mirror of
https://github.com/open-webui/pipelines
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124 lines
2.7 KiB
Python
124 lines
2.7 KiB
Python
from fastapi import FastAPI, Request, Depends, status
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from fastapi.middleware.cors import CORSMiddleware
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from starlette.responses import StreamingResponse, Response
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from pydantic import BaseModel, ConfigDict
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from typing import List
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import time
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import json
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import uuid
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from config import MODEL_ID, MODEL_NAME
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app = FastAPI(docs_url="/docs", redoc_url=None)
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origins = ["*"]
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app.add_middleware(
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CORSMiddleware,
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allow_origins=origins,
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.middleware("http")
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async def check_url(request: Request, call_next):
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start_time = int(time.time())
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response = await call_next(request)
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process_time = int(time.time()) - start_time
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response.headers["X-Process-Time"] = str(process_time)
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return response
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@app.get("/")
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async def get_status():
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return {"status": True}
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@app.get("/models")
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@app.get("/v1/models")
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async def get_models():
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"""
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Returns the model that is available inside Dialog in the OpenAI format.
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"""
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return {
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"data": [
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{
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"id": MODEL_ID,
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"name": MODEL_NAME,
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"object": "model",
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"created": int(time.time()),
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"owned_by": "openai",
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}
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]
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}
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class OpenAIChatMessage(BaseModel):
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role: str
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content: str
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model_config = ConfigDict(extra="allow")
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class OpenAIChatCompletionForm(BaseModel):
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model: str
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messages: List[OpenAIChatMessage]
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model_config = ConfigDict(extra="allow")
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def stream_message_template(message: str):
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return {
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"id": f"rag-{str(uuid.uuid4())}",
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"object": "chat.completion.chunk",
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"created": int(time.time()),
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"model": MODEL_ID,
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"choices": [
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{
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"index": 0,
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"delta": {"content": message},
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"logprobs": None,
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"finish_reason": None,
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}
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],
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}
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def get_response():
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return "rag response"
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@app.post("/chat/completions")
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@app.post("/v1/chat/completions")
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async def generate_openai_chat_completion(form_data: OpenAIChatCompletionForm):
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res = get_response()
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finish_message = {
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"id": f"rag-{str(uuid.uuid4())}",
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"object": "chat.completion.chunk",
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"created": int(time.time()),
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"model": MODEL_ID,
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"choices": [
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{"index": 0, "delta": {}, "logprobs": None, "finish_reason": "stop"}
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],
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}
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def stream_content():
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message = stream_message_template(res)
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yield f"data: {json.dumps(message)}\n\n"
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yield f"data: {json.dumps(finish_message)}\n\n"
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yield f"data: [DONE]"
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return StreamingResponse(stream_content(), media_type="text/event-stream")
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