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TO DO

  • basic functioning flask application to load model, get text and convert to SQL
  • Search database based on schema and tables
  • Added manual verification process before executing the SQL query
  • change GPT to llama for sql generation
  • create a select all and unselect all functionality based on schema and tables
  • added few validations and preloader
  • change the db creds to come from UI instead of .env
  • fine-tune code-llama-instruct model with custom SQL datasets
    • prepared dataset "shiroyasha13/llama_text_to_sql_dataset" (will increase data size)
    • prepared the fine-tuning code and tested the functionality in colab
    • fine-tuning "TheBloke/CodeLlama-7B-Instruct-GPTQ" (6-bit quuantized) model with SageMaker
    • test the updated model and based on results upload to huggingface and use the model
  • Replace the standard code-llama-instruct-7B with fine-tuned model
  • store the response history for current session ( testing feasibility )
  • Adding documentation to code and this repo