Sync with upstream

.clabot

@@ -0,0 +1,4 @@
+{
+  "contributors": ["eyurtsev", "hwchase17", "nfcampos", "efriis", "jacoblee93", "dqbd", "kreneskyp", "adarsh-jha-dev", "harris", "baskaryan", "hinthornw", "bracesproul", "jakerachleff"],
+  "message": "Thank you for your pull request and welcome to our community. We require contributors to sign our Contributor License Agreement, and we don't seem to have the username {{usersWithoutCLA}} on file. In order for us to review and merge your code, please complete the Individual Contributor License Agreement here https://forms.gle/Ljhqvt9Gdi1N385W6 .\n\nThis process is done manually on our side, so after signing the form one of the maintainers will add you to the contributors list.\n\nFor more details about why we have a CLA and other contribution guidelines please see: https://github.com/langchain-ai/langserve/blob/main/CONTRIBUTING.md."
+}

.github/workflows/_pydantic_compatibility.yml

@@ -13,6 +13,7 @@ env:
 
 jobs:
   build:
+    timeout-minutes: 5
     defaults:
       run:
         working-directory: ${{ inputs.working-directory }}

.github/workflows/langserve_ci.yml

@@ -39,7 +39,14 @@ jobs:
       working-directory: .
     secrets: inherit
 
+  pydantic-compatibility:
+    uses:
+      ./.github/workflows/_pydantic_compatibility.yml
+    with:
+      working-directory: .
+    secrets: inherit
   test:
+    timeout-minutes: 5
     runs-on: ubuntu-latest
     defaults:
       run:
@@ -51,7 +58,7 @@ jobs:
           - "3.9"
           - "3.10"
           - "3.11"
-    name: Python ${{ matrix.python-version }} extended tests
+    name: Python ${{ matrix.python-version }} tests
     steps:
       - uses: actions/checkout@v3
 

Makefile

@@ -33,10 +33,10 @@ lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=. --name-only --
 
 lint lint_diff:
 	poetry run ruff .
-	poetry run black $(PYTHON_FILES) --check
+	poetry run ruff format $(PYTHON_FILES) --check
 
 format format_diff:
-	poetry run black $(PYTHON_FILES)
+	poetry run ruff format $(PYTHON_FILES)
 	poetry run ruff --select I --fix $(PYTHON_FILES)
 
 spell_check:

README.md

@@ -1,5 +1,10 @@
 # GigaServe 🦜️🏓 = LangServe + GigaChat
 
+[![Release Notes](https://img.shields.io/github/release/langchain-ai/langserve)](https://github.com/langchain-ai/langserve/releases)
+[![Downloads](https://static.pepy.tech/badge/langserve/month)](https://pepy.tech/project/langserve)
+[![Open Issues](https://img.shields.io/github/issues-raw/langchain-ai/langserve)](https://github.com/langchain-ai/langserve/issues)
+[![](https://dcbadge.vercel.app/api/server/6adMQxSpJS?compact=true&style=flat)](https://discord.com/channels/1038097195422978059/1170024642245832774)
+
 🚩 We will be releasing a hosted version of LangServe for one-click deployments of LangChain applications. [Sign up here](https://airtable.com/app0hN6sd93QcKubv/shrAjst60xXa6quV2) to get on the waitlist.
 
 ## Overview
@@ -26,7 +31,7 @@ A javascript client is available in [LangChainJS](https://js.langchain.com/docs/
 ### Limitations
 
 - Client callbacks are not yet supported for events that originate on the server
-- Does not work with [pydantic v2 yet](https://github.com/tiangolo/fastapi/issues/10360)
+- OpenAPI docs will not be generated when using Pydantic V2. Fast API does not support [mixing pydantic v1 and v2 namespaces](https://github.com/tiangolo/fastapi/issues/10360). See section below for more details.
 
 ## Hosted LangServe
 
@@ -38,10 +43,10 @@ We will be releasing a hosted version of LangServe for one-click deployments of
 
 ## LangChain CLI 🛠️
 
-Use the `LangChain` CLI to bootstrap a `LangServe` project quickly.
+Use the `GigaChain` CLI to bootstrap a `GigaChain` project quickly.
 
-To use the langchain CLI make sure that you have a recent version of `gigachain-cli` 
-installed. You can install it with `pip install -U "gigachain-cli[serve]"`.
+To use the gigachain CLI make sure that you have a recent version of `gigachain-cli` 
+installed. You can install it with `pip install -U gigachain-cli`.
 
 ```sh
 langchain app new ../path/to/directory
@@ -257,6 +262,15 @@ You can deploy to GCP Cloud Run using the following command:
 gcloud run deploy [your-service-name] --source . --port 8001 --allow-unauthenticated --region us-central1 --set-env-vars=OPENAI_API_KEY=your_key
 ```
 
+## Pydantic
+
+LangServe provides support for Pydantic 2 with some limitations.
+
+1. OpenAPI docs will not be generated for invoke/batch/stream/stream_log when using Pydantic V2. Fast API does not support [mixing pydantic v1 and v2 namespaces].
+2. LangChain uses the v1 namespace in Pydantic v2. Please read the [following guidelines to ensure compatibility with LangChain](https://github.com/langchain-ai/langchain/discussions/9337)
+
+Except for these limitations, we expect the API endpoints, the playground and any other features to work as expected. 
+
 ## Advanced
 
 ### Files
@@ -381,7 +395,10 @@ that are uploaded as base64 encoded strings. Here's the full [example](https://g
 Snippet:
 
 ```python
-from pydantic import Field
+try:
+    from pydantic.v1 import Field
+except ImportError:
+    from pydantic import Field
 
 from langserve import CustomUserType
 

examples/agent/server.py

@@ -7,9 +7,9 @@
 from langchain.chat_models import ChatOpenAI
 from langchain.embeddings import OpenAIEmbeddings
 from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain.pydantic_v1 import BaseModel
 from langchain.tools.render import format_tool_to_openai_function
 from langchain.vectorstores import FAISS
-from pydantic import BaseModel
 
 from langserve import add_routes
 

examples/configurable_chain/client.ipynb

@@ -18,28 +18,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'output': \"Why don't scientists trust atoms who play sports?\\n\\nBecause they make up everything!\",\n",
-       " 'callback_events': []}"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import requests\n",
     "\n",
     "inputs = {\"input\": {\"topic\": \"sports\"}}\n",
-    "response = requests.post(\"http://localhost:8000/invoke\", json=inputs)\n",
+    "response = requests.post(\"http://localhost:8000/configurable_temp/invoke\", json=inputs)\n",
     "\n",
     "response.json()"
    ]
@@ -61,7 +49,7 @@
    "source": [
     "from langserve import RemoteRunnable\n",
     "\n",
-    "remote_runnable = RemoteRunnable(\"http://localhost:8000/\")"
+    "remote_runnable = RemoteRunnable(\"http://localhost:8000/configurable_temp\")"
    ]
   },
   {
@@ -177,6 +165,104 @@
     "    },\n",
     ")"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Configurability Based on Request Properties\n",
+    "\n",
+    "If you want to change your chain invocation based on your request's properties,\n",
+    "you can do so with `add_routes`'s `per_req_config_modifier` method as follows:\n",
+    "\n",
+    "```python \n",
+    "\n",
+    "# Add another example route where you can configure the model based\n",
+    "# on properties of the request. This is useful for passing in API\n",
+    "# keys from request headers (WITH CAUTION) or using other properties\n",
+    "# of the request to configure the model.\n",
+    "def fetch_api_key_from_header(config: Dict[str, Any], req: Request) -> Dict[str, Any]:\n",
+    "    if \"x-api-key\" in req.headers:\n",
+    "        config[\"configurable\"][\"openai_api_key\"] = req.headers[\"x-api-key\"]\n",
+    "    return config\n",
+    "\n",
+    "dynamic_auth_model = ChatOpenAI(openai_api_key='placeholder').configurable_fields(\n",
+    "    openai_api_key=ConfigurableField(\n",
+    "        id=\"openai_api_key\",\n",
+    "        name=\"OpenAI API Key\",\n",
+    "        description=(\n",
+    "            \"API Key for OpenAI interactions\"\n",
+    "        ),\n",
+    "    ),\n",
+    ")\n",
+    "\n",
+    "dynamic_auth_chain = dynamic_auth_model | StrOutputParser()\n",
+    "\n",
+    "add_routes(\n",
+    "    app, \n",
+    "    dynamic_auth_chain, \n",
+    "    path=\"/auth_from_header\",\n",
+    "    config_keys=[\"configurable\"], \n",
+    "    per_req_config_modifier=fetch_api_key_from_header\n",
+    ")\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, we can see that our request to the model will only work if we have a specific request\n",
+    "header set:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The model will fail with an auth error\n",
+    "unauthenticated_response = requests.post(\n",
+    "    \"http://localhost:8000/auth_from_header/invoke\", json={\"input\": \"hello\"}\n",
+    ")\n",
+    "unauthenticated_response.json()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, ensure that you have run the following locally on your shell\n",
+    "```bash\n",
+    "export TEST_API_KEY=<INSERT MY KEY HERE>\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# The model will succeed as long as the above shell script is run previously\n",
+    "import os\n",
+    "\n",
+    "test_key = os.environ[\"TEST_API_KEY\"]\n",
+    "authenticated_response = requests.post(\n",
+    "    \"http://localhost:8000/auth_from_header/invoke\",\n",
+    "    json={\"input\": \"hello\"},\n",
+    "    headers={\"x-api-key\": test_key},\n",
+    ")\n",
+    "authenticated_response.json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -195,7 +281,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,

examples/configurable_chain/server.py

@@ -6,7 +6,9 @@
 1) Configurable Fields: Use this to specify values for a given initialization parameter
 2) Configurable Alternatives: Use this to specify complete alternative runnables
 """
-from fastapi import FastAPI
+from typing import Any, Dict
+
+from fastapi import FastAPI, HTTPException, Request
 from fastapi.middleware.cors import CORSMiddleware
 from langchain.chat_models import ChatOpenAI
 from langchain.prompts import PromptTemplate
@@ -15,6 +17,25 @@
 
 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",
+)
+
+# Set all CORS enabled origins
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+    expose_headers=["*"],
+)
+
+###############################################################################
+#                EXAMPLE 1: Configure fields based on RunnableConfig          #
+###############################################################################
 model = ChatOpenAI(temperature=0.5).configurable_alternatives(
     ConfigurableField(
         id="llm",
@@ -38,26 +59,46 @@
 )
 chain = prompt | model | StrOutputParser()
 
-app = FastAPI(
-    title="GigaChain Server",
-    version="1.0",
-    description="Spin up a simple api server using Langchain's Runnable interfaces",
-)
+# Add routes requires you to specify which config keys are accepted
+# specifically, you must accept `configurable` as a config key.
+add_routes(app, chain, path="/configurable_temp", config_keys=["configurable"])
 
-# Set all CORS enabled origins
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-    expose_headers=["*"],
+
+###############################################################################
+#             EXAMPLE 2: Configure fields based on Request metadata           #
+###############################################################################
+
+
+# Add another example route where you can configure the model based
+# on properties of the request. This is useful for passing in API
+# keys from request headers (WITH CAUTION) or using other properties
+# of the request to configure the model.
+def fetch_api_key_from_header(config: Dict[str, Any], req: Request) -> Dict[str, Any]:
+    if "x-api-key" in req.headers:
+        config["configurable"]["openai_api_key"] = req.headers["x-api-key"]
+    else:
+        raise HTTPException(401, "No API key provided")
+
+    return config
+
+
+dynamic_auth_model = ChatOpenAI(openai_api_key="placeholder").configurable_fields(
+    openai_api_key=ConfigurableField(
+        id="openai_api_key",
+        name="OpenAI API Key",
+        description=("API Key for OpenAI interactions"),
+    ),
 )
 
+dynamic_auth_chain = dynamic_auth_model | StrOutputParser()
 
-# Add routes requires you to specify which config keys are accepted
-# specifically, you must accept `configurable` as a config key.
-add_routes(app, chain, config_keys=["configurable"])
+add_routes(
+    app,
+    dynamic_auth_chain,
+    path="/auth_from_header",
+    config_keys=["configurable"],
+    per_req_config_modifier=fetch_api_key_from_header,
+)
 
 if __name__ == "__main__":
     import uvicorn

examples/conversational_retrieval_chain/server.py

@@ -6,8 +6,8 @@
 from langchain.chains import ConversationalRetrievalChain
 from langchain.chat_models import ChatOpenAI
 from langchain.embeddings import OpenAIEmbeddings
+from langchain.pydantic_v1 import BaseModel, Field
 from langchain.vectorstores import FAISS
-from pydantic import BaseModel, Field
 
 from langserve import add_routes
 

examples/file_processing/server.py

@@ -17,8 +17,8 @@
 from fastapi import FastAPI
 from langchain.document_loaders.blob_loaders import Blob
 from langchain.document_loaders.parsers.pdf import PDFMinerParser
+from langchain.pydantic_v1 import Field
 from langchain.schema.runnable import RunnableLambda
-from pydantic import Field
 
 from langserve import CustomUserType, add_routes