Integrate OpenWebUI bot with AI service
This commit is contained in:
Iyeoluwa Akinrinola
+150
-367
@@ -13,13 +13,14 @@ from fastapi.middleware.cors import CORSMiddleware
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import List, Optional
|
||||
import uuid
|
||||
import asyncio
|
||||
from datetime import datetime, timezone
|
||||
|
||||
from ai_service.models.model_service import model_service
|
||||
from ai_service.models.chat_service import chat_service
|
||||
from ai_service.openwebui_api import router as openwebui_router
|
||||
from ai_service.openwebui_channels import openwebui_channels
|
||||
from ai_service.config import config
|
||||
from ai_service import bot_manager
|
||||
|
||||
# Create FastAPI app
|
||||
app = FastAPI(
|
||||
@@ -43,26 +44,64 @@ app.include_router(openwebui_router, prefix="/api")
|
||||
# Include Ollama proxy routes
|
||||
app.include_router(openwebui_router, prefix="/ollama")
|
||||
|
||||
# Register webhook for channel messages on startup
|
||||
# API startup event
|
||||
@app.on_event("startup")
|
||||
async def startup_event():
|
||||
"""
|
||||
Register webhook for channel messages on startup.
|
||||
Startup event for the API.
|
||||
"""
|
||||
# Get the public URL of this service
|
||||
service_url = f"http://{config.API_HOST}:{config.API_PORT}"
|
||||
if config.PUBLIC_URL:
|
||||
service_url = config.PUBLIC_URL
|
||||
print("=" * 50)
|
||||
print(f"Starting AI Service API on {config.API_HOST}:{config.API_PORT}")
|
||||
print(f"OpenWebUI URL: {config.OPENWEBUI_URL}")
|
||||
print(f"Default model: {config.DEFAULT_MODEL}")
|
||||
|
||||
# Register webhook
|
||||
webhook_url = f"{service_url}/webhooks/channel-message"
|
||||
print(f"Registering webhook for channel messages: {webhook_url}")
|
||||
# Start the OpenWebUI bot if enabled
|
||||
if config.BOT_ENABLED:
|
||||
print("=" * 50)
|
||||
print("Starting OpenWebUI bot...")
|
||||
|
||||
success = openwebui_channels.register_webhook(webhook_url)
|
||||
if success:
|
||||
print("Successfully registered webhook for channel messages")
|
||||
# Start the bot with configuration
|
||||
success = await bot_manager.start_bot(
|
||||
openwebui_url=config.OPENWEBUI_URL,
|
||||
api_key=config.OPENWEBUI_API_KEY,
|
||||
model_id=config.DEFAULT_MODEL,
|
||||
system_prompt=config.BOT_SYSTEM_PROMPT,
|
||||
temperature=config.BOT_TEMPERATURE,
|
||||
max_tokens=config.BOT_MAX_TOKENS,
|
||||
top_p=config.BOT_TOP_P,
|
||||
triggers=config.BOT_TRIGGERS,
|
||||
respond_to_all=config.BOT_RESPOND_TO_ALL
|
||||
)
|
||||
|
||||
if success:
|
||||
print("Bot started successfully!")
|
||||
else:
|
||||
print("Failed to start bot. Check the logs for details.")
|
||||
print("=" * 50)
|
||||
else:
|
||||
print("Failed to register webhook for channel messages")
|
||||
print("OpenWebUI bot is disabled. Set BOT_ENABLED=true in .env to enable it.")
|
||||
|
||||
print("=" * 50)
|
||||
|
||||
# API shutdown event
|
||||
@app.on_event("shutdown")
|
||||
async def shutdown_event():
|
||||
"""
|
||||
Shutdown event for the API.
|
||||
"""
|
||||
print("=" * 50)
|
||||
print("Shutting down AI Service API...")
|
||||
|
||||
# Stop the OpenWebUI bot if it's running
|
||||
if bot_manager.is_bot_running():
|
||||
print("Stopping OpenWebUI bot...")
|
||||
success = await bot_manager.stop_bot()
|
||||
if success:
|
||||
print("Bot stopped successfully!")
|
||||
else:
|
||||
print("Failed to stop bot. Check the logs for details.")
|
||||
|
||||
print("=" * 50)
|
||||
|
||||
# Define API models for health check
|
||||
class HealthResponse(BaseModel):
|
||||
@@ -137,172 +176,6 @@ async def health_check():
|
||||
"""
|
||||
return {"status": "healthy"}
|
||||
|
||||
@app.get("/test-ollama")
|
||||
async def test_ollama_connection():
|
||||
"""
|
||||
Test the connection to the Ollama API.
|
||||
|
||||
Returns:
|
||||
Connection status and available models from Ollama.
|
||||
"""
|
||||
import requests
|
||||
|
||||
try:
|
||||
# Try to connect to Ollama API
|
||||
response = requests.get(f"{config.OLLAMA_API_URL}/api/tags", timeout=config.API_TIMEOUT)
|
||||
response.raise_for_status()
|
||||
|
||||
# Return the models from Ollama
|
||||
return {
|
||||
"status": "success",
|
||||
"message": "Successfully connected to Ollama API",
|
||||
"ollama_url": config.OLLAMA_API_URL,
|
||||
"models": response.json()
|
||||
}
|
||||
except requests.exceptions.Timeout as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Timeout connecting to Ollama API: {str(e)}. The request exceeded the {config.API_TIMEOUT} second timeout.",
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
except requests.exceptions.ConnectionError as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Connection error to Ollama API: {str(e)}. Please check if Ollama is running at {config.OLLAMA_API_URL}.",
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
except Exception as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Failed to connect to Ollama API: {str(e)}",
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
|
||||
@app.post("/test-chat")
|
||||
async def test_chat_completion():
|
||||
"""
|
||||
Test the chat completion with a simple prompt.
|
||||
|
||||
Returns:
|
||||
Model response.
|
||||
"""
|
||||
try:
|
||||
# Use the model service directly
|
||||
response = model_service.generate_response(
|
||||
model_id=config.DEFAULT_MODEL,
|
||||
prompt="Hello, how are you?",
|
||||
context=[],
|
||||
use_rag=False
|
||||
)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"model": config.DEFAULT_MODEL,
|
||||
"response": response,
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
except Exception as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Failed to get chat completion: {str(e)}",
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
|
||||
@app.post("/test-rag")
|
||||
async def test_rag_completion(query: str = "What information do you have in your knowledge database?"):
|
||||
"""
|
||||
Test the RAG (Retrieval Augmented Generation) functionality with a query.
|
||||
|
||||
This endpoint tests the integration with OpenWebUI's knowledge database.
|
||||
|
||||
Args:
|
||||
query: The question to ask about documents in the knowledge database.
|
||||
|
||||
Returns:
|
||||
Model response using RAG.
|
||||
"""
|
||||
try:
|
||||
# Use the model service directly with RAG enabled
|
||||
response = model_service.generate_response(
|
||||
model_id=config.DEFAULT_MODEL,
|
||||
prompt=query,
|
||||
context=[],
|
||||
use_rag=True # Enable RAG
|
||||
)
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"model": config.DEFAULT_MODEL,
|
||||
"query": query,
|
||||
"use_rag": True,
|
||||
"response": response,
|
||||
"openwebui_url": config.OPENWEBUI_URL
|
||||
}
|
||||
except Exception as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Failed to get RAG completion: {str(e)}",
|
||||
"openwebui_url": config.OPENWEBUI_URL
|
||||
}
|
||||
|
||||
@app.post("/test-ollama-direct")
|
||||
async def test_ollama_direct():
|
||||
"""
|
||||
Test the Ollama API directly with a simple chat request.
|
||||
|
||||
Returns:
|
||||
Raw Ollama API response.
|
||||
"""
|
||||
import requests
|
||||
|
||||
try:
|
||||
# Prepare a simple chat request
|
||||
request_json = {
|
||||
"model": config.DEFAULT_MODEL,
|
||||
"messages": [
|
||||
{"role": "system", "content": "You are a helpful assistant."},
|
||||
{"role": "user", "content": "Hello, how are you?"}
|
||||
],
|
||||
"stream": False
|
||||
}
|
||||
|
||||
# Make the API call to Ollama
|
||||
print(f"Sending direct request to Ollama API at: {config.OLLAMA_API_URL}/api/chat")
|
||||
response = requests.post(
|
||||
f"{config.OLLAMA_API_URL}/api/chat",
|
||||
headers={"Content-Type": "application/json"},
|
||||
json=request_json,
|
||||
timeout=config.API_TIMEOUT
|
||||
)
|
||||
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
|
||||
return {
|
||||
"status": "success",
|
||||
"ollama_url": config.OLLAMA_API_URL,
|
||||
"request": request_json,
|
||||
"response": result
|
||||
}
|
||||
except requests.exceptions.Timeout as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Timeout connecting to Ollama API: {str(e)}. The request exceeded the {config.API_TIMEOUT} second timeout.",
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
except requests.exceptions.ConnectionError as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Connection error to Ollama API: {str(e)}. Please check if Ollama is running at {config.OLLAMA_API_URL}.",
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
except Exception as e:
|
||||
return {
|
||||
"status": "error",
|
||||
"message": f"Failed to connect to Ollama API: {str(e)}",
|
||||
"ollama_url": config.OLLAMA_API_URL
|
||||
}
|
||||
|
||||
@app.get("/config")
|
||||
async def get_config():
|
||||
"""
|
||||
@@ -318,38 +191,114 @@ async def get_config():
|
||||
"ollama_api_url": config.OLLAMA_API_URL,
|
||||
"default_model": config.DEFAULT_MODEL,
|
||||
"api_timeout": config.API_TIMEOUT,
|
||||
"bot": {
|
||||
"enabled": config.BOT_ENABLED,
|
||||
"running": bot_manager.is_bot_running(),
|
||||
"model_id": config.DEFAULT_MODEL,
|
||||
"system_prompt": config.BOT_SYSTEM_PROMPT[:50] + "..." if len(config.BOT_SYSTEM_PROMPT) > 50 else config.BOT_SYSTEM_PROMPT,
|
||||
"temperature": config.BOT_TEMPERATURE,
|
||||
"max_tokens": config.BOT_MAX_TOKENS,
|
||||
"top_p": config.BOT_TOP_P,
|
||||
"triggers": config.BOT_TRIGGERS,
|
||||
"respond_to_all": config.BOT_RESPOND_TO_ALL
|
||||
},
|
||||
"available_models": list(model_service.AVAILABLE_MODELS.keys())
|
||||
}
|
||||
|
||||
@app.get("/test-webhook")
|
||||
async def test_webhook():
|
||||
@app.get("/bot/status")
|
||||
async def get_bot_status():
|
||||
"""
|
||||
Test the webhook registration.
|
||||
Get the status and configuration of the OpenWebUI bot.
|
||||
|
||||
Returns:
|
||||
Webhook registration status.
|
||||
Bot status and configuration.
|
||||
"""
|
||||
# Get the public URL of this service
|
||||
service_url = f"http://{config.API_HOST}:{config.API_PORT}"
|
||||
if config.PUBLIC_URL:
|
||||
service_url = config.PUBLIC_URL
|
||||
|
||||
# Webhook URL
|
||||
webhook_url = f"{service_url}/webhooks/channel-message"
|
||||
|
||||
# Try to register the webhook again
|
||||
success = openwebui_channels.register_webhook(webhook_url)
|
||||
|
||||
# Get all registered webhooks
|
||||
webhooks = openwebui_channels.get_webhooks()
|
||||
|
||||
return {
|
||||
"webhook_url": webhook_url,
|
||||
"registration_success": success,
|
||||
"registered_webhooks": webhooks
|
||||
"enabled": config.BOT_ENABLED,
|
||||
"running": bot_manager.is_bot_running(),
|
||||
"config": {
|
||||
"model_id": config.DEFAULT_MODEL,
|
||||
"system_prompt": config.BOT_SYSTEM_PROMPT[:50] + "..." if len(config.BOT_SYSTEM_PROMPT) > 50 else config.BOT_SYSTEM_PROMPT,
|
||||
"temperature": config.BOT_TEMPERATURE,
|
||||
"max_tokens": config.BOT_MAX_TOKENS,
|
||||
"top_p": config.BOT_TOP_P,
|
||||
"triggers": config.BOT_TRIGGERS,
|
||||
"respond_to_all": config.BOT_RESPOND_TO_ALL
|
||||
}
|
||||
}
|
||||
|
||||
@app.post("/bot/start")
|
||||
async def start_bot(
|
||||
model_id: str = None,
|
||||
system_prompt: str = None,
|
||||
temperature: float = None,
|
||||
max_tokens: int = None,
|
||||
top_p: float = None,
|
||||
respond_to_all: bool = None
|
||||
):
|
||||
"""
|
||||
Start the OpenWebUI bot with optional configuration.
|
||||
|
||||
Args:
|
||||
model_id: ID of the model to use (default: config.DEFAULT_MODEL)
|
||||
system_prompt: System prompt for the bot (default: config.BOT_SYSTEM_PROMPT)
|
||||
temperature: Temperature for response generation (default: config.BOT_TEMPERATURE)
|
||||
max_tokens: Maximum number of tokens to generate (default: config.BOT_MAX_TOKENS)
|
||||
top_p: Top-p sampling parameter (default: config.BOT_TOP_P)
|
||||
respond_to_all: Whether to respond to all messages (default: config.BOT_RESPOND_TO_ALL)
|
||||
|
||||
Returns:
|
||||
Start status.
|
||||
"""
|
||||
if bot_manager.is_bot_running():
|
||||
return {"status": "already_running", "message": "Bot is already running"}
|
||||
|
||||
# Use provided values or defaults from config
|
||||
success = await bot_manager.start_bot(
|
||||
openwebui_url=config.OPENWEBUI_URL,
|
||||
api_key=config.OPENWEBUI_API_KEY,
|
||||
model_id=model_id or config.DEFAULT_MODEL,
|
||||
system_prompt=system_prompt or config.BOT_SYSTEM_PROMPT,
|
||||
temperature=temperature if temperature is not None else config.BOT_TEMPERATURE,
|
||||
max_tokens=max_tokens if max_tokens is not None else config.BOT_MAX_TOKENS,
|
||||
top_p=top_p if top_p is not None else config.BOT_TOP_P,
|
||||
triggers=config.BOT_TRIGGERS,
|
||||
respond_to_all=respond_to_all if respond_to_all is not None else config.BOT_RESPOND_TO_ALL
|
||||
)
|
||||
|
||||
if success:
|
||||
return {
|
||||
"status": "success",
|
||||
"message": "Bot started successfully",
|
||||
"config": {
|
||||
"model_id": model_id or config.DEFAULT_MODEL,
|
||||
"system_prompt": (system_prompt or config.BOT_SYSTEM_PROMPT)[:50] + "..." if len(system_prompt or config.BOT_SYSTEM_PROMPT) > 50 else (system_prompt or config.BOT_SYSTEM_PROMPT),
|
||||
"temperature": temperature if temperature is not None else config.BOT_TEMPERATURE,
|
||||
"max_tokens": max_tokens if max_tokens is not None else config.BOT_MAX_TOKENS,
|
||||
"top_p": top_p if top_p is not None else config.BOT_TOP_P,
|
||||
"respond_to_all": respond_to_all if respond_to_all is not None else config.BOT_RESPOND_TO_ALL
|
||||
}
|
||||
}
|
||||
else:
|
||||
return {"status": "error", "message": "Failed to start bot"}
|
||||
|
||||
@app.post("/bot/stop")
|
||||
async def stop_bot():
|
||||
"""
|
||||
Stop the OpenWebUI bot.
|
||||
|
||||
Returns:
|
||||
Stop status.
|
||||
"""
|
||||
if not bot_manager.is_bot_running():
|
||||
return {"status": "not_running", "message": "Bot is not running"}
|
||||
|
||||
success = await bot_manager.stop_bot()
|
||||
|
||||
if success:
|
||||
return {"status": "success", "message": "Bot stopped successfully"}
|
||||
else:
|
||||
return {"status": "error", "message": "Failed to stop bot"}
|
||||
|
||||
# Model endpoints
|
||||
@app.get("/models", response_model=List[ModelInfo])
|
||||
@@ -543,170 +492,4 @@ async def delete_chat(chat_id: str):
|
||||
|
||||
return {"status": "success", "message": "Chat deleted"}
|
||||
|
||||
# OpenWebUI Channels endpoints
|
||||
@app.get("/channels")
|
||||
async def get_openwebui_channels():
|
||||
"""
|
||||
Get all OpenWebUI channels.
|
||||
|
||||
Returns:
|
||||
List of channels.
|
||||
"""
|
||||
channels = openwebui_channels.get_channels()
|
||||
return channels
|
||||
|
||||
@app.get("/channels/{channel_id}")
|
||||
async def get_openwebui_channel(channel_id: str):
|
||||
"""
|
||||
Get an OpenWebUI channel by ID.
|
||||
|
||||
Args:
|
||||
channel_id: Channel ID.
|
||||
|
||||
Returns:
|
||||
Channel information.
|
||||
"""
|
||||
channel = openwebui_channels.get_channel(channel_id)
|
||||
if not channel:
|
||||
raise HTTPException(status_code=404, detail="Channel not found")
|
||||
|
||||
return channel
|
||||
|
||||
@app.post("/channels")
|
||||
async def create_openwebui_channel(name: str, description: str = "", is_private: bool = False):
|
||||
"""
|
||||
Create a new OpenWebUI channel.
|
||||
|
||||
Args:
|
||||
name: Channel name.
|
||||
description: Channel description.
|
||||
is_private: Whether the channel is private.
|
||||
|
||||
Returns:
|
||||
Created channel.
|
||||
"""
|
||||
channel = openwebui_channels.create_channel(name, description, is_private)
|
||||
if not channel:
|
||||
raise HTTPException(status_code=400, detail="Failed to create channel")
|
||||
|
||||
return channel
|
||||
|
||||
# Webhook endpoint for OpenWebUI channel messages
|
||||
class ChannelMessageWebhook(BaseModel):
|
||||
"""Model for channel message webhook."""
|
||||
channel_id: str = Field(..., description="Channel ID")
|
||||
message: str = Field(..., description="Message content")
|
||||
user_id: str = Field(..., description="User ID")
|
||||
timestamp: Optional[str] = Field(None, description="Message timestamp")
|
||||
|
||||
@app.post("/webhooks/channel-message")
|
||||
async def channel_message_webhook(request: ChannelMessageWebhook):
|
||||
"""
|
||||
Webhook endpoint for receiving messages from OpenWebUI channels.
|
||||
|
||||
This endpoint is called by OpenWebUI when a message is sent in a channel.
|
||||
The AI service will process the message and respond in the channel.
|
||||
|
||||
Args:
|
||||
request: Channel message webhook request.
|
||||
|
||||
Returns:
|
||||
Processing status.
|
||||
"""
|
||||
try:
|
||||
print("=" * 50)
|
||||
print("WEBHOOK RECEIVED")
|
||||
print(f"Channel ID: {request.channel_id}")
|
||||
print(f"User ID: {request.user_id}")
|
||||
print(f"Message: {request.message}")
|
||||
print(f"Timestamp: {request.timestamp}")
|
||||
print("=" * 50)
|
||||
|
||||
# Find the chat associated with this OpenWebUI channel
|
||||
print(f"Looking for chat with OpenWebUI channel ID: {request.channel_id}")
|
||||
print(f"Number of chats in system: {len(chat_service.chats)}")
|
||||
|
||||
# Debug: Print all chats and their channel IDs
|
||||
print("All chats in the system:")
|
||||
for cid, chat in chat_service.chats.items():
|
||||
is_team = chat.get('is_team_chat', False)
|
||||
channel_id = chat.get('openwebui_channel_id', 'None')
|
||||
print(f" Chat ID: {cid}, Is Team Chat: {is_team}, OpenWebUI Channel ID: {channel_id}")
|
||||
|
||||
chat_id = None
|
||||
for cid, chat in chat_service.chats.items():
|
||||
if chat.get('is_team_chat') and chat.get('openwebui_channel_id') == request.channel_id:
|
||||
chat_id = cid
|
||||
print(f"Found matching chat: {cid}")
|
||||
break
|
||||
|
||||
if not chat_id:
|
||||
print(f"No chat found for OpenWebUI channel {request.channel_id}")
|
||||
|
||||
# If no chat exists for this channel, create one
|
||||
print("Creating a new team chat for this channel...")
|
||||
try:
|
||||
new_chat_id = chat_service.create_chat(
|
||||
user_id=request.user_id,
|
||||
title=f"Channel Chat {request.channel_id}",
|
||||
model_id=config.DEFAULT_MODEL,
|
||||
is_team_chat=True
|
||||
)
|
||||
|
||||
# Manually set the OpenWebUI channel ID for this chat
|
||||
chat_service.chats[new_chat_id]['openwebui_channel_id'] = request.channel_id
|
||||
chat_service._save_chats()
|
||||
|
||||
print(f"Created new chat with ID {new_chat_id} for channel {request.channel_id}")
|
||||
|
||||
# Use this new chat
|
||||
chat_id = new_chat_id
|
||||
except Exception as e:
|
||||
print(f"Error creating new chat for channel: {str(e)}")
|
||||
return {"status": "error", "message": "No chat found for this channel and failed to create one"}
|
||||
|
||||
# Skip messages from the AI assistant to avoid loops
|
||||
if request.user_id == "ai-assistant":
|
||||
return {"status": "skipped", "message": "Skipping AI assistant message"}
|
||||
|
||||
# Check if we should respond to all messages or only to mentions
|
||||
if not config.AI_RESPOND_TO_ALL:
|
||||
# Check if the message mentions the AI using configured triggers
|
||||
message_lower = request.message.lower()
|
||||
|
||||
is_triggered = False
|
||||
for trigger in config.AI_TRIGGERS:
|
||||
if trigger.lower() in message_lower:
|
||||
is_triggered = True
|
||||
break
|
||||
|
||||
# If no trigger is found, skip processing
|
||||
if not is_triggered:
|
||||
print(f"No AI mention found in message, skipping: {request.message[:50]}...")
|
||||
return {"status": "skipped", "message": "No AI mention found in message"}
|
||||
|
||||
# Extract the actual message content (remove the trigger)
|
||||
# This is a simple approach - for more complex cases, you might want more sophisticated parsing
|
||||
processed_message = request.message
|
||||
message_lower = request.message.lower()
|
||||
|
||||
# Only try to remove triggers if we're not responding to all messages
|
||||
if not config.AI_RESPOND_TO_ALL:
|
||||
for trigger in config.AI_TRIGGERS:
|
||||
if trigger.lower() in message_lower:
|
||||
# Remove the trigger from the message
|
||||
processed_message = request.message.replace(trigger, "").strip()
|
||||
break
|
||||
|
||||
# Process the message and generate a response
|
||||
response = chat_service.get_chat_response(
|
||||
chat_id=chat_id,
|
||||
message=processed_message,
|
||||
user_id=request.user_id
|
||||
)
|
||||
|
||||
return {"status": "success", "message": "Message processed", "response": response}
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error processing channel message webhook: {str(e)}")
|
||||
return {"status": "error", "message": f"Error processing message: {str(e)}"}
|
||||
|
||||
Reference in New Issue
Block a user