Upload 5 files

Backend.py

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+import os
+import google.generativeai as generativeai
+from dotenv import load_dotenv
+
+# Load API key from environment
+load_dotenv()
+generativeai.configure(api_key=os.getenv("GOOGLE_GEMINI_KEY"))
+
+def get_correction_and_comments(code_snippet):
+    prompt = [
+        "Analyze and correct the following Python code, add comments, and format it:",
+        code_snippet
+    ]
+    response = generativeai.GenerativeModel('gemini-pro').generate_content(prompt)
+    return response.text if response else "No suggestions available."
+
+def generate_questions(question):
+    prompt = ["You are Python coding assistant generate only question and answer based of the given code"
+              , question]
+    response = generativeai.GenerativeModel('gemini-pro').generate_content(prompt)
+    return response.text if response else "No answer available."

frontend.py

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+import streamlit as st
+from Backend import get_correction_and_comments, generate_questions
+from logger import logger
+from pymongo import MongoClient, errors
+import interpreter
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+# Configure the page
+st.set_page_config(page_title="Interactive Code Assistant", layout="wide")
+st.title("✨ Interactive Code Assistant with Python Interpreter ✨")
+
+# Initialize session state for feedback to persist data
+if "helpful" not in st.session_state:
+    st.session_state.helpful = None  # Initialize feedback as None
+
+# Set up MongoDB connection
+try:
+    client = MongoClient(os.getenv("MONGO_URI"), serverSelectionTimeoutMS=5000)
+    client.server_info()  # Trigger an exception if MongoDB is not reachable
+    db = client["Capstone"]
+    feedback_collection = db["Feedback"]
+except errors.ServerSelectionTimeoutError:
+    st.error("Error: Could not connect to MongoDB. Please ensure MongoDB is running.")
+
+# Create two expanded columns for wider side-by-side text areas
+colu1, colu2 = st.columns([1, 1])  # Both columns have equal width
+
+# Text area in the first column for entering code
+with colu1:
+    st.subheader("Code Input")
+    code_input = st.text_area("Enter Your Python Code:", height=400, max_chars=10000)
+
+# Text area in the second column to display the output from Google Gemini
+with colu2:
+    st.subheader("Corrected Output")
+    gemini_output = st.empty()
+
+# Buttons for different functionalities
+col1, col2, col3 = st.columns([0.3, 0.3, 0.3])
+with col1:
+    if st.button("Run Code"):
+        try:
+            output = interpreter.run_code(code_input)
+            st.subheader("✨ Code Output ✨")
+            st.write(output)
+        except Exception as e:
+            st.error(f"Error: {e}")
+            logger.error(f"Code execution error: {e}")
+
+with col2:
+    if st.button("Generate Questions"):
+            # Generate questions automatically, displayed below the text boxes
+            generated_questions = generate_questions(code_input)
+            st.subheader("🤖 Model-Generated Questions")
+            st.write(f"Raw Response: {generated_questions}")
+
+                
+with col3:
+    if st.button("Corrected Code"):
+        logger.info("User requested code correction.")
+        corrected_code = get_correction_and_comments(code_input)
+        gemini_output.code(corrected_code, language="python")
+
+# Feedback form (outside of the columns, after all content)
+st.subheader("Feedback")
+st.session_state.helpful = st.radio("Were the questions helpful?", ("Yes", "No"))
+
+if st.button("Submit Feedback"):
+    if st.session_state.helpful is not None:
+        try:
+            feedback_collection.insert_one({"helpful": st.session_state.helpful})
+            st.success("Feedback submitted successfully.")
+        except Exception as e:
+            st.error(f"Failed to submit feedback: {e}")
+# Hide Streamlit's default menu and style adjustments for a cleaner look
+st.markdown(
+    """
+    <style>
+    .reportview-container .main .block-container {
+        padding-top: 1rem;
+        padding-bottom: 1rem;
+        max-width: 1200px;
+    }
+    .stTextArea {
+        font-size: 14px;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True
+)

interpreter.py

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+import io
+import sys
+from logger import logger
+
+def run_code(code):
+    # Redirect stdout to capture code output
+    old_stdout = sys.stdout
+    redirected_output = sys.stdout = io.StringIO()
+
+    try:
+        exec(code)
+    except Exception as e:
+        logger.error(f"Execution error: {e}")
+        return f"Error: {e}"
+    finally:
+        # Reset stdout
+        sys.stdout = old_stdout
+
+    return redirected_output.getvalue()

logger.py

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+import logging
+import pymongo
+from datetime import datetime
+from dotenv import load_dotenv
+import os 
+
+load_dotenv()
+
+# MongoDB setup
+client = pymongo.MongoClient(os.getenv("MONGO_URI"))
+db = client["Capstone"]
+log_collection = db["logs"]
+
+class MongoHandler(logging.Handler):
+    def emit(self, record):
+        log = {
+            "level": record.levelname,
+            "message": record.getMessage(),
+            "timestamp": datetime.now()
+        }
+        log_collection.insert_one(log)
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger("ProjectLogger")
+logger.addHandler(MongoHandler())

req.txt

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+googlegenrativeai
+requests
+numpy
+pandas
+torch
+huggingface
+logging
+maths 
+tktinker