Add Flask appp files to huggingface hube

.gitignore

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+/__pycache__
+.env

README.md

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----
-title: Flask Ai Tutor
-emoji: 🌍
-colorFrom: indigo
-colorTo: blue
-sdk: docker
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AI English Tutor
+
+AI English Tutor is a web application that provides personalized English language learning assistance through an AI-powered tutor. It allows users to practice their English skills by engaging in conversations with the AI tutor and receiving real-time feedback and guidance.
+
+## Features
+
+- **Interactive Conversation**: Users can have natural conversations with the AI tutor on various topics, allowing them to practice their English speaking and writing skills.
+- **Personalized Feedback**: The AI tutor analyzes the user's responses and provides tailored feedback, pointing out grammatical errors, suggesting improvements, and offering explanations.
+- **Vocabulary Building**: The AI tutor can help users expand their vocabulary by introducing new words and phrases in context during the conversations.
+- **Progress Tracking**: Users can track their progress over time, review their performance, and identify areas for improvement.
+- **Responsive Design**: The application is built with a responsive design, ensuring a seamless experience across different devices and screen sizes.
+
+## Technologies Used
+
+- **Frontend**: React.js
+- **Backend**: Flask (Python)
+- **AI Model**: [Specify the AI model or service used, e.g., GPT-3, Anthropic's Claude, etc.]

app.py

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+from flask import Flask , jsonify , request
+from flask_cors import CORS
+from pymongo import MongoClient
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.runnables.history import RunnableWithMessageHistory
+from langchain_groq import ChatGroq
+from langchain_mongodb.chat_message_histories import MongoDBChatMessageHistory
+from passlib.hash import pbkdf2_sha256
+from uuid import uuid4
+import os 
+from dotenv import load_dotenv
+import prompt
+import json
+
+app = Flask(__name__)
+CORS(app)
+  
+# MongoDB Connection
+load_dotenv()
+username = os.getenv("MONGO_USERNAME")
+password = os.getenv("MONGO_PASSWORD")
+client = MongoClient(f"mongodb+srv://{username}:{password}@cluster0.hpg57sk.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0")
+db=client['my_db']
+chat_collection=db["chat_histories"]
+user_collection=db["user_data"]
+ 
+system_prompt = prompt.system_prompt()
+groq_api_key = os.getenv("GROQ_API_KEY")
+
+chat = ChatGroq(temperature=0 ,groq_api_key=groq_api_key , model_name="llama3-70b-8192")
+prompt = ChatPromptTemplate.from_messages(
+    [
+        ("system", system_prompt),
+        MessagesPlaceholder(variable_name="history"),
+        ("human", "{question}"),
+    ]
+)
+chain = prompt | chat
+chain_with_history = RunnableWithMessageHistory(
+    chain,
+    lambda session_id: MongoDBChatMessageHistory(
+        session_id=session_id,
+        connection_string=f"mongodb+srv://{username}:{password}@cluster0.hpg57sk.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0",
+        database_name="my_db",
+        collection_name="chat_histories",
+    ),
+    input_messages_key="question",
+    history_messages_key="history",
+)
+
+@app.route('/' , methods=["POST","GET"] )
+def main():
+    return jsonify({'message' : 'API calls successfully'}) , 201
+
+@app.route('/register' , methods=["POST"] )
+def register():
+    data = request.json
+    username = data.get("username")
+    password = data.get("password")
+
+    if user_collection.find_one({'username':username}):
+        return jsonify({'message':'Username already exists!'}) , 400
+
+    hashed_password = pbkdf2_sha256.hash(password)
+
+    user_collection.insert_one({
+        'username': username,
+        'password': hashed_password
+    })
+    return jsonify({'message' : 'User registered successfully'}) , 201
+
+
+@app.route('/login' , methods=["POST"] )
+def login():
+    data = request.json
+    username = data.get("username")
+    password = data.get("password")
+    
+    user = user_collection.find_one({'username':username})
+    
+    if user:
+        if  pbkdf2_sha256.verify(password , user["password"]):
+            return jsonify({ 'message' : 'Login Successful!'}) , 200
+        return jsonify({ 'message' : 'Password is not correct'}) , 401
+    else:
+        return jsonify({ 'message' : 'Invalid username' }) , 401  
+
+@app.route('/logout' , methods=["POST"])
+def logout():
+    data = request.json
+    username = data.get("username")
+    result = user_collection.delete_one({'username' : username})
+    if result.deleted_count == 1:
+        return jsonify({ 'message' : 'Logout successfully' }) , 201  
+    else:
+        return jsonify({ 'message' : 'User not found in database' }) , 401  
+
+@app.route('/chat' , methods=['POST'])
+def chat():
+    data = request.json
+    SessionId = data.get('SessionId') 
+    question = data.get('question') 
+    if not SessionId:
+        SessionId = str(uuid4())
+    
+    config = {"configurable": {"session_id": SessionId}}
+    response = chain_with_history.invoke({"question": question}, config=config)
+    print(response)
+    return jsonify({
+        'response' : str(response.content) , 
+        'SessionId' : SessionId
+    }) , 200
+
+@app.route('/history' , methods=['POST'])
+def history():
+    user_chats = []
+    data = request.json
+    SessionId = data.get('SessionId')
+    try :
+        cur = chat_collection.find({"SessionId":SessionId})
+        for doc in cur:
+            role = json.loads(doc["History"])['type'] 
+            content = json.loads(doc["History"])['data']['content']
+            user_chats.append({'role':role , 'content':content})
+        return jsonify({
+            'response' : user_chats
+        }) , 200
+    except:
+        return jsonify({
+            'response' : 'error while fetching chat history'
+        }) , 400
+        
+    
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=5000)

prompt.py

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+def system_prompt():
+    prompt = """
+        You are an AI English teacher. Your purpose is to assist users in improving their English language skills through clear explanations, practice exercises, and constructive feedback.
+
+        Key Guidelines:
+
+        Tone and Approach:
+
+        Be friendly, encouraging, and patient.
+        Adjust your teaching style to the user's proficiency level and goals.
+        Clarity and Simplicity:
+
+        Provide clear and simple explanations.
+        Use examples to illustrate concepts.
+        Feedback and Correction:
+
+        Offer constructive feedback on grammar, vocabulary, and pronunciation.
+        Suggest corrections in a supportive manner.
+        Engagement and Practice:
+
+        Encourage active participation and practice.
+        Provide exercises or questions to reinforce learning.
+        Adaptability:
+
+        Tailor your responses to the user’s needs, whether it’s conversational practice, grammar help, or vocabulary building.
+        Be sensitive to cultural and regional variations in English usage.
+        Examples:
+
+        Grammar Help: "Can you explain when to use 'a' vs. 'an'?"
+
+        AI: "'A' is used before words that start with a consonant sound, and 'an' is used before words that start with a vowel sound. For example, 'a cat' and 'an apple'."
+        Conversational Practice: "How can I improve my spoken English?"
+
+        AI: "Practice speaking regularly, listen to native speakers, and try repeating phrases. Let's practice a conversation now. How was your day?"
+        Vocabulary Building: "What does 'meticulous' mean?"
+
+        AI: "'Meticulous' means showing great attention to detail. For example, 'She was meticulous in organizing her notes.'"
+        Limitations:
+
+        Avoid giving personal advice outside of language learning.
+        Do not store or request personal information unless necessary for learning tasks.
+        Encouragement:
+
+        Always be positive and motivate users to keep practicing and learning.
+        """
+    return prompt 
+