Update app.py
Browse files
app.py
CHANGED
@@ -5,37 +5,127 @@ from telegram import Update
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from telegram.ext import ApplicationBuilder, CommandHandler, ContextTypes
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import os
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# Replace this with your Hugging Face Space URL
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HUGGING_FACE_SPACE_URL = "https://demaking-decision-helper-bot.hf.space"
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# Get Telegram bot token from environment variables
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TOKEN = os.getenv("TELEGRAM_BOT_TOKEN")
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if not TOKEN:
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raise ValueError("Missing Telegram Bot Token. Please set TELEGRAM_BOT_TOKEN environment variable.")
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async def call_hugging_face_space(input_data: str):
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async with httpx.AsyncClient(timeout=45.0) as client:
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try:
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response = await client.post(HUGGING_FACE_SPACE_URL, json={"input": input_data})
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response.raise_for_status() # Raise
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return response.json()
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except httpx.HTTPStatusError as e:
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return {"
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except httpx.ConnectError as e:
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return {"error": "Could not connect to the Hugging Face Space"}
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except Exception as e:
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return {"
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@app.post("/webhook/{token}")
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async def webhook(token: str, request: Request):
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if token != TOKEN:
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return JSONResponse(status_code=403, content={"message": "Forbidden"})
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update = Update.de_json(await request.json(), None)
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@@ -52,22 +142,22 @@ def start_telegram_bot():
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# Set up a command handler
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async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
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await update.message.reply_text("Hello! Tell me your decision-making issue, and I'll try to help.")
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application.add_handler(CommandHandler("start", start))
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# Start the bot
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application.run_polling()
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from telegram.ext import ApplicationBuilder, CommandHandler, ContextTypes
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import os
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import logging
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# from transformers import pipeline
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from huggingface_hub import InferenceClient, login
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import langid
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# Configure logging
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logging.basicConfig(format="%(asctime)s - %(levelname)s - %(message)s", level=logging.INFO)
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logger = logging.getLogger(__name__)
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# Replace this with your Hugging Face Space URL
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HUGGING_FACE_SPACE_URL = "https://demaking-decision-helper-bot.hf.space/generate_response"
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# Get Telegram bot token from environment variables
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TOKEN = os.getenv("TELEGRAM_BOT_TOKEN")
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if not TOKEN:
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raise ValueError("Missing Telegram Bot Token. Please set TELEGRAM_BOT_TOKEN environment variable.")
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# Get Hugging Face API token from environment variable
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HF_HUB_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
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if not HF_HUB_TOKEN:
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raise ValueError("Missing Hugging Face API token. Please set HUGGINGFACEHUB_API_TOKEN."
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# Login and initialize the client
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login(token=HF_HUB_TOKEN)
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client = InferenceClient(api_key=HF_HUB_TOKEN)
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app = FastAPI()
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# Function to detect language
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def detect_language(user_input):
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try:
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lang, _ = langid.classify(user_input)
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return "hebrew" if lang == "he" else "english" if lang == "en" else "unsupported"
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except Exception as e:
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logging.error(f"Language detection error: {e}")
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return "unsupported"
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# Function to generate response
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def generate_response(text):
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language = detect_language(text)
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if language == "hebrew":
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content = "转注谞讛 讘拽爪专讛 讗讘诇 转砖转祝 讗转 转讛诇讬讱 拽讘诇转 讛讛讞诇讟讜转 砖诇讱, " + text
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model = "microsoft/Phi-3.5-mini-instruct"
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elif language == "english":
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content = "keep it short but tell your decision making process, " + text
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model = "mistralai/Mistral-Nemo-Instruct-2407"
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else:
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return "Sorry, I only support Hebrew and English."
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messages = [{"role": "user", "content": content}]
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completion = client.chat.completions.create(
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model=model,
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messages=messages,
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max_tokens=2048,
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temperature=0.5,
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top_p=0.7
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)
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return completion.choices[0].message.content
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@app.post("/generate_response")
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async def generate_text(request: Request):
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"""
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Endpoint to generate a response from the chat model.
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Expects a JSON with a "text" field.
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"""
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try:
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data = await request.json()
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text = data.get("text", "").strip()
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if not text:
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return {"error": "No text provided"}
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response = generate_response(text)
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return {"response": response}
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except Exception as e:
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logging.error(f"Error processing request: {e}")
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return {"error": "An unexpected error occurred."}
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@app.get("/")
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async def root():
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"""
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Root endpoint to check that the API is running.
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"""
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return {"message": "Decision Helper API is running!"}
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# -------------------------
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# Function to fetch response from FastAPI
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# -------------------------
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async def call_hugging_face_space(input_data: str):
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"""
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Sends a POST request to the FastAPI API with the user's imput and returns the JSON response.
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"""
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async with httpx.AsyncClient(timeout=45.0) as client:
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try:
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response = await client.post(HUGGING_FACE_SPACE_URL, json={"input": input_data})
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response.raise_for_status() # Raise exception for HTTP 4XX/5XX errors
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return response.json()
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except httpx.HTTPStatusError as e:
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logger.error(f"HTTP Error: {e.response.status_code} - {e.response.text}")
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return {"response": "Error: API returned an error."}
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except httpx.RequestError as e:
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logger.error(f"Request Error: {e}")
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return {"response": "Error: Request Error. Could not reach API."}
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except httpx.ConnectError as e:
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logger.error(f"Connection error: {e}")
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return {"error": "Could not connect to the Hugging Face Space"}
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except Exception as e:
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logger.error(f"Unexpected Error: {e}")
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return {"response": "Error: Unexpected error occurred."}
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@app.post("/webhook/{token}")
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async def webhook(token: str, request: Request):
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if token != TOKEN:
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logger.error(f"Tokens doesn't match. {e}")
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return JSONResponse(status_code=403, content={"message": "Forbidden"})
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update = Update.de_json(await request.json(), None)
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# Set up a command handler
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async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
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await update.message.reply_text("Hello! Tell me your decision-making issue, and I'll try to help.")
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logger.info("Start command received.")
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async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
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user_text = update.message.text
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logger.info(f"User message: {user_text}")
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# Send the user text to the FastAPI server and get the response.
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result = await call_hugging_face_space(user_text)
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response_text = result.get("response", "Error generating response.")
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logger.info(f"API Response: {response_text}")
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await update.message.reply_text(response_text)
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application.add_handler(CommandHandler("start", start))
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application.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))
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# Start the bot
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application.run_polling()
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