Update main.py

main.py

@@ -7,6 +7,8 @@ import json
 from datetime import datetime
 import edge_tts
 import io
+from telegraph.aio import Telegraph
+import aiohttp
 
 # Add these constants at the top
 API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo"
@@ -16,6 +18,27 @@ AI_HEADERS = {
     "Accept": "application/json"
 }
 
+# Initialize Telegraph and aiohttp session
+telegraph = None
+session = None
+
+async def init_telegraph():
+    global telegraph, session
+    try:
+        if telegraph is None:
+            session = aiohttp.ClientSession()
+            telegraph = Telegraph(session=session)
+            await telegraph.create_account(short_name='TelegramAIBot')
+        return True
+    except Exception as e:
+        print(f"Telegraph initialization error: {e}")
+        return False
+
+async def cleanup():
+    global session
+    if session:
+        await session.close()
+
 # TTS settings
 DEFAULT_VOICE = "en-IN-NeerjaNeural"
 DEFAULT_RATE = "+25%"
@@ -55,6 +78,12 @@ def save_message_to_history(user_id, username, message_type, content, bot_respon
     message_history.append(message_data)
     print("Message History Update:", json.dumps(message_data, indent=2))
 
+def condense_text(text, max_length=100):
+    """Condense text to a maximum length while keeping it readable"""
+    if len(text) <= max_length:
+        return text
+    return text[:max_length-3] + "..."
+
 # Add command to print history
 @myaibot.on_message(filters.command("history"))
 async def history_command(client, message):
@@ -63,18 +92,36 @@ async def history_command(client, message):
         return
     
     try:
-        # Create a formatted message
-        history_text = "📜 Message History:\n\n"
-        for idx, msg in enumerate(message_history[-10:], 1):  # Show last 10 messages
-            history_text += f"{idx}. Message: {msg['content']}\n"
+        total_messages = len(message_history)
+        history_text = f"📜 Chat History (Total: {total_messages} messages)\n\n"
+        
+        # If we have many messages, summarize older ones
+        if total_messages > 10:
+            history_text += "Earlier messages:\n"
+            for msg in message_history[:-10]:
+                history_text += f"• {condense_text(msg['content'], 50)}\n"
+            
+            history_text += "\nRecent messages:\n"
+            recent_messages = message_history[-10:]
+        else:
+            recent_messages = message_history
+        
+        # Add recent messages with more detail
+        for idx, msg in enumerate(recent_messages, 1):
+            history_text += f"{idx}. Q: {condense_text(msg['content'], 150)}\n"
             if msg['response']:
-                history_text += f"   Response: {msg['response']}\n"
+                history_text += f"   A: {condense_text(msg['response'], 150)}\n"
             history_text += "\n"
         
         await message.reply_text(history_text)
         
     except Exception as e:
-        await message.reply_text(f"Error retrieving history: {str(e)}")
+        print(f"Error in history command: {str(e)}")
+        # Fallback to super condensed version
+        short_history = "📜 Last 5 Messages:\n\n"
+        for msg in message_history[-5:]:
+            short_history += f"• {condense_text(msg['content'], 30)}\n"
+        await message.reply_text(short_history)
 
 # Command handler for /start
 @myaibot.on_message(filters.command("start"))
@@ -175,42 +222,41 @@ async def transcribe_audio(file_path):
 # Add this new function after transcribe_audio function
 async def get_ai_response(text):
     try:
-        # Create condensed history from all messages
+        # Create context from history
         context = ""
         if message_history:
-            # If we have more than 10 messages, summarize older ones
-            if len(message_history) > 10:
-                older_messages = message_history[:-10]
-                recent_messages = message_history[-10:]
-                
-                # Summarize older messages in pairs to save space
-                context = "Earlier conversation summary:\n"
-                for i in range(0, len(older_messages), 2):
-                    pair = older_messages[i:i+2]
-                    combined_content = " | ".join(msg['content'] for msg in pair)
-                    if len(combined_content) > 100:
-                        combined_content = combined_content[:100] + "..."
-                    context += f"Chat: {combined_content}\n"
-                
-                # Add a separator
-                context += "\nRecent conversation:\n"
-                
-                # Add recent messages in full detail
-                for msg in recent_messages:
-                    if msg['content'] and msg['response']:
-                        context += f"Human: {msg['content']}\nAssistant: {msg['response']}\n"
-            else:
-                # If less than 10 messages, include all in detail
-                context = "Conversation history:\n"
-                for msg in message_history:
-                    if msg['content'] and msg['response']:
-                        context += f"Human: {msg['content']}\nAssistant: {msg['response']}\n"
+            # Get last 5 relevant messages for context
+            recent_history = message_history[-5:]
+            context = (
+                "You are a helpful AI assistant. Below is the conversation history. "
+                "Use this context to provide a relevant response to the user's latest message. "
+                "If the current message is related to previous ones, make sure to reference and build upon that information.\n\n"
+                "Previous conversation:\n"
+            )
+            
+            # Add conversation history with clear markers
+            for i, msg in enumerate(recent_history, 1):
+                context += f"Message {i}:\n"
+                context += f"User: {msg['content']}\n"
+                if msg['response']:
+                    context += f"Assistant: {msg['response']}\n"
+                context += "\n"
+            
+            # Add specific instructions for the response
+            context += (
+                "Instructions:\n"
+                "1. Consider the conversation history above\n"
+                "2. If the new message relates to previous ones, reference that information\n"
+                "3. Maintain consistency with previous responses\n"
+                "4. Provide a direct and relevant answer\n\n"
+                "New message to respond to:\n"
+            )
         
         # Combine context with current query
-        full_query = f"{context}Human: {text}"
+        full_prompt = f"{context}User: {text}\nAssistant: Let me provide a relevant response based on our conversation..."
         
         payload = {
-            "query": full_query,
+            "query": full_prompt,
             "stream": False
         }
         
@@ -226,7 +272,7 @@ async def get_ai_response(text):
         
         # The API returns the response directly
         if isinstance(response_data, dict) and 'response' in response_data:
-            return response_data['response']
+            return response_data['response'].replace("Assistant: Let me provide a relevant response based on our conversation...", "").strip()
         else:
             return str(response_data)
             
@@ -297,4 +343,10 @@ async def handle_voice(client, message):
 # Run the bot
 if __name__ == "__main__":
     print("Bot is running...")
-    myaibot.run() 
+    try:
+        myaibot.run()
+    finally:
+        # Cleanup
+        if session:
+            loop = asyncio.get_event_loop()
+            loop.run_until_complete(cleanup())