mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
88 lines
2.4 KiB
Plaintext
88 lines
2.4 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# TextGen\n",
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"\n",
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"[GitHub:oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui) A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA.\n",
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"\n",
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"This example goes over how to use LangChain to interact with LLM models via the `text-generation-webui` API integration.\n",
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"\n",
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"Please ensure that you have `text-generation-webui` configured and an LLM installed. Recommended installation via the [one-click installer appropriate](https://github.com/oobabooga/text-generation-webui#one-click-installers) for your OS.\n",
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"\n",
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"Once `text-generation-webui` is installed and confirmed working via the web interface, please enable the `api` option either through the web model configuration tab, or by adding the run-time arg `--api` to your start command."
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Set model_url and run the example"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"model_url = \"http://localhost:5000\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"import langchain\n",
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"from langchain import PromptTemplate, LLMChain\n",
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"from langchain.llms import TextGen\n",
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"\n",
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"langchain.debug = True\n",
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"\n",
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"template = \"\"\"Question: {question}\n",
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"\n",
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"Answer: Let's think step by step.\"\"\"\n",
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"\n",
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"\n",
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"prompt = PromptTemplate(template=template, input_variables=[\"question\"])\n",
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"llm = TextGen(model_url=model_url)\n",
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"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
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"question = \"What NFL team won the Super Bowl in the year Justin Bieber was born?\"\n",
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"\n",
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"llm_chain.run(question)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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