Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,74 +1,115 @@
 import streamlit as st
 import json
-from io import StringIO
+from datetime import datetime
 
-# Configure page
-st.set_page_config(page_title="Document Parser", layout="wide")
+# Page config
+st.set_page_config(page_title="Document Parser", layout="wide", page_icon="📄")
 
-# Session state for conversation history
+# Initialize state
 if "conversation" not in st.session_state:
     st.session_state.conversation = []
+if "last_question" not in st.session_state:
+    st.session_state.last_question = None
 
-# Sidebar: API key + temperature
+# Sidebar settings
 with st.sidebar:
     st.title("⚙️ Settings")
-    api_key = st.text_input("🔑 OpenAI API Key", type="password")
-    temperature = st.slider("🔥 Model Temperature", 0.0, 1.0, 0.0, 0.1)
+    api_key = st.text_input("🔑 OpenAI API Key", type="password", help="Paste your OpenAI API key")
+    temperature = st.slider("🔥 Model Temperature", 0.0, 1.0, 0.3, 0.05, help="Higher values make responses more creative.")
+    st.markdown("---")
+    st.caption("Built with ❤️ using Streamlit")
 
-# Main header
+# Title & instructions
 st.title("📄 Document Parser")
-st.markdown("Upload documents and chat with a GPT-4 powered assistant.")
+st.markdown("Upload your documents and ask questions powered by GPT-4 and LlamaIndex (or mock engine).")
 
-# Upload documents
+# File upload
 uploaded_files = st.file_uploader(
     "📤 Upload Documents (PDF, DOCX, TXT, etc.)",
     type=["pdf", "docx", "doc", "txt", "rtf", "html"],
     accept_multiple_files=True
 )
 
+# File display
 if uploaded_files:
     st.success(f"{len(uploaded_files)} document(s) uploaded.")
+    with st.expander("📚 Uploaded Files Overview"):
+        for file in uploaded_files:
+            st.write(f"• `{file.name}` ({round(file.size / 1024, 2)} KB)")
+        st.markdown("✅ Ready to ask questions.")
 else:
-    st.info("Please upload at least one document to continue.")
+    st.warning("⚠️ Please upload at least one document.")
+
+# Suggestive prompts
+if uploaded_files:
+    st.markdown("#### 💡 Suggested Questions")
+    suggestions = [
+        "What is the main topic of the documents?",
+        "Summarize the contents.",
+        "Are there any deadlines or dates mentioned?",
+        "What are the key takeaways?"
+    ]
+    for i, s in enumerate(suggestions):
+        if st.button(f"💬 {s}", key=f"suggestion_{i}"):
+            st.session_state.last_question = s
+
+# Text input
+question = st.text_input("🔎 Ask a question about your documents:", value=st.session_state.last_question or "")
 
-# Input for user question
-question = st.text_input("💬 Ask a question about your documents:")
+# Ask button
+ask_col, retry_col = st.columns([4, 1])
+with ask_col:
+    send = st.button("🚀 Ask")
+with retry_col:
+    retry = st.button("🔁 Retry")
 
-# Send button
-if st.button("🚀 Ask") and question and uploaded_files and api_key:
-    with st.spinner("Processing..."):
-        # Here you'd pass files + question + temperature + API key to your backend
-        # Replace this with real logic (e.g., LlamaIndex + OpenAI)
-        mock_answer = f"🧠 Based on the uploaded documents, here's a mock answer to: '{question}'"
+if (send or retry) and question and api_key and uploaded_files:
+    st.session_state.last_question = question
+    with st.spinner("Analyzing your documents..."):
+        # TODO: Replace this with actual LLM logic
+        mock_answer = f"🤖 Here's a simulated response to your question: **'{question}'**"
 
-        # Add to conversation history
-        st.session_state.conversation.append({"role": "user", "content": question})
-        st.session_state.conversation.append({"role": "assistant", "content": mock_answer})
+        # Tag this session
+        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
-# Display conversation
+        # Store in conversation
+        st.session_state.conversation.append({
+            "role": "user",
+            "content": question,
+            "timestamp": timestamp
+        })
+        st.session_state.conversation.append({
+            "role": "assistant",
+            "content": mock_answer,
+            "timestamp": timestamp
+        })
+
+elif send or retry:
+    st.error("Please make sure you've uploaded documents and provided an API key.")
+
+# Conversation history
 if st.session_state.conversation:
-    st.markdown("## 🧾 Conversation")
+    st.markdown("## 🧾 Conversation History")
     for msg in st.session_state.conversation:
-        if msg["role"] == "user":
-            st.markdown(f"**You:** {msg['content']}")
-        else:
-            st.markdown(f"**Assistant:** {msg['content']}")
+        author = "🧑 You" if msg["role"] == "user" else "🤖 Assistant"
+        st.markdown(f"**{author}** *(at {msg['timestamp']})*:\n\n{msg['content']}", unsafe_allow_html=True)
 
+    # Actions
     st.markdown("---")
-
-    # Download buttons
     col1, col2 = st.columns(2)
 
     with col1:
         if st.button("🗑️ Clear Conversation"):
             st.session_state.conversation = []
+            st.session_state.last_question = None
             st.experimental_rerun()
 
     with col2:
         format = st.selectbox("Download Format", ["TXT", "JSON"])
         if format == "TXT":
             content = "\n\n".join(
-                f"{msg['role'].capitalize()}:\n{msg['content']}" for msg in st.session_state.conversation
+                f"{msg['role'].capitalize()} ({msg['timestamp']}):\n{msg['content']}"
+                for msg in st.session_state.conversation
             )
             mime = "text/plain"
             filename = "conversation.txt"
@@ -77,4 +118,4 @@ if st.session_state.conversation:
             mime = "application/json"
             filename = "conversation.json"
 
-        st.download_button("📥 Download", content, filename=filename, mime=mime)
+        st.download_button("📥 Download", content, file_name=filename, mime=mime)