Type: Web Article Original link: https://arxiv.org/abs/2502.00032v1 Publication date: 2025-09-06
Summary #
WHAT - This research article presents a method for integrating Large Language Models (LLMs) with databases using Function Calling, allowing LLMs to execute queries on private or real-time updated data.
WHY - It is relevant for AI business because it demonstrates how LLMs can access and manipulate data more efficiently, improving integration with existing systems and increasing data management capabilities.
WHO - The main authors are Connor Shorten, Charles Pierse, and other researchers. The work was presented on arXiv, a widely used preprint platform in the scientific community.
WHERE - It is positioned within the context of advanced research on LLMs and databases, contributing to the AI ecosystem with a specific focus on the integration of external tools.
WHEN - The document was submitted in January 2025, indicating recent and cutting-edge research work in the field.
BUSINESS IMPACT:
- Opportunities: Implement Function Calling techniques to improve real-time data access, increasing the accuracy and efficiency of queries.
- Risks: Competitors could quickly adopt these techniques, reducing competitive advantage if not acted upon promptly.
- Integration: Possible integration with the existing stack to enhance data management capabilities and interaction with external databases.
TECHNICAL SUMMARY:
- Core technology stack: Uses LLMs and Function Calling techniques to interface with databases. The Gorilla LLM framework was adapted to create synthetic database schemas and queries.
- Scalability and architectural limits: The method demonstrates robustness with high-performance models like Claude Sonnet and GPT-o, but shows variability with less performant models.
- Key technical differentiators: Use of boolean and aggregation operators, the ability to handle complex queries, and the possibility of executing parallel queries.
Use Cases #
- Private AI Stack: Integration into proprietary pipelines
- Client Solutions: Implementation for client projects
- Strategic Intelligence: Input for technological roadmaps
- Competitive Analysis: Monitoring AI ecosystem
Resources #
Original Links #
- [2502.00032v1] Querying Databases with Function Calling - Original link
Article recommended and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-06 10:52 Original source: https://arxiv.org/abs/2502.00032v1
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