Open Manus with PocketFlow Integration

This repository extends the Open Manus project with PocketFlow(https://github.com/The-Pocket-World/Pocket-Flow-Framework) integration for orchestrating complex agent workflows.

Features

• PocketFlow Integration: Lightweight workflow orchestration with Open Manus agents
• Bidirectional Adapters: Use Open Manus tools/agents as PocketFlow nodes and vice versa
• Workflow Orchestration: Multi-agent workflows with structured control flow
• Hybrid Planning: Combine planning and execution agents flexibly

Installing PocketFlow Framework

pip install pocketflow_framework

Getting Started

git clone https://github.com/The-Pocket-World/PocketManus.git
cd PocketManus

2. Install dependencies and PocketFlow:

pip install -r requirements.txt
pip install pocketflow_framework

3. Set up your configuration file:

cp config/config.example.toml config/config.toml

Configuration Setup

Edit config/config.toml with your API keys and settings:

# Global LLM configuration
[llm]
model = "gpt-4o"                     # The LLM model to use
base_url = "https://api.openai.com/v1" # API endpoint URL
api_key = "YOUR_API_KEY"             # Your API key
max_tokens = 4096                    # Maximum number of tokens in the response
temperature = 0.0                    # Controls randomness

# Optional configuration for specific LLM models
[llm.vision]
model = "gpt-4o"                     # The vision model to use
base_url = "https://api.openai.com/v1" # API endpoint URL for vision model
api_key = "YOUR_API_KEY"             # Your API key for vision model

# Add PocketFlow specific configuration
[pocketflow]
log_level = "INFO"

Running Example Workflows

# Multi-agent workflow
python run_fixed_pocketflow.py --workflow multi_agent --task "Create a Python script that analyzes stock data"

# Planning workflow with parallel execution
python run_fixed_pocketflow.py --workflow planning_parallel --task "Research and summarize the latest AI trends"

# RAG workflow
python run_fixed_pocketflow.py --workflow rag --query "How does transformer architecture work?" --documents documents.json

See example applications in the examples/ directory.

Creating Custom Workflows

from app.pocketflow.fixed_orchestrator import WorkflowOrchestrator
from app.agent.planning import PlanningAgent
from app.agent.react import ReactAgent

# Create and register agents
orchestrator = WorkflowOrchestrator()
orchestrator.register_agent(PlanningAgent(), "planner")
orchestrator.register_agent(ReactAgent(), "executor")

# Create and run workflow
workflow = orchestrator.create_agent_workflow(
    agents=["planner", "executor"],
    flow_name="CustomWorkflow"
)

result = orchestrator.run_workflow(
    workflow_name="CustomWorkflow",
    inputs={"task": "Your task here"}
)

Architecture

• Adapters: Bridge between PocketFlow and Open Manus components
• Orchestrator: Manages workflows and provides a unified interface
• Flow Factory: Creates PocketFlow-based flows with agent, planning, and hybrid patterns

PocketFlow Framework

PocketFlow is a lightweight workflow orchestration system for AI agent workflows with:

• Node-based architecture for workflows
• Support for sequential, parallel, and conditional flows
• Easy integration with existing systems

The framework uses nodes (computation units), edges (connections), and flows (complete workflows) to enable flexible agent orchestration patterns.