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Build API endpoints to interact with a pre-trained model

Model will be deployed locally on a server.

Performance Requirement:
The model needs to respond within a reasonable amount of time. Multiple methods should be tested and benchmarked:

  • Local Model (benchmark different models)
  • Cloud (hugginface inference api)

Need to include moderation

We should moderate the responses from the model to filter out any inappropriate language. We can check if prompt-engineering is enough for this, otherwise we could still see if it makes sense to implement an OpenAI endpoint for moderation

Build API endpoints for chat

This is similar to the functionality from ExecGPT.
Need to decide on the tech used:

  • Server (nodejs or fastapi)
  • Database (SQL vs NoSQL)

Build script to deploy the database

Deploy on MongoDB Docker Image.
Build scripts (possibly a combo of python, yaml, sql and shell scripts) to build and deploy a basic Mongo Database for this project.
Some tables to include:

  • chats
  • messages
  • models

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