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ChatDB Magic: Augmenting LLMs with Databases as Their Symbolic Memory [Support SQLite database]

forked from https://github.com/huchenxucs/ChatDB

Changes:

  • Support SQLiteDB.
  • Default DB changed to SQLite, you can set back to mysql in .env file.

    DB_TYPE=sqlite or DB_TYPE=mysql

Run and Use:

  • Follow README instructions.
  • Quick demo:
    copy .env.template .env     # Set your OpenAI key and host, if use mysql, need to set host, port, name, password.
    pip install -r requirements.txt
    python chatdb.py

    START!
    USER INPUT: How many apples does the customer named 'Chenzhuang Du' bought on 2010-03-27
    
    Step1: Retrieve the quantity of apples bought by the customer
    SELECT si.quantity_sold
    FROM customers c
    JOIN sales s ON c.customer_id = s.customer_id
    JOIN sale_items si ON s.sale_id = si.sale_id
    JOIN fruits f ON si.fruit_id = f.fruit_id
    WHERE c.first_name = 'Chenzhuang' AND c.last_name = 'Du' AND f.fruit_name = 'apple' AND s.sale_date = '2010-03-27';
    
    Execute: 
    
    
    Database response:
    no results found.
    
    Finish!
  • Use your own data:
  I fixed some bugs, it's better to follow these steps:
  1. Put your sqlite db file to replace try1024.db. 
  2. Open chatdb.py, set init_db = True to False, to disable create and insert sample data.
  3. Open table_schema.py and add your table schema and then add these variables to `tables` list at the bottom.
  4. Run chatdb.py
  5. Input your query, like the demo above.
  Also, you can change sql_examples.py to use your own examples.

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Make ChatDB support SQLite

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