Remove dependency on langserve

backend/app/api/runs.py

@@ -6,7 +6,6 @@
 from langchain.pydantic_v1 import ValidationError
 from langchain_core.messages import AnyMessage
 from langchain_core.runnables import RunnableConfig
-from langserve.schema import FeedbackCreateRequest
 from langsmith.utils import tracing_is_enabled
 from pydantic import BaseModel, Field
 from sse_starlette import EventSourceResponse
@@ -102,6 +101,26 @@ async def config_schema() -> dict:
 if tracing_is_enabled():
     langsmith_client = langsmith.client.Client()
 
+    class BaseFeedback(BaseModel):
+        """
+        Shared information between create requests of feedback and feedback objects
+        """
+
+        run_id: UUID
+        """The associated run ID this feedback is logged for."""
+
+        key: str
+        """The metric name, tag, or aspect to provide feedback on."""
+
+        score: Optional[Union[float, int, bool]] = None
+        """Value or score to assign the run."""
+
+        value: Optional[Union[float, int, bool, str, Dict]] = None
+        """The display value for the feedback if not a metric."""
+
+        comment: Optional[str] = None
+        """Comment or explanation for the feedback."""
+
     @router.post("/feedback")
     def create_run_feedback(feedback_create_req: FeedbackCreateRequest) -> dict:
         """

backend/app/stream.py

@@ -1,10 +1,10 @@
+import functools
 from typing import Any, AsyncIterator, Dict, Optional, Sequence, Union
 
 import orjson
 import structlog
 from langchain_core.messages import AnyMessage, BaseMessage, message_chunk_to_message
 from langchain_core.runnables import Runnable, RunnableConfig
-from langserve.serialization import WellKnownLCSerializer
 
 logger = structlog.get_logger(__name__)
 
@@ -54,7 +54,13 @@ async def astream_state(
             yield [messages[message.id]]
 
 
-_serializer = WellKnownLCSerializer()
+def _default(obj) -> Any:
+    if hasattr(obj, "dict") and callable(obj.dict):
+        return obj.dict()
+    raise TypeError(f"Object of type {obj.__class__.__name__} is not JSON serializable")
+
+
+dumps = functools.partial(orjson.dumps, default=_default)
 
 
 async def to_sse(messages_stream: MessagesStream) -> AsyncIterator[dict]:
@@ -72,7 +78,7 @@ async def to_sse(messages_stream: MessagesStream) -> AsyncIterator[dict]:
             else:
                 yield {
                     "event": "data",
-                    "data": _serializer.dumps(
+                    "data": dumps(
                         [message_chunk_to_message(msg) for msg in chunk]
                     ).decode(),
                 }

backend/pyproject.toml

@@ -12,7 +12,6 @@ sse-starlette = "^1.6.5"
 tomli-w = "^1.0.0"
 uvicorn = "^0.23.2"
 fastapi = "^0.103.2"
-langserve = "0.0.32"
 # Uncomment if you need to work from a development branch
 # This will only work for local development though!
 # langchain = { git = "[email protected]:langchain-ai/langchain.git/", branch = "nc/subclass-runnable-binding" , subdirectory = "libs/langchain"}