Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,303 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import uuid
+import hashlib
+from typing import List, Optional, Dict, Any, TypedDict,Generic, TypeVar
+from huggingface_hub import login
+import logging
+import time
+import os
+from dotenv import load_dotenv
+from langgraph_init import upload_documents, submit_feedback, get_conversations,get_conversation_history, chat_with_rag, login_hf
+# --- 1. Configuration ---
+# API_URL = "https://sra25-fastapi-backend.hf.space"
+# API_URL = "http://localhost:8000"
 
-"""
-# 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])),
-    ))
+load_dotenv()
+login_hf()
+# hf_token = os.getenv("hf_user_token")
+# login(hf_token)
+
+# --- 1. Database Setup ---
+
+
+# --- 2. Streamlit UI Components and State Management ---
+st.set_page_config(page_title="Conversational RAG Chatbot", layout="wide")
+st.title("💬 Conversational RAG Chatbot")
+st.caption("Powered by a FastAPI backend")
+
+# Initialize session state for conversations, messages, and the current session ID
+if "conversations" not in st.session_state:
+    st.session_state.conversations = []
+if "session_id" not in st.session_state:
+    st.session_state.session_id = str(uuid.uuid4())
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+if "retriever_ready" not in st.session_state:
+    st.session_state.retriever_ready = False
+if "feedback_given" not in st.session_state:
+    st.session_state.feedback_given = {}
+# New state variable to handle negative feedback comments
+if "negative_feedback_for" not in st.session_state:
+    st.session_state.negative_feedback_for = None
+
+# Initialize session state for storing uploaded file hashes
+if 'uploaded_file_hashes' not in st.session_state:
+    st.session_state.uploaded_file_hashes = set()
+if 'uploaded_files_info' not in st.session_state:
+    st.session_state.uploaded_files_info = []
+
+def get_file_hash(file):
+    """Generates a unique hash for a file using its name, size, and content."""
+    hasher = hashlib.sha256()
+    # Read a small chunk of the file to ensure content-based uniqueness
+    # Combine with file name and size for a robust identifier
+    file_content = file.getvalue()
+    hasher.update(file.name.encode('utf-8'))
+    hasher.update(str(file.size).encode('utf-8'))
+    hasher.update(file_content[:1024])  # Use first 1KB of content
+    return hasher.hexdigest()
+# --- 3. Helper Functions for Backend Communication ---
+# def send_documents_to_backend(uploaded_files):
+#     try:
+#         for file in uploaded_files:
+#             process_status = upload_documents(file)
+#         return process_status
+#     except Exception as e:
+#         st.error(f"Error processing documents: {e}")
+#         return None
+
+def send_chat_message_to_backend(prompt: str, chat_history: List[Dict[str, Any]]):
+    """Sends a chat message to the FastAPI backend and handles the response."""
+    if not prompt.strip():
+        return {"empty":"Invalid Question"}
+    history_for_api = [
+        {"role": msg.get("role"), "content": msg.get("content")} 
+        for msg in chat_history
+    ]
+    
+    payload = {
+        "user_question": str(prompt),
+        "session_id": st.session_state.session_id,
+        "chat_history": history_for_api,
+    }
+    print(f"Sending payload: {payload}")  # Debug print
+    response_dict = chat_with_rag(payload)
+    try:
+        return response_dict
+    except Exception as e:
+        st.error(f"Error communicating with the backend")
+        print(f"Error communicating with the backend: {e}")
+        return None
+
+def send_feedback_to_backend(telemetry_entry_id: str, feedback_score: int, feedback_text: Optional[str] = None):
+    """Sends feedback to the FastAPI backend."""
+    payload = {
+        "session_id": st.session_state.session_id,
+        "telemetry_entry_id": telemetry_entry_id,
+        "feedback_score": feedback_score,
+        "feedback_text": feedback_text
+    }
+    try:
+        # response = requests.post(f"{API_URL}/feedback", json=payload)
+        response = submit_feedback(payload)
+        # response.raise_for_status()
+        st.toast("Feedback submitted! Thank you.")
+    except Exception as e:
+        st.error(f"Error submitting feedback: {e}")
+
+def get_conversations_from_backend() -> list:
+    """Fetches a list of all conversations from the backend."""
+    try:
+        # response = requests.get(f"{API_URL}/conversations")
+        response = get_conversations()
+        # response.raise_for_status()
+        return response
+    except Exception as e:
+        st.sidebar.error(f"Error fetching conversations: {e}")
+        return []
+
+def get_conversation_history_from_backend(session_id: str):
+    """Fetches the messages for a specific conversation ID."""
+    try:
+        # response = requests.get(f"{API_URL}/conversations/{session_id}")
+
+        response = get_conversation_history(session_id)
+        return response
+    except Exception as e:
+        st.error(f"Error loading conversation history: {e}")
+        return None
+
+def handle_positive_feedback(telemetry_id):
+    """Handles positive feedback submission."""
+    send_feedback_to_backend(telemetry_id, 1)
+    st.session_state.feedback_given[telemetry_id] = True
+
+
+def handle_negative_feedback_comment_submit(telemetry_id, comment_text):
+    """Handles the negative feedback comment submission."""
+    send_feedback_to_backend(telemetry_id, -1, comment_text)
+    st.session_state.feedback_given[telemetry_id] = True
+    st.session_state.negative_feedback_for = None
+
+
+def refresh_conversations():
+    """Refreshes the conversation list in the sidebar."""
+    st.session_state.conversations = get_conversations_from_backend()
+
+# --- 4. Sidebar for Document Upload and Conversation History ---
+with st.sidebar:
+    st.header("Upload Documents")
+    uploaded_files = st.file_uploader(
+        "Upload Text, PDF, Docx files:",
+        type=["txt","pdf","docx"],
+        accept_multiple_files=True,
+        key="file_uploader"
+    )
+    if st.button("Process Documents", key="process_docs_button"):
+        if uploaded_files:
+            new_uploaded_files = []
+            newly_added_files_info = []
+            duplicate_file = []
+            for file in uploaded_files:
+                file_hash = get_file_hash(file)
+
+                if file_hash not in st.session_state.uploaded_file_hashes:
+                    st.session_state.uploaded_file_hashes.add(file_hash)
+                    new_uploaded_files.append(file)
+                    newly_added_files_info.append({"name": file.name, "size": file.size})
+                else:
+                    st.warning(f"File '{file.name}' has already been uploaded.")
+                    duplicate_file.append(file)
+
+            if new_uploaded_files:
+                st.session_state.uploaded_files_info.extend(newly_added_files_info)
+                with st.spinner("Processing documents..."):
+                    process_status = upload_documents(new_uploaded_files)
+                    if process_status:
+                        st.session_state.retriever_ready = True
+                        # st.success(response_data.get("message", "Documents processed and knowledge base ready!"))
+                        st.success(process_status)
+                        st.session_state.messages = []
+                        refresh_conversations() # sql query need to be added here
+                    else:
+                        st.session_state.retriever_ready = False
+                        st.error("Failed to process documents.")
+            elif duplicate_file:
+                # st.session_state.uploaded_files_info.extend(newly_added_files_info)
+                with st.spinner("Processing documents..."):
+                    process_status = upload_documents(duplicate_file)
+                    if process_status:
+                        st.session_state.retriever_ready = True
+                        # st.success(response_data.get("message", "Documents processed and knowledge base ready!"))
+                        st.success(process_status)
+                        st.session_state.messages = []
+                        refresh_conversations()
+                    else:
+                        st.session_state.retriever_ready = False
+                        st.error("Failed to process documents.")
+        else:
+            st.warning("Please upload at least one document to process.")
+
+    st.markdown("---")
+    st.header("Conversations")
+    if st.button("➕ New Chat", key="new_chat_button", use_container_width=True, type="primary"):
+        st.session_state.session_id = str(uuid.uuid4())
+        st.session_state.messages = []
+        st.session_state.feedback_given = {}
+        st.session_state.negative_feedback_for = None
+        refresh_conversations()
+        st.rerun()
+    
+    refresh_conversations()
+    
+    if st.session_state.conversations:
+        for conv in st.session_state.conversations:
+            if st.button(
+                conv["title"], 
+                key=f"conv_{conv['session_id']}",
+                use_container_width=True
+            ):
+                if st.session_state.session_id != conv["session_id"]:
+                    st.session_state.session_id = conv["session_id"]
+                    history = get_conversation_history_from_backend(conv["session_id"])
+                    if history != [] or history != None:
+                        st.session_state.messages = history
+                        st.session_state.feedback_given = {msg.get("telemetry_id"): True for msg in history if msg.get("telemetry_id")}
+                    else:
+                        st.session_state.messages = []
+                    st.session_state.negative_feedback_for = None
+                    st.rerun()
+
+# --- 5. Main Chat Interface ---
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+        
+    # Display feedback buttons for the last AI response
+    if message["role"] == "assistant" and message.get("telemetry_id") and not st.session_state.feedback_given.get(message["telemetry_id"], False):
+        col1, col2 = st.columns(2)
+        with col1:
+            if st.button("👍", key=f"positive_{message['telemetry_id']}", on_click=handle_positive_feedback, args=(message['telemetry_id'],)):
+                pass
+        with col2:
+            if st.button("👎", key=f"negative_{message['telemetry_id']}"):
+                st.session_state.negative_feedback_for = message['telemetry_id']
+                st.rerun()
+        
+        # --- NEW LOGIC FOR NEGATIVE FEEDBACK COMMENT ---
+        # Only render the comment input if this is the message the user clicked thumbs down on
+        if st.session_state.negative_feedback_for == message['telemetry_id']:
+            with st.container():
+                comment = st.text_area(
+                    "Please provide some details (optional):", 
+                    key=f"feedback_text_{message['telemetry_id']}"
+                )
+                if st.button("Submit Comment", key=f"submit_feedback_button_{message['telemetry_id']}"):
+                    handle_negative_feedback_comment_submit(message['telemetry_id'], comment)
+
+# Chat input for new questions
+if st.session_state.retriever_ready:
+    if prompt := st.chat_input("Ask me anything about the uploaded documents..."):
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        with st.chat_message("user"):
+            st.markdown(prompt)
+
+        with st.chat_message("assistant"):
+            with st.spinner("Thinking..."):
+                response_data = send_chat_message_to_backend(prompt, st.session_state.messages)
+                if response_data:
+                    if response_data.get("is_restricted"):
+                        ai_response = response_data.get("ai_response", "Sorry, I couldn't generate a response.")
+                        reason = response_data.get("moderation_reason")
+                        st.markdown(ai_response)
+                        st.markdown(reason)
+                    elif response_data.get("empty"):
+                        st.markdown(response_data.get("empty"))
+                        
+                    ai_response = response_data.get("ai_response", "Sorry, I couldn't generate a response.")
+                    telemetry_id = response_data.get("telemetry_entry_id")
+
+                    st.markdown(ai_response)
+                    
+                    st.session_state.messages.append({
+                        "role": "assistant",
+                        "content": ai_response,
+                        "telemetry_id": telemetry_id
+                    })
+                    
+                    refresh_conversations()
+                    
+                    if telemetry_id:
+                        col1, col2 = st.columns(2)
+                        with col1:
+                            if st.button("👍", key=f"positive_{telemetry_id}", on_click=handle_positive_feedback, args=(telemetry_id,)):
+                                pass
+                        with col2:
+                            if st.button("👎", key=f"negative_{telemetry_id}"):
+                                st.session_state.negative_feedback_for = telemetry_id
+                                st.rerun()
+                else:
+                    st.markdown("An error occurred.")
+else:
+    st.info("Please upload and process documents to start chatting.")