Deploy chatbot

Dockerfile

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+# Use the official Python image.
+FROM python:3.9
+
+# Set environment variables
+ENV PATH="/home/user/.local/bin:$PATH"
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the requirements file
+COPY requirements.txt requirements.txt
+
+# Install dependencies
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Copy the content of the local src directory to the working directory
+COPY . /app
+
+# Expose port 7860
+EXPOSE 7860
+
+# Command to run the app
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+import os
+import sqlite3
+from fastapi import FastAPI, Request, Depends, HTTPException
+from fastapi.responses import JSONResponse, RedirectResponse
+from pydantic import BaseModel
+from functools import wraps
+import hashlib
+from textblob import TextBlob
+from groq import Groq
+from starlette.middleware.sessions import SessionMiddleware
+from starlette.responses import RedirectResponse
+from starlette.staticfiles import StaticFiles
+
+app = FastAPI()
+
+# Secret key for sessions
+app.add_middleware(SessionMiddleware, secret_key=os.urandom(24))
+
+# Initialize the Groq client with your API key
+client = Groq(api_key='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')
+
+# Database initialization
+def init_db():
+    conn = sqlite3.connect('chat_history.db')
+    c = conn.cursor()
+    
+    # Users table
+    c.execute('''CREATE TABLE IF NOT EXISTS users
+                 (id INTEGER PRIMARY KEY AUTOINCREMENT,
+                  username TEXT UNIQUE NOT NULL,
+                  password TEXT NOT NULL,
+                  created_at DATETIME DEFAULT CURRENT_TIMESTAMP)''')
+    
+    c.execute('''CREATE TABLE IF NOT EXISTS chats
+                 (id INTEGER PRIMARY KEY AUTOINCREMENT,
+                  user_id INTEGER NOT NULL,
+                  user_message TEXT NOT NULL,
+                  bot_response TEXT NOT NULL,
+                  sentiment_score REAL,
+                  timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
+                  FOREIGN KEY (user_id) REFERENCES users (id))''')
+    
+    conn.commit()
+    conn.close()
+
+init_db()
+
+# Helper functions
+def hash_password(password):
+    return hashlib.sha256(password.encode()).hexdigest()
+
+def get_sentiment(text):
+    analysis = TextBlob(text)
+    return analysis.sentiment.polarity
+
+def store_chat(user_id, user_message, bot_response, sentiment_score):
+    conn = sqlite3.connect('chat_history.db')
+    c = conn.cursor()
+    c.execute('''INSERT INTO chats (user_id, user_message, bot_response, sentiment_score)
+                 VALUES (?, ?, ?, ?)''', (user_id, user_message, bot_response, sentiment_score))
+    conn.commit()
+    conn.close()
+
+# New generate_response function using Groq API
+def generate_response(prompt):
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are Amara, a chatbot created to help. Be helpful, truthful, and attentive to emotions. Consider the previous conversation context for personalized responses. Keep it short and concise."
+                },
+                {
+                    "role": "user",
+                    "content": prompt,
+                }
+            ],
+            model="llama3-70b-8192",
+            temperature=0.5,
+            max_tokens=1024,
+            top_p=1,
+            stop=None,
+            stream=False
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        return f"Error generating response: {e}"
+
+# Define request models
+class UserMessage(BaseModel):
+    message: str
+
+@app.post("/chat")
+async def chat_endpoint(request: Request, message: UserMessage):
+    user_message = message.message
+    user_id = request.session.get("user_id")
+    
+    if not user_id:
+        raise HTTPException(status_code=401, detail="User not logged in")
+
+    # Get user's recent chat history for context
+    conn = sqlite3.connect('chat_history.db')
+    c = conn.cursor()
+    c.execute('''SELECT user_message, bot_response 
+                 FROM chats 
+                 WHERE user_id = ? 
+                 ORDER BY timestamp DESC LIMIT 5''', (user_id,))
+    recent_chats = c.fetchall()
+    conn.close()
+    
+    context = "Previous conversation:\n"
+    for user_msg, bot_msg in reversed(recent_chats):
+        context += f"User: {user_msg}\nAmara: {bot_msg}\n"
+    
+    full_prompt = f"{context}\nUser: {user_message}\nAmara:"
+
+    try:
+        bot_response = generate_response(full_prompt)
+        sentiment_score = get_sentiment(user_message)
+        store_chat(user_id, user_message, bot_response, sentiment_score)
+
+        return JSONResponse({
+            'response': bot_response,
+            'sentiment': sentiment_score
+        })
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"I apologize, but I encountered an error: {str(e)}")
+

requirements.txt

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+Flask==3.0.3
+huggingface_hub==0.24.3
+textblob==0.18.0.post0
+torch==2.1.2
+transformers==4.45.2
+fastapi
+uvicorn[standard]
+sqlite3
+textblob
+groq
+hashlib
+pydantic