Passthrough example (#305)

Including an example to show how to do pass through of arbitrary inputs
to the response

examples/passthrough_dict/client.ipynb

@@ -0,0 +1,148 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Passthrough information\n",
+    "\n",
+    "An example that shows how to pass through additional info with the request, and get it back with the response."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from langchain.prompts.chat import ChatPromptTemplate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from langserve import RemoteRunnable\n",
+    "\n",
+    "chain = RemoteRunnable(\"http://localhost:8000/v1/\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's create a prompt composed of a system message and a human message."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'output': AIMessage(content='`apple` translates to `mela` in Italian.'),\n",
+       " 'info': {'info': {'user_id': 42, 'user_info': {'address': 42}}}}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chain.invoke({'thing': 'apple', 'language': 'italian', 'info': {\"user_id\": 42, \"user_info\": {\"address\": 42}}})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'info': {'info': {'user_id': 42, 'user_info': {'address': 42}}}}\n",
+      "{'output': AIMessageChunk(content='')}\n",
+      "{'output': AIMessageChunk(content='m')}\n",
+      "{'output': AIMessageChunk(content='ela')}\n",
+      "{'output': AIMessageChunk(content='')}\n"
+     ]
+    }
+   ],
+   "source": [
+    "for chunk in chain.stream({'thing': 'apple', 'language': 'italian', 'info': {\"user_id\": 42, \"user_info\": {\"address\": 42}}}):\n",
+    "    print(chunk)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from langserve import RemoteRunnable\n",
+    "\n",
+    "chain = RemoteRunnable(\"http://localhost:8000/v2/\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'output': AIMessage(content='`apple` translates to `mela` in Italian.'),\n",
+       " 'info': {'user_id': 42, 'user_info': {'address': 42}}}"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "chain.invoke({'thing': 'apple', 'language': 'italian', 'info': {\"user_id\": 42, \"user_info\": {\"address\": 42}}})"
+   ]
+  }
+ ],
+ "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": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/passthrough_dict/server.py

@@ -0,0 +1,86 @@
+#!/usr/bin/env python
+"""Example LangChain server exposes multiple runnables (LLMs in this case)."""
+
+from typing import Any, Callable, Dict, List, Optional, TypedDict
+
+from fastapi import FastAPI
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.schema.runnable import RunnableMap, RunnablePassthrough
+
+from langserve import add_routes
+
+app = FastAPI(
+    title="LangChain Server",
+    version="1.0",
+    description="Spin up a simple api server using Langchain's Runnable interfaces",
+)
+
+
+def _create_projection(
+    *, include_keys: Optional[List] = None, exclude_keys: Optional[List[str]] = None
+) -> Callable[[dict], dict]:
+    """Create a projection function."""
+
+    def _project_dict(
+        d: dict,
+    ) -> dict:
+        """Project dictionary."""
+        keys = d.keys()
+        if include_keys is not None:
+            keys = set(keys) & set(include_keys)
+        if exclude_keys is not None:
+            keys = set(keys) - set(exclude_keys)
+        return {k: d[k] for k in keys}
+
+    return _project_dict
+
+
+prompt = ChatPromptTemplate.from_messages(
+    [("human", "translate `{thing}` to {language}")]
+)
+model = ChatOpenAI()
+
+underlying_chain = prompt | model
+
+wrapped_chain = RunnableMap(
+    {
+        "output": _create_projection(exclude_keys=["info"]) | underlying_chain,
+        "info": _create_projection(include_keys=["info"]),
+    }
+)
+
+
+class Input(TypedDict):
+    thing: str
+    language: str
+    info: Dict[str, Any]
+
+
+class Output(TypedDict):
+    output: underlying_chain.output_schema
+    info: Dict[str, Any]
+
+
+add_routes(
+    app, wrapped_chain.with_types(input_type=Input, output_type=Output), path="/v1"
+)
+
+
+# Version 2
+# Uses RunnablePassthrough.assign
+wrapped_chain_2 = RunnablePassthrough.assign(output=underlying_chain) | {
+    "output": lambda x: x["output"],
+    "info": lambda x: x["info"],
+}
+
+add_routes(
+    app,
+    wrapped_chain_2.with_types(input_type=Input, output_type=Output),
+    path="/v2",
+)
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="localhost", port=8000)