str = None, status=None, chunk_callback=None):
+    &#34;&#34;&#34;Analyze actual command execution results using Network Architect 1-shot.&#34;&#34;&#34;
+    import json
+    results_str = json.dumps(results, indent=2)
+    
+    prompt = f&#34;@architect: Please analyze the following actual execution results. Diagnose any issues, highlight successful actions, and suggest strategic remediation steps if needed.&#34;
+    if query:
+        prompt += f&#34;\nSpecific user request: {query}&#34;
+    prompt += f&#34;\n\nResults Data:\n{results_str}&#34;
+    prompt += &#34;\n\nCRITICAL DIRECTIVE: You are running in a strictly 1-shot offline diagnostics mode (--analyze). There is no active conversation loop, and you are NOT conversing with a Network Engineer. You MUST deliver your complete strategic analysis immediately. DO NOT suggest, mention, or attempt to delegate the session back to the engineer.&#34;
+    
+    # Delegate to self.ask, setting stream=True and forwarding callback/status.
+    # This will invoke standard ai.ask with &#39;@architect:&#39; prefix, forcing 1-shot architect brain.
+    return self.ask(prompt, status=status, chunk_callback=chunk_callback, one_shot=True)</code></pre>
+</details>
+<div class="desc"><p>Analyze actual command execution results using Network Architect 1-shot.</p></div>
+</dd>
 <dt id="connpy.services.AIService.ask"><code class="name flex">
 <span>def <span class="ident">ask</span></span>(<span>self,<br>input_text,<br>dryrun=False,<br>chat_history=None,<br>status=None,<br>debug=False,<br>session_id=None,<br>console=None,<br>chunk_callback=None,<br>confirm_handler=None,<br>trust=False,<br>**overrides)</span>
 </code></dt>
@@ -618,6 +677,22 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Identifies command blocks in the terminal history.</p></div>
 </dd>
+<dt id="connpy.services.AIService.build_playbook_chat"><code class="name flex">
+<span>def <span class="ident">build_playbook_chat</span></span>(<span>self, user_input: str, chat_history: list = None, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def build_playbook_chat(self, user_input: str, chat_history: list = None, status=None, chunk_callback=None):
+    &#34;&#34;&#34;Interact with the specialized Playbook Builder Agent.&#34;&#34;&#34;
+    from connpy.ai import PlaybookBuilderAgent
+    agent = PlaybookBuilderAgent(self.config)
+    return agent.ask(user_input, chat_history=chat_history, status=status, chunk_callback=chunk_callback)</code></pre>
+</details>
+<div class="desc"><p>Interact with the specialized Playbook Builder Agent.</p></div>
+</dd>
 <dt id="connpy.services.AIService.configure_mcp"><code class="name flex">
 <span>def <span class="ident">configure_mcp</span></span>(<span>self, name, url=None, enabled=None, auto_load_on_os=None, remove=False)</span>
 </code></dt>
@@ -774,6 +849,29 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Load a session's raw data by ID.</p></div>
 </dd>
+<dt id="connpy.services.AIService.predict_execution_results"><code class="name flex">
+<span>def <span class="ident">predict_execution_results</span></span>(<span>self, target_nodes: list, commands: list, status=None, chunk_callback=None)</span>
+</code></dt>
+<dd>
+<details class="source">
+<summary>
+<span>Expand source code</span>
+</summary>
+<pre><code class="python">def predict_execution_results(self, target_nodes: list, commands: list, status=None, chunk_callback=None):
+    &#34;&#34;&#34;Predict and simulate execution results preventively using the Preflight Simulation Agent (1-shot).&#34;&#34;&#34;
+    nodes_str = &#34;, &#34;.join(target_nodes)
+    commands_str = &#34;\n&#34;.join(f&#34;- {cmd}&#34; for cmd in commands)
+    
+    prompt = f&#34;@engineer: Act as a Preflight Simulation Agent. Simulate and predict the expected outputs and behaviors of the following commands on the target nodes. Alert about potential safety or configuration risks based on node profiles.&#34;
+    prompt += f&#34;\n\nTarget Nodes: {nodes_str}&#34;
+    prompt += f&#34;\nCommands to simulate:\n{commands_str}&#34;
+    prompt += &#34;\n\nCRITICAL SCALABILITY DIRECTIVE: If there are many target nodes, DO NOT list predictions node-by-node. Instead, group them by Operating System, vendor, or platform, and provide a highly concise Executive Summary. Detail individual risks only for nodes that present specific anomalies or security concerns. Focus on overall impact.&#34;
+    
+    # Delegate to self.ask, using the standard engineer brain but with the simulated preflight prompt.
+    return self.ask(prompt, status=status, chunk_callback=chunk_callback)</code></pre>
+</details>
+<div class="desc"><p>Predict and simulate execution results preventively using the Preflight Simulation Agent (1-shot).</p></div>
+</dd>
 <dt id="connpy.services.AIService.process_copilot_input"><code class="name flex">
 <span>def <span class="ident">process_copilot_input</span></span>(<span>self, input_text: str, session_state: dict) ‑> dict</span>
 </code></dt>
@@ -1255,56 +1353,7 @@ el.replaceWith(d);
         except Exception as e:
             raise ConnpyError(f&#34;Failed to read script {script_path}: {e}&#34;)
             
-        return self.run_commands(nodes_filter, commands, parallel=parallel)
-
-    def run_yaml_playbook(self, playbook_data: str, parallel: int = 10) -&gt; Dict[str, Any]:
-        &#34;&#34;&#34;Run a structured Connpy YAML automation playbook (from path or content).&#34;&#34;&#34;
-        playbook = None
-        if playbook_data.startswith(&#34;---YAML---\n&#34;):
-            try:
-                content = playbook_data[len(&#34;---YAML---\n&#34;):]
-                playbook = yaml.load(content, Loader=yaml.FullLoader)
-            except Exception as e:
-                raise ConnpyError(f&#34;Failed to parse YAML content: {e}&#34;)
-        else:
-            if not os.path.exists(playbook_data):
-                raise ConnpyError(f&#34;Playbook file not found: {playbook_data}&#34;)
-            try:
-                with open(playbook_data, &#34;r&#34;) as f:
-                    playbook = yaml.load(f, Loader=yaml.FullLoader)
-            except Exception as e:
-                raise ConnpyError(f&#34;Failed to load playbook {playbook_data}: {e}&#34;)
-            
-        # Basic validation
-        if not isinstance(playbook, dict) or &#34;nodes&#34; not in playbook or &#34;commands&#34; not in playbook:
-            raise ConnpyError(&#34;Invalid playbook format: missing &#39;nodes&#39; or &#39;commands&#39; keys.&#34;)
-            
-        action = playbook.get(&#34;action&#34;, &#34;run&#34;)
-        options = playbook.get(&#34;options&#34;, {})
-        
-        # Extract all fields similar to RunHandler.cli_run
-        exec_args = {
-            &#34;nodes_filter&#34;: playbook[&#34;nodes&#34;],
-            &#34;commands&#34;: playbook[&#34;commands&#34;],
-            &#34;variables&#34;: playbook.get(&#34;variables&#34;),
-            &#34;parallel&#34;: options.get(&#34;parallel&#34;, parallel),
-            &#34;timeout&#34;: playbook.get(&#34;timeout&#34;, options.get(&#34;timeout&#34;, 20)),
-            &#34;prompt&#34;: options.get(&#34;prompt&#34;),
-            &#34;name&#34;: playbook.get(&#34;name&#34;, &#34;Task&#34;)
-        }
-
-        # Map &#39;output&#39; field to folder path if it&#39;s not stdout/null
-        output_cfg = playbook.get(&#34;output&#34;)
-        if output_cfg not in [None, &#34;stdout&#34;]:
-            exec_args[&#34;folder&#34;] = output_cfg
-
-        if action == &#34;run&#34;:
-            return self.run_commands(**exec_args)
-        elif action == &#34;test&#34;:
-            exec_args[&#34;expected&#34;] = playbook.get(&#34;expected&#34;, [])
-            return self.test_commands(**exec_args)
-        else:
-            raise ConnpyError(f&#34;Unsupported playbook action: {action}&#34;)</code></pre>
+        return self.run_commands(nodes_filter, commands, parallel=parallel)</code></pre>
 </details>
 <div class="desc"><p>Business logic for executing commands on nodes and running automation scripts.</p>
 <p>Initialize the service.</p>
@@ -1399,65 +1448,6 @@ el.replaceWith(d);
 </details>
 <div class="desc"><p>Execute commands on a set of nodes.</p></div>
 </dd>
-<dt id="connpy.services.ExecutionService.run_yaml_playbook"><code class="name flex">
-<span>def <span class="ident">run_yaml_playbook</span></span>(<span>self, playbook_data: str, parallel: int = 10) ‑> Dict[str, Any]</span>
-</code></dt>
-<dd>
-<details class="source">
-<summary>
-<span>Expand source code</span>
-</summary>
-<pre><code class="python">def run_yaml_playbook(self, playbook_data: str, parallel: int = 10) -&gt; Dict[str, Any]:
-    &#34;&#34;&#34;Run a structured Connpy YAML automation playbook (from path or content).&#34;&#34;&#34;
-    playbook = None
-    if playbook_data.startswith(&#34;---YAML---\n&#34;):
-        try:
-            content = playbook_data[len(&#34;---YAML---\n&#34;):]
-            playbook = yaml.load(content, Loader=yaml.FullLoader)
-        except Exception as e:
-            raise ConnpyError(f&#34;Failed to parse YAML content: {e}&#34;)
-    else:
-        if not os.path.exists(playbook_data):
-            raise ConnpyError(f&#34;Playbook file not found: {playbook_data}&#34;)
-        try:
-            with open(playbook_data, &#34;r&#34;) as f:
-                playbook = yaml.load(f, Loader=yaml.FullLoader)
-        except Exception as e:
-            raise ConnpyError(f&#34;Failed to load playbook {playbook_data}: {e}&#34;)
-        
-    # Basic validation
-    if not isinstance(playbook, dict) or &#34;nodes&#34; not in playbook or &#34;commands&#34; not in playbook:
-        raise ConnpyError(&#34;Invalid playbook format: missing &#39;nodes&#39; or &#39;commands&#39; keys.&#34;)
-        
-    action = playbook.get(&#34;action&#34;, &#34;run&#34;)
-    options = playbook.get(&#34;options&#34;, {})
-    
-    # Extract all fields similar to RunHandler.cli_run
-    exec_args = {
-        &#34;nodes_filter&#34;: playbook[&#34;nodes&#34;],
-        &#34;commands&#34;: playbook[&#34;commands&#34;],
-        &#34;variables&#34;: playbook.get(&#34;variables&#34;),
-        &#34;parallel&#34;: options.get(&#34;parallel&#34;, parallel),
-        &#34;timeout&#34;: playbook.get(&#34;timeout&#34;, options.get(&#34;timeout&#34;, 20)),
-        &#34;prompt&#34;: options.get(&#34;prompt&#34;),
-        &#34;name&#34;: playbook.get(&#34;name&#34;, &#34;Task&#34;)
-    }
-
-    # Map &#39;output&#39; field to folder path if it&#39;s not stdout/null
-    output_cfg = playbook.get(&#34;output&#34;)
-    if output_cfg not in [None, &#34;stdout&#34;]:
-        exec_args[&#34;folder&#34;] = output_cfg
-
-    if action == &#34;run&#34;:
-        return self.run_commands(**exec_args)
-    elif action == &#34;test&#34;:
-        exec_args[&#34;expected&#34;] = playbook.get(&#34;expected&#34;, [])
-        return self.test_commands(**exec_args)
-    else:
-        raise ConnpyError(f&#34;Unsupported playbook action: {action}&#34;)</code></pre>
-</details>
-<div class="desc"><p>Run a structured Connpy YAML automation playbook (from path or content).</p></div>
-</dd>
 <dt id="connpy.services.ExecutionService.test_commands"><code class="name flex">
 <span>def <span class="ident">test_commands</span></span>(<span>self,<br>nodes_filter: str,<br>commands: List[str],<br>expected: List[str],<br>variables: Dict[str, Any] | None = None,<br>parallel: int = 10,<br>timeout: int = 20,<br>folder: str | None = None,<br>prompt: str | None = None,<br>on_node_complete: Callable | None = None,<br>logger: Callable | None = None,<br>name: str | None = None) ‑> Dict[str, Dict[str, bool]]</span>
 </code></dt>
@@ -4006,9 +3996,11 @@ el.replaceWith(d);
 <h4><code><a title="connpy.services.AIService" href="#connpy.services.AIService">AIService</a></code></h4>
 <ul class="">
 <li><code><a title="connpy.services.AIService.aask_copilot" href="#connpy.services.AIService.aask_copilot">aask_copilot</a></code></li>
+<li><code><a title="connpy.services.AIService.analyze_execution_results" href="#connpy.services.AIService.analyze_execution_results">analyze_execution_results</a></code></li>
 <li><code><a title="connpy.services.AIService.ask" href="#connpy.services.AIService.ask">ask</a></code></li>
 <li><code><a title="connpy.services.AIService.ask_copilot" href="#connpy.services.AIService.ask_copilot">ask_copilot</a></code></li>
 <li><code><a title="connpy.services.AIService.build_context_blocks" href="#connpy.services.AIService.build_context_blocks">build_context_blocks</a></code></li>
+<li><code><a title="connpy.services.AIService.build_playbook_chat" href="#connpy.services.AIService.build_playbook_chat">build_playbook_chat</a></code></li>
 <li><code><a title="connpy.services.AIService.configure_mcp" href="#connpy.services.AIService.configure_mcp">configure_mcp</a></code></li>
 <li><code><a title="connpy.services.AIService.configure_provider" href="#connpy.services.AIService.configure_provider">configure_provider</a></code></li>
 <li><code><a title="connpy.services.AIService.confirm" href="#connpy.services.AIService.confirm">confirm</a></code></li>
@@ -4016,6 +4008,7 @@ el.replaceWith(d);
 <li><code><a title="connpy.services.AIService.list_mcp_servers" href="#connpy.services.AIService.list_mcp_servers">list_mcp_servers</a></code></li>
 <li><code><a title="connpy.services.AIService.list_sessions" href="#connpy.services.AIService.list_sessions">list_sessions</a></code></li>
 <li><code><a title="connpy.services.AIService.load_session_data" href="#connpy.services.AIService.load_session_data">load_session_data</a></code></li>
+<li><code><a title="connpy.services.AIService.predict_execution_results" href="#connpy.services.AIService.predict_execution_results">predict_execution_results</a></code></li>
 <li><code><a title="connpy.services.AIService.process_copilot_input" href="#connpy.services.AIService.process_copilot_input">process_copilot_input</a></code></li>
 </ul>
 </li>
@@ -4041,7 +4034,6 @@ el.replaceWith(d);
 <ul class="">
 <li><code><a title="connpy.services.ExecutionService.run_cli_script" href="#connpy.services.ExecutionService.run_cli_script">run_cli_script</a></code></li>
 <li><code><a title="connpy.services.ExecutionService.run_commands" href="#connpy.services.ExecutionService.run_commands">run_commands</a></code></li>
-<li><code><a title="connpy.services.ExecutionService.run_yaml_playbook" href="#connpy.services.ExecutionService.run_yaml_playbook">run_yaml_playbook</a></code></li>
 <li><code><a title="connpy.services.ExecutionService.test_commands" href="#connpy.services.ExecutionService.test_commands">test_commands</a></code></li>
 </ul>
 </li>