A developer built a private AI assistant to query their project management and Git history data using only local LLMs. The system leverages a Text-to-SQL approach, translating natural language questions into SQL queries executed against a local SQLite database. This method ensures all data remains on the user's machine, prioritizing privacy and avoiding cloud-based APIs. The assistant uses Ollama to run models like Qwen2.5-coder locally, with a system prompt that includes the database schema, sample values, and few-shot examples to guide the LLM in generating accurate SQL queries and summarizing results. AI
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IMPACT Enables developers to build custom, private AI tools for managing structured data, reducing reliance on cloud services.
RANK_REASON The cluster describes a personal project building a tool using existing LLMs and technologies, rather than a new model release or significant industry event.