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https://github.com/open-webui/open-webui
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@ -161,7 +161,7 @@ async def get_file_by_id(id: str, user=Depends(get_verified_user)):
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return file
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else:
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raise HTTPException(
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status_code=status.HTTP_401_UNAUTHORIZED,
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status_code=status.HTTP_404_NOT_FOUND,
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detail=ERROR_MESSAGES.NOT_FOUND,
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)
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@ -180,17 +180,16 @@ async def get_file_content_by_id(id: str, user=Depends(get_verified_user)):
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# Check if the file already exists in the cache
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if file_path.is_file():
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print(f"file_path: {file_path}")
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return FileResponse(file_path)
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else:
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raise HTTPException(
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status_code=status.HTTP_401_UNAUTHORIZED,
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status_code=status.HTTP_404_NOT_FOUND,
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detail=ERROR_MESSAGES.NOT_FOUND,
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)
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else:
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raise HTTPException(
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status_code=status.HTTP_401_UNAUTHORIZED,
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status_code=status.HTTP_404_NOT_FOUND,
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detail=ERROR_MESSAGES.NOT_FOUND,
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)
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@ -215,6 +214,6 @@ async def delete_file_by_id(id: str, user=Depends(get_verified_user)):
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)
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else:
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raise HTTPException(
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status_code=status.HTTP_401_UNAUTHORIZED,
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status_code=status.HTTP_404_NOT_FOUND,
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detail=ERROR_MESSAGES.NOT_FOUND,
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)
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@ -82,6 +82,152 @@ class Filter:
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return {"messages": messages}
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`;
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const _boilerplate = `from pydantic import BaseModel
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from typing import Optional, Union, Generator, Iterator
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from utils.misc import get_last_user_message
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import os
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import requests
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# Filter Class: This class is designed to serve as a pre-processor and post-processor
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# for request and response modifications. It checks and transforms requests and responses
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# to ensure they meet specific criteria before further processing or returning to the user.
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class Filter:
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class Valves(BaseModel):
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max_turns: int = 4
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pass
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def __init__(self):
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# Indicates custom file handling logic. This flag helps disengage default routines in favor of custom
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# implementations, informing the WebUI to defer file-related operations to designated methods within this class.
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# Alternatively, you can remove the files directly from the body in from the inlet hook
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self.file_handler = True
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# Initialize 'valves' with specific configurations. Using 'Valves' instance helps encapsulate settings,
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# which ensures settings are managed cohesively and not confused with operational flags like 'file_handler'.
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self.valves = self.Valves(**{"max_turns": 2})
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pass
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def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
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# Modify the request body or validate it before processing by the chat completion API.
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# This function is the pre-processor for the API where various checks on the input can be performed.
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# It can also modify the request before sending it to the API.
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print(f"inlet:{__name__}")
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print(f"inlet:body:{body}")
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print(f"inlet:user:{user}")
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if user.get("role", "admin") in ["user", "admin"]:
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messages = body.get("messages", [])
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if len(messages) > self.valves.max_turns:
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raise Exception(
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f"Conversation turn limit exceeded. Max turns: {self.valves.max_turns}"
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)
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return body
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def outlet(self, body: dict, user: Optional[dict] = None) -> dict:
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# Modify or analyze the response body after processing by the API.
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# This function is the post-processor for the API, which can be used to modify the response
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# or perform additional checks and analytics.
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print(f"outlet:{__name__}")
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print(f"outlet:body:{body}")
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print(f"outlet:user:{user}")
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messages = [
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{
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**message,
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"content": f"{message['content']} - @@Modified from Filter Outlet",
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}
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for message in body.get("messages", [])
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]
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return {"messages": messages}
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# Pipe Class: This class functions as a customizable pipeline.
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# It can be adapted to work with any external or internal models,
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# making it versatile for various use cases outside of just OpenAI models.
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class Pipe:
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class Valves(BaseModel):
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OPENAI_API_BASE_URL: str = "https://api.openai.com/v1"
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OPENAI_API_KEY: str = "your-key"
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pass
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def __init__(self):
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self.type = "manifold"
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self.valves = self.Valves()
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self.pipes = self.get_openai_models()
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pass
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def get_openai_models(self):
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if self.valves.OPENAI_API_KEY:
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try:
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headers = {}
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headers["Authorization"] = f"Bearer {self.valves.OPENAI_API_KEY}"
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headers["Content-Type"] = "application/json"
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r = requests.get(
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f"{self.valves.OPENAI_API_BASE_URL}/models", headers=headers
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)
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models = r.json()
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return [
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{
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"id": model["id"],
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"name": model["name"] if "name" in model else model["id"],
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}
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for model in models["data"]
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if "gpt" in model["id"]
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]
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except Exception as e:
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print(f"Error: {e}")
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return [
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{
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"id": "error",
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"name": "Could not fetch models from OpenAI, please update the API Key in the valves.",
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},
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]
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else:
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return []
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def pipe(self, body: dict) -> Union[str, Generator, Iterator]:
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# This is where you can add your custom pipelines like RAG.
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print(f"pipe:{__name__}")
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if "user" in body:
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print(body["user"])
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del body["user"]
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headers = {}
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headers["Authorization"] = f"Bearer {self.valves.OPENAI_API_KEY}"
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headers["Content-Type"] = "application/json"
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model_id = body["model"][body["model"].find(".") + 1 :]
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payload = {**body, "model": model_id}
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print(payload)
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try:
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r = requests.post(
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url=f"{self.valves.OPENAI_API_BASE_URL}/chat/completions",
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json=payload,
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headers=headers,
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stream=True,
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)
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r.raise_for_status()
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if body["stream"]:
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return r.iter_lines()
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else:
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return r.json()
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except Exception as e:
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return f"Error: {e}"
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`;
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const saveHandler = async () => {
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