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import base64
import uuid
from contextlib import asynccontextmanager
from authlib.integrations.starlette_client import OAuth
from authlib.oidc.core import UserInfo
import json
import time
import os
import sys
import logging
import aiohttp
import requests
import mimetypes
import shutil
import inspect
from fastapi import FastAPI, Request, Depends, status, UploadFile, File, Form
from fastapi.staticfiles import StaticFiles
from fastapi.responses import JSONResponse
from fastapi import HTTPException
from fastapi.middleware.cors import CORSMiddleware
from sqlalchemy import text
from starlette.exceptions import HTTPException as StarletteHTTPException
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.middleware.sessions import SessionMiddleware
from starlette.responses import StreamingResponse, Response, RedirectResponse
from apps.socket.main import app as socket_app, get_event_emitter, get_event_call
from apps.ollama.main import (
app as ollama_app,
get_all_models as get_ollama_models,
generate_openai_chat_completion as generate_ollama_chat_completion,
)
from apps.openai.main import (
app as openai_app,
get_all_models as get_openai_models,
generate_chat_completion as generate_openai_chat_completion,
)
from apps.audio.main import app as audio_app
from apps.images.main import app as images_app
from apps.rag.main import app as rag_app
from apps.webui.main import (
app as webui_app,
get_pipe_models,
generate_function_chat_completion,
)
from apps.webui.internal.db import Session
from pydantic import BaseModel
from typing import Optional
from apps.webui.models.auths import Auths
from apps.webui.models.models import Models
from apps.webui.models.tools import Tools
from apps.webui.models.functions import Functions
from apps.webui.models.users import Users
from apps.webui.utils import load_toolkit_module_by_id, load_function_module_by_id
from utils.utils import (
get_admin_user,
get_verified_user,
get_current_user,
get_http_authorization_cred,
get_password_hash,
create_token,
)
from utils.task import (
title_generation_template,
search_query_generation_template,
tools_function_calling_generation_template,
)
from utils.misc import (
get_last_user_message,
add_or_update_system_message,
prepend_to_first_user_message_content,
parse_duration,
)
from apps.rag.utils import get_rag_context, rag_template
from config import (
WEBUI_NAME,
WEBUI_URL,
WEBUI_AUTH,
ENV,
VERSION,
CHANGELOG,
FRONTEND_BUILD_DIR,
CACHE_DIR,
STATIC_DIR,
DEFAULT_LOCALE,
ENABLE_OPENAI_API,
ENABLE_OLLAMA_API,
ENABLE_MODEL_FILTER,
MODEL_FILTER_LIST,
GLOBAL_LOG_LEVEL,
SRC_LOG_LEVELS,
WEBHOOK_URL,
ENABLE_ADMIN_EXPORT,
WEBUI_BUILD_HASH,
TASK_MODEL,
TASK_MODEL_EXTERNAL,
TITLE_GENERATION_PROMPT_TEMPLATE,
SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE,
SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD,
TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
SAFE_MODE,
OAUTH_PROVIDERS,
ENABLE_OAUTH_SIGNUP,
OAUTH_MERGE_ACCOUNTS_BY_EMAIL,
WEBUI_SECRET_KEY,
WEBUI_SESSION_COOKIE_SAME_SITE,
WEBUI_SESSION_COOKIE_SECURE,
ENABLE_ADMIN_CHAT_ACCESS,
AppConfig,
)
from constants import ERROR_MESSAGES, WEBHOOK_MESSAGES, TASKS
from utils.webhook import post_webhook
if SAFE_MODE:
print("SAFE MODE ENABLED")
Functions.deactivate_all_functions()
logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL)
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["MAIN"])
class SPAStaticFiles(StaticFiles):
async def get_response(self, path: str, scope):
try:
return await super().get_response(path, scope)
except (HTTPException, StarletteHTTPException) as ex:
if ex.status_code == 404:
return await super().get_response("index.html", scope)
else:
raise ex
print(
rf"""
___ __ __ _ _ _ ___
/ _ \ _ __ ___ _ __ \ \ / /__| |__ | | | |_ _|
| | | | '_ \ / _ \ '_ \ \ \ /\ / / _ \ '_ \| | | || |
| |_| | |_) | __/ | | | \ V V / __/ |_) | |_| || |
\___/| .__/ \___|_| |_| \_/\_/ \___|_.__/ \___/|___|
|_|
v{VERSION} - building the best open-source AI user interface.
{f"Commit: {WEBUI_BUILD_HASH}" if WEBUI_BUILD_HASH != "dev-build" else ""}
https://github.com/open-webui/open-webui
"""
)
def run_migrations():
try:
from alembic.config import Config
from alembic import command
alembic_cfg = Config("alembic.ini")
command.upgrade(alembic_cfg, "head")
except Exception as e:
print(f"Error: {e}")
@asynccontextmanager
async def lifespan(app: FastAPI):
run_migrations()
yield
app = FastAPI(
docs_url="/docs" if ENV == "dev" else None, redoc_url=None, lifespan=lifespan
)
app.state.config = AppConfig()
app.state.config.ENABLE_OPENAI_API = ENABLE_OPENAI_API
app.state.config.ENABLE_OLLAMA_API = ENABLE_OLLAMA_API
app.state.config.ENABLE_MODEL_FILTER = ENABLE_MODEL_FILTER
app.state.config.MODEL_FILTER_LIST = MODEL_FILTER_LIST
app.state.config.WEBHOOK_URL = WEBHOOK_URL
app.state.config.TASK_MODEL = TASK_MODEL
app.state.config.TASK_MODEL_EXTERNAL = TASK_MODEL_EXTERNAL
app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE = TITLE_GENERATION_PROMPT_TEMPLATE
app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE = (
SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE
)
app.state.config.SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD = (
SEARCH_QUERY_PROMPT_LENGTH_THRESHOLD
)
app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = (
TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE
)
app.state.MODELS = {}
origins = ["*"]
##################################
#
# ChatCompletion Middleware
#
##################################
async def get_body_and_model_and_user(request):
# Read the original request body
body = await request.body()
body_str = body.decode("utf-8")
body = json.loads(body_str) if body_str else {}
model_id = body["model"]
if model_id not in app.state.MODELS:
raise Exception("Model not found")
model = app.state.MODELS[model_id]
user = get_current_user(
request,
get_http_authorization_cred(request.headers.get("Authorization")),
)
return body, model, user
def get_task_model_id(default_model_id):
# Set the task model
task_model_id = default_model_id
# Check if the user has a custom task model and use that model
if app.state.MODELS[task_model_id]["owned_by"] == "ollama":
if (
app.state.config.TASK_MODEL
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
return task_model_id
def get_filter_function_ids(model):
def get_priority(function_id):
function = Functions.get_function_by_id(function_id)
if function is not None and hasattr(function, "valves"):
return (function.valves if function.valves else {}).get("priority", 0)
return 0
filter_ids = [function.id for function in Functions.get_global_filter_functions()]
if "info" in model and "meta" in model["info"]:
filter_ids.extend(model["info"]["meta"].get("filterIds", []))
filter_ids = list(set(filter_ids))
enabled_filter_ids = [
function.id
for function in Functions.get_functions_by_type("filter", active_only=True)
]
filter_ids = [
filter_id for filter_id in filter_ids if filter_id in enabled_filter_ids
]
filter_ids.sort(key=get_priority)
return filter_ids
async def get_function_call_response(
messages,
files,
tool_id,
template,
task_model_id,
user,
__event_emitter__=None,
__event_call__=None,
):
tool = Tools.get_tool_by_id(tool_id)
tools_specs = json.dumps(tool.specs, indent=2)
content = tools_function_calling_generation_template(template, tools_specs)
user_message = get_last_user_message(messages)
prompt = (
"History:\n"
+ "\n".join(
[
f"{message['role'].upper()}: \"\"\"{message['content']}\"\"\""
for message in messages[::-1][:4]
]
)
+ f"\nQuery: {user_message}"
)
print(prompt)
payload = {
"model": task_model_id,
"messages": [
{"role": "system", "content": content},
{"role": "user", "content": f"Query: {prompt}"},
],
"stream": False,
"task": str(TASKS.FUNCTION_CALLING),
}
try:
payload = filter_pipeline(payload, user)
except Exception as e:
raise e
model = app.state.MODELS[task_model_id]
response = None
try:
response = await generate_chat_completions(form_data=payload, user=user)
content = None
if hasattr(response, "body_iterator"):
async for chunk in response.body_iterator:
data = json.loads(chunk.decode("utf-8"))
content = data["choices"][0]["message"]["content"]
# Cleanup any remaining background tasks if necessary
if response.background is not None:
await response.background()
else:
content = response["choices"][0]["message"]["content"]
if content is None:
return None, None, False
# Parse the function response
print(f"content: {content}")
result = json.loads(content)
print(result)
citation = None
if "name" not in result:
return None, None, False
# Call the function
if tool_id in webui_app.state.TOOLS:
toolkit_module = webui_app.state.TOOLS[tool_id]
else:
toolkit_module, _ = load_toolkit_module_by_id(tool_id)
webui_app.state.TOOLS[tool_id] = toolkit_module
file_handler = False
# check if toolkit_module has file_handler self variable
if hasattr(toolkit_module, "file_handler"):
file_handler = True
print("file_handler: ", file_handler)
if hasattr(toolkit_module, "valves") and hasattr(toolkit_module, "Valves"):
valves = Tools.get_tool_valves_by_id(tool_id)
toolkit_module.valves = toolkit_module.Valves(**(valves if valves else {}))
function = getattr(toolkit_module, result["name"])
function_result = None
try:
# Get the signature of the function
sig = inspect.signature(function)
params = result["parameters"]
# Extra parameters to be passed to the function
extra_params = {
"__model__": model,
"__id__": tool_id,
"__messages__": messages,
"__files__": files,
"__event_emitter__": __event_emitter__,
"__event_call__": __event_call__,
}
# Add extra params in contained in function signature
for key, value in extra_params.items():
if key in sig.parameters:
params[key] = value
if "__user__" in sig.parameters:
# Call the function with the '__user__' parameter included
__user__ = {
"id": user.id,
"email": user.email,
"name": user.name,
"role": user.role,
}
try:
if hasattr(toolkit_module, "UserValves"):
__user__["valves"] = toolkit_module.UserValves(
**Tools.get_user_valves_by_id_and_user_id(tool_id, user.id)
)
except Exception as e:
print(e)
params = {**params, "__user__": __user__}
if inspect.iscoroutinefunction(function):
function_result = await function(**params)
else:
function_result = function(**params)
if hasattr(toolkit_module, "citation") and toolkit_module.citation:
citation = {
"source": {"name": f"TOOL:{tool.name}/{result['name']}"},
"document": [function_result],
"metadata": [{"source": result["name"]}],
}
except Exception as e:
print(e)
# Add the function result to the system prompt
if function_result is not None:
return function_result, citation, file_handler
except Exception as e:
print(f"Error: {e}")
return None, None, False
async def chat_completion_functions_handler(
body, model, user, __event_emitter__, __event_call__
):
skip_files = None
filter_ids = get_filter_function_ids(model)
for filter_id in filter_ids:
filter = Functions.get_function_by_id(filter_id)
if not filter:
continue
if filter_id in webui_app.state.FUNCTIONS:
function_module = webui_app.state.FUNCTIONS[filter_id]
else:
function_module, _, _ = load_function_module_by_id(filter_id)
webui_app.state.FUNCTIONS[filter_id] = function_module
# Check if the function has a file_handler variable
if hasattr(function_module, "file_handler"):
skip_files = function_module.file_handler
if hasattr(function_module, "valves") and hasattr(function_module, "Valves"):
valves = Functions.get_function_valves_by_id(filter_id)
function_module.valves = function_module.Valves(
**(valves if valves else {})
)
if not hasattr(function_module, "inlet"):
continue
try:
inlet = function_module.inlet
# Get the signature of the function
sig = inspect.signature(inlet)
params = {"body": body}
# Extra parameters to be passed to the function
extra_params = {
"__model__": model,
"__id__": filter_id,
"__event_emitter__": __event_emitter__,
"__event_call__": __event_call__,
}
# Add extra params in contained in function signature
for key, value in extra_params.items():
if key in sig.parameters:
params[key] = value
if "__user__" in sig.parameters:
__user__ = {
"id": user.id,
"email": user.email,
"name": user.name,
"role": user.role,
}
try:
if hasattr(function_module, "UserValves"):
__user__["valves"] = function_module.UserValves(
**Functions.get_user_valves_by_id_and_user_id(
filter_id, user.id
)
)
except Exception as e:
print(e)
params = {**params, "__user__": __user__}
if inspect.iscoroutinefunction(inlet):
body = await inlet(**params)
else:
body = inlet(**params)
except Exception as e:
print(f"Error: {e}")
raise e
if skip_files:
if "files" in body:
del body["files"]
return body, {}
async def chat_completion_tools_handler(body, user, __event_emitter__, __event_call__):
skip_files = None
contexts = []
citations = None
task_model_id = get_task_model_id(body["model"])
# If tool_ids field is present, call the functions
if "tool_ids" in body:
print(body["tool_ids"])
for tool_id in body["tool_ids"]:
print(tool_id)
try:
response, citation, file_handler = await get_function_call_response(
messages=body["messages"],
files=body.get("files", []),
tool_id=tool_id,
template=app.state.config.TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE,
task_model_id=task_model_id,
user=user,
__event_emitter__=__event_emitter__,
__event_call__=__event_call__,
)
print(file_handler)
if isinstance(response, str):
contexts.append(response)
if citation:
if citations is None:
citations = [citation]
else:
citations.append(citation)
if file_handler:
skip_files = True
except Exception as e:
print(f"Error: {e}")
del body["tool_ids"]
print(f"tool_contexts: {contexts}")
if skip_files:
if "files" in body:
del body["files"]
return body, {
**({"contexts": contexts} if contexts is not None else {}),
**({"citations": citations} if citations is not None else {}),
}
async def chat_completion_files_handler(body):
contexts = []
citations = None
if "files" in body:
files = body["files"]
del body["files"]
contexts, citations = get_rag_context(
files=files,
messages=body["messages"],
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,
)
log.debug(f"rag_contexts: {contexts}, citations: {citations}")
return body, {
**({"contexts": contexts} if contexts is not None else {}),
**({"citations": citations} if citations is not None else {}),
}
class ChatCompletionMiddleware(BaseHTTPMiddleware):
async def dispatch(self, request: Request, call_next):
if request.method == "POST" and any(
endpoint in request.url.path
for endpoint in ["/ollama/api/chat", "/chat/completions"]
):
log.debug(f"request.url.path: {request.url.path}")
try:
body, model, user = await get_body_and_model_and_user(request)
except Exception as e:
return JSONResponse(
status_code=status.HTTP_400_BAD_REQUEST,
content={"detail": str(e)},
)
metadata = {
"chat_id": body.pop("chat_id", None),
"message_id": body.pop("id", None),
"session_id": body.pop("session_id", None),
"valves": body.pop("valves", None),
}
__event_emitter__ = get_event_emitter(metadata)
__event_call__ = get_event_call(metadata)
# Initialize data_items to store additional data to be sent to the client
data_items = []
# Initialize context, and citations
contexts = []
citations = []
try:
body, flags = await chat_completion_functions_handler(
body, model, user, __event_emitter__, __event_call__
)
except Exception as e:
return JSONResponse(
status_code=status.HTTP_400_BAD_REQUEST,
content={"detail": str(e)},
)
try:
body, flags = await chat_completion_tools_handler(
body, user, __event_emitter__, __event_call__
)
contexts.extend(flags.get("contexts", []))
citations.extend(flags.get("citations", []))
except Exception as e:
print(e)
pass
try:
body, flags = await chat_completion_files_handler(body)
contexts.extend(flags.get("contexts", []))
citations.extend(flags.get("citations", []))
except Exception as e:
print(e)
pass
# If context is not empty, insert it into the messages
if len(contexts) > 0:
context_string = "/n".join(contexts).strip()
prompt = get_last_user_message(body["messages"])
# Workaround for Ollama 2.0+ system prompt issue
# TODO: replace with add_or_update_system_message
if model["owned_by"] == "ollama":
body["messages"] = prepend_to_first_user_message_content(
rag_template(
rag_app.state.config.RAG_TEMPLATE, context_string, prompt
),
body["messages"],
)
else:
body["messages"] = add_or_update_system_message(
rag_template(
rag_app.state.config.RAG_TEMPLATE, context_string, prompt
),
body["messages"],
)
# If there are citations, add them to the data_items
if len(citations) > 0:
data_items.append({"citations": citations})
body["metadata"] = metadata
modified_body_bytes = json.dumps(body).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")),
*[
(k, v)
for k, v in request.headers.raw
if k.lower() != b"content-length"
],
]
response = await call_next(request)
if isinstance(response, StreamingResponse):
# If it's a streaming response, inject it as SSE event or NDJSON line
content_type = response.headers.get("Content-Type")
if "text/event-stream" in content_type:
return StreamingResponse(
self.openai_stream_wrapper(response.body_iterator, data_items),
)
if "application/x-ndjson" in content_type:
return StreamingResponse(
self.ollama_stream_wrapper(response.body_iterator, data_items),
)
return response
else:
return response
# If it's not a chat completion request, just pass it through
response = await call_next(request)
return response
async def _receive(self, body: bytes):
return {"type": "http.request", "body": body, "more_body": False}
async def openai_stream_wrapper(self, original_generator, data_items):
for item in data_items:
yield f"data: {json.dumps(item)}\n\n"
async for data in original_generator:
yield data
async def ollama_stream_wrapper(self, original_generator, data_items):
for item in data_items:
yield f"{json.dumps(item)}\n"
async for data in original_generator:
yield data
app.add_middleware(ChatCompletionMiddleware)
##################################
#
# Pipeline Middleware
#
##################################
def get_sorted_filters(model_id):
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"])
return sorted_filters
def filter_pipeline(payload, user):
user = {"id": user.id, "email": user.email, "name": user.name, "role": user.role}
model_id = payload["model"]
sorted_filters = get_sorted_filters(model_id)
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:
res = r.json()
if "detail" in res:
raise Exception(r.status_code, res["detail"])
return payload
class PipelineMiddleware(BaseHTTPMiddleware):
async def dispatch(self, request: Request, call_next):
if request.method == "POST" and (
"/ollama/api/chat" in request.url.path
or "/chat/completions" in request.url.path
):
log.debug(f"request.url.path: {request.url.path}")
# Read the original request body
body = await request.body()
# Decode body to string
body_str = body.decode("utf-8")
# Parse string to JSON
data = json.loads(body_str) if body_str else {}
user = get_current_user(
request,
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]},
)
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")),
*[
(k, v)
for k, v in request.headers.raw
if k.lower() != b"content-length"
],
]
response = await call_next(request)
return response
async def _receive(self, body: bytes):
return {"type": "http.request", "body": body, "more_body": False}
app.add_middleware(PipelineMiddleware)
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.middleware("http")
async def commit_session_after_request(request: Request, call_next):
response = await call_next(request)
log.debug("Commit session after request")
Session.commit()
return response
@app.middleware("http")
async def check_url(request: Request, call_next):
if len(app.state.MODELS) == 0:
await get_all_models()
else:
pass
start_time = int(time.time())
response = await call_next(request)
process_time = int(time.time()) - start_time
response.headers["X-Process-Time"] = str(process_time)
return response
@app.middleware("http")
async def update_embedding_function(request: Request, call_next):
response = await call_next(request)
if "/embedding/update" in request.url.path:
webui_app.state.EMBEDDING_FUNCTION = rag_app.state.EMBEDDING_FUNCTION
return response
app.mount("/ws", socket_app)
app.mount("/ollama", ollama_app)
app.mount("/openai", openai_app)
app.mount("/images/api/v1", images_app)
app.mount("/audio/api/v1", audio_app)
app.mount("/rag/api/v1", rag_app)
app.mount("/api/v1", webui_app)
webui_app.state.EMBEDDING_FUNCTION = rag_app.state.EMBEDDING_FUNCTION
async def get_all_models():
# TODO: Optimize this function
pipe_models = []
openai_models = []
ollama_models = []
pipe_models = await get_pipe_models()
if app.state.config.ENABLE_OPENAI_API:
openai_models = await get_openai_models()
openai_models = openai_models["data"]
if app.state.config.ENABLE_OLLAMA_API:
ollama_models = await get_ollama_models()
ollama_models = [
{
"id": model["model"],
"name": model["name"],
"object": "model",
"created": int(time.time()),
"owned_by": "ollama",
"ollama": model,
}
for model in ollama_models["models"]
]
models = pipe_models + openai_models + ollama_models
global_action_ids = [
function.id for function in Functions.get_global_action_functions()
]
enabled_action_ids = [
function.id
for function in Functions.get_functions_by_type("action", active_only=True)
]
custom_models = Models.get_all_models()
for custom_model in custom_models:
if custom_model.base_model_id is None:
for model in models:
if (
custom_model.id == model["id"]
or custom_model.id == model["id"].split(":")[0]
):
model["name"] = custom_model.name
model["info"] = custom_model.model_dump()
action_ids = []
if "info" in model and "meta" in model["info"]:
action_ids.extend(model["info"]["meta"].get("actionIds", []))
model["action_ids"] = action_ids
else:
owned_by = "openai"
pipe = None
action_ids = []
for model in models:
if (
custom_model.base_model_id == model["id"]
or custom_model.base_model_id == model["id"].split(":")[0]
):
owned_by = model["owned_by"]
if "pipe" in model:
pipe = model["pipe"]
if "info" in model and "meta" in model["info"]:
action_ids.extend(model["info"]["meta"].get("actionIds", []))
break
models.append(
{
"id": custom_model.id,
"name": custom_model.name,
"object": "model",
"created": custom_model.created_at,
"owned_by": owned_by,
"info": custom_model.model_dump(),
"preset": True,
**({"pipe": pipe} if pipe is not None else {}),
"action_ids": action_ids,
}
)
for model in models:
action_ids = []
if "action_ids" in model:
action_ids = model["action_ids"]
del model["action_ids"]
action_ids = action_ids + global_action_ids
action_ids = list(set(action_ids))
action_ids = [
action_id for action_id in action_ids if action_id in enabled_action_ids
]
model["actions"] = []
for action_id in action_ids:
action = Functions.get_function_by_id(action_id)
if action_id in webui_app.state.FUNCTIONS:
function_module = webui_app.state.FUNCTIONS[action_id]
else:
function_module, _, _ = load_function_module_by_id(action_id)
webui_app.state.FUNCTIONS[action_id] = function_module
__webui__ = False
if hasattr(function_module, "__webui__"):
__webui__ = function_module.__webui__
if hasattr(function_module, "actions"):
actions = function_module.actions
model["actions"].extend(
[
{
"id": f"{action_id}.{_action['id']}",
"name": _action.get(
"name", f"{action.name} ({_action['id']})"
),
"description": action.meta.description,
"icon_url": _action.get(
"icon_url", action.meta.manifest.get("icon_url", None)
),
**({"__webui__": __webui__} if __webui__ else {}),
}
for _action in actions
]
)
else:
model["actions"].append(
{
"id": action_id,
"name": action.name,
"description": action.meta.description,
"icon_url": action.meta.manifest.get("icon_url", None),
**({"__webui__": __webui__} if __webui__ else {}),
}
)
app.state.MODELS = {model["id"]: model for model in models}
webui_app.state.MODELS = app.state.MODELS
return models
@app.get("/api/models")
async def get_models(user=Depends(get_verified_user)):
models = await get_all_models()
# Filter out filter pipelines
models = [
model
for model in models
if "pipeline" not in model or model["pipeline"].get("type", None) != "filter"
]
if app.state.config.ENABLE_MODEL_FILTER:
if user.role == "user":
models = list(
filter(
lambda model: model["id"] in app.state.config.MODEL_FILTER_LIST,
models,
)
)
return {"data": models}
return {"data": models}
@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]
# `task` field is used to determine the type of the request, e.g. `title_generation`, `query_generation`, etc.
task = None
if "task" in form_data:
task = form_data["task"]
del form_data["task"]
if task:
if "metadata" in form_data:
form_data["metadata"]["task"] = task
else:
form_data["metadata"] = {"task": task}
if model.get("pipe"):
return await generate_function_chat_completion(form_data, user=user)
if model["owned_by"] == "ollama":
print("generate_ollama_chat_completion")
return await generate_ollama_chat_completion(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
model_id = 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]
sorted_filters = get_sorted_filters(model_id)
if "pipeline" in model:
sorted_filters = [model] + sorted_filters
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/outlet",
headers=headers,
json={
"user": {
"id": user.id,
"name": user.name,
"email": user.email,
"role": user.role,
},
"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 Exception:
pass
else:
pass
__event_emitter__ = get_event_emitter(
{
"chat_id": data["chat_id"],
"message_id": data["id"],
"session_id": data["session_id"],
}
)
__event_call__ = get_event_call(
{
"chat_id": data["chat_id"],
"message_id": data["id"],
"session_id": data["session_id"],
}
)
def get_priority(function_id):
function = Functions.get_function_by_id(function_id)
if function is not None and hasattr(function, "valves"):
return (function.valves if function.valves else {}).get("priority", 0)
return 0
filter_ids = [function.id for function in Functions.get_global_filter_functions()]
if "info" in model and "meta" in model["info"]:
filter_ids.extend(model["info"]["meta"].get("filterIds", []))
filter_ids = list(set(filter_ids))
enabled_filter_ids = [
function.id
for function in Functions.get_functions_by_type("filter", active_only=True)
]
filter_ids = [
filter_id for filter_id in filter_ids if filter_id in enabled_filter_ids
]
# Sort filter_ids by priority, using the get_priority function
filter_ids.sort(key=get_priority)
for filter_id in filter_ids:
filter = Functions.get_function_by_id(filter_id)
if not filter:
continue
if filter_id in webui_app.state.FUNCTIONS:
function_module = webui_app.state.FUNCTIONS[filter_id]
else:
function_module, _, _ = load_function_module_by_id(filter_id)
webui_app.state.FUNCTIONS[filter_id] = function_module
if hasattr(function_module, "valves") and hasattr(function_module, "Valves"):
valves = Functions.get_function_valves_by_id(filter_id)
function_module.valves = function_module.Valves(
**(valves if valves else {})
)
if not hasattr(function_module, "outlet"):
continue
try:
outlet = function_module.outlet
# Get the signature of the function
sig = inspect.signature(outlet)
params = {"body": data}
# Extra parameters to be passed to the function
extra_params = {
"__model__": model,
"__id__": filter_id,
"__event_emitter__": __event_emitter__,
"__event_call__": __event_call__,
}
# Add extra params in contained in function signature
for key, value in extra_params.items():
if key in sig.parameters:
params[key] = value
if "__user__" in sig.parameters:
__user__ = {
"id": user.id,
"email": user.email,
"name": user.name,
"role": user.role,
}
try:
if hasattr(function_module, "UserValves"):
__user__["valves"] = function_module.UserValves(
**Functions.get_user_valves_by_id_and_user_id(
filter_id, user.id
)
)
except Exception as e:
print(e)
params = {**params, "__user__": __user__}
if inspect.iscoroutinefunction(outlet):
data = await outlet(**params)
else:
data = outlet(**params)
except Exception as e:
print(f"Error: {e}")
return JSONResponse(
status_code=status.HTTP_400_BAD_REQUEST,
content={"detail": str(e)},
)
return data
@app.post("/api/chat/actions/{action_id}")
async def chat_action(action_id: str, form_data: dict, user=Depends(get_verified_user)):
if "." in action_id:
action_id, sub_action_id = action_id.split(".")
else:
sub_action_id = None
action = Functions.get_function_by_id(action_id)
if not action:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Action not found",
)
data = form_data
model_id = 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]
__event_emitter__ = get_event_emitter(
{
"chat_id": data["chat_id"],
"message_id": data["id"],
"session_id": data["session_id"],
}
)
__event_call__ = get_event_call(
{
"chat_id": data["chat_id"],
"message_id": data["id"],
"session_id": data["session_id"],
}
)
if action_id in webui_app.state.FUNCTIONS:
function_module = webui_app.state.FUNCTIONS[action_id]
else:
function_module, _, _ = load_function_module_by_id(action_id)
webui_app.state.FUNCTIONS[action_id] = function_module
if hasattr(function_module, "valves") and hasattr(function_module, "Valves"):
valves = Functions.get_function_valves_by_id(action_id)
function_module.valves = function_module.Valves(**(valves if valves else {}))
if hasattr(function_module, "action"):
try:
action = function_module.action
# Get the signature of the function
sig = inspect.signature(action)
params = {"body": data}
# Extra parameters to be passed to the function
extra_params = {
"__model__": model,
"__id__": sub_action_id if sub_action_id is not None else action_id,
"__event_emitter__": __event_emitter__,
"__event_call__": __event_call__,
}
# Add extra params in contained in function signature
for key, value in extra_params.items():
if key in sig.parameters:
params[key] = value
if "__user__" in sig.parameters:
__user__ = {
"id": user.id,
"email": user.email,
"name": user.name,
"role": user.role,
}
try:
if hasattr(function_module, "UserValves"):
__user__["valves"] = function_module.UserValves(
**Functions.get_user_valves_by_id_and_user_id(
action_id, user.id
)
)
except Exception as e:
print(e)
params = {**params, "__user__": __user__}
if inspect.iscoroutinefunction(action):
data = await action(**params)
else:
data = action(**params)
except Exception as e:
print(f"Error: {e}")
return JSONResponse(
status_code=status.HTTP_400_BAD_REQUEST,
content={"detail": str(e)},
)
return data
##################################
#
# Task Endpoints
#
##################################
# TODO: Refactor task API endpoints below into a separate file
@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
model_id = get_task_model_id(model_id)
print(model_id)
template = app.state.config.TITLE_GENERATION_PROMPT_TEMPLATE
content = title_generation_template(
template,
form_data["prompt"],
{
"name": user.name,
"location": user.info.get("location") if user.info else None,
},
)
payload = {
"model": model_id,
"messages": [{"role": "user", "content": content}],
"stream": False,
"max_tokens": 50,
"chat_id": form_data.get("chat_id", None),
"task": str(TASKS.TITLE_GENERATION),
}
log.debug(payload)
try:
payload = filter_pipeline(payload, user)
except Exception as e:
return JSONResponse(
status_code=e.args[0],
content={"detail": e.args[1]},
)
if "chat_id" in payload:
del payload["chat_id"]
return await generate_chat_completions(form_data=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
model_id = get_task_model_id(model_id)
print(model_id)
template = app.state.config.SEARCH_QUERY_GENERATION_PROMPT_TEMPLATE
content = search_query_generation_template(
template, form_data["prompt"], {"name": user.name}
)
payload = {
"model": model_id,
"messages": [{"role": "user", "content": content}],
"stream": False,
"max_tokens": 30,
"task": str(TASKS.QUERY_GENERATION),
}
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 "chat_id" in payload:
del payload["chat_id"]
return await generate_chat_completions(form_data=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
model_id = get_task_model_id(model_id)
print(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"],
{
"name": user.name,
"location": user.info.get("location") if user.info else None,
},
)
payload = {
"model": model_id,
"messages": [{"role": "user", "content": content}],
"stream": False,
"max_tokens": 4,
"chat_id": form_data.get("chat_id", None),
"task": str(TASKS.EMOJI_GENERATION),
}
log.debug(payload)
try:
payload = filter_pipeline(payload, user)
except Exception as e:
return JSONResponse(
status_code=e.args[0],
content={"detail": e.args[1]},
)
if "chat_id" in payload:
del payload["chat_id"]
return await generate_chat_completions(form_data=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
model_id = get_task_model_id(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.get("files", []),
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]},
)
##################################
#
# Pipelines Endpoints
#
##################################
# TODO: Refactor pipelines API endpoints below into a separate file
@app.get("/api/pipelines/list")
async def get_pipelines_list(user=Depends(get_admin_user)):
responses = await get_openai_models(raw=True)
print(responses)
urlIdxs = [
idx
for idx, response in enumerate(responses)
if response is not None and "pipelines" in response
]
return {
"data": [
{
"url": openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx],
"idx": urlIdx,
}
for urlIdx in urlIdxs
]
}
@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)
r = None
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"
status_code = status.HTTP_404_NOT_FOUND
if r is not None:
status_code = r.status_code
try:
res = r.json()
if "detail" in res:
detail = res["detail"]
except Exception:
pass
raise HTTPException(
status_code=status_code,
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
@app.post("/api/pipelines/add")
async def add_pipeline(form_data: AddPipelineForm, user=Depends(get_admin_user)):
r = None
try:
urlIdx = form_data.urlIdx
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
headers = {"Authorization": f"Bearer {key}"}
r = requests.post(
f"{url}/pipelines/add", headers=headers, json={"url": form_data.url}
)
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 Exception:
pass
raise HTTPException(
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
detail=detail,
)
class DeletePipelineForm(BaseModel):
id: str
urlIdx: int
@app.delete("/api/pipelines/delete")
async def delete_pipeline(form_data: DeletePipelineForm, user=Depends(get_admin_user)):
r = None
try:
urlIdx = form_data.urlIdx
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
headers = {"Authorization": f"Bearer {key}"}
r = requests.delete(
f"{url}/pipelines/delete", headers=headers, json={"id": form_data.id}
)
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 Exception:
pass
raise HTTPException(
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
detail=detail,
)
@app.get("/api/pipelines")
async def get_pipelines(urlIdx: Optional[int] = None, user=Depends(get_admin_user)):
r = None
try:
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
headers = {"Authorization": f"Bearer {key}"}
r = requests.get(f"{url}/pipelines", headers=headers)
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 Exception:
pass
raise HTTPException(
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
detail=detail,
)
@app.get("/api/pipelines/{pipeline_id}/valves")
async def get_pipeline_valves(
urlIdx: Optional[int],
pipeline_id: str,
user=Depends(get_admin_user),
):
r = None
try:
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
headers = {"Authorization": f"Bearer {key}"}
r = requests.get(f"{url}/{pipeline_id}/valves", headers=headers)
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 Exception:
pass
raise HTTPException(
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
detail=detail,
)
@app.get("/api/pipelines/{pipeline_id}/valves/spec")
async def get_pipeline_valves_spec(
urlIdx: Optional[int],
pipeline_id: str,
user=Depends(get_admin_user),
):
r = None
try:
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
headers = {"Authorization": f"Bearer {key}"}
r = requests.get(f"{url}/{pipeline_id}/valves/spec", headers=headers)
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 Exception:
pass
raise HTTPException(
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
detail=detail,
)
@app.post("/api/pipelines/{pipeline_id}/valves/update")
async def update_pipeline_valves(
urlIdx: Optional[int],
pipeline_id: str,
form_data: dict,
user=Depends(get_admin_user),
):
r = None
try:
url = openai_app.state.config.OPENAI_API_BASE_URLS[urlIdx]
key = openai_app.state.config.OPENAI_API_KEYS[urlIdx]
headers = {"Authorization": f"Bearer {key}"}
r = requests.post(
f"{url}/{pipeline_id}/valves/update",
headers=headers,
json={**form_data},
)
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 Exception:
pass
raise HTTPException(
status_code=(r.status_code if r is not None else status.HTTP_404_NOT_FOUND),
detail=detail,
)
##################################
#
# Config Endpoints
#
##################################
@app.get("/api/config")
async def get_app_config():
return {
"status": True,
"name": WEBUI_NAME,
"version": VERSION,
"default_locale": str(DEFAULT_LOCALE),
"default_models": webui_app.state.config.DEFAULT_MODELS,
"default_prompt_suggestions": webui_app.state.config.DEFAULT_PROMPT_SUGGESTIONS,
"features": {
"auth": WEBUI_AUTH,
"auth_trusted_header": bool(webui_app.state.AUTH_TRUSTED_EMAIL_HEADER),
"enable_signup": webui_app.state.config.ENABLE_SIGNUP,
"enable_login_form": webui_app.state.config.ENABLE_LOGIN_FORM,
"enable_web_search": rag_app.state.config.ENABLE_RAG_WEB_SEARCH,
"enable_image_generation": images_app.state.config.ENABLED,
"enable_community_sharing": webui_app.state.config.ENABLE_COMMUNITY_SHARING,
"enable_admin_export": ENABLE_ADMIN_EXPORT,
"enable_admin_chat_access": ENABLE_ADMIN_CHAT_ACCESS,
},
"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)
for name, config in OAUTH_PROVIDERS.items()
}
},
}
@app.get("/api/config/model/filter")
async def get_model_filter_config(user=Depends(get_admin_user)):
return {
"enabled": app.state.config.ENABLE_MODEL_FILTER,
"models": app.state.config.MODEL_FILTER_LIST,
}
class ModelFilterConfigForm(BaseModel):
enabled: bool
models: list[str]
@app.post("/api/config/model/filter")
async def update_model_filter_config(
form_data: ModelFilterConfigForm, user=Depends(get_admin_user)
):
app.state.config.ENABLE_MODEL_FILTER = form_data.enabled
app.state.config.MODEL_FILTER_LIST = form_data.models
return {
"enabled": app.state.config.ENABLE_MODEL_FILTER,
"models": app.state.config.MODEL_FILTER_LIST,
}
# TODO: webhook endpoint should be under config endpoints
@app.get("/api/webhook")
async def get_webhook_url(user=Depends(get_admin_user)):
return {
"url": app.state.config.WEBHOOK_URL,
}
class UrlForm(BaseModel):
url: str
@app.post("/api/webhook")
async def update_webhook_url(form_data: UrlForm, user=Depends(get_admin_user)):
app.state.config.WEBHOOK_URL = form_data.url
webui_app.state.WEBHOOK_URL = app.state.config.WEBHOOK_URL
return {"url": app.state.config.WEBHOOK_URL}
@app.get("/api/version")
async def get_app_version():
return {
"version": VERSION,
}
@app.get("/api/changelog")
async def get_app_changelog():
return {key: CHANGELOG[key] for idx, key in enumerate(CHANGELOG) if idx < 5}
@app.get("/api/version/updates")
async def get_app_latest_release_version():
try:
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:
response.raise_for_status()
data = await response.json()
latest_version = data["tag_name"]
return {"current": VERSION, "latest": latest_version[1:]}
except aiohttp.ClientError:
raise HTTPException(
status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
detail=ERROR_MESSAGES.RATE_LIMIT_EXCEEDED,
)
############################
# OAuth Login & Callback
############################
oauth = OAuth()
for provider_name, provider_config in OAUTH_PROVIDERS.items():
oauth.register(
name=provider_name,
client_id=provider_config["client_id"],
client_secret=provider_config["client_secret"],
server_metadata_url=provider_config["server_metadata_url"],
client_kwargs={
"scope": provider_config["scope"],
},
redirect_uri=provider_config["redirect_uri"],
)
# SessionMiddleware is used by authlib for oauth
if len(OAUTH_PROVIDERS) > 0:
app.add_middleware(
SessionMiddleware,
secret_key=WEBUI_SECRET_KEY,
session_cookie="oui-session",
same_site=WEBUI_SESSION_COOKIE_SAME_SITE,
https_only=WEBUI_SESSION_COOKIE_SECURE,
)
@app.get("/oauth/{provider}/login")
async def oauth_login(provider: str, request: Request):
if provider not in OAUTH_PROVIDERS:
raise HTTPException(404)
# If the provider has a custom redirect URL, use that, otherwise automatically generate one
redirect_uri = OAUTH_PROVIDERS[provider].get("redirect_uri") or request.url_for(
"oauth_callback", provider=provider
)
return await oauth.create_client(provider).authorize_redirect(request, redirect_uri)
# OAuth login logic is as follows:
# 1. Attempt to find a user with matching subject ID, tied to the provider
# 2. If OAUTH_MERGE_ACCOUNTS_BY_EMAIL is true, find a user with the email address provided via OAuth
# - This is considered insecure in general, as OAuth providers do not always verify email addresses
# 3. If there is no user, and ENABLE_OAUTH_SIGNUP is true, create a user
# - Email addresses are considered unique, so we fail registration if the email address is alreayd taken
@app.get("/oauth/{provider}/callback")
async def oauth_callback(provider: str, request: Request, response: Response):
if provider not in OAUTH_PROVIDERS:
raise HTTPException(404)
client = oauth.create_client(provider)
try:
token = await client.authorize_access_token(request)
except Exception as e:
log.warning(f"OAuth callback error: {e}")
raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED)
user_data: UserInfo = token["userinfo"]
sub = user_data.get("sub")
if not sub:
log.warning(f"OAuth callback failed, sub is missing: {user_data}")
raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED)
provider_sub = f"{provider}@{sub}"
email_claim = webui_app.state.config.OAUTH_EMAIL_CLAIM
email = user_data.get(email_claim, "").lower()
# We currently mandate that email addresses are provided
if not email:
log.warning(f"OAuth callback failed, email is missing: {user_data}")
raise HTTPException(400, detail=ERROR_MESSAGES.INVALID_CRED)
# Check if the user exists
user = Users.get_user_by_oauth_sub(provider_sub)
if not user:
# If the user does not exist, check if merging is enabled
if OAUTH_MERGE_ACCOUNTS_BY_EMAIL.value:
# Check if the user exists by email
user = Users.get_user_by_email(email)
if user:
# Update the user with the new oauth sub
Users.update_user_oauth_sub_by_id(user.id, provider_sub)
if not user:
# If the user does not exist, check if signups are enabled
if ENABLE_OAUTH_SIGNUP.value:
# Check if an existing user with the same email already exists
existing_user = Users.get_user_by_email(user_data.get("email", "").lower())
if existing_user:
raise HTTPException(400, detail=ERROR_MESSAGES.EMAIL_TAKEN)
picture_claim = webui_app.state.config.OAUTH_PICTURE_CLAIM
picture_url = user_data.get(picture_claim, "")
if picture_url:
# Download the profile image into a base64 string
try:
async with aiohttp.ClientSession() as session:
async with session.get(picture_url) as resp:
picture = await resp.read()
base64_encoded_picture = base64.b64encode(picture).decode(
"utf-8"
)
guessed_mime_type = mimetypes.guess_type(picture_url)[0]
if guessed_mime_type is None:
# assume JPG, browsers are tolerant enough of image formats
guessed_mime_type = "image/jpeg"
picture_url = f"data:{guessed_mime_type};base64,{base64_encoded_picture}"
except Exception as e:
log.error(f"Error downloading profile image '{picture_url}': {e}")
picture_url = ""
if not picture_url:
picture_url = "/user.png"
username_claim = webui_app.state.config.OAUTH_USERNAME_CLAIM
role = (
"admin"
if Users.get_num_users() == 0
else webui_app.state.config.DEFAULT_USER_ROLE
)
user = Auths.insert_new_auth(
email=email,
password=get_password_hash(
str(uuid.uuid4())
), # Random password, not used
name=user_data.get(username_claim, "User"),
profile_image_url=picture_url,
role=role,
oauth_sub=provider_sub,
)
if webui_app.state.config.WEBHOOK_URL:
post_webhook(
webui_app.state.config.WEBHOOK_URL,
WEBHOOK_MESSAGES.USER_SIGNUP(user.name),
{
"action": "signup",
"message": WEBHOOK_MESSAGES.USER_SIGNUP(user.name),
"user": user.model_dump_json(exclude_none=True),
},
)
else:
raise HTTPException(
status.HTTP_403_FORBIDDEN, detail=ERROR_MESSAGES.ACCESS_PROHIBITED
)
jwt_token = create_token(
data={"id": user.id},
expires_delta=parse_duration(webui_app.state.config.JWT_EXPIRES_IN),
)
# Set the cookie token
response.set_cookie(
key="token",
value=jwt_token,
httponly=True, # Ensures the cookie is not accessible via JavaScript
)
# Redirect back to the frontend with the JWT token
redirect_url = f"{request.base_url}auth#token={jwt_token}"
return RedirectResponse(url=redirect_url)
@app.get("/manifest.json")
async def get_manifest_json():
return {
"name": WEBUI_NAME,
"short_name": WEBUI_NAME,
"start_url": "/",
"display": "standalone",
"background_color": "#343541",
"orientation": "portrait-primary",
"icons": [
{
"src": "/static/logo.png",
"type": "image/png",
"sizes": "500x500",
"purpose": "any",
},
{
"src": "/static/logo.png",
"type": "image/png",
"sizes": "500x500",
"purpose": "maskable",
},
],
}
@app.get("/opensearch.xml")
async def get_opensearch_xml():
xml_content = rf"""
<OpenSearchDescription xmlns="http://a9.com/-/spec/opensearch/1.1/" xmlns:moz="http://www.mozilla.org/2006/browser/search/">
<ShortName>{WEBUI_NAME}</ShortName>
<Description>Search {WEBUI_NAME}</Description>
<InputEncoding>UTF-8</InputEncoding>
<Image width="16" height="16" type="image/x-icon">{WEBUI_URL}/static/favicon.png</Image>
<Url type="text/html" method="get" template="{WEBUI_URL}/?q={"{searchTerms}"}"/>
<moz:SearchForm>{WEBUI_URL}</moz:SearchForm>
</OpenSearchDescription>
"""
return Response(content=xml_content, media_type="application/xml")
@app.get("/health")
async def healthcheck():
return {"status": True}
@app.get("/health/db")
async def healthcheck_with_db():
Session.execute(text("SELECT 1;")).all()
return {"status": True}
app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
app.mount("/cache", StaticFiles(directory=CACHE_DIR), name="cache")
if os.path.exists(FRONTEND_BUILD_DIR):
mimetypes.add_type("text/javascript", ".js")
app.mount(
"/",
SPAStaticFiles(directory=FRONTEND_BUILD_DIR, html=True),
name="spa-static-files",
)
else:
log.warning(
f"Frontend build directory not found at '{FRONTEND_BUILD_DIR}'. Serving API only."
)
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