Integrate LLM4: Llama

[Ghemechis]

Item type: data pipeline

Description: As part of our multiple LLM strategy, this task involves implementing the third best LLM --Llama that will be implemented as additional LLM to the previously LLMs. This enhance our application's capabilities by leveraging the strengths of multiple LLMs, ensuring better performance, flexibility, and robustness in handling various tasks involved in the langchain framework.

The third LLM should be the open source Llama which is hosted fro free via the groq service.
https://groq.com/

The groq service mentions in their documentation:

Developer access can be obtained completely self-serve through Playground on GroqCloud. There you can obtain your API key and access our documentation as well as our terms and conditions on Playground. Join our Discord community here.
If you are currently using OpenAI API, you just need three things to convert over to Groq:

Groq API key
Endpoint
Model

The official documentation for running LLama in external hosts
https://llama.meta.com/docs/llama-everywhere/running-meta-llama-in-the-cloud/

User Story

• As a developer,
• I want to select and implement a new LLM into the Langchain framework to support our multiple LLM strategy,
• so that our application can support the comparison of the responses of multiple LLMs.

Acceptance Criteria

• Llama has been integrated in the app
• Llama can be easily switched with other LLMs in the as part of the multiple LLM strategy
• Perform thorough testing to ensure the new LLM interacts correctly with existing components.

Definition of Done

• The feature has been fully implemented and integrated into the app.
• The feature has been manually tested and works as expected without critical bugs.
• The feature code is documented with clear explanations of its functionality and usage.
• The feature code has been reviewed and approved by at least one team member.
• The feature branches have been merged into the main branch and closed.
• The feature utility, function and usage have been documented in the respective project wiki on github.