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langchain/cookbook/hugginggpt.ipynb

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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
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"source": [
"# HuggingGPT\n",
"Implementation of [HuggingGPT](https://github.com/microsoft/JARVIS). HuggingGPT is a system to connect LLMs (ChatGPT) with ML community (Hugging Face).\n",
"\n",
"+ 🔥 Paper: https://arxiv.org/abs/2303.17580\n",
"+ 🚀 Project: https://github.com/microsoft/JARVIS\n",
"+ 🤗 Space: https://huggingface.co/spaces/microsoft/HuggingGPT"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set up tools\n",
"\n",
"We set up the tools available from [Transformers Agent](https://huggingface.co/docs/transformers/transformers_agents#tools). It includes a library of tools supported by Transformers and some customized tools such as image generator, video generator, text downloader and other tools."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from transformers import load_tool"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"hf_tools = [\n",
" load_tool(tool_name)\n",
" for tool_name in [\n",
" \"document-question-answering\",\n",
" \"image-captioning\",\n",
" \"image-question-answering\",\n",
" \"image-segmentation\",\n",
" \"speech-to-text\",\n",
" \"summarization\",\n",
" \"text-classification\",\n",
" \"text-question-answering\",\n",
" \"translation\",\n",
" \"huggingface-tools/text-to-image\",\n",
" \"huggingface-tools/text-to-video\",\n",
" \"text-to-speech\",\n",
" \"huggingface-tools/text-download\",\n",
" \"huggingface-tools/image-transformation\",\n",
" ]\n",
"]"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Setup model and HuggingGPT\n",
"\n",
"We create an instance of HuggingGPT and use ChatGPT as the controller to rule the above tools."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain_experimental.autonomous_agents import HuggingGPT\n",
"from langchain_openai import OpenAI\n",
"\n",
"# %env OPENAI_API_BASE=http://localhost:8000/v1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"llm = OpenAI(model_name=\"gpt-3.5-turbo\")\n",
"agent = HuggingGPT(llm, hf_tools)"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## Run an example\n",
"\n",
"Given a text, show a related image and video."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"agent.run(\"please show me a video and an image of 'a boy is running'\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "langchain",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.17"
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}