GraphCanon updated 2w · GitHub synced 2w
Decision brief
Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages.
Good fit when
- You should consider using Gorilla if you need a comprehensive framework for developing LLMs capable of leveraging external functions effectively.
- If your project requires interactive testing through web interfaces like Colab and Gradio, Gorilla provides dedicated demos that can help streamline this process.
Avoid when
- Avoid Gorilla if your primary focus is not on function calling or tool usage capabilities for LLMs; another model-specific framework may better fit your needs.
- If the lack of a direct comparison tool to other models' function-calling performance is critical in your decision process, and you find no suitable alternatives listed on their leaderboard.
- Pricing:
- freemium
- Requirements:
- Gorilla works best with Python environments and requires installation through pip or local repository cloning.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (117d since push)
- As of 2w
- Provenance
- Not a fork · Personal account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install gorillaSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A toolset for training and evaluating large language models with functions calls or tool usages.
Capability facts
- Languages
- python
Source: github.language · Aug 8, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 8, 2026)
```python import openaiSource link
Tags
README
Quick Start
Try Gorilla in your browser:
- 🚀 Gorilla Colab Demo: Try the base Gorilla model
- 🌐 Gorilla Gradio Demo: Interactive web interface
- 🔥 OpenFunctions Colab Demo: Try the latest OpenFunctions model
- 🎯 OpenFunctions Website Demo: Experiment with function calling
- 📊 Berkeley Function Calling Leaderboard: Compare function calling capabilities
Installation Options
- Gorilla CLI - Fastest way to get started
pip install gorilla-cli
gorilla generate 100 random characters into a file called test.txt
Learn more about Gorilla CLI →
- Run Gorilla Locally
git clone https://github.com/ShishirPatil/gorilla.git
cd gorilla/inference
Detailed local setup instructions →
- Use OpenFunctions
import openai
openai.api_key = "EMPTY"
openai.api_base = "http://luigi.millennium.berkeley.edu:8000/v1"
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## License
Gorilla is Apache 2.0 licensed, making it suitable for both academic and commercial use.
For agents
This page has a .md twin and JSON over the API.