main.py

from fastapi import FastAPI, Request, Response, HTTPException, Depends
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import StreamingResponse, JSONResponse, FileResponse

import requests
import json
from pydantic import BaseModel


from apps.web.models.users import Users
from constants import ERROR_MESSAGES
from utils.utils import (
    decode_token,
    get_current_user,
    get_verified_user,
    get_admin_user,
)
from config import OPENAI_API_BASE_URL, OPENAI_API_KEY, CACHE_DIR

import hashlib
from pathlib import Path

app = FastAPI()
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

app.state.OPENAI_API_BASE_URL = OPENAI_API_BASE_URL
app.state.OPENAI_API_KEY = OPENAI_API_KEY


class UrlUpdateForm(BaseModel):
    url: str


class KeyUpdateForm(BaseModel):
    key: str


@app.get("/url")
async def get_openai_url(user=Depends(get_admin_user)):
    return {"OPENAI_API_BASE_URL": app.state.OPENAI_API_BASE_URL}


@app.post("/url/update")
async def update_openai_url(form_data: UrlUpdateForm, user=Depends(get_admin_user)):
    app.state.OPENAI_API_BASE_URL = form_data.url
    return {"OPENAI_API_BASE_URL": app.state.OPENAI_API_BASE_URL}


@app.get("/key")
async def get_openai_key(user=Depends(get_admin_user)):
    return {"OPENAI_API_KEY": app.state.OPENAI_API_KEY}


@app.post("/key/update")
async def update_openai_key(form_data: KeyUpdateForm, user=Depends(get_admin_user)):
    app.state.OPENAI_API_KEY = form_data.key
    return {"OPENAI_API_KEY": app.state.OPENAI_API_KEY}


@app.post("/audio/speech")
async def speech(request: Request, user=Depends(get_verified_user)):
    target_url = f"{app.state.OPENAI_API_BASE_URL}/audio/speech"

    if app.state.OPENAI_API_KEY == "":
        raise HTTPException(status_code=401, detail=ERROR_MESSAGES.API_KEY_NOT_FOUND)

    body = await request.body()

    name = hashlib.sha256(body).hexdigest()

    SPEECH_CACHE_DIR = Path(CACHE_DIR).joinpath("./audio/speech/")
    SPEECH_CACHE_DIR.mkdir(parents=True, exist_ok=True)
    file_path = SPEECH_CACHE_DIR.joinpath(f"{name}.mp3")
    file_body_path = SPEECH_CACHE_DIR.joinpath(f"{name}.json")

    # Check if the file already exists in the cache
    if file_path.is_file():
        return FileResponse(file_path)

    headers = {}
    headers["Authorization"] = f"Bearer {app.state.OPENAI_API_KEY}"
    headers["Content-Type"] = "application/json"

    try:
        print("openai")
        r = requests.post(
            url=target_url,
            data=body,
            headers=headers,
            stream=True,
        )

        r.raise_for_status()

        # Save the streaming content to a file
        with open(file_path, "wb") as f:
            for chunk in r.iter_content(chunk_size=8192):
                f.write(chunk)

        with open(file_body_path, "w") as f:
            json.dump(json.loads(body.decode("utf-8")), f)

        # Return the saved file
        return FileResponse(file_path)

    except Exception as e:
        print(e)
        error_detail = "Open WebUI: Server Connection Error"
        if r is not None:
            try:
                res = r.json()
                if "error" in res:
                    error_detail = f"External: {res['error']}"
            except:
                error_detail = f"External: {e}"

        raise HTTPException(status_code=r.status_code, detail=error_detail)


@app.api_route("/{path:path}", methods=["GET", "POST", "PUT", "DELETE"])
async def proxy(path: str, request: Request, user=Depends(get_verified_user)):
    target_url = f"{app.state.OPENAI_API_BASE_URL}/{path}"
    print(target_url, app.state.OPENAI_API_KEY)

    if app.state.OPENAI_API_KEY == "":
        raise HTTPException(status_code=401, detail=ERROR_MESSAGES.API_KEY_NOT_FOUND)

    body = await request.body()

    # TODO: Remove below after gpt-4-vision fix from Open AI
    # Try to decode the body of the request from bytes to a UTF-8 string (Require add max_token to fix gpt-4-vision)
    try:
        body = body.decode("utf-8")
        body = json.loads(body)

        # Check if the model is "gpt-4-vision-preview" and set "max_tokens" to 4000
        # This is a workaround until OpenAI fixes the issue with this model
        if body.get("model") == "gpt-4-vision-preview":
            if "max_tokens" not in body:
                body["max_tokens"] = 4000
            print("Modified body_dict:", body)

        # Fix for ChatGPT calls failing because the num_ctx key is in body
        if 'num_ctx' in body:
            # If 'num_ctx' is in the dictionary, delete it
            # Leaving it there generates an error with the
            # OpenAI API (Feb 2024)
            del body['num_ctx']
        # OpenAI API (Feb 2024) accepts max_tokens
        body["max_tokens"] = 1600

        # Convert the modified body back to JSON
        body = json.dumps(body)
    except json.JSONDecodeError as e:
        print("Error loading request body into a dictionary:", e)

    headers = {}
    headers["Authorization"] = f"Bearer {app.state.OPENAI_API_KEY}"
    headers["Content-Type"] = "application/json"

    try:
        r = requests.request(
            method=request.method,
            url=target_url,
            data=body,
            headers=headers,
            stream=True,
        )

        r.raise_for_status()

        # Check if response is SSE
        if "text/event-stream" in r.headers.get("Content-Type", ""):
            return StreamingResponse(
                r.iter_content(chunk_size=8192),
                status_code=r.status_code,
                headers=dict(r.headers),
            )
        else:
            # For non-SSE, read the response and return it
            # response_data = (
            #     r.json()
            #     if r.headers.get("Content-Type", "")
            #     == "application/json"
            #     else r.text
            # )

            response_data = r.json()

            if "openai" in app.state.OPENAI_API_BASE_URL and path == "models":
                response_data["data"] = list(
                    filter(lambda model: "gpt" in model["id"], response_data["data"])
                )

            return response_data
    except Exception as e:
        print(e)
        error_detail = "Open WebUI: Server Connection Error"
        if r is not None:
            try:
                res = r.json()
                if "error" in res:
                    error_detail = f"External: {res['error']}"
            except:
                error_detail = f"External: {e}"

        raise HTTPException(status_code=r.status_code, detail=error_detail)