LLM Integration

The LLM (Large Language Model) Integration component is responsible for interacting with a chosen Large Language Model to process the user's translated English queries and generate appropriate responses.

Process

1. Input: Receives the translated English text from the Translation component.
2. Contextualization (Optional): Additional context relevant to the conversation or user preferences can be added to the prompt before sending it to the LLM.
3. LLM Inference: The prepared prompt is sent to the LLM. The LLM processes the input and generates a response in English.
4. Output: The LLM's English response is sent back to the Translation component for conversion into Igbo.

Technology Considerations

• LLM Choice: The primary Large Language Model for this project will be Cohere's Command R. This model will be responsible for processing the translated English queries and generating appropriate responses.
• API Client: A suitable API client will be used to communicate with the chosen LLM. This will handle authentication, request formatting, and response parsing.
• Prompt Engineering: Careful consideration will be given to prompt engineering to ensure the LLM understands the user's intent and provides relevant and helpful responses.
• Context Management: Strategies for managing conversational context (e.g., storing previous turns, summarizing conversations) will be explored to enable more natural and coherent interactions with the LLM.