CrewAI + Claude 3 Haiku
AI Summary
Summary: Custom CrewAI Agent with Sub-Agents Using Claude Models
- Previous Video Recap:
- Discussed creating a custom CrewAI agent with sub-agents.
- Used GPT-4 Turbo, which is effective but costly.
- Current Focus:
- Demonstrating the use of cheaper Claude models (Haiku).
- Addressing potential issues and considerations.
- Setup Requirements:
- Installation of Anthropic and LangChain.
- Switch from OpenAI’s key to Anthropic’s key.
- Code Adjustments:
- Minimal changes to adapt code for Anthropic and Haiku models.
- Improved input handling and reintroduced context usage.
- Maintained the same tools and agents, but prompts may need revising for better results with Anthropic.
- Sequential Processing:
- Added context to tasks for improved sequential processing.
- Noted cheaper token costs with Claude models.
- Hierarchical Processing Challenges:
- Manager agent seems tailored for OpenAI, causing issues with Claude models.
- Formatting and prompt mismatches lead to errors.
- Swapping between Claude Sonnet and Opus models showed mixed results.
- Manager LLM’s prompt is not exposed, limiting control and leading to suboptimal results.
- Final Output:
- Achieved an article with some hallucination and non-succinct information.
- Key highlights were not always placed correctly.
- Frustrations and Limitations:
- Desire for full control over prompts and transparency in input/output.
- CrewAI operates at a higher level, which can be restrictive.
- Anticipation of future support for Claude models in CrewAI.
- Potential Solutions:
- Using OpenAI as the manager LLM while sub-agents use Claude models.
- Future Plans:
- Exploring other methods and frameworks.
- Creating a series on Autogen, LangGraph, and building tools from scratch with Python.
- Engagement:
- Invites comments, questions, and feedback.
- Encourages likes and subscriptions for the video channel.