Use crewAI and add a custom tool to store notes in Obsidian

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AI Summary

Tutorial Summary: Creating a Custom Tool for Crew AI in Obsidian

• Objective: Create a custom tool to integrate search results into Obsidian using Crew AI, Chat GPT, and local LLMS.

• Crew AI Overview:

  • Multi-agent framework for complex problem-solving.
  • More control by assigning tasks to agents.
  • Core concepts include agent blueprints, well-defined tasks, and collaboration.

• Custom Tools in Crew AI:

  • Tools are functions used by agents.
  • Longchain tools can be pre-built or custom.
  • Custom tools are defined using a tool decorator.
  • Important components: name, description, and argument schema.
  • Single input tools are preferable for compatibility with agents.

• Development Steps:

  1. Create a directory and initialize a Python package.
  2. Install necessary packages in a virtual environment.
  3. Define custom tools using the tool decorator and document strings.
  4. Implement a function to write search results to an Obsidian note.
  5. Test the tool by creating a main.py and running it to generate a note in Obsidian.

• Crew AI Extension:

  1. Define agents (researcher, notetaker, editor) with specific roles and tools.
  2. Set up tasks for searching, summarizing, and storing information in Obsidian.
  3. Configure and run Crew AI to execute tasks and generate notes.

• Testing with Different Models:

  • OpenAI’s Chat GPT-4 and GPT-3.5 Turbo were tested.
  • Local LLMS like Mistral and Nexus Raven were also tested using AMA.
  • Results varied in content completeness and markdown formatting.

• Challenges and Insights:

  • Multi-agent frameworks can be costly in token usage.
  • Local LLMS can be used to save on costs but may not be production-ready.
  • Programming logic can be more reliable and cost-effective than LLMS for certain tasks.
  • LLMS excel in areas like semantic search and summarization.

• Conclusion:

  • Custom tools can extend Crew AI’s capabilities.
  • No-code developers may find LLMS not yet reliable for production.
  • Programmers can leverage their skills for more efficient and cost-effective solutions.