66 lines
2.4 KiB
Markdown
66 lines
2.4 KiB
Markdown
# FlowPilot Agent Orchestration PoC
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This proof-of-concept demonstrates the core agent orchestration ideas from the FlowPilot PRD:
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## Core Concepts Demonstrated
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1. **HR Manager Agent**: Decomposes high-level tasks into atomic tasks and creates executor agents
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2. **Experience Manager Agent**: Logs executions, provides context, and maintains a knowledge base
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3. **Atomic Task Decomposition**: Breaking down complex tasks into single-agent-completable units
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4. **Agent Lifecycle Management**: Dynamic creation of executor agents for specific task types
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## How to Run
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```bash
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python3 agent_poc.py
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```
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## Output
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The PoC processes three sample high-level tasks from the project management handbook:
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- Creating a project charter
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- Identifying software development risks
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- Creating a project schedule
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For each task, it shows:
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- How the HR Manager decomposes the task into atomic tasks
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- How executor agents are created for each atomic task type
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- How the Experience Manager logs executions and provides context
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- The final results and execution logs
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## Next Steps for Development
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1. **Replace simulation with actual LLM calls** - Integrate with OpenAI/Anthropic/etc APIs
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2. **Add real task execution** - Instead of mock results, have agents actually perform tasks
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3. **Implement persistence** - Store agent configurations, execution logs, and knowledge base in database
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4. **Add feedback loops** - HR Manager improves based on execution scores
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5. **Integrate with Feishu** - Build the actual frontend and Feishu bot interfaces
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## Files
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- `agent_poc.py`: Main PoC implementation
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- `poc_results.json`: Detailed execution results from the last run
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- `.gitignore`: Git ignore file
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## Design Notes
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This PoC focuses on demonstrating the orchestration logic rather than actual AI execution.
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In a real implementation:
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- The `_simulate_execution` method would call actual LLM APIs
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- Agents would have specific prompt templates for their task types
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- The Experience Manager would use vector embeddings for context retrieval
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- Task decomposition would be more sophisticated (possibly using LLMs themselves)
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## Relation to PRD
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This PoC validates the core architectural concepts from PRD v0.2:
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- Dual agent management (HR Manager + Experience Manager)
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- Atomic task decomposition
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- Agent lifecycle management
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- Context sharing and knowledge base
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It does not yet cover:
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- Feishu integration
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- Full PMBOK process coverage
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- Production-level error handling and scaling
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- Actual LLM provider integration |