mirror of
https://github.com/Significant-Gravitas/AutoGPT.git
synced 2026-04-08 03:00:28 -04:00
dd10e1b339
- Remove separate task_id creation for long-running tools - Update stream_registry to use session_id as primary identifier - Update all stream_registry calls across codebase to use session_id - Keep ActiveTask.task_id field for backwards compatibility (equals session_id) - Fix mini game showing forever by ensuring results reach correct stream - Remove _task_id parameter from stream_chat_completion - Update processor, service, sdk/service, routes, completion handlers Root cause: Long-running tools were creating separate task_ids and publishing to different streams than the frontend was subscribed to. Now everything uses session_id, ensuring results reach the frontend properly. Files modified: - backend/copilot/stream_registry.py - backend/api/features/chat/routes.py - backend/copilot/executor/processor.py - backend/copilot/service.py - backend/copilot/sdk/service.py - backend/copilot/completion_handler.py - backend/copilot/completion_consumer.py - frontend EditAgent/CreateAgent components (remove duplicate loader) - frontend ChatMessagesContainer (remove unused imports) Tests: 139/140 passed (1 SDK initialization failure unrelated to changes)
281 lines
10 KiB
Python
281 lines
10 KiB
Python
"""EditAgentTool - Edits existing agents using natural language."""
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import logging
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from typing import Any
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from backend.copilot.model import ChatSession
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from .agent_generator import (
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AgentGeneratorNotConfiguredError,
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generate_agent_patch,
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get_agent_as_json,
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get_user_message_for_error,
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save_agent_to_library,
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)
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from .base import BaseTool
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from .models import (
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AgentPreviewResponse,
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AgentSavedResponse,
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ClarificationNeededResponse,
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ClarifyingQuestion,
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ErrorResponse,
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ToolResponseBase,
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)
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logger = logging.getLogger(__name__)
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class EditAgentTool(BaseTool):
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"""Tool for editing existing agents using natural language."""
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@property
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def name(self) -> str:
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return "edit_agent"
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@property
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def description(self) -> str:
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return (
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"Edit an existing agent from the user's library using natural language. "
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"Generates updates to the agent while preserving unchanged parts. "
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"\n\nIMPORTANT: Before calling this tool, if the changes involve adding new "
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"functionality, search for relevant existing agents using find_library_agent "
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"that could be used as building blocks. Pass their IDs in library_agent_ids."
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)
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@property
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def requires_auth(self) -> bool:
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return True
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@property
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def is_long_running(self) -> bool:
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return True
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@property
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def parameters(self) -> dict[str, Any]:
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return {
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"type": "object",
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"properties": {
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"agent_id": {
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"type": "string",
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"description": (
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"The ID of the agent to edit. "
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"Can be a graph ID or library agent ID."
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),
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},
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"changes": {
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"type": "string",
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"description": (
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"Natural language description of what changes to make. "
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"Be specific about what to add, remove, or modify."
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),
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},
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"context": {
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"type": "string",
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"description": (
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"Additional context or answers to previous clarifying questions."
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),
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},
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"library_agent_ids": {
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"type": "array",
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"items": {"type": "string"},
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"description": (
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"List of library agent IDs to use as building blocks for the changes. "
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"If adding new functionality, search for relevant agents using "
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"find_library_agent first, then pass their IDs here."
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),
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},
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"save": {
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"type": "boolean",
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"description": (
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"Whether to save the changes. "
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"Default is true. Set to false for preview only."
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),
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"default": True,
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},
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},
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"required": ["agent_id", "changes"],
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}
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async def _execute(
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self,
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user_id: str | None,
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session: ChatSession,
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**kwargs,
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) -> ToolResponseBase:
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"""Execute the edit_agent tool.
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Flow:
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1. Fetch the current agent
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2. Generate updated agent (external service handles fixing and validation)
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3. Preview or save based on the save parameter
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"""
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agent_id = kwargs.get("agent_id", "").strip()
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changes = kwargs.get("changes", "").strip()
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context = kwargs.get("context", "")
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library_agent_ids = kwargs.get("library_agent_ids", [])
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save = kwargs.get("save", True)
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session_id = session.session_id if session else None
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if not agent_id:
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return ErrorResponse(
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message="Please provide the agent ID to edit.",
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error="Missing agent_id parameter",
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session_id=session_id,
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)
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if not changes:
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return ErrorResponse(
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message="Please describe what changes you want to make.",
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error="Missing changes parameter",
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session_id=session_id,
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)
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current_agent = await get_agent_as_json(agent_id, user_id)
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if current_agent is None:
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return ErrorResponse(
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message=f"Could not find agent with ID '{agent_id}' in your library.",
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error="agent_not_found",
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session_id=session_id,
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)
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# Fetch library agents by IDs if provided
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library_agents = None
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if user_id and library_agent_ids:
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try:
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from .agent_generator import get_library_agents_by_ids
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graph_id = current_agent.get("id")
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# Filter out the current agent being edited
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filtered_ids = [id for id in library_agent_ids if id != graph_id]
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library_agents = await get_library_agents_by_ids(
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user_id=user_id,
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agent_ids=filtered_ids,
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)
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logger.debug(
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f"Fetched {len(library_agents)} library agents by ID for sub-agent composition"
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)
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except Exception as e:
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logger.warning(f"Failed to fetch library agents by IDs: {e}")
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update_request = changes
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if context:
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update_request = f"{changes}\n\nAdditional context:\n{context}"
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try:
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result = await generate_agent_patch(
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update_request,
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current_agent,
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library_agents,
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)
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except AgentGeneratorNotConfiguredError:
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return ErrorResponse(
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message=(
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"Agent editing is not available. "
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"The Agent Generator service is not configured."
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),
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error="service_not_configured",
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session_id=session_id,
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)
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if result is None:
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return ErrorResponse(
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message="Failed to generate changes. The agent generation service may be unavailable or timed out. Please try again.",
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error="update_generation_failed",
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details={"agent_id": agent_id, "changes": changes[:100]},
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session_id=session_id,
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)
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# Check if the result is an error from the external service
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if isinstance(result, dict) and result.get("type") == "error":
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error_msg = result.get("error", "Unknown error")
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error_type = result.get("error_type", "unknown")
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user_message = get_user_message_for_error(
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error_type,
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operation="generate the changes",
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llm_parse_message="The AI had trouble generating the changes. Please try again or simplify your request.",
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validation_message="The generated changes failed validation. Please try rephrasing your request.",
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error_details=error_msg,
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)
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return ErrorResponse(
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message=user_message,
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error=f"update_generation_failed:{error_type}",
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details={
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"agent_id": agent_id,
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"changes": changes[:100],
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"service_error": error_msg,
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"error_type": error_type,
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},
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session_id=session_id,
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)
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if result.get("type") == "clarifying_questions":
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questions = result.get("questions", [])
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return ClarificationNeededResponse(
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message=(
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"I need some more information about the changes. "
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"Please answer the following questions:"
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),
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questions=[
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ClarifyingQuestion(
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question=q.get("question", ""),
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keyword=q.get("keyword", ""),
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example=q.get("example"),
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)
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for q in questions
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],
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session_id=session_id,
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)
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updated_agent = result
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agent_name = updated_agent.get("name", "Updated Agent")
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agent_description = updated_agent.get("description", "")
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node_count = len(updated_agent.get("nodes", []))
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link_count = len(updated_agent.get("links", []))
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if not save:
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return AgentPreviewResponse(
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message=(
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f"I've updated the agent. "
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f"The agent now has {node_count} blocks. "
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f"Review it and call edit_agent with save=true to save the changes."
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),
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agent_json=updated_agent,
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agent_name=agent_name,
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description=agent_description,
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node_count=node_count,
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link_count=link_count,
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session_id=session_id,
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)
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if not user_id:
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return ErrorResponse(
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message="You must be logged in to save agents.",
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error="auth_required",
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session_id=session_id,
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)
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try:
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created_graph, library_agent = await save_agent_to_library(
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updated_agent, user_id, is_update=True
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)
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return AgentSavedResponse(
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message=f"Updated agent '{created_graph.name}' has been saved to your library!",
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agent_id=created_graph.id,
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agent_name=created_graph.name,
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library_agent_id=library_agent.id,
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library_agent_link=f"/library/agents/{library_agent.id}",
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agent_page_link=f"/build?flowID={created_graph.id}",
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session_id=session_id,
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)
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except Exception as e:
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return ErrorResponse(
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message=f"Failed to save the updated agent: {str(e)}",
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error="save_failed",
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details={"exception": str(e)},
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session_id=session_id,
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)
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