[Feature]: LLM Consensus-Based Response Verification

[rootCircle]

Description

I propose implementing a consensus-based response verification feature in gptEngine.ts, utilizing Langchain's output parser. This feature aims to enhance the accuracy of responses generated by LLMs when automatically filling out google forms.

Proposed Implementation Details:

1. User-Controlled Option: Introduce a configuration setting that allows users to enable or disable the consensus-based response verification.

2. Gathering Responses: Collect responses from multiple LLM providers (e.g., ChatGPT, Gemini, LLaMA 3).

3. Consensus Mechanism:

   • Internal Voting: Implement a voting system where each model's response is evaluated. For instance, if the majority of models agree on a response (e.g., "Earth is round"), this consensus will override minority opinions (e.g., "Earth is flat").
   • Weighted Voting: Assign weights to each model's response based on the model’s reliability and accuracy. More reliable models should have a greater influence on the final decision. (user configurable, but good to have a better defaults)

4. Integration with Langchain:

   • Response Parsing: Utilize Langchain’s output parser to process and analyze responses from different models.
   • Consensus Evaluation: Incorporate logic to evaluate and determine the most appropriate response based on consensus and weighted voting.

By implementing this feature, we can significantly improve the reliability and accuracy of automated responses.

Suggested Solution

Implementation Steps:

• Update gptEngine.ts to include the consensus-based response verification logic.
• Configure Langchain’s output parser to integrate with the consensus mechanism.
• Add user settings for enabling and configuring this feature.
• Test and validate the new feature to ensure it functions as expected.

Alternatives

No response

Additional Context

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