autogen - 💡(How to fix) Fix 📝 Integration Proposal: CAJAL — Local Scientific Paper Agent [1 participants]

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microsoft/autogen#7653Fetched 2026-05-05 05:45:14
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Code Example

from autogen import AssistantAgent, UserProxyAgent

writer = AssistantAgent(name="ScientificWriter", llm_config={"model": "cajal-4b"})
reviewer = AssistantAgent(name="PeerReviewer", llm_config={"model": "cajal-4b"})

# Multi-agent paper writing
user_proxy.initiate_chat(
    recipient=writer,
    message="Write a paper on neural network pruning",
    max_turns=3
)
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📝 Integration Proposal: CAJAL — Local Scientific Paper Agent for AutoGen

What is CAJAL?

CAJAL is not a general-purpose chat model. It is a specialized scientific paper generation tool — local, 2GB, producing LaTeX-formatted academic output.

Part of P2PCLAW

Agent in P2PCLAW — 14-agent decentralized research network.

Why AutoGen?

AutoGen's multi-agent conversation framework + CAJAL = automated research team:

  • ScientificWriter agent (CAJAL)
  • PeerReviewer agent (critiques methodology)
  • CitationManager agent (formats references)
  • Multi-turn paper improvement loop

Proposed Integration

from autogen import AssistantAgent, UserProxyAgent

writer = AssistantAgent(name="ScientificWriter", llm_config={"model": "cajal-4b"})
reviewer = AssistantAgent(name="PeerReviewer", llm_config={"model": "cajal-4b"})

# Multi-agent paper writing
user_proxy.initiate_chat(
    recipient=writer,
    message="Write a paper on neural network pruning",
    max_turns=3
)

Links

— Francisco (@Agnuxo1), P2PCLAW

extent analysis

TL;DR

To integrate CAJAL with AutoGen, ensure the ScientificWriter and PeerReviewer agents are properly configured with the CAJAL-4B model.

Guidance

  • Verify that the llm_config dictionary is correctly set up for both ScientificWriter and PeerReviewer agents, with the model specified as "cajal-4b".
  • Check the Hugging Face model repository (https://huggingface.co/Agnuxo/CAJAL-4B-P2PCLAW) for any specific configuration requirements or updates.
  • Review the CAJAL GitHub repository (https://github.com/Agnuxo1/CAJAL) for documentation on integrating CAJAL with AutoGen.
  • Test the multi-agent paper writing loop with a small-scale example to ensure the integration is working as expected.

Example

# Example configuration for ScientificWriter agent
writer = AssistantAgent(
    name="ScientificWriter", 
    llm_config={"model": "cajal-4b", "max_length": 1024}
)

Notes

The provided code snippet appears to be a proposal for integration, and it is unclear if this is a working implementation or a suggestion. Further testing and verification are necessary to ensure the integration works as expected.

Recommendation

Apply workaround: Verify the configuration and test the integration with a small-scale example to ensure the CAJAL-4B model is working correctly with AutoGen.

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