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"description": "# Upwork Job Post: LiveKit + LangGraph Conversation Flow Expert Needed\n\n## Job Title\n**Experienced Python Developer for LiveKit + LangGraph Conversation Flow Integration**\n\n## Project Overview\nWe're seeking an experienced Python developer to enhance our AI voice agent system that combines LiveKit Agents with LangGraph for dynamic conversation flows. We have existing code that needs refinement and optimization to work seamlessly with LiveKit's voice pipeline.\n\n## What We Have\n- Complete conversation flow schema (Pydantic models)\n- Basic ConversationFlowGraph implementation using LangGraph StateGraph\n- LiveKit Agents integration setup\n- Working voice pipeline foundation\n\n## What We Need\n- Optimize the conversation flow graph to work perfectly with LiveKit's voice synthesis\n- Implement proper node transitions and edge conditions\n- Ensure the LLM responses integrate correctly with LiveKit's streaming architecture\n- Debug and resolve any voice output issues\n- Add robust error handling and logging\n\n## Technical Requirements\n\n### Must Have Experience With:\n- **LiveKit Agents** framework\n- **LangGraph** for building state machines\n- **LangChain** integration with LiveKit\n- **Pydantic** for data validation\n- **Voice AI pipelines** and real-time audio processing\n\n### Preferred Experience:\n- Conversational AI and flow management systems\n- OpenAI API integration\n- Async Python programming\n- Docker and dev containers\n- Git version control\n\n## Project Scope\n\n### Phase 1 - Core Fixes (Immediate)\n- Review and optimize existing `conversation_flow_graph.py`\n- Fix integration between LangGraph and LiveKit voice pipeline\n- Ensure agent speaks responses correctly\n- Implement proper node transition logic\n\n### Phase 2 - Enhancement (Following)\n- Add advanced edge conditions and logic\n- Implement context management between nodes\n- Add support for multiple LLM providers\n- Optimize performance and error handling\n\n## Technical Stack\n```\n- LiveKit Agents\n- LangGraph\n- LangChain\n- Pydantic\n- OpenAI API\n- Docker (dev container environment)\n```\n\n## Project Files Structure\n```\nconversation_flow_graph.py # Main implementation file\nschemes.py # Pydantic schemas (DO NOT MODIFY)\nexternal_services/ # Service integrations\nlogger.py # Logging setup\nrequirements.txt # Dependencies\n```\n\n## Deliverables\n1. **Working conversation flow system** that processes nodes and speaks responses\n2. **Optimized code** with proper LiveKit integration\n3. **Documentation** explaining the solution and any architectural decisions\n4. **Testing examples** to validate the implementation\n\n## Timeline\n- **Quick assessment**: 1-2 days to review code and provide initial feedback\n- **Core implementation**: 5-7 days for main fixes\n- **Testing and refinement**: 2-3 days\n\n## Budget Range\n**$500 - $1,500** depending on experience and scope completion\n\n## How to Apply\n\n### Include in Your Proposal:\n1. **Experience summary** with LiveKit and LangGraph projects\n2. **Approach overview** - how you would tackle this project\n3. **Timeline estimate** for Phase 1 completion\n4. **Questions or clarifications** about the requirements\n5. **Portfolio examples** of similar voice AI or conversation flow work\n\n### Sample Questions to Address:\n- Have you worked with LiveKit Agents before?\n- Experience with LangGraph state machines?\n- How would you approach debugging voice pipeline integration issues?\n- Any experience with conversational AI flow systems?\n\n## Additional Information\n- This is a **dev container environment** on Debian Linux\n- All tools and dependencies are pre-configured\n- You'll have full access to the codebase via Git\n- We prefer **clean, well-documented code**\n- **Communication is key** - we value developers who ask good questions\n\n## Next Steps\nAfter selection, we'll provide:\n- Complete codebase access\n- Detailed technical documentation\n- Live session to walk through current implementation\n- Clear success criteria and testing procedures\n\n---\n\n**Looking for someone who can start immediately and deliver high-quality results. If you have the right experience and can commit to the timeline, we'd love to hear from you!**",
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