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Rather have the user at the center, Gorilla enables users to interact with a wide range of services through LLMs. Gorilla is an open-source, state-of-the-art LLM that invokes API calls to interact with services!
- Overview
- News
- Get Started
- Repository Organization
- Contributing Your API
- FAQ(s)
- Project Roadmap
- Citation
🔥 Gorilla OpenFunctions is a drop-in alternative for function calling! Release Blog
🟢 Gorilla is Apache 2.0 With Gorilla being fine-tuned on MPT, and Falcon, you can use Gorilla commercially with no obligations! ⛳
🚀 Try Gorilla in 60s
💻 Use Gorilla in your CLI with pip install gorilla-cli
🗞️ Checkout our paper!
👋 Join our Discord!
•🔥 [11/16] Excited to release Gorilla OpenFunctions
•💻 [06/29] Released gorilla-cli, LLMs for your CLI!
•🟢 [06/06] Released Commercially usable, Apache 2.0 licensed Gorilla models
•🚀 [05/30] Provided the CLI interface to chat with Gorilla!
•🚀 [05/28] Released Torch Hub and TensorFlow Hub Models!
•🚀 [05/27] Released the first Gorilla model! or 🤗!
Inference: Run Gorilla locally inference/README.md
Evaluation: We have included prompts and responses for the APIBench with and without retrievers along with the Abstract Syntax Tree (AST) matching evaluation script at evaluation.
Our repository organization is shown below.
•The data folder contains all the evaluation APIs (APIBench) and the community contributed APIs.
•The eval folder contains all our evaluation code as well as the Gorilla outputs.
•The inference folder contains all the inference code for running Gorilla locally.
•[Coming Soon!] The train folder contains all the training code associated with Gorilla finetuning.
For our dataset collections, all the 1640 API documentation is in data/api. We also include the APIBench dataset created by self-instruct in data/apibench. For evaluation, we convert this into a LLM-friendly chat format, and the questions are in eval/eval-data/questions, and the corresponding responses are in eval/eval-data/responses. We have also included the evaluation scripts are in eval/eval-scripts. This would be entirely sufficient to train Gorilla yourself, and reproduce our results. Please see evaluation for the details on how to use our evaluation pipeline.
We aim to build an open-source, one-stop-shop for all APIs, LLMs can interact with! Any suggestions and contributions are welcome! Please see the details on how to contribute. THIS WILL ALWAYS REMAIN OPEN SOURCE.
1.I would like to use Gorilla commercially. Is there going to be a Apache 2.0 licensed version?
Yes! We now have models that you can use commercially without any obligations.
1.Can we use Gorilla with Langchain, Toolformer, AutoGPT etc?
Absolutely! You've highlighted a great aspect of our tools. Gorilla is an end-to-end model, specifically tailored to serve correct API calls without requiring any additional coding. It's designed to work as part of a wider ecosystem and can be flexibly integrated with other tools.
Langchain, is a versatile developer tool. Its "agents" can efficiently swap in any LLM, Gorilla included, making it a highly adaptable solution for various needs.
AutoGPT, on the other hand, concentrates on the art of prompting GPT series models. It's worth noting that Gorilla, as a fully fine-tuned model, consistently shows remarkable accuracy, and lowers hallucination, outperforming GPT-4 in making specific API calls.
In the immediate future, we plan to release the following:
•Dataset and Eval Code
•Opening up the APIZoo for contributions from community
•Hosted Gorilla LLM chat for HF model APIs [May 27, 2023]
•Release weights for HF model APIs [May 27, 2023]
•Run Gorilla LLM locally [May 28, 2023]
If you use Gorilla or APIBench, please cite our paper:
Jun 6, 2023 · Gorilla is a Meta LLaMA model fine-tuned to improve its ability to make API calls without additional coding. It outperforms GPT-4 and Claude in terms of API functionality accuracy and reducing hallucination errors.
Gorilla's innovative AI offers groundbreaking Smart City solutions that enhance quality of life and economic competitiveness across the globe.
May 24, 2023 · Gorilla is a large language model that can write API calls with high accuracy and low hallucination. It uses a document retriever to adapt to test-time changes and integrates with HuggingFace, TorchHub, and TensorHub APIs.
- arXiv:2305.15334 [cs.CL]
Jul 4, 2023 · In experiments measuring generated code accuracy, Gorilla outperfor Researchers from UC Berkeley and Microsoft have open-sourced Gorilla, a large language model (LLM) that can write code to...
Aug 4, 2023 · Gorilla is an AI model, developed by Microsoft and UC Berkeley, that can autonomously interact with various online tools using API calls. Unlike other large language models, Gorilla can...
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