PROJECT - Langchain Retrieval Template

Brainstorm:

A comprehensive guide for creating a Question Answering system should include information on the following:

1. Data Model: Different methods of loading documents such as S3, EveryNote, and Website should be discussed, along with the required metadata for each method.

2. Vector Database: The guide should provide details on various vector databases, including Pinecone, Weaviate, Zilliz, Milvus, Qdrant, and Redis,

3. Embeddings: The documentation should cover the various options available for embeddings such as Cohere, OpenAI, and Hugging Face Hosted LLM.

4. Docker Container: The guide should explain the usage of Fast API or Flask for building the container.

5. API Authentication: The documentation should outline the different methods available for API authentication.

6. Cloud Deployment: The guide should provide instructions for deploying the backend API in the cloud.

7. Utility Services: Preprocessing and post-processing scripts should be discussed in the guide.

8. Testing: The guide should cover the testing phase.

9. API Swagger: For each template, the guide should include API Swagger documentation.

10. Memory Management: The documentation should provide information on how to store and retrieve conversations.

11. Personalization: The guide should cover personalization and customization in prompts, prompt templates

12. CI/CD Pipeline: The documentation should cover the CI/CD pipeline. Webhooks: The guide should discuss webhooks for external integration with messaging platforms such as Slack, as well as an Iframe embed approach for website integration.

Authors: Sangeetha Venkatesan, Misbah Syed