Update app.py

app.py

@@ -1,142 +1,142 @@
-import streamlit as st
-import google.generativeai as genai
-from langchain.document_loaders import PyPDFDirectoryLoader
-import os
-import shutil
-
-# Configuration
-GOOGLE_API_KEY = "your_api_key_here"  # Replace with your actual API key
-
-# Page configuration
-st.set_page_config(page_title="Chat with PDFs", page_icon="📚")
-
-def initialize_session_state():
-    """Initialize session state variables"""
-    session_state_vars = {
-        "messages": [],
-        "loaded_files": False,
-        "pdf_content": None,
-        "chat": None
-    }
-    
-    for var, value in session_state_vars.items():
-        if var not in st.session_state:
-            st.session_state[var] = value
-
-def load_pdfs(pdf_folder):
-    """Load PDFs and return their content"""
-    if not os.path.exists(pdf_folder):
-        os.makedirs(pdf_folder)
-        
-    loader = PyPDFDirectoryLoader(pdf_folder)
-    documents = loader.load()
-    
-    # Concatenate all documents content
-    content = "\n\n".join([doc.page_content for doc in documents])
-    return content
-
-def initialize_chat(pdf_content):
-    """Initialize Gemini chat with PDF content"""
-    genai.configure(api_key="AIzaSyDXxoKVLaal5itTj981_ByYLtxok09MIRM")
-    
-    generation_config = {
-        "temperature": 0.7,
-        "top_p": 0.95,
-        "top_k": 40,
-        "max_output_tokens": 8192,
-    }
-    
-    model = genai.GenerativeModel(
-        model_name="gemini-1.5-pro",
-        generation_config=generation_config,
-    )
-    
-    # Start chat with context
-    context_prompt = f"""You are a helpful assistant that answers questions based on the following document content:
-
-{pdf_content}
-
-Please use this content to answer user questions. If the answer cannot be found in the content, say so."""
-
-    chat = model.start_chat(history=[])
-    # Send initial context
-    chat.send_message(context_prompt)
-    return chat
-
-def main():
-    initialize_session_state()
-    
-    st.title("💬 Chat with PDFs")
-    
-    # Sidebar for PDF upload
-    with st.sidebar:
-        st.header("Upload Documents")
-        uploaded_files = st.file_uploader(
-            "Upload your PDFs",
-            type=["pdf"],
-            accept_multiple_files=True
-        )
-
-        if uploaded_files and not st.session_state.loaded_files:
-            # Create pdfs directory if it doesn't exist
-            if not os.path.exists("pdfs"):
-                os.makedirs("pdfs")
-            
-            # Clean up old PDF files
-            for file in os.listdir("pdfs"):
-                os.remove(os.path.join("pdfs", file))
-            
-            # Save uploaded files
-            for file in uploaded_files:
-                with open(f"pdfs/{file.name}", "wb") as f:
-                    f.write(file.getvalue())
-            
-            # Load PDF content
-            with st.spinner("Processing PDFs..."):
-                try:
-                    pdf_content = load_pdfs("pdfs")
-                    st.session_state.pdf_content = pdf_content
-                    st.session_state.loaded_files = True
-                    
-                    # Initialize chat with content
-                    st.session_state.chat = initialize_chat(pdf_content)
-                except Exception as e:
-                    st.error(f"Error processing PDFs: {str(e)}")
-                    return
-
-    # Main chat interface
-    if st.session_state.loaded_files:
-        # Display chat messages
-        for message in st.session_state.messages:
-            with st.chat_message(message["role"]):
-                st.markdown(message["content"])
-
-        # Chat input
-        if prompt := st.chat_input("Ask a question about your PDFs:"):
-            # Add user message to chat history
-            st.session_state.messages.append({"role": "user", "content": prompt})
-            with st.chat_message("user"):
-                st.markdown(prompt)
-
-            with st.chat_message("assistant"):
-                response_placeholder = st.empty()
-                try:
-                    # Get response from Gemini
-                    if not st.session_state.chat:
-                        st.session_state.chat = initialize_chat(st.session_state.pdf_content)
-                    
-                    response = st.session_state.chat.send_message(prompt)
-                    response_text = response.text
-                    
-                    response_placeholder.markdown(response_text)
-                    
-                    # Add assistant response to chat history
-                    st.session_state.messages.append({"role": "assistant", "content": response_text})
-                except Exception as e:
-                    response_placeholder.error(f"Error generating response: {str(e)}")
-
-    else:
-        st.info("Please upload PDFs to start chatting.")
-
-if __name__ == "__main__":
-    main()
+import streamlit as st
+import google.generativeai as genai
+from langchain.document_loaders import PyPDFDirectoryLoader
+import os
+import shutil
+
+# Configuration
+GOOGLE_API_KEY = st.secrets["GOOGLE_API_KEY"]
+
+# Page configuration
+st.set_page_config(page_title="Chat with PDFs", page_icon="📚")
+
+def initialize_session_state():
+    """Initialize session state variables"""
+    session_state_vars = {
+        "messages": [],
+        "loaded_files": False,
+        "pdf_content": None,
+        "chat": None
+    }
+    
+    for var, value in session_state_vars.items():
+        if var not in st.session_state:
+            st.session_state[var] = value
+
+def load_pdfs(pdf_folder):
+    """Load PDFs and return their content"""
+    if not os.path.exists(pdf_folder):
+        os.makedirs(pdf_folder)
+        
+    loader = PyPDFDirectoryLoader(pdf_folder)
+    documents = loader.load()
+    
+    # Concatenate all documents content
+    content = "\n\n".join([doc.page_content for doc in documents])
+    return content
+
+def initialize_chat(pdf_content):
+    """Initialize Gemini chat with PDF content"""
+    genai.configure(api_key=GOOGLE_API_KEY)
+    
+    generation_config = {
+        "temperature": 0.7,
+        "top_p": 0.95,
+        "top_k": 40,
+        "max_output_tokens": 8192,
+    }
+    
+    model = genai.GenerativeModel(
+        model_name="gemini-1.5-pro",
+        generation_config=generation_config,
+    )
+    
+    # Start chat with context
+    context_prompt = f"""You are a helpful assistant that answers questions based on the following document content:
+
+{pdf_content}
+
+Please use this content to answer user questions. If the answer cannot be found in the content, say so."""
+
+    chat = model.start_chat(history=[])
+    # Send initial context
+    chat.send_message(context_prompt)
+    return chat
+
+def main():
+    initialize_session_state()
+    
+    st.title("💬 Chat with PDFs")
+    
+    # Sidebar for PDF upload
+    with st.sidebar:
+        st.header("Upload Documents")
+        uploaded_files = st.file_uploader(
+            "Upload your PDFs",
+            type=["pdf"],
+            accept_multiple_files=True
+        )
+
+        if uploaded_files and not st.session_state.loaded_files:
+            # Create pdfs directory if it doesn't exist
+            if not os.path.exists("pdfs"):
+                os.makedirs("pdfs")
+            
+            # Clean up old PDF files
+            for file in os.listdir("pdfs"):
+                os.remove(os.path.join("pdfs", file))
+            
+            # Save uploaded files
+            for file in uploaded_files:
+                with open(f"pdfs/{file.name}", "wb") as f:
+                    f.write(file.getvalue())
+            
+            # Load PDF content
+            with st.spinner("Processing PDFs..."):
+                try:
+                    pdf_content = load_pdfs("pdfs")
+                    st.session_state.pdf_content = pdf_content
+                    st.session_state.loaded_files = True
+                    
+                    # Initialize chat with content
+                    st.session_state.chat = initialize_chat(pdf_content)
+                except Exception as e:
+                    st.error(f"Error processing PDFs: {str(e)}")
+                    return
+
+    # Main chat interface
+    if st.session_state.loaded_files:
+        # Display chat messages
+        for message in st.session_state.messages:
+            with st.chat_message(message["role"]):
+                st.markdown(message["content"])
+
+        # Chat input
+        if prompt := st.chat_input("Ask a question about your PDFs:"):
+            # Add user message to chat history
+            st.session_state.messages.append({"role": "user", "content": prompt})
+            with st.chat_message("user"):
+                st.markdown(prompt)
+
+            with st.chat_message("assistant"):
+                response_placeholder = st.empty()
+                try:
+                    # Get response from Gemini
+                    if not st.session_state.chat:
+                        st.session_state.chat = initialize_chat(st.session_state.pdf_content)
+                    
+                    response = st.session_state.chat.send_message(prompt)
+                    response_text = response.text
+                    
+                    response_placeholder.markdown(response_text)
+                    
+                    # Add assistant response to chat history
+                    st.session_state.messages.append({"role": "assistant", "content": response_text})
+                except Exception as e:
+                    response_placeholder.error(f"Error generating response: {str(e)}")
+
+    else:
+        st.info("Please upload PDFs to start chatting.")
+
+if __name__ == "__main__":
+    main()