mirror of
https://github.com/hwchase17/langchain
synced 2024-11-04 06:00:26 +00:00
136 lines
3.4 KiB
Plaintext
136 lines
3.4 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"attachments": {},
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"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.llms import OpenAI\n",
|
|
"from langchain_experimental.autonomous_agents import HuggingGPT\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"
|
|
},
|
|
"orig_nbformat": 4
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|