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.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+homeopathy_book.pdf filter=lfs diff=lfs merge=lfs -text
+vector_db/chroma.sqlite3 filter=lfs diff=lfs merge=lfs -text

Dockerfile

@@ -0,0 +1,18 @@
+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker# you will also find guides on how best to write your Dockerfile
+FROM python:3.10-slim
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the dependency file and install dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the application files (including vector_db)
+COPY . .
+
+# Grant execution permissions to the run script
+RUN chmod +x run.sh
+
+# This tells the container what command to run when it starts
+ENTRYPOINT ["./run.sh"]

doctor_bot.py

@@ -0,0 +1,168 @@
+import os
+import requests
+import json
+from dotenv import load_dotenv
+import logging
+
+# Set up basic logging
+logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
+logger = logging.getLogger(__name__)
+
+# Reverting to community package imports as in the original code
+from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain_community.vectorstores import Chroma
+
+# Load environment variables
+load_dotenv()
+
+class HomeopathyDoctorBot:
+    def __init__(self):
+        # Initialize embeddings and vector store
+        self.embeddings = HuggingFaceEmbeddings(
+            model_name="sentence-transformers/all-MiniLM-L6-v2"
+        )
+        self.vector_store = Chroma(
+            persist_directory="./vector_db",
+            embedding_function=self.embeddings
+        )
+        self.retriever = self.vector_store.as_retriever(search_kwargs={"k": 4})
+        
+        # Initialize chat history for state management
+        self.chat_history = []
+        
+    def get_relevant_context(self, query):
+        """Retrieve relevant context from the vector database"""
+        # Using the modern .invoke() method remains correct for the retriever object
+        docs = self.retriever.invoke(query) 
+        context = "\n".join([doc.page_content for doc in docs])
+        return context
+        
+    def query_ai(self, user_message, context, history):
+        """Query the AI model via Chute.ai"""
+        api_key = os.getenv("CHUTEAI_API_KEY")
+        
+        if not api_key:
+            logger.error("CHUTEAI_API_KEY is missing or empty in the environment.")
+            return "Error: Configuration missing CHUTEAI_API_KEY."
+            
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json"
+        }
+        
+        # System prompt remains the same
+        system_prompt = """You are an expert Homeopathy Doctor. Your goal is to find the best possible remedy from the provided Context.
+
+**DIAGNOSTIC PROCESS & CONSTRAINTS:**
+1. **Focus:** Analyze the patient's full symptom set, including the **Chat History**. Only analyze the symptoms explicitly mentioned by the patient. IGNORE any symptoms found *only* in the Context that the patient has not mentioned.
+2. **Clarification:** You MUST conclude the diagnosis and suggest a remedy within the first **two or three turns** of the conversation. Ask a MAXIMUM of 3 concise clarifying questions in the first turn only, if needed. In subsequent turns, prioritize diagnosing based on the accumulated history.
+3. **Prescription Rule:** **MUST** prescribe the single best-matching remedy when:
+    a) You have clear matching symptoms from the Context.
+    b) The patient explicitly asks for the medicine, or indicates they cannot answer more questions. In this case, use the best available information from the Chat History to prescribe.
+4. **Safety:** If unsure or the context doesn't contain a relevant remedy, admit it honestly.
+5. **Tone:** Always be professional, caring, and responsible.
+"""
+        messages = [
+            {"role": "system", "content": system_prompt},
+            *history,
+            {"role": "user", "content": f"Context from homeopathy book:\n{context}\n\nPatient Complaint: {user_message}"}
+        ]
+        
+        data = {
+            # FIX: Replaced the likely incorrect model name ("Gemma 3 4b It") 
+            # with a known working model from the user's Chute.ai example, 
+            # as the 404 error is usually caused by an invalid model identifier.
+            "model": "meituan-longcat/LongCat-Flash-Chat-FP8", 
+            "messages": messages,
+            "temperature": 0.2,
+            "max_tokens": 500
+        }
+        
+        # --- FIX: Corrected hostname from llm.chute.ai to llm.chutes.ai ---
+        api_url = "https://llm.chutes.ai/v1/chat/completions"
+
+        try:
+            response = requests.post(
+                api_url,
+                headers=headers,
+                json=data,
+                timeout=30
+            )
+            
+            if response.status_code == 200:
+                return response.json()["choices"][0]["message"]["content"]
+            else:
+                error_data = response.json()
+                error_message = error_data.get("error", {}).get("message", "No detailed error message.")
+                logger.error(f"Chute.ai API Error Status: {response.status_code}. Message: {error_message}")
+                return f"Error: Unable to get response (Status: {response.status_code}). Chute.ai Message: {error_message}"
+                
+        except requests.exceptions.RequestException as e:
+            logger.error(f"Connection/Request Error: {e}")
+            return f"Error: Failed to connect to Chute.ai. Check your connection or API endpoint. Details: {str(e)}"
+        
+    def start_consultation(self):
+        
+        print("🤖 Homeopathy AI Doctor is ready!")
+        print("=" * 50)
+        print("Please describe your symptoms... (Type 'quit' to exit)")
+        print()
+        
+        while True:
+            try:
+                user_input = input("Patient: ").strip()
+                
+                if user_input.lower() in ['quit', 'exit', 'bye']:
+                    print("\nHomeopathy Doctor: Thank you for consulting! Wishing you good health! 🌿")
+                    break
+                
+                if not user_input:
+                    print("Homeopathy Doctor: Please describe your symptoms.")
+                    continue
+                
+                print("Homeopathy Doctor: Analyzing your symptoms...")
+                
+                # --- Get relevant context ---
+                context = self.get_relevant_context(user_input)
+                
+                # --- Get AI response ---
+                # Pass the history to the query function
+                response = self.query_ai(user_input, context, self.chat_history)
+                
+                print(f"Homeopathy Doctor: {response}\n")
+                print("-" * 50)
+
+                # --- Update chat history with patient input and bot response ---
+                self.chat_history.append({"role": "user", "content": user_input})
+                # Check if the response contains an error message before appending as assistant's content
+                if not response.startswith("Error:"):
+                    self.chat_history.append({"role": "assistant", "content": response})
+                
+            except KeyboardInterrupt:
+                print("\n\nHomeopathy Doctor: Consultation ended. Take care!")
+                break
+            except Exception as e:
+                print(f"Homeopathy Doctor: I encountered an issue. Please try again. Error: {str(e)}")
+
+def main():
+    print("🚀 Starting Homeopathy AI Doctor Setup...")
+    
+    # Check if vector database exists
+    if not os.path.exists("./vector_db"):
+        print("❌ Vector database not found.")
+        print("💡 Please run 'python ingest_book.py' first to create the knowledge base.")
+        return
+    
+    # Check API key
+    if not os.getenv("CHUTEAI_API_KEY"):
+        print("❌ CHUTEAI_API_KEY not found in .env file.")
+        return
+    
+    try:
+        bot = HomeopathyDoctorBot()
+        bot.start_consultation()
+    except Exception as e:
+        print(f"❌ Failed to start bot: {str(e)}")
+
+if __name__ == "__main__":
+    main()

homeopathy_book.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:290679bb4a824b003e0d79d7d4ded27e27dc36d229a0ff41e1c3c8071d452138
+size 2472154

ingest_book.py

@@ -0,0 +1,33 @@
+import os
+from langchain_community.document_loaders import PyPDFLoader
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import Chroma
+from langchain_community.embeddings import HuggingFaceEmbeddings
+
+def main():
+    print("📖 Loading homeopathy_book.pdf...")
+    loader = PyPDFLoader("homeopathy_book.pdf")
+    documents = loader.load()
+    
+    print("✂️ Splitting text into chunks...")
+    text_splitter = RecursiveCharacterTextSplitter(
+        chunk_size=1000,
+        chunk_overlap=200
+    )
+    chunks = text_splitter.split_documents(documents)
+    
+    print(f"🧠 Creating memory database with {len(chunks)} chunks...")
+    embeddings = HuggingFaceEmbeddings(
+        model_name="sentence-transformers/all-MiniLM-L6-v2"
+    )
+    
+    vector_store = Chroma.from_documents(
+        documents=chunks,
+        embedding=embeddings,
+        persist_directory="./vector_db"
+    )
+    
+    print("✅ Ingestion complete! Memory saved to 'vector_db' folder.")
+
+if __name__ == "__main__":
+    main()

requirements.txt

@@ -0,0 +1,134 @@
+aiohappyeyeballs==2.6.1
+aiohttp==3.13.2
+aiosignal==1.4.0
+annotated-types==0.7.0
+anyio==4.12.0
+attrs==25.4.0
+backoff==2.2.1
+bcrypt==5.0.0
+build==1.3.0
+cachetools==6.2.2
+certifi==2025.11.12
+charset-normalizer==3.4.4
+chromadb==1.3.5
+click==8.3.1
+colorama==0.4.6
+coloredlogs==15.0.1
+dataclasses-json==0.6.7
+distro==1.9.0
+durationpy==0.10
+filelock==3.20.0
+flatbuffers==25.9.23
+frozenlist==1.8.0
+fsspec==2025.10.0
+google-auth==2.43.0
+googleapis-common-protos==1.72.0
+greenlet==3.2.4
+grpcio==1.76.0
+h11==0.16.0
+httpcore==1.0.9
+httptools==0.7.1
+httpx==0.28.1
+httpx-sse==0.4.3
+huggingface-hub==0.36.0
+humanfriendly==10.0
+idna==3.11
+importlib_metadata==8.7.0
+importlib_resources==6.5.2
+Jinja2==3.1.6
+joblib==1.5.2
+jsonpatch==1.33
+jsonpointer==3.0.0
+jsonschema==4.25.1
+jsonschema-specifications==2025.9.1
+kubernetes==34.1.0
+langchain==1.1.0
+langchain-chroma==1.0.0
+langchain-classic==1.0.0
+langchain-community==0.4.1
+langchain-core==1.1.0
+langchain-huggingface==1.1.0
+langchain-text-splitters==1.0.0
+langgraph==1.0.4
+langgraph-checkpoint==3.0.1
+langgraph-prebuilt==1.0.5
+langgraph-sdk==0.2.10
+langsmith==0.4.49
+markdown-it-py==4.0.0
+MarkupSafe==3.0.3
+marshmallow==3.26.1
+mdurl==0.1.2
+mmh3==5.2.0
+mpmath==1.3.0
+multidict==6.7.0
+mypy_extensions==1.1.0
+networkx==3.6
+numpy==2.3.5
+oauthlib==3.3.1
+onnxruntime==1.23.2
+opentelemetry-api==1.38.0
+opentelemetry-exporter-otlp-proto-common==1.38.0
+opentelemetry-exporter-otlp-proto-grpc==1.38.0
+opentelemetry-proto==1.38.0
+opentelemetry-sdk==1.38.0
+opentelemetry-semantic-conventions==0.59b0
+orjson==3.11.4
+ormsgpack==1.12.0
+overrides==7.7.0
+packaging==25.0
+pillow==12.0.0
+posthog==5.4.0
+propcache==0.4.1
+protobuf==6.33.1
+pyasn1==0.6.1
+pyasn1_modules==0.4.2
+pybase64==1.4.2
+pydantic==2.12.5
+pydantic-settings==2.12.0
+pydantic_core==2.41.5
+Pygments==2.19.2
+pypdf==6.4.0
+PyPika==0.48.9
+pyproject_hooks==1.2.0
+pyreadline3==3.5.4
+python-dateutil==2.9.0.post0
+python-dotenv==1.2.1
+python-telegram-bot==22.5
+PyYAML==6.0.3
+referencing==0.37.0
+regex==2025.11.3
+requests==2.32.5
+requests-oauthlib==2.0.0
+requests-toolbelt==1.0.0
+rich==14.2.0
+rpds-py==0.29.0
+rsa==4.9.1
+safetensors==0.7.0
+scikit-learn==1.7.2
+scipy==1.16.3
+sentence-transformers==5.1.2
+setuptools==80.9.0
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+SQLAlchemy==2.0.44
+sympy==1.14.0
+tenacity==9.1.2
+threadpoolctl==3.6.0
+tokenizers==0.22.1
+torch==2.9.1
+tqdm==4.67.1
+transformers==4.57.3
+typer==0.20.0
+typing-inspect==0.9.0
+typing-inspection==0.4.2
+typing_extensions==4.15.0
+urllib3==2.3.0
+uvicorn==0.38.0
+watchfiles==1.1.1
+websocket-client==1.9.0
+websockets==15.0.1
+xxhash==3.6.0
+yarl==1.22.0
+zipp==3.23.0
+zstandard==0.25.0

telegram_bot.py

@@ -0,0 +1,395 @@
+import os
+import requests
+import json
+from dotenv import load_dotenv
+from telegram import Update, ReplyKeyboardMarkup, ReplyKeyboardRemove
+import datetime
+from telegram.ext import Application, CommandHandler, MessageHandler, filters, ContextTypes, ConversationHandler
+import logging
+
+# FIX 1: Using the langchain_community package imports for stability
+from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain_community.vectorstores import Chroma
+
+# Load environment variables
+load_dotenv()
+
+# Enable logging
+logging.basicConfig(
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    level=logging.INFO
+)
+logger = logging.getLogger(__name__)
+
+# Conversation states
+DESCRIBING_SYMPTOMS = 1
+
+class TelegramHomeopathyBot:
+    def __init__(self):
+        # Create logs directory if not exists
+        self.logs_dir = "UserChatLogs"
+        os.makedirs(self.logs_dir, exist_ok=True)
+        
+        # Initialize embeddings and vector store
+        self.embeddings = HuggingFaceEmbeddings(
+            model_name="sentence-transformers/all-MiniLM-L6-v2"
+        )
+        self.vector_store = Chroma(
+            persist_directory="./vector_db",
+            embedding_function=self.embeddings
+        )
+        self.retriever = self.vector_store.as_retriever(search_kwargs={"k": 4})
+        
+        # Store user sessions: includes chat_history
+        self.user_sessions = {}
+    
+    # FIX 4: Removed duplicate log_chat definition
+    def log_chat(self, user_id: int, username: str, message: str, is_bot: bool = False):
+        """Log user/bot messages to individual files"""
+        try:
+            log_file = os.path.join(self.logs_dir, f"user_{user_id}.log")
+            timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            direction = "BOT" if is_bot else "USER"
+            
+            with open(log_file, "a", encoding="utf-8") as f:
+                f.write(f"[{timestamp}] {direction} ({username}): {message}\n")
+        except Exception as e:
+            logger.error(f"Failed to log chat: {e}")
+
+    def get_user_session(self, user_id):
+        """Get or create user session, initializing history."""
+        if user_id not in self.user_sessions:
+            self.user_sessions[user_id] = {
+                'chat_history': [],
+                'consultation_count': 0,
+                'last_query': None  # Track query context
+            }
+        return self.user_sessions[user_id]
+    
+    def get_relevant_context(self, query, history):
+        """
+        Retrieve relevant context from the vector database using the latest query 
+        and the accumulated user history for better RAG results.
+        """
+        # Create a composite query string from previous user inputs and the latest query
+        user_history = [msg['content'] for msg in history if msg['role'] == 'user']
+        history_summary = " ".join(user_history)
+        
+        # Combine the user's history and current message for a comprehensive retrieval query
+        composite_query = f"Patient's case summary: {history_summary} {query}" if history_summary else query
+        
+        docs = self.retriever.invoke(composite_query) 
+        context = "\n".join([doc.page_content for doc in docs])
+        return context
+        
+    def query_ai(self, user_message, context, history):
+        """Query the AI model via Chute.ai"""
+        api_key = os.getenv("CHUTEAI_API_KEY")
+        
+        if not api_key:
+            logger.error("🚨 CRITICAL API ERROR: CHUTEAI_API_KEY is missing or empty during function call.")
+            return "❌ Configuration Error: The AI service API key (CHUTEAI_API_KEY) is missing. Please check your setup."
+
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json"
+        }
+        
+        # System prompt remains the same
+        system_prompt = """You are an expert Homeopathy Doctor. Your goal is to find the best possible remedy from the provided Context.
+
+**DIAGNOSTIC PROCESS & CONSTRAINTS:**
+1. **Focus:** Analyze the patient's full symptom set, including the **Chat History**. Only analyze the symptoms explicitly mentioned by the patient. IGNORE any symptoms found *only* in the Context that the patient has not mentioned.
+2. **Clarification:** You MUST conclude the diagnosis and suggest a remedy within the first **two or three turns** of the conversation. Ask a MAXIMUM of 3 concise clarifying questions in the first turn only, if needed. In subsequent turns, prioritize diagnosing based on the accumulated history.
+3. **Prescription Rule:** **MUST** prescribe the single best-matching remedy when:
+    a) You have clear matching symptoms from the Context.
+    b) The patient explicitly asks for the medicine, or indicates they cannot answer more questions. In this case, use the best available information from the Chat History to prescribe.
+4. **Safety:** If unsure or the context doesn't contain a relevant remedy, admit it honestly.
+5. **Tone:** Always be professional, caring, and responsible.
+"""
+        messages = [
+            {"role": "system", "content": system_prompt},
+            *history,
+            {"role": "user", "content": f"Context from homeopathy book:\n{context}\n\nPatient Complaint: {user_message}"}
+        ]
+        
+        data = {
+            # FIX 3: Changed to the working model that resolved the 404 error in the console bot
+            "model": "meituan-longcat/LongCat-Flash-Chat-FP8", 
+            "messages": messages,
+            "temperature": 0.2,
+            "max_tokens": 500
+        }
+        
+        # FIX 2: Corrected API URL to the one that successfully connected
+        api_url = "https://llm.chutes.ai/v1/chat/completions"
+
+        try:
+            response = requests.post(
+                api_url,
+                headers=headers,
+                json=data,
+                timeout=30
+            )
+            
+            if response.status_code == 200:
+                return response.json()["choices"][0]["message"]["content"]
+            else:
+                error_data = response.json()
+                error_message = error_data.get("error", {}).get("message", "No detailed error message.")
+                
+                if response.status_code == 401:
+                    logger.error("🚨 CRITICAL API ERROR (401 Unauthorized) 🚨: The CHUTEAI_API_KEY is likely invalid or missing. Please check your .env file.")
+                
+                logger.error(f"Chute.ai Error {response.status_code}: {error_message}")
+                return f"❌ I'm having technical difficulties. Please try again later. (Error: {response.status_code})"
+                
+        except Exception as e:
+            logger.error(f"Connection Error: {e}")
+            return f"❌ Connection error. Please try again. Error: {str(e)}"
+
+# Create bot instance
+homeopathy_bot = TelegramHomeopathyBot()
+
+# Telegram Bot Handlers
+async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """Send welcome message when the command /start is issued."""
+    user = update.effective_user
+    welcome_text = f"""
+👋 Hello *{user.first_name}*! I'm your AI Homeopathy Doctor 🤖
+
+I can help you analyze symptoms and suggest potential homeopathic remedies based on medical knowledge.
+
+💡 *How to use:*
+1. Describe your symptoms in detail
+2. I'll ask clarifying questions (max 3 in the first turn)
+3. I'll suggest potential homeopathic remedies within 3 turns
+
+⚠️ *Important Disclaimer:*
+This is for educational purposes only. Always consult a qualified homeopath or medical professional for proper diagnosis and treatment.
+
+Type your symptoms below to begin...
+    """
+    
+    # Reset session for a clean start
+    user_id = update.effective_user.id
+    homeopathy_bot.user_sessions[user_id] = {'chat_history': [], 'consultation_count': 0}
+    
+    await update.message.reply_text(welcome_text, parse_mode='Markdown')
+    # Log start command
+    homeopathy_bot.log_chat(
+        user.id,
+        user.username or f"{user.first_name} {user.last_name or ''}".strip(),
+        "/start command received",
+        is_bot=False
+    )
+    return DESCRIBING_SYMPTOMS
+
+async def handle_symptoms(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """Handle user's symptom description and continue the diagnosis."""
+    user_id = update.effective_user.id
+    user_input = update.message.text
+    
+    # Get user session
+    session = homeopathy_bot.get_user_session(user_id)
+    session['consultation_count'] += 1
+    
+    # Send typing action
+    await update.message.reply_chat_action(action="typing")
+    
+    # Send processing message
+    processing_msg = await update.message.reply_text("🔍 Analyzing your symptoms...")
+    
+    try:
+        # Get relevant context (using the history to enrich the retrieval query)
+        context_text = homeopathy_bot.get_relevant_context(user_input, session['chat_history'])
+        
+        # Get AI response
+        response = homeopathy_bot.query_ai(user_input, context_text, session['chat_history'])
+        
+        # Update chat history
+        if not response.startswith("❌"): # Only update history if not an error message
+            session['chat_history'].append({"role": "user", "content": user_input})
+            session['chat_history'].append({"role": "assistant", "content": response})
+        
+        # Log user input and bot response
+        user = update.effective_user
+        homeopathy_bot.log_chat(
+            user.id,
+            user.username or f"{user.first_name} {user.last_name or ''}".strip(),
+            user_input,
+            is_bot=False
+        )
+        homeopathy_bot.log_chat(
+            user.id,
+            user.username or f"{user.first_name} {user.last_name or ''}".strip(),
+            response,
+            is_bot=True
+        )
+        
+        # Keep only last 6 messages (3 user + 3 assistant) to prevent context overflow
+        if len(session['chat_history']) > 6:
+            session['chat_history'] = session['chat_history'][-6:]
+        
+        # Send response using Markdown for clear formatting
+        try:
+            await processing_msg.delete()  # Remove processing message
+        except Exception as e:
+            logger.warning(f"Could not delete processing message: {e}")
+        await update.message.reply_text(
+            f"🩺 *Homeopathy Doctor:*\n\n{response}",
+            parse_mode='Markdown' # Use Markdown for formatting
+        )
+        
+        # Add quick actions
+        quick_actions = [["🔍 Describe more symptoms or answer questions"], ["🔄 Start a new consultation"]]
+        reply_markup = ReplyKeyboardMarkup(quick_actions, one_time_keyboard=True, resize_keyboard=True)
+        await update.message.reply_text("What would you like to do next?", reply_markup=reply_markup)
+        
+    except Exception as e:
+        logger.error(f"Error processing message: {e}")
+        try:
+            await processing_msg.delete()
+        except:
+            pass
+        await update.message.reply_text("❌ Sorry, I encountered an error. Please try again.")
+    
+    return DESCRIBING_SYMPTOMS
+
+async def handle_quick_actions(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """Handle quick action buttons."""
+    user_input = update.message.text
+    
+    if user_input in ["🔍 Describe more symptoms or answer questions", "Reset please"]:
+        # If the bot has prescribed a remedy, the user might be ready to start fresh, 
+        # so this is a good opportunity to offer the reset.
+        if len(homeopathy_bot.get_user_session(update.effective_user.id)['chat_history']) >= 4: # If 2 turns have passed
+             await update.message.reply_text("Please provide any additional details or clarify the Doctor's previous questions...")
+        else:
+             await update.message.reply_text("Please provide any additional details or clarify the Doctor's previous questions...")
+             
+    elif user_input in ["🔄 Start a new consultation", "Reset please"]:
+        user_id = update.effective_user.id
+        if user_id in homeopathy_bot.user_sessions:
+            # Clear history and reset embeddings for a completely fresh start
+            homeopathy_bot.user_sessions[user_id] = {
+                'chat_history': [],
+                'consultation_count': 0,
+                'last_query': None  # Reset any cached query context
+            }
+            # Reinitialize the retriever to clear any cached context
+            homeopathy_bot.retriever = homeopathy_bot.vector_store.as_retriever(search_kwargs={"k": 4})
+        await update.message.reply_text("🔄 Starting new consultation. Please describe your symptoms...", reply_markup=ReplyKeyboardRemove())
+    
+    return DESCRIBING_SYMPTOMS
+
+async def cancel(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """Cancel the conversation."""
+    user_id = update.effective_user.id
+    if user_id in homeopathy_bot.user_sessions:
+        del homeopathy_bot.user_sessions[user_id]
+        
+    await update.message.reply_text(
+        "👋 Consultation ended. Thank you for using Homeopathy AI Doctor!\n\n"
+        "Remember to consult a qualified homeopath for proper treatment. 🌿",
+        reply_markup=ReplyKeyboardRemove()
+    )
+    return ConversationHandler.END
+
+async def help_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """Send help message."""
+    help_text = """
+🤖 *Homeopathy AI Doctor Bot Help*
+
+*Available Commands:*
+/start - Begin a new consultation (resets history)
+/help - Show this help message
+/cancel - End current consultation
+
+*How to get the best results:*
+• Describe symptoms in detail
+• Mention location, intensity, and timing
+• Share what makes symptoms better/worse
+• Be specific about associated feelings
+
+*Disclaimer:* This bot provides educational information only. Always consult qualified medical professionals.
+    """
+    await update.message.reply_text(help_text, parse_mode='Markdown')
+
+# FIX: Add a new handler to catch unhandled text messages and guide the user.
+async def generic_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """Handles any plain text message received outside the ConversationHandler."""
+    await update.message.reply_text(
+        "👋 Welcome! To begin a new consultation and describe your symptoms, please use the */start* command. Thank you!",
+        parse_mode='Markdown'
+    )
+
+async def error_handler(update: Update, context: ContextTypes.DEFAULT_TYPE):
+    """Log errors and send a friendly message."""
+    logger.error(f"Update {update} caused error {context.error}")
+    if update and update.message:
+        await update.message.reply_text(
+            "❌ Sorry, I encountered an unexpected error. Please try again or use /start to begin a new consultation."
+        )
+
+def check_dependencies():
+    """Checks for required environment variables and the vector database."""
+    if not os.getenv("TELEGRAM_BOT_TOKEN"):
+        print("❌ TELEGRAM_BOT_TOKEN not found in .env file. Please set it to run the bot.")
+        return False
+    
+    if not os.path.exists("./vector_db"):
+        print("❌ Vector database not found. Please run 'python ingest_book.py' first.")
+        return False
+    
+    # FIX 5: Changed dependency check to look for CHUTEAI_API_KEY
+    if not os.getenv("CHUTEAI_API_KEY"):
+        print("❌ CHUTEAI_API_KEY not found in .env file. Please set it to run the bot.")
+        return False
+    
+    return True
+
+def main():
+    """Start the bot."""
+    
+    if not check_dependencies():
+        return
+    
+    print("🚀 Starting Telegram Homeopathy Bot...")
+    
+    # Get Telegram bot token from environment variable
+    TELEGRAM_TOKEN = os.getenv("TELEGRAM_BOT_TOKEN")
+    
+    # Create Application
+    application = Application.builder().token(TELEGRAM_TOKEN).build()
+    
+    # Add conversation handler
+    conv_handler = ConversationHandler(
+        entry_points=[CommandHandler('start', start)],
+        states={
+            DESCRIBING_SYMPTOMS: [
+                MessageHandler(filters.Regex(r'^(🔍|🔄)'), handle_quick_actions),
+                MessageHandler(filters.TEXT & ~filters.COMMAND, handle_symptoms),
+            ],
+        },
+        fallbacks=[CommandHandler('cancel', cancel)],
+    )
+    
+    # Add handlers
+    application.add_handler(conv_handler)
+    application.add_handler(CommandHandler('help', help_command))
+    application.add_handler(CommandHandler('cancel', cancel))
+    
+    # Handler for general text outside the conversation flow
+    application.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, generic_message))
+    
+    # Add error handler
+    application.add_error_handler(error_handler)
+    
+    # Start the Bot
+    print("✅ Bot is running... Press Ctrl+C to stop")
+    application.run_polling(allowed_updates=Update.ALL_TYPES)
+
+if __name__ == '__main__':
+    # Ensure all initialization warnings are visible before starting the main loop
+    main()

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