add conversational retrieval chain (#30)

examples/conversational_retrieval_chain/client.ipynb

@@ -0,0 +1,105 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Client\n",
+    "\n",
+    "Demo of a client interacting with a remote retriever. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from langserve import RemoteRunnable\n",
+    "\n",
+    "remote_runnable = RemoteRunnable(\"http://localhost:8000/\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Remote runnable has the same interface as local runnables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'answer': 'Cats like fish.'}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "await remote_runnable.ainvoke({\"question\": \"what do cats like?\", \"chat_history\": \"\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'answer': 'Cats like fish.'}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "await remote_runnable.ainvoke({\"question\": \"what do cats like?\", \"chat_history\": [(\"hi\", \"hi\")]})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/conversational_retrieval_chain/server.py

@@ -0,0 +1,34 @@
+#!/usr/bin/env python
+"""Example LangChain server exposes a conversational retrieval chain."""
+from fastapi import FastAPI
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.vectorstores import FAISS
+from langchain.chains import ConversationalRetrievalChain
+from langchain.chat_models import ChatOpenAI
+
+from langserve import add_routes
+
+vectorstore = FAISS.from_texts(
+    ["cats like fish", "dogs like sticks"], embedding=OpenAIEmbeddings()
+)
+retriever = vectorstore.as_retriever()
+
+model = ChatOpenAI()
+
+chain = ConversationalRetrievalChain.from_llm(model, retriever)
+
+app = FastAPI(
+    title="LangChain Server",
+    version="1.0",
+    description="Spin up a simple api server using Langchain's Runnable interfaces",
+)
+# Adds routes to the app for using the chain under:
+# /invoke
+# /batch
+# /stream
+add_routes(app, chain)
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="localhost", port=8000)

examples/retrieval/server.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python
-"""Example LangChain server exposes a retrieval."""
+"""Example LangChain server exposes a retriever."""
 from fastapi import FastAPI
 from langchain.embeddings import OpenAIEmbeddings
 from langchain.vectorstores import FAISS