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kaarthik108

snowChat

Chat snowflake - Text to SQL

ApplicationsSpecialistsPython
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创建于 2023-04-10 · 更新于 2026-10-05 · 今日第 17213 名
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kaarthik108kaarthik-tracksuit

kaarthik108/snowChat 排名第 17,213，有 550 个星标。

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kaarthik108/snowChat 排名第 17,213，此处有 8 个同类条目；dappros/ethora 排名第 17,210。

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关键参数与规格
关键参数与规格
参数值
语言Python
类别Applications
子类别Specialists
关键词Data analysis, Text-to-SQL
星标数550
分叉数274
贡献者2
创建日期2023-04-10
更新日期2026-10-05
1 天星标数0
7 天星标数0
排名17,213
上次排名16,995
排名变化-218
7 天星标排名15,973
上次 7 天星标排名15,981
7 天星标排名变化8
总星标排名17,968
上次总星标排名17,937
总星标排名变化-31
国家New Zealand
README 摘录

snowChat 💬❄️ **snowChat** is an intuitive and user-friendly application that allows users to interact with their Snowflake data using natural language queries. Type in your questions or requests, and SnowChat will generate the appropriate SQL query and return the data you need. No more complex SQL queries or digging through tables - SnowChat makes it easy to access your data! By bringing data one step closer, SnowChat empowers users to make data-driven decisions faster and more efficiently, reducing the barriers

between users and the insights they seek. 1 405B 🌟 Features **Conversational AI**: Use ChatGPT and other models to translate natural language into precise SQL queries. **Conversational Memory**: Retains context for interactive, dynamic responses. **Snowflake Integration**: Offers seamless, real-time data insights straight from your Snowflake database. **Self-healing SQL**: Proactively suggests solutions for SQL errors, streamlining data access. **Interactive User Interface**: Transforms data querying into an engaging conversation, complete with a chat reset option. **Agent-based Architecture**: Utilizes an agent

to manage interactions and tool usage. Install the required packages: cd snowchat pip install -r requirements. Set up your , , , , , , , , , , , , , in project directory . Cloudflare is used here for caching Snowflake responses in KV. Make you're schemas and store them in docs folder that matches you're database. Create supabase extention, table and function from the supabase/scripts. Run to get convert to embeddings and store as an index file. Run the Streamlit app to start chatting: streamlit run main. py Star History

🤝 Contributing Feel free to contribute to this project by submitting a pull request or opening an issue. Your feedback and suggestions are greatly appreciated! 📄 License This project is licensed under the MIT License - see the LICENSE file for details.

常见问题

记录了多少星标和分叉？

kaarthik108/snowChat 有 550 个星标和 274 个分叉。

仓库排名是多少？

kaarthik108/snowChat 排名第 17,213。

记录的语言和类别是什么？

kaarthik108/snowChat 有 550 个星标，语言为 Python，类别为 Applications。

哪个仓库排名最接近？

kaarthik108/snowChat 与 dappros/ethora 比较，后者排名第 17,210，有 550 个星标。

README

snowChat 💬❄️

snowChat is an intuitive and user-friendly application that allows users to interact with their Snowflake data using natural language queries. Type in your questions or requests, and SnowChat will generate the appropriate SQL query and return the data you need. No more complex SQL queries or digging through tables - SnowChat makes it easy to access your data! By bringing data one step closer, SnowChat empowers users to make data-driven decisions faster and more efficiently, reducing the barriers between users and the insights they seek.

Supported LLM's

  • GPT-4o
  • Gemini Flash 1.5 8B
  • Claude 3 Haiku
  • Llama 3.2 3B
  • Llama 3.1 405B

https://github.com/kaarthik108/snowChat/assets/53030784/24105e23-69d3-4676-b6d6-d8157dd1580a

🌟 Features

  • Conversational AI: Use ChatGPT and other models to translate natural language into precise SQL queries.
  • Conversational Memory: Retains context for interactive, dynamic responses.
  • Snowflake Integration: Offers seamless, real-time data insights straight from your Snowflake database.
  • Self-healing SQL: Proactively suggests solutions for SQL errors, streamlining data access.
  • Interactive User Interface: Transforms data querying into an engaging conversation, complete with a chat reset option.
  • Agent-based Architecture: Utilizes an agent to manage interactions and tool usage.

🛠️ Installation

  1. Clone this repository: git clone https://github.com/yourusername/snowchat.git

  2. Install the required packages: cd snowchat pip install -r requirements.txt

  3. Set up your OPENAI_API_KEY, ACCOUNT, USER_NAME, PASSWORD, ROLE, DATABASE, SCHEMA, WAREHOUSE, SUPABASE_URL , SUPABASE_SERVICE_KEY, SUPABASE_STORAGE_URL,CLOUDFLARE_ACCOUNT_ID, CLOUDFLARE_NAMESPACE_ID, CLOUDFLARE_API_TOKEN in project directory secrets.toml. Cloudflare is used here for caching Snowflake responses in KV.

  4. Make you're schemas and store them in docs folder that matches you're database.

  5. Create supabase extention, table and function from the supabase/scripts.sql.

  6. Run python ingest.py to get convert to embeddings and store as an index file.

  7. Run the Streamlit app to start chatting: streamlit run main.py

Star History

[]

🤝 Contributing

Feel free to contribute to this project by submitting a pull request or opening an issue. Your feedback and suggestions are greatly appreciated!

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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