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https://github.com/open-webui/pipelines
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393a130e34
145
examples/filters/langfuse_filter_pipeline_outlet.py
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145
examples/filters/langfuse_filter_pipeline_outlet.py
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"""
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title: Langfuse Filter Pipeline Outlet
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author: open-webui
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date: 2025-02-19
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version: 1.4
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license: MIT
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description: A filter pipeline that uses Langfuse.
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requirements: langfuse
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"""
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from typing import List, Optional
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import os
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import uuid
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from utils.pipelines.main import get_last_assistant_message
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from pydantic import BaseModel
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from langfuse import Langfuse
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from langfuse.api.resources.commons.errors.unauthorized_error import UnauthorizedError
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def get_last_assistant_message_obj(messages: List[dict]) -> dict:
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for message in reversed(messages):
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if message["role"] == "assistant":
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return message
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return {}
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def remove_last_assistant_message(messages: List[dict]) -> List[dict]:
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if messages and messages[-1]["role"] == "assistant":
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return messages[:-1]
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return messages
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class Pipeline:
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class Valves(BaseModel):
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pipelines: List[str] = []
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priority: int = 0
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secret_key: str
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public_key: str
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host: str
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def __init__(self):
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self.type = "filter"
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self.name = "Langfuse Filter Outlet"
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self.valves = self.Valves(
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**{
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"pipelines": ["*"],
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"secret_key": os.getenv("LANGFUSE_SECRET_KEY", "your-secret-key-here"),
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"public_key": os.getenv("LANGFUSE_PUBLIC_KEY", "your-public-key-here"),
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"host": os.getenv("LANGFUSE_HOST", "https://cloud.langfuse.com"),
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}
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)
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self.langfuse = None
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async def on_startup(self):
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print(f"on_startup:{__name__}")
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self.set_langfuse()
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async def on_shutdown(self):
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print(f"on_shutdown:{__name__}")
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self.langfuse.flush()
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async def on_valves_updated(self):
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self.set_langfuse()
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def set_langfuse(self):
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try:
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self.langfuse = Langfuse(
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secret_key=self.valves.secret_key,
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public_key=self.valves.public_key,
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host=self.valves.host,
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debug=False,
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)
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self.langfuse.auth_check()
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except UnauthorizedError:
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print(
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"Langfuse credentials incorrect. Please re-enter your Langfuse credentials in the pipeline settings."
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)
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except Exception as e:
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print(
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f"Langfuse error: {e} Please re-enter your Langfuse credentials in the pipeline settings."
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)
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async def outlet(self, body: dict, user: Optional[dict] = None) -> dict:
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print(f"outlet:{__name__}")
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print(f"Received body: {body}")
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if "chat_id" not in body:
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print("chat_id not in body")
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return body
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user_id = user.get("id") if user else None
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user_name = user.get("name") if user else None
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user_email = user.get("email") if user else None
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input_messages = remove_last_assistant_message(body["messages"])
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trace = self.langfuse.trace(
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name=f"filter:{__name__}",
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input=input_messages,
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user_id=user_email,
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metadata={
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"user_name": user_name,
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"user_id": user_id,
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"chat_id": body["chat_id"],
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},
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session_id=body["chat_id"],
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)
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generation = trace.generation(
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name=body["chat_id"],
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model=body["model"],
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input=input_messages,
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metadata={"interface": "open-webui"},
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)
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assistant_message = get_last_assistant_message(body["messages"])
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# Extract usage information for models that support it
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usage = None
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assistant_message_obj = get_last_assistant_message_obj(body["messages"])
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if assistant_message_obj:
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info = assistant_message_obj.get("info", {})
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if isinstance(info, dict):
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input_tokens = info.get("prompt_eval_count") or info.get(
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"prompt_tokens"
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)
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output_tokens = info.get("eval_count") or info.get("completion_tokens")
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if input_tokens is not None and output_tokens is not None:
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usage = {
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"input": input_tokens,
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"output": output_tokens,
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"unit": "TOKENS",
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}
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# Update generation
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trace.update(
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output=assistant_message,
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)
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generation.end(
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output=assistant_message,
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metadata={"interface": "open-webui"},
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usage=usage,
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)
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return body
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