mirror of
https://github.com/open-webui/open-webui.git
synced 2025-12-16 11:57:51 +01:00
Merge remote-tracking branch 'upstream/dev' into feat/oauth
This commit is contained in:
Jun Siang Cheah
777
backend/main.py
777
backend/main.py
@@ -13,8 +13,12 @@ import logging
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import aiohttp
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import requests
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import mimetypes
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import shutil
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import os
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import inspect
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import asyncio
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from fastapi import FastAPI, Request, Depends, status
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from fastapi import FastAPI, Request, Depends, status, UploadFile, File, Form
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from fastapi.staticfiles import StaticFiles
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from fastapi.responses import JSONResponse
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from fastapi import HTTPException
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@@ -27,21 +31,33 @@ from starlette.responses import StreamingResponse, Response, RedirectResponse
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from apps.socket.main import app as socket_app
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from apps.ollama.main import app as ollama_app, get_all_models as get_ollama_models
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from apps.openai.main import app as openai_app, get_all_models as get_openai_models
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from apps.ollama.main import (
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app as ollama_app,
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OpenAIChatCompletionForm,
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get_all_models as get_ollama_models,
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generate_openai_chat_completion as generate_ollama_chat_completion,
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)
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from apps.openai.main import (
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app as openai_app,
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get_all_models as get_openai_models,
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generate_chat_completion as generate_openai_chat_completion,
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)
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from apps.audio.main import app as audio_app
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from apps.images.main import app as images_app
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from apps.rag.main import app as rag_app
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from apps.webui.main import app as webui_app
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import asyncio
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from pydantic import BaseModel
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from typing import List, Optional
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from apps.webui.models.auths import Auths
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from apps.webui.models.models import Models
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from apps.webui.models.models import Models, ModelModel
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from apps.webui.models.tools import Tools
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from apps.webui.models.users import Users
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from apps.webui.utils import load_toolkit_module_by_id
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from utils.misc import parse_duration
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from utils.utils import (
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get_admin_user,
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@@ -51,7 +67,14 @@ from utils.utils import (
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get_password_hash,
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create_token,
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)
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from apps.rag.utils import rag_messages
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from utils.task import (
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title_generation_template,
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search_query_generation_template,
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tools_function_calling_generation_template,
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)
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from utils.misc import get_last_user_message, add_or_update_system_message
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from apps.rag.utils import get_rag_context, rag_template
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from config import (
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CONFIG_DATA,
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@@ -72,14 +95,20 @@ from config import (
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SRC_LOG_LEVELS,
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WEBHOOK_URL,
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ENABLE_ADMIN_EXPORT,
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AppConfig,
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WEBUI_BUILD_HASH,
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TASK_MODEL,
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TASK_MODEL_EXTERNAL,
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TITLE_GENERATION_PROMPT_TEMPLATE,
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SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE,
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SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD,
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TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
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OAUTH_PROVIDERS,
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ENABLE_OAUTH_SIGNUP,
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OAUTH_MERGE_ACCOUNTS_BY_EMAIL,
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WEBUI_SECRET_KEY,
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WEBUI_SESSION_COOKIE_SAME_SITE,
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WEBUI_SESSION_COOKIE_SECURE,
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AppConfig,
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)
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from constants import ERROR_MESSAGES, WEBHOOK_MESSAGES
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from utils.webhook import post_webhook
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@@ -134,27 +163,133 @@ app.state.config.ENABLE_OLLAMA_API = ENABLE_OLLAMA_API
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app.state.config.ENABLE_MODEL_FILTER = ENABLE_MODEL_FILTER
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app.state.config.MODEL_FILTER_LIST = MODEL_FILTER_LIST
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app.state.config.WEBHOOK_URL = WEBHOOK_URL
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app.state.config.TASK_MODEL = TASK_MODEL
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app.state.config.TASK_MODEL_EXTERNAL = TASK_MODEL_EXTERNAL
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app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE = TITLE_GENERATION_PROMPT_TEMPLATE
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app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = (
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SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE
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)
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app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD = (
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SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD
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)
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app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = (
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TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE
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)
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app.state.MODELS = {}
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origins = ["*"]
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# Custom middleware to add security headers
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# class SecurityHeadersMiddleware(BaseHTTPMiddleware):
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# async def dispatch(self, request: Request, call_next):
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# response: Response = await call_next(request)
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# response.headers["Cross-Origin-Opener-Policy"] = "same-origin"
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# response.headers["Cross-Origin-Embedder-Policy"] = "require-corp"
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# return response
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async def get_function_call_response(messages, tool_id, template, task_model_id, user):
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tool = Tools.get_tool_by_id(tool_id)
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tools_specs = json.dumps(tool.specs, indent=2)
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content = tools_function_calling_generation_template(template, tools_specs)
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user_message = get_last_user_message(messages)
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prompt = (
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"History:\n"
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+ "\n".join(
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[
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f"{message['role'].upper()}: \"\"\"{message['content']}\"\"\""
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for message in messages[::-1][:4]
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]
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)
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+ f"\nQuery: {user_message}"
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)
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print(prompt)
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payload = {
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"model": task_model_id,
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"messages": [
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{"role": "system", "content": content},
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{"role": "user", "content": f"Query: {prompt}"},
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],
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"stream": False,
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}
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try:
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payload = filter_pipeline(payload, user)
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except Exception as e:
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raise e
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model = app.state.MODELS[task_model_id]
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response = None
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try:
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if model["owned_by"] == "ollama":
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response = await generate_ollama_chat_completion(
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OpenAIChatCompletionForm(**payload), user=user
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)
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else:
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response = await generate_openai_chat_completion(payload, user=user)
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content = None
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if hasattr(response, "body_iterator"):
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async for chunk in response.body_iterator:
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data = json.loads(chunk.decode("utf-8"))
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content = data["choices"][0]["message"]["content"]
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# Cleanup any remaining background tasks if necessary
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if response.background is not None:
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await response.background()
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else:
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content = response["choices"][0]["message"]["content"]
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# Parse the function response
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if content is not None:
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print(f"content: {content}")
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result = json.loads(content)
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print(result)
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# Call the function
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if "name" in result:
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if tool_id in webui_app.state.TOOLS:
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toolkit_module = webui_app.state.TOOLS[tool_id]
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else:
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toolkit_module = load_toolkit_module_by_id(tool_id)
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webui_app.state.TOOLS[tool_id] = toolkit_module
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function = getattr(toolkit_module, result["name"])
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function_result = None
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try:
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# Get the signature of the function
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sig = inspect.signature(function)
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# Check if '__user__' is a parameter of the function
|
||||
if "__user__" in sig.parameters:
|
||||
# Call the function with the '__user__' parameter included
|
||||
function_result = function(
|
||||
**{
|
||||
**result["parameters"],
|
||||
"__user__": {
|
||||
"id": user.id,
|
||||
"email": user.email,
|
||||
"name": user.name,
|
||||
"role": user.role,
|
||||
},
|
||||
}
|
||||
)
|
||||
else:
|
||||
# Call the function without modifying the parameters
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||||
function_result = function(**result["parameters"])
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||||
except Exception as e:
|
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print(e)
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|
||||
# Add the function result to the system prompt
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if function_result:
|
||||
return function_result
|
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except Exception as e:
|
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print(f"Error: {e}")
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|
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return None
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||||
|
||||
|
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# app.add_middleware(SecurityHeadersMiddleware)
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|
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|
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class RAGMiddleware(BaseHTTPMiddleware):
|
||||
class ChatCompletionMiddleware(BaseHTTPMiddleware):
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async def dispatch(self, request: Request, call_next):
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return_citations = False
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@@ -171,35 +306,98 @@ class RAGMiddleware(BaseHTTPMiddleware):
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# Parse string to JSON
|
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data = json.loads(body_str) if body_str else {}
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|
||||
user = get_current_user(
|
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get_http_authorization_cred(request.headers.get("Authorization"))
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)
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|
||||
# Remove the citations from the body
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return_citations = data.get("citations", False)
|
||||
if "citations" in data:
|
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del data["citations"]
|
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|
||||
# Example: Add a new key-value pair or modify existing ones
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||||
# data["modified"] = True # Example modification
|
||||
# Set the task model
|
||||
task_model_id = data["model"]
|
||||
if task_model_id not in app.state.MODELS:
|
||||
raise HTTPException(
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||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="Model not found",
|
||||
)
|
||||
|
||||
# Check if the user has a custom task model
|
||||
# If the user has a custom task model, use that model
|
||||
if app.state.MODELS[task_model_id]["owned_by"] == "ollama":
|
||||
if (
|
||||
app.state.config.TASK_MODEL
|
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and app.state.config.TASK_MODEL in app.state.MODELS
|
||||
):
|
||||
task_model_id = app.state.config.TASK_MODEL
|
||||
else:
|
||||
if (
|
||||
app.state.config.TASK_MODEL_EXTERNAL
|
||||
and app.state.config.TASK_MODEL_EXTERNAL in app.state.MODELS
|
||||
):
|
||||
task_model_id = app.state.config.TASK_MODEL_EXTERNAL
|
||||
|
||||
prompt = get_last_user_message(data["messages"])
|
||||
context = ""
|
||||
|
||||
# If tool_ids field is present, call the functions
|
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if "tool_ids" in data:
|
||||
print(data["tool_ids"])
|
||||
for tool_id in data["tool_ids"]:
|
||||
print(tool_id)
|
||||
try:
|
||||
response = await get_function_call_response(
|
||||
messages=data["messages"],
|
||||
tool_id=tool_id,
|
||||
template=app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
|
||||
task_model_id=task_model_id,
|
||||
user=user,
|
||||
)
|
||||
|
||||
if response:
|
||||
context += ("\n" if context != "" else "") + response
|
||||
except Exception as e:
|
||||
print(f"Error: {e}")
|
||||
del data["tool_ids"]
|
||||
|
||||
print(f"tool_context: {context}")
|
||||
|
||||
# If docs field is present, generate RAG completions
|
||||
if "docs" in data:
|
||||
data = {**data}
|
||||
data["messages"], citations = rag_messages(
|
||||
rag_context, citations = get_rag_context(
|
||||
docs=data["docs"],
|
||||
messages=data["messages"],
|
||||
template=rag_app.state.config.RAG_TEMPLATE,
|
||||
embedding_function=rag_app.state.EMBEDDING_FUNCTION,
|
||||
k=rag_app.state.config.TOP_K,
|
||||
reranking_function=rag_app.state.sentence_transformer_rf,
|
||||
r=rag_app.state.config.RELEVANCE_THRESHOLD,
|
||||
hybrid_search=rag_app.state.config.ENABLE_RAG_HYBRID_SEARCH,
|
||||
)
|
||||
|
||||
if rag_context:
|
||||
context += ("\n" if context != "" else "") + rag_context
|
||||
|
||||
del data["docs"]
|
||||
|
||||
log.debug(
|
||||
f"data['messages']: {data['messages']}, citations: {citations}"
|
||||
log.debug(f"rag_context: {rag_context}, citations: {citations}")
|
||||
|
||||
if context != "":
|
||||
system_prompt = rag_template(
|
||||
rag_app.state.config.RAG_TEMPLATE, context, prompt
|
||||
)
|
||||
|
||||
print(system_prompt)
|
||||
|
||||
data["messages"] = add_or_update_system_message(
|
||||
f"\n{system_prompt}", data["messages"]
|
||||
)
|
||||
|
||||
modified_body_bytes = json.dumps(data).encode("utf-8")
|
||||
|
||||
# Replace the request body with the modified one
|
||||
request._body = modified_body_bytes
|
||||
|
||||
# Set custom header to ensure content-length matches new body length
|
||||
request.headers.__dict__["_list"] = [
|
||||
(b"content-length", str(len(modified_body_bytes)).encode("utf-8")),
|
||||
@@ -242,7 +440,80 @@ class RAGMiddleware(BaseHTTPMiddleware):
|
||||
yield data
|
||||
|
||||
|
||||
app.add_middleware(RAGMiddleware)
|
||||
app.add_middleware(ChatCompletionMiddleware)
|
||||
|
||||
|
||||
def filter_pipeline(payload, user):
|
||||
user = {"id": user.id, "name": user.name, "role": user.role}
|
||||
model_id = payload["model"]
|
||||
filters = [
|
||||
model
|
||||
for model in app.state.MODELS.values()
|
||||
if "pipeline" in model
|
||||
and "type" in model["pipeline"]
|
||||
and model["pipeline"]["type"] == "filter"
|
||||
and (
|
||||
model["pipeline"]["pipelines"] == ["*"]
|
||||
or any(
|
||||
model_id == target_model_id
|
||||
for target_model_id in model["pipeline"]["pipelines"]
|
||||
)
|
||||
)
|
||||
]
|
||||
sorted_filters = sorted(filters, key=lambda x: x["pipeline"]["priority"])
|
||||
|
||||
model = app.state.MODELS[model_id]
|
||||
|
||||
if "pipeline" in model:
|
||||
sorted_filters.append(model)
|
||||
|
||||
for filter in sorted_filters:
|
||||
r = None
|
||||
try:
|
||||
urlIdx = filter["urlIdx"]
|
||||
|
||||
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
||||
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
||||
|
||||
if key != "":
|
||||
headers = {"Authorization": f"Bearer {key}"}
|
||||
r = requests.post(
|
||||
f"{url}/{filter['id']}/filter/inlet",
|
||||
headers=headers,
|
||||
json={
|
||||
"user": user,
|
||||
"body": payload,
|
||||
},
|
||||
)
|
||||
|
||||
r.raise_for_status()
|
||||
payload = r.json()
|
||||
except Exception as e:
|
||||
# Handle connection error here
|
||||
print(f"Connection error: {e}")
|
||||
|
||||
if r is not None:
|
||||
try:
|
||||
res = r.json()
|
||||
except:
|
||||
pass
|
||||
if "detail" in res:
|
||||
raise Exception(r.status_code, res["detail"])
|
||||
|
||||
else:
|
||||
pass
|
||||
|
||||
if "pipeline" not in app.state.MODELS[model_id]:
|
||||
if "chat_id" in payload:
|
||||
del payload["chat_id"]
|
||||
|
||||
if "title" in payload:
|
||||
del payload["title"]
|
||||
|
||||
if "task" in payload:
|
||||
del payload["task"]
|
||||
|
||||
return payload
|
||||
|
||||
|
||||
class PipelineMiddleware(BaseHTTPMiddleware):
|
||||
@@ -260,85 +531,17 @@ class PipelineMiddleware(BaseHTTPMiddleware):
|
||||
# Parse string to JSON
|
||||
data = json.loads(body_str) if body_str else {}
|
||||
|
||||
model_id = data["model"]
|
||||
filters = [
|
||||
model
|
||||
for model in app.state.MODELS.values()
|
||||
if "pipeline" in model
|
||||
and "type" in model["pipeline"]
|
||||
and model["pipeline"]["type"] == "filter"
|
||||
and (
|
||||
model["pipeline"]["pipelines"] == ["*"]
|
||||
or any(
|
||||
model_id == target_model_id
|
||||
for target_model_id in model["pipeline"]["pipelines"]
|
||||
)
|
||||
user = get_current_user(
|
||||
get_http_authorization_cred(request.headers.get("Authorization"))
|
||||
)
|
||||
|
||||
try:
|
||||
data = filter_pipeline(data, user)
|
||||
except Exception as e:
|
||||
return JSONResponse(
|
||||
status_code=e.args[0],
|
||||
content={"detail": e.args[1]},
|
||||
)
|
||||
]
|
||||
sorted_filters = sorted(filters, key=lambda x: x["pipeline"]["priority"])
|
||||
|
||||
user = None
|
||||
if len(sorted_filters) > 0:
|
||||
try:
|
||||
user = get_current_user(
|
||||
get_http_authorization_cred(
|
||||
request.headers.get("Authorization")
|
||||
)
|
||||
)
|
||||
user = {"id": user.id, "name": user.name, "role": user.role}
|
||||
except:
|
||||
pass
|
||||
|
||||
model = app.state.MODELS[model_id]
|
||||
|
||||
if "pipeline" in model:
|
||||
sorted_filters.append(model)
|
||||
|
||||
for filter in sorted_filters:
|
||||
r = None
|
||||
try:
|
||||
urlIdx = filter["urlIdx"]
|
||||
|
||||
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
||||
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
||||
|
||||
if key != "":
|
||||
headers = {"Authorization": f"Bearer {key}"}
|
||||
r = requests.post(
|
||||
f"{url}/{filter['id']}/filter/inlet",
|
||||
headers=headers,
|
||||
json={
|
||||
"user": user,
|
||||
"body": data,
|
||||
},
|
||||
)
|
||||
|
||||
r.raise_for_status()
|
||||
data = r.json()
|
||||
except Exception as e:
|
||||
# Handle connection error here
|
||||
print(f"Connection error: {e}")
|
||||
|
||||
if r is not None:
|
||||
try:
|
||||
res = r.json()
|
||||
if "detail" in res:
|
||||
return JSONResponse(
|
||||
status_code=r.status_code,
|
||||
content=res,
|
||||
)
|
||||
except:
|
||||
pass
|
||||
|
||||
else:
|
||||
pass
|
||||
|
||||
if "pipeline" not in app.state.MODELS[model_id]:
|
||||
if "chat_id" in data:
|
||||
del data["chat_id"]
|
||||
|
||||
if "title" in data:
|
||||
del data["title"]
|
||||
|
||||
modified_body_bytes = json.dumps(data).encode("utf-8")
|
||||
# Replace the request body with the modified one
|
||||
@@ -499,6 +702,302 @@ async def get_models(user=Depends(get_verified_user)):
|
||||
return {"data": models}
|
||||
|
||||
|
||||
@app.get("/api/task/config")
|
||||
async def get_task_config(user=Depends(get_verified_user)):
|
||||
return {
|
||||
"TASK_MODEL": app.state.config.TASK_MODEL,
|
||||
"TASK_MODEL_EXTERNAL": app.state.config.TASK_MODEL_EXTERNAL,
|
||||
"TITLE_GENERATION_PROMPT_TEMPLATE": app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE,
|
||||
"SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE": app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE,
|
||||
"SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD": app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD,
|
||||
"TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE": app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
|
||||
}
|
||||
|
||||
|
||||
class TaskConfigForm(BaseModel):
|
||||
TASK_MODEL: Optional[str]
|
||||
TASK_MODEL_EXTERNAL: Optional[str]
|
||||
TITLE_GENERATION_PROMPT_TEMPLATE: str
|
||||
SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE: str
|
||||
SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD: int
|
||||
TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE: str
|
||||
|
||||
|
||||
@app.post("/api/task/config/update")
|
||||
async def update_task_config(form_data: TaskConfigForm, user=Depends(get_admin_user)):
|
||||
app.state.config.TASK_MODEL = form_data.TASK_MODEL
|
||||
app.state.config.TASK_MODEL_EXTERNAL = form_data.TASK_MODEL_EXTERNAL
|
||||
app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE = (
|
||||
form_data.TITLE_GENERATION_PROMPT_TEMPLATE
|
||||
)
|
||||
app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = (
|
||||
form_data.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE
|
||||
)
|
||||
app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD = (
|
||||
form_data.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD
|
||||
)
|
||||
app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = (
|
||||
form_data.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE
|
||||
)
|
||||
|
||||
return {
|
||||
"TASK_MODEL": app.state.config.TASK_MODEL,
|
||||
"TASK_MODEL_EXTERNAL": app.state.config.TASK_MODEL_EXTERNAL,
|
||||
"TITLE_GENERATION_PROMPT_TEMPLATE": app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE,
|
||||
"SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE": app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE,
|
||||
"SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD": app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD,
|
||||
"TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE": app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
|
||||
}
|
||||
|
||||
|
||||
@app.post("/api/task/title/completions")
|
||||
async def generate_title(form_data: dict, user=Depends(get_verified_user)):
|
||||
print("generate_title")
|
||||
|
||||
model_id = form_data["model"]
|
||||
if model_id not in app.state.MODELS:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="Model not found",
|
||||
)
|
||||
|
||||
# Check if the user has a custom task model
|
||||
# If the user has a custom task model, use that model
|
||||
if app.state.MODELS[model_id]["owned_by"] == "ollama":
|
||||
if app.state.config.TASK_MODEL:
|
||||
task_model_id = app.state.config.TASK_MODEL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
else:
|
||||
if app.state.config.TASK_MODEL_EXTERNAL:
|
||||
task_model_id = app.state.config.TASK_MODEL_EXTERNAL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
|
||||
print(model_id)
|
||||
model = app.state.MODELS[model_id]
|
||||
|
||||
template = app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE
|
||||
|
||||
content = title_generation_template(
|
||||
template, form_data["prompt"], user.model_dump()
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": model_id,
|
||||
"messages": [{"role": "user", "content": content}],
|
||||
"stream": False,
|
||||
"max_tokens": 50,
|
||||
"chat_id": form_data.get("chat_id", None),
|
||||
"title": True,
|
||||
}
|
||||
|
||||
print(payload)
|
||||
|
||||
try:
|
||||
payload = filter_pipeline(payload, user)
|
||||
except Exception as e:
|
||||
return JSONResponse(
|
||||
status_code=e.args[0],
|
||||
content={"detail": e.args[1]},
|
||||
)
|
||||
|
||||
if model["owned_by"] == "ollama":
|
||||
return await generate_ollama_chat_completion(
|
||||
OpenAIChatCompletionForm(**payload), user=user
|
||||
)
|
||||
else:
|
||||
return await generate_openai_chat_completion(payload, user=user)
|
||||
|
||||
|
||||
@app.post("/api/task/query/completions")
|
||||
async def generate_search_query(form_data: dict, user=Depends(get_verified_user)):
|
||||
print("generate_search_query")
|
||||
|
||||
if len(form_data["prompt"]) < app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_400_BAD_REQUEST,
|
||||
detail=f"Skip search query generation for short prompts (< {app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD} characters)",
|
||||
)
|
||||
|
||||
model_id = form_data["model"]
|
||||
if model_id not in app.state.MODELS:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="Model not found",
|
||||
)
|
||||
|
||||
# Check if the user has a custom task model
|
||||
# If the user has a custom task model, use that model
|
||||
if app.state.MODELS[model_id]["owned_by"] == "ollama":
|
||||
if app.state.config.TASK_MODEL:
|
||||
task_model_id = app.state.config.TASK_MODEL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
else:
|
||||
if app.state.config.TASK_MODEL_EXTERNAL:
|
||||
task_model_id = app.state.config.TASK_MODEL_EXTERNAL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
|
||||
print(model_id)
|
||||
model = app.state.MODELS[model_id]
|
||||
|
||||
template = app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE
|
||||
|
||||
content = search_query_generation_template(
|
||||
template, form_data["prompt"], user.model_dump()
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": model_id,
|
||||
"messages": [{"role": "user", "content": content}],
|
||||
"stream": False,
|
||||
"max_tokens": 30,
|
||||
"task": True,
|
||||
}
|
||||
|
||||
print(payload)
|
||||
|
||||
try:
|
||||
payload = filter_pipeline(payload, user)
|
||||
except Exception as e:
|
||||
return JSONResponse(
|
||||
status_code=e.args[0],
|
||||
content={"detail": e.args[1]},
|
||||
)
|
||||
|
||||
if model["owned_by"] == "ollama":
|
||||
return await generate_ollama_chat_completion(
|
||||
OpenAIChatCompletionForm(**payload), user=user
|
||||
)
|
||||
else:
|
||||
return await generate_openai_chat_completion(payload, user=user)
|
||||
|
||||
|
||||
@app.post("/api/task/emoji/completions")
|
||||
async def generate_emoji(form_data: dict, user=Depends(get_verified_user)):
|
||||
print("generate_emoji")
|
||||
|
||||
model_id = form_data["model"]
|
||||
if model_id not in app.state.MODELS:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="Model not found",
|
||||
)
|
||||
|
||||
# Check if the user has a custom task model
|
||||
# If the user has a custom task model, use that model
|
||||
if app.state.MODELS[model_id]["owned_by"] == "ollama":
|
||||
if app.state.config.TASK_MODEL:
|
||||
task_model_id = app.state.config.TASK_MODEL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
else:
|
||||
if app.state.config.TASK_MODEL_EXTERNAL:
|
||||
task_model_id = app.state.config.TASK_MODEL_EXTERNAL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
|
||||
print(model_id)
|
||||
model = app.state.MODELS[model_id]
|
||||
|
||||
template = '''
|
||||
Your task is to reflect the speaker's likely facial expression through a fitting emoji. Interpret emotions from the message and reflect their facial expression using fitting, diverse emojis (e.g., 😊, 😢, 😡, 😱).
|
||||
|
||||
Message: """{{prompt}}"""
|
||||
'''
|
||||
|
||||
content = title_generation_template(
|
||||
template, form_data["prompt"], user.model_dump()
|
||||
)
|
||||
|
||||
payload = {
|
||||
"model": model_id,
|
||||
"messages": [{"role": "user", "content": content}],
|
||||
"stream": False,
|
||||
"max_tokens": 4,
|
||||
"chat_id": form_data.get("chat_id", None),
|
||||
"task": True,
|
||||
}
|
||||
|
||||
print(payload)
|
||||
|
||||
try:
|
||||
payload = filter_pipeline(payload, user)
|
||||
except Exception as e:
|
||||
return JSONResponse(
|
||||
status_code=e.args[0],
|
||||
content={"detail": e.args[1]},
|
||||
)
|
||||
|
||||
if model["owned_by"] == "ollama":
|
||||
return await generate_ollama_chat_completion(
|
||||
OpenAIChatCompletionForm(**payload), user=user
|
||||
)
|
||||
else:
|
||||
return await generate_openai_chat_completion(payload, user=user)
|
||||
|
||||
|
||||
@app.post("/api/task/tools/completions")
|
||||
async def get_tools_function_calling(form_data: dict, user=Depends(get_verified_user)):
|
||||
print("get_tools_function_calling")
|
||||
|
||||
model_id = form_data["model"]
|
||||
if model_id not in app.state.MODELS:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="Model not found",
|
||||
)
|
||||
|
||||
# Check if the user has a custom task model
|
||||
# If the user has a custom task model, use that model
|
||||
if app.state.MODELS[model_id]["owned_by"] == "ollama":
|
||||
if app.state.config.TASK_MODEL:
|
||||
task_model_id = app.state.config.TASK_MODEL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
else:
|
||||
if app.state.config.TASK_MODEL_EXTERNAL:
|
||||
task_model_id = app.state.config.TASK_MODEL_EXTERNAL
|
||||
if task_model_id in app.state.MODELS:
|
||||
model_id = task_model_id
|
||||
|
||||
print(model_id)
|
||||
template = app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE
|
||||
|
||||
try:
|
||||
context = await get_function_call_response(
|
||||
form_data["messages"], form_data["tool_id"], template, model_id, user
|
||||
)
|
||||
return context
|
||||
except Exception as e:
|
||||
return JSONResponse(
|
||||
status_code=e.args[0],
|
||||
content={"detail": e.args[1]},
|
||||
)
|
||||
|
||||
|
||||
@app.post("/api/chat/completions")
|
||||
async def generate_chat_completions(form_data: dict, user=Depends(get_verified_user)):
|
||||
model_id = form_data["model"]
|
||||
if model_id not in app.state.MODELS:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="Model not found",
|
||||
)
|
||||
|
||||
model = app.state.MODELS[model_id]
|
||||
print(model)
|
||||
|
||||
if model["owned_by"] == "ollama":
|
||||
return await generate_ollama_chat_completion(
|
||||
OpenAIChatCompletionForm(**form_data), user=user
|
||||
)
|
||||
else:
|
||||
return await generate_openai_chat_completion(form_data, user=user)
|
||||
|
||||
|
||||
@app.post("/api/chat/completed")
|
||||
async def chat_completed(form_data: dict, user=Depends(get_verified_user)):
|
||||
data = form_data
|
||||
@@ -591,6 +1090,63 @@ async def get_pipelines_list(user=Depends(get_admin_user)):
|
||||
}
|
||||
|
||||
|
||||
@app.post("/api/pipelines/upload")
|
||||
async def upload_pipeline(
|
||||
urlIdx: int = Form(...), file: UploadFile = File(...), user=Depends(get_admin_user)
|
||||
):
|
||||
print("upload_pipeline", urlIdx, file.filename)
|
||||
# Check if the uploaded file is a python file
|
||||
if not file.filename.endswith(".py"):
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_400_BAD_REQUEST,
|
||||
detail="Only Python (.py) files are allowed.",
|
||||
)
|
||||
|
||||
upload_folder = f"{CACHE_DIR}/pipelines"
|
||||
os.makedirs(upload_folder, exist_ok=True)
|
||||
file_path = os.path.join(upload_folder, file.filename)
|
||||
|
||||
try:
|
||||
# Save the uploaded file
|
||||
with open(file_path, "wb") as buffer:
|
||||
shutil.copyfileobj(file.file, buffer)
|
||||
|
||||
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
|
||||
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
|
||||
|
||||
headers = {"Authorization": f"Bearer {key}"}
|
||||
|
||||
with open(file_path, "rb") as f:
|
||||
files = {"file": f}
|
||||
r = requests.post(f"{url}/pipelines/upload", headers=headers, files=files)
|
||||
|
||||
r.raise_for_status()
|
||||
data = r.json()
|
||||
|
||||
return {**data}
|
||||
except Exception as e:
|
||||
# Handle connection error here
|
||||
print(f"Connection error: {e}")
|
||||
|
||||
detail = "Pipeline not found"
|
||||
if r is not None:
|
||||
try:
|
||||
res = r.json()
|
||||
if "detail" in res:
|
||||
detail = res["detail"]
|
||||
except:
|
||||
pass
|
||||
|
||||
raise HTTPException(
|
||||
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
|
||||
detail=detail,
|
||||
)
|
||||
finally:
|
||||
# Ensure the file is deleted after the upload is completed or on failure
|
||||
if os.path.exists(file_path):
|
||||
os.remove(file_path)
|
||||
|
||||
|
||||
class AddPipelineForm(BaseModel):
|
||||
url: str
|
||||
urlIdx: int
|
||||
@@ -857,6 +1413,15 @@ async def get_app_config():
|
||||
"enable_community_sharing": webui_app.state.config.ENABLE_COMMUNITY_SHARING,
|
||||
"enable_admin_export": ENABLE_ADMIN_EXPORT,
|
||||
},
|
||||
"audio": {
|
||||
"tts": {
|
||||
"engine": audio_app.state.config.TTS_ENGINE,
|
||||
"voice": audio_app.state.config.TTS_VOICE,
|
||||
},
|
||||
"stt": {
|
||||
"engine": audio_app.state.config.STT_ENGINE,
|
||||
},
|
||||
},
|
||||
"oauth": {
|
||||
"providers": {
|
||||
name: config.get("name", name)
|
||||
@@ -925,7 +1490,7 @@ async def get_app_changelog():
|
||||
@app.get("/api/version/updates")
|
||||
async def get_app_latest_release_version():
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with aiohttp.ClientSession(trust_env=True) as session:
|
||||
async with session.get(
|
||||
"https://api.github.com/repos/open-webui/open-webui/releases/latest"
|
||||
) as response:
|
||||
|
||||
Reference in New Issue
Block a user