Gorilla

Overview

Gorilla is a Python framework for training and evaluating large language models on function calling tasks. It provides datasets, training pipelines, and benchmarks to improve LLM accuracy when selecting and invoking external tools and APIs.

Best for

Best for
Developers building agent systems who need LLMs to reliably invoke specific functions and APIs

Use cases

• Training models to correctly call APIs and functions from natural language
• Benchmarking LLM tool-use performance across different model sizes
• Building reliable agent systems that need accurate function selection

Notes

Gorilla is a Python framework for training and evaluating large language models on function calling tasks. It provides datasets, training pipelines, and benchmarks to improve LLM accuracy when selecting and invoking external tools and APIs.

12,878 stars on GitHub. Last updated 2026-04-13. Licensed Apache-2.0.

Use cases

• Training models to correctly call APIs and functions from natural language
• Benchmarking LLM tool-use performance across different model sizes
• Building reliable agent systems that need accurate function selection

Pros

• Focused dataset and evaluation methodology specifically for function calling
• Open source with active community support (12k+ stars)
• Enables fine-tuning of models for tool use rather than relying on base model capabilities

Cons

• Requires Python expertise and familiarity with LLM training workflows
• Limited to function calling tasks, not general-purpose LLM training
• Community-maintained project without commercial support guarantees

Indexed from awesome-langchain and enriched against its public facts.