Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,225 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import os
+import json
+from datetime import datetime
+import PyPDF2
+import google.generativeai as genai
+
+# --- Configuration and Setup ---
+CLASSROOMS_DIR = "classrooms"
+if not os.path.exists(CLASSROOMS_DIR):
+    os.makedirs(CLASSROOMS_DIR)
+
+# --- Helper Functions ---
+
+def extract_text_from_pdf(pdf_files):
+    """Extracts text from a list of uploaded PDF files."""
+    full_text = ""
+    for pdf_file in pdf_files:
+        try:
+            pdf_reader = PyPDF2.PdfReader(pdf_file)
+            for page in pdf_reader.pages:
+                full_text += page.extract_text() + "\n"
+        except Exception as e:
+            st.error(f"Error reading {pdf_file.name}: {e}")
+    return full_text
+
+def save_classroom_data(class_name, api_key, context):
+    """Saves the classroom data (context, API key, and chat log)."""
+    class_dir = os.path.join(CLASSROOMS_DIR, class_name)
+    if not os.path.exists(class_dir):
+        os.makedirs(class_dir)
+
+    # Save context
+    with open(os.path.join(class_dir, "context.txt"), "w", encoding="utf-8") as f:
+        f.write(context)
+
+    # Save API key
+    with open(os.path.join(class_dir, "api_key.txt"), "w") as f:
+        f.write(api_key)
+
+    # Initialize chat log
+    with open(os.path.join(class_dir, "chat_log.json"), "w") as f:
+        json.dump([], f)
+
+    return True
+
+def get_gemini_response(api_key, context, chat_history, question):
+    """Generates a response from the Gemini API based on the context."""
+    try:
+        genai.configure(api_key=api_key)
+        model = genai.GenerativeModel('gemini-pro')
+
+        # Construct a more detailed prompt for the model
+        prompt = (
+            "You are a helpful classroom assistant. Your role is to answer questions based ONLY on the provided context. "
+            "If the answer is not found in the context, you must state that you cannot answer the question based on the provided material. "
+            "Do not use any external knowledge.\n\n"
+            f"**Context:**\n{context}\n\n"
+            "**Chat History:**\n"
+        )
+
+        for message in chat_history:
+             prompt += f"{message['role']}: {message['content']}\n"
+
+        prompt += f"**New Question:**\n{question}\n\n**Answer:**"
+
+
+        response = model.generate_content(prompt)
+        return response.text
+    except Exception as e:
+        return f"An error occurred with the Gemini API: {e}"
+
+def log_interaction(class_name, user_query, bot_response):
+    """Logs the student's interaction in the classroom's JSON file."""
+    log_file = os.path.join(CLASSROOMS_DIR, class_name, "chat_log.json")
+    try:
+        with open(log_file, "r+") as f:
+            logs = json.load(f)
+            logs.append({
+                "timestamp": datetime.now().isoformat(),
+                "user_query": user_query,
+                "bot_response": bot_response
+            })
+            f.seek(0)
+            json.dump(logs, f, indent=4)
+    except (FileNotFoundError, json.JSONDecodeError):
+        # If file is empty or corrupt, start a new log
+        with open(log_file, "w") as f:
+            json.dump([{
+                "timestamp": datetime.now().isoformat(),
+                "user_query": user_query,
+                "bot_response": bot_response
+            }], f, indent=4)
+
+
+# --- Streamlit UI ---
+
+st.set_page_config(page_title="Classroom Chatbot", layout="wide")
+
+# Initialize session state variables
+if 'role' not in st.session_state:
+    st.session_state.role = None
+if 'class_name' not in st.session_state:
+    st.session_state.class_name = None
+if 'chat_history' not in st.session_state:
+    st.session_state.chat_history = []
+
+
+# --- Main App Logic ---
+
+# Role Selection
+if st.session_state.role is None:
+    st.title("Welcome to the Classroom Chatbot! 📚")
+    st.write("Please select your role to begin.")
+    col1, col2 = st.columns(2)
+    with col1:
+        if st.button("I am a Faculty Member", use_container_width=True):
+            st.session_state.role = "Faculty"
+            st.rerun()
+    with col2:
+        if st.button("I am a Student", use_container_width=True):
+            st.session_state.role = "Student"
+            st.rerun()
+
+# --- Faculty View ---
+elif st.session_state.role == "Faculty":
+    st.title("🎓 Faculty Dashboard")
+    st.header("Create a New Classroom")
+
+    with st.form("create_classroom_form"):
+        class_name = st.text_input("Classroom Name / Code", help="A unique name for your class, e.g., 'CS101-Fall24'")
+        api_key = st.text_input("Google Gemini API Key", type="password", help="Your API key will be stored securely for this classroom's use.")
+        uploaded_files = st.file_uploader(
+            "Upload Course Materials (PDFs only)",
+            type="pdf",
+            accept_multiple_files=True
+        )
+        submitted = st.form_submit_button("Create Classroom")
+
+        if submitted:
+            if not class_name or not api_key or not uploaded_files:
+                st.warning("Please fill out all fields and upload at least one document.")
+            elif os.path.exists(os.path.join(CLASSROOMS_DIR, class_name)):
+                 st.error(f"A classroom with the name '{class_name}' already exists. Please choose a different name.")
+            else:
+                with st.spinner("Processing documents and setting up classroom..."):
+                    context = extract_text_from_pdf(uploaded_files)
+                    if context:
+                        save_classroom_data(class_name, api_key, context)
+                        st.success(f"Classroom '{class_name}' created successfully!")
+                        st.info(f"Students can now join using the code: **{class_name}**")
+                    else:
+                        st.error("Could not extract any text from the uploaded PDFs. Please check the files and try again.")
+
+    if st.button("Go Back to Role Selection"):
+        for key in st.session_state.keys():
+            del st.session_state[key]
+        st.rerun()
+
+
+# --- Student View ---
+elif st.session_state.role == "Student":
+    st.title("🧑‍🎓 Student Portal")
+
+    # Student joins a class
+    if st.session_state.class_name is None:
+        st.header("Join a Classroom")
+        class_name_input = st.text_input("Enter the Classroom Code provided by your faculty:")
+        if st.button("Join"):
+            class_dir = os.path.join(CLASSROOMS_DIR, class_name_input)
+            if os.path.isdir(class_dir):
+                st.session_state.class_name = class_name_input
+                st.success(f"Successfully joined classroom: {class_name_input}")
+                st.rerun()
+            else:
+                st.error("Invalid classroom code. Please check with your faculty.")
+        if st.button("Go Back to Role Selection"):
+            for key in st.session_state.keys():
+                del st.session_state[key]
+            st.rerun()
+
+    # Chat interface for joined students
+    else:
+        st.header(f"Chatbot for: {st.session_state.class_name}")
+        st.markdown("Ask questions about the course materials provided by your faculty.")
+
+        # Load classroom data
+        class_dir = os.path.join(CLASSROOMS_DIR, st.session_state.class_name)
+        try:
+            with open(os.path.join(class_dir, "context.txt"), "r", encoding="utf-8") as f:
+                context = f.read()
+            with open(os.path.join(class_dir, "api_key.txt"), "r") as f:
+                api_key = f.read().strip()
+        except FileNotFoundError:
+            st.error("Classroom data is missing. Please contact your faculty.")
+            st.stop()
+
+
+        # Display chat history
+        for message in st.session_state.chat_history:
+            with st.chat_message(message["role"]):
+                st.markdown(message["content"])
+
+        # Chat input
+        if prompt := st.chat_input("What is your question?"):
+            # Add user message to chat history
+            st.session_state.chat_history.append({"role": "user", "content": prompt})
+            with st.chat_message("user"):
+                st.markdown(prompt)
+
+            # Get bot response
+            with st.chat_message("assistant"):
+                with st.spinner("Thinking..."):
+                    response = get_gemini_response(api_key, context, st.session_state.chat_history, prompt)
+                    st.markdown(response)
+
+            # Add bot response to chat history and log it
+            st.session_state.chat_history.append({"role": "assistant", "content": response})
+            log_interaction(st.session_state.class_name, prompt, response)
+
+        if st.button("Leave Classroom"):
+            st.session_state.class_name = None
+            st.session_state.chat_history = []
+            st.rerun()
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))