mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
69 lines
1.6 KiB
Plaintext
69 lines
1.6 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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"id": "681a5d1e",
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"metadata": {},
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"source": [
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"## Run Template\n",
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"\n",
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"In `server.py`, set -\n",
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"```\n",
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"from fastapi import FastAPI\n",
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"from langserve import add_routes\n",
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"from propositional_retrieval import chain\n",
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"\n",
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"app = FastAPI(\n",
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" title=\"LangChain Server\",\n",
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" version=\"1.0\",\n",
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" description=\"Retriever and Generator for RAG Chroma Dense Retrieval\",\n",
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")\n",
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"\n",
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"add_routes(app, chain, path=\"/propositional-retrieval\")\n",
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"\n",
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"if __name__ == \"__main__\":\n",
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" import uvicorn\n",
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"\n",
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" uvicorn.run(app, host=\"localhost\", port=8000)\n",
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"\n",
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"```"
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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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"id": "d774be2a",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langserve.client import RemoteRunnable\n",
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"\n",
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"rag_app = RemoteRunnable(\"http://localhost:8001/propositional-retrieval\")\n",
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"rag_app.invoke(\"How are transformers related to convolutional neural networks?\")"
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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": "3.11.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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