Update runs/python/telegram_gemini2.py
Browse files- runs/python/telegram_gemini2.py +56 -56
runs/python/telegram_gemini2.py
CHANGED
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@@ -1,56 +1,56 @@
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import asyncio
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import aiohttp # برای درخواستهای async
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from telegram import Update
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from telegram.ext import ApplicationBuilder, MessageHandler, ContextTypes, filters
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import logging
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# تنظیمات
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BOT_TOKEN = "
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LLAMA_API_URL = "http://127.0.0.1:8080/completion"
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# لاگگیری
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logging.basicConfig(
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
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)
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# گرفتن پاسخ از llama.cpp به صورت async
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async def get_llama_response(prompt: str) -> str:
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system_prompt = f"User: {prompt}\nAssistant:"
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payload = {
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"prompt": system_prompt,
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"max_tokens": 64,
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"temperature": 0.7,
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"stop": ["</s>", "User:"]
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}
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try:
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async with aiohttp.ClientSession() as session:
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async with session.post(LLAMA_API_URL, json=payload, timeout=60) as resp:
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if resp.status == 200:
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data = await resp.json()
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return data.get("content", "").strip()
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else:
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logging.error(f"LLaMA API Error: {resp.status}")
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return "❌ خطا در دریافت پاسخ از مدل زبان."
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except asyncio.TimeoutError:
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return "⏱️ مدل دیر پاسخ داد. لطفاً دوباره تلاش کنید."
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except Exception as e:
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logging.exception("خطا در ارتباط با مدل:")
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return "⚠️ خطا در پردازش درخواست شما."
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# هندل کردن پیامهای دستوری
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async def handle_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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message = update.message
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if message and message.text:
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user_input = message.text.lstrip('/')
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await message.chat.send_action("typing")
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response = await get_llama_response(user_input)
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await message.reply_text(response)
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# راهاندازی ربات
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def main():
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app = ApplicationBuilder().token(BOT_TOKEN).build()
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app.add_handler(MessageHandler(filters.COMMAND, handle_command))
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app.run_polling()
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if __name__ == "__main__":
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main()
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import asyncio
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import aiohttp # برای درخواستهای async
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from telegram import Update
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from telegram.ext import ApplicationBuilder, MessageHandler, ContextTypes, filters
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import logging
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# تنظیمات
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BOT_TOKEN = ""
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LLAMA_API_URL = "http://127.0.0.1:8080/completion"
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# لاگگیری
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logging.basicConfig(
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO
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)
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+
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# گرفتن پاسخ از llama.cpp به صورت async
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async def get_llama_response(prompt: str) -> str:
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system_prompt = f"User: {prompt}\nAssistant:"
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payload = {
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"prompt": system_prompt,
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"max_tokens": 64,
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"temperature": 0.7,
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"stop": ["</s>", "User:"]
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}
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try:
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async with aiohttp.ClientSession() as session:
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async with session.post(LLAMA_API_URL, json=payload, timeout=60) as resp:
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if resp.status == 200:
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data = await resp.json()
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return data.get("content", "").strip()
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else:
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logging.error(f"LLaMA API Error: {resp.status}")
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return "❌ خطا در دریافت پاسخ از مدل زبان."
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except asyncio.TimeoutError:
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return "⏱️ مدل دیر پاسخ داد. لطفاً دوباره تلاش کنید."
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except Exception as e:
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logging.exception("خطا در ارتباط با مدل:")
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return "⚠️ خطا در پردازش درخواست شما."
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# هندل کردن پیامهای دستوری
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async def handle_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
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message = update.message
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if message and message.text:
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user_input = message.text.lstrip('/')
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await message.chat.send_action("typing")
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response = await get_llama_response(user_input)
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await message.reply_text(response)
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# راهاندازی ربات
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def main():
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app = ApplicationBuilder().token(BOT_TOKEN).build()
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app.add_handler(MessageHandler(filters.COMMAND, handle_command))
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app.run_polling()
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if __name__ == "__main__":
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main()
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