OpenManus/app/flow/planning.py

395 lines
16 KiB
Python

import json
import time
from typing import Dict, List, Optional, Union
from pydantic import Field
from app.agent.base import BaseAgent
from app.flow.base import BaseFlow, PlanStepStatus
from app.llm import LLM
from app.logger import logger
from app.schema import AgentState, Message, ToolChoice
from app.tool import PlanningTool
class PlanningFlow(BaseFlow):
"""A flow that manages planning and execution of tasks using agents."""
llm: LLM = Field(default_factory=lambda: LLM())
planning_tool: PlanningTool = Field(default_factory=PlanningTool)
executor_keys: List[str] = Field(default_factory=list)
active_plan_id: str = Field(default_factory=lambda: f"plan_{int(time.time())}")
current_step_index: Optional[int] = None
def __init__(
self, agents: Union[BaseAgent, List[BaseAgent], Dict[str, BaseAgent]], **data
):
# Set executor keys before super().__init__
if "executors" in data:
data["executor_keys"] = data.pop("executors")
# Set plan ID if provided
if "plan_id" in data:
data["active_plan_id"] = data.pop("plan_id")
# Initialize the planning tool if not provided
if "planning_tool" not in data:
planning_tool = PlanningTool()
data["planning_tool"] = planning_tool
# Call parent's init with the processed data
super().__init__(agents, **data)
# Set executor_keys to all agent keys if not specified
if not self.executor_keys:
self.executor_keys = list(self.agents.keys())
def get_executor(self, step_type: Optional[str] = None) -> BaseAgent:
"""
Get an appropriate executor agent for the current step.
Can be extended to select agents based on step type/requirements.
"""
# If step type is provided and matches an agent key, use that agent
if step_type and step_type in self.agents:
return self.agents[step_type]
# Otherwise use the first available executor or fall back to primary agent
for key in self.executor_keys:
if key in self.agents:
return self.agents[key]
# Fallback to primary agent
return self.primary_agent
async def execute(self, input_text: str) -> str:
"""Execute the planning flow with agents."""
try:
if not self.primary_agent:
raise ValueError("No primary agent available")
# Create initial plan if input provided
if input_text:
await self._create_initial_plan(input_text)
# Verify plan was created successfully
if self.active_plan_id not in self.planning_tool.plans:
logger.error(
f"Plan creation failed. Plan ID {self.active_plan_id} not found in planning tool."
)
return f"Failed to create plan for: {input_text}"
result = ""
while True:
# Get current step to execute
self.current_step_index, step_info = await self._get_current_step_info()
# Exit if no more steps or plan completed
if self.current_step_index is None:
result += await self._finalize_plan()
break
# Execute current step with appropriate agent
step_type = step_info.get("type") if step_info else None
executor = self.get_executor(step_type)
step_result = await self._execute_step(executor, step_info)
result += step_result + "\n"
# Check if agent wants to terminate
if hasattr(executor, "state") and executor.state == AgentState.FINISHED:
break
return result
except Exception as e:
logger.error(f"Error in PlanningFlow: {str(e)}")
return f"Execution failed: {str(e)}"
async def _create_initial_plan(self, request: str) -> None:
"""Create an initial plan based on the request using the flow's LLM and PlanningTool."""
logger.info(f"Creating initial plan with ID: {self.active_plan_id}")
# Create a system message for plan creation
system_message = Message.system_message(
"You are a planning assistant. Create a concise, actionable plan with clear steps. "
"Focus on key milestones rather than detailed sub-steps. "
"Optimize for clarity and efficiency."
)
# Create a user message with the request
user_message = Message.user_message(
f"Create a reasonable plan with clear steps to accomplish the task: {request}"
)
# Call LLM with PlanningTool
response = await self.llm.ask_tool(
messages=[user_message],
system_msgs=[system_message],
tools=[self.planning_tool.to_param()],
tool_choice=ToolChoice.AUTO,
)
# Process tool calls if present
if response.tool_calls:
for tool_call in response.tool_calls:
if tool_call.function.name == "planning":
# Parse the arguments
args = tool_call.function.arguments
if isinstance(args, str):
try:
args = json.loads(args)
except json.JSONDecodeError:
logger.error(f"Failed to parse tool arguments: {args}")
continue
# Ensure plan_id is set correctly and execute the tool
args["plan_id"] = self.active_plan_id
# Execute the tool via ToolCollection instead of directly
result = await self.planning_tool.execute(**args)
logger.info(f"Plan creation result: {str(result)}")
return
# If execution reached here, create a default plan
logger.warning("Creating default plan")
# Create default plan using the ToolCollection
await self.planning_tool.execute(
**{
"command": "create",
"plan_id": self.active_plan_id,
"title": f"Plan for: {request[:50]}{'...' if len(request) > 50 else ''}",
"steps": ["Analyze request", "Execute task", "Verify results"],
}
)
async def _get_current_step_info(self) -> tuple[Optional[int], Optional[dict]]:
"""
Parse the current plan to identify the first non-completed step's index and info.
Returns (None, None) if no active step is found.
"""
if (
not self.active_plan_id
or self.active_plan_id not in self.planning_tool.plans
):
logger.error(f"Plan with ID {self.active_plan_id} not found")
return None, None
try:
# Direct access to plan data from planning tool storage
plan_data = self.planning_tool.plans[self.active_plan_id]
steps = plan_data.get("steps", [])
step_statuses = plan_data.get("step_statuses", [])
# Find first non-completed step
for i, step in enumerate(steps):
if i >= len(step_statuses):
status = PlanStepStatus.NOT_STARTED.value
else:
status = step_statuses[i]
if status in PlanStepStatus.get_active_statuses():
# Extract step type/category if available
step_info = {"text": step}
# Try to extract step type from the text (e.g., [SEARCH] or [CODE])
import re
type_match = re.search(r"\[([A-Z_]+)\]", step)
if type_match:
step_info["type"] = type_match.group(1).lower()
# Mark current step as in_progress
try:
await self.planning_tool.execute(
command="mark_step",
plan_id=self.active_plan_id,
step_index=i,
step_status=PlanStepStatus.IN_PROGRESS.value,
)
except Exception as e:
logger.warning(f"Error marking step as in_progress: {e}")
# Update step status directly if needed
if i < len(step_statuses):
step_statuses[i] = PlanStepStatus.IN_PROGRESS.value
else:
while len(step_statuses) < i:
step_statuses.append(PlanStepStatus.NOT_STARTED.value)
step_statuses.append(PlanStepStatus.IN_PROGRESS.value)
plan_data["step_statuses"] = step_statuses
return i, step_info
return None, None # No active step found
except Exception as e:
logger.warning(f"Error finding current step index: {e}")
return None, None
async def _execute_step(self, executor: BaseAgent, step_info: dict) -> str:
"""Execute the current step with the specified agent using agent.run()."""
# Prepare context for the agent with current plan status
plan_status = await self._get_plan_text()
step_text = step_info.get("text", f"Step {self.current_step_index}")
# Create a prompt for the agent to execute the current step
step_prompt = f"""
CURRENT PLAN STATUS:
{plan_status}
YOUR CURRENT TASK:
You are now working on step {self.current_step_index}: "{step_text}"
Please execute this step using the appropriate tools. When you're done, provide a summary of what you accomplished.
"""
# Use agent.run() to execute the step
try:
step_result = await executor.run(step_prompt)
# Mark the step as completed after successful execution
await self._mark_step_completed()
return step_result
except Exception as e:
logger.error(f"Error executing step {self.current_step_index}: {e}")
return f"Error executing step {self.current_step_index}: {str(e)}"
async def _mark_step_completed(self) -> None:
"""Mark the current step as completed."""
if self.current_step_index is None:
return
try:
# Mark the step as completed
await self.planning_tool.execute(
command="mark_step",
plan_id=self.active_plan_id,
step_index=self.current_step_index,
step_status=PlanStepStatus.COMPLETED.value,
)
logger.info(
f"Marked step {self.current_step_index} as completed in plan {self.active_plan_id}"
)
except Exception as e:
logger.warning(f"Failed to update plan status: {e}")
# Update step status directly in planning tool storage
if self.active_plan_id in self.planning_tool.plans:
plan_data = self.planning_tool.plans[self.active_plan_id]
step_statuses = plan_data.get("step_statuses", [])
# Ensure the step_statuses list is long enough
while len(step_statuses) <= self.current_step_index:
step_statuses.append(PlanStepStatus.NOT_STARTED.value)
# Update the status
step_statuses[self.current_step_index] = PlanStepStatus.COMPLETED.value
plan_data["step_statuses"] = step_statuses
async def _get_plan_text(self) -> str:
"""Get the current plan as formatted text."""
try:
result = await self.planning_tool.execute(
command="get", plan_id=self.active_plan_id
)
return result.output if hasattr(result, "output") else str(result)
except Exception as e:
logger.error(f"Error getting plan: {e}")
return self._generate_plan_text_from_storage()
def _generate_plan_text_from_storage(self) -> str:
"""Generate plan text directly from storage if the planning tool fails."""
try:
if self.active_plan_id not in self.planning_tool.plans:
return f"Error: Plan with ID {self.active_plan_id} not found"
plan_data = self.planning_tool.plans[self.active_plan_id]
title = plan_data.get("title", "Untitled Plan")
steps = plan_data.get("steps", [])
step_statuses = plan_data.get("step_statuses", [])
step_notes = plan_data.get("step_notes", [])
# Ensure step_statuses and step_notes match the number of steps
while len(step_statuses) < len(steps):
step_statuses.append(PlanStepStatus.NOT_STARTED.value)
while len(step_notes) < len(steps):
step_notes.append("")
# Count steps by status
status_counts = {status: 0 for status in PlanStepStatus.get_all_statuses()}
for status in step_statuses:
if status in status_counts:
status_counts[status] += 1
completed = status_counts[PlanStepStatus.COMPLETED.value]
total = len(steps)
progress = (completed / total) * 100 if total > 0 else 0
plan_text = f"Plan: {title} (ID: {self.active_plan_id})\n"
plan_text += "=" * len(plan_text) + "\n\n"
plan_text += (
f"Progress: {completed}/{total} steps completed ({progress:.1f}%)\n"
)
plan_text += f"Status: {status_counts[PlanStepStatus.COMPLETED.value]} completed, {status_counts[PlanStepStatus.IN_PROGRESS.value]} in progress, "
plan_text += f"{status_counts[PlanStepStatus.BLOCKED.value]} blocked, {status_counts[PlanStepStatus.NOT_STARTED.value]} not started\n\n"
plan_text += "Steps:\n"
status_marks = PlanStepStatus.get_status_marks()
for i, (step, status, notes) in enumerate(
zip(steps, step_statuses, step_notes)
):
# Use status marks to indicate step status
status_mark = status_marks.get(
status, status_marks[PlanStepStatus.NOT_STARTED.value]
)
plan_text += f"{i}. {status_mark} {step}\n"
if notes:
plan_text += f" Notes: {notes}\n"
return plan_text
except Exception as e:
logger.error(f"Error generating plan text from storage: {e}")
return f"Error: Unable to retrieve plan with ID {self.active_plan_id}"
async def _finalize_plan(self) -> str:
"""Finalize the plan and provide a summary using the flow's LLM directly."""
plan_text = await self._get_plan_text()
# Create a summary using the flow's LLM directly
try:
system_message = Message.system_message(
"You are a planning assistant. Your task is to summarize the completed plan."
)
user_message = Message.user_message(
f"The plan has been completed. Here is the final plan status:\n\n{plan_text}\n\nPlease provide a summary of what was accomplished and any final thoughts."
)
response = await self.llm.ask(
messages=[user_message], system_msgs=[system_message]
)
return f"Plan completed:\n\n{response}"
except Exception as e:
logger.error(f"Error finalizing plan with LLM: {e}")
# Fallback to using an agent for the summary
try:
agent = self.primary_agent
summary_prompt = f"""
The plan has been completed. Here is the final plan status:
{plan_text}
Please provide a summary of what was accomplished and any final thoughts.
"""
summary = await agent.run(summary_prompt)
return f"Plan completed:\n\n{summary}"
except Exception as e2:
logger.error(f"Error finalizing plan with agent: {e2}")
return "Plan completed. Error generating summary."