Final Changes

Dockerfile

@@ -1,4 +1,3 @@
-# Use an official, lightweight Python image
 FROM python:3.11-slim
 
 RUN apt-get update && apt-get install -y \
@@ -13,20 +12,13 @@ RUN apt-get update && apt-get install -y \
     poppler-utils \
     && rm -rf /var/lib/apt/lists/*
 
-# Set the working directory inside the container
 WORKDIR /app
 
-# Copy the requirements file and install dependencies
-# (We use standard pip inside the container because it's universally stable)
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Copy all your project files into the container
 COPY . .
 
-# Expose the port FastAPI runs on
-# Change this
 EXPOSE 7860
 
-# And change this
 CMD ["uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -2,12 +2,17 @@ import streamlit as st
 import requests
 import uuid
 
-# 1. PAGE CONFIGURATION
-st.set_page_config(page_title="Enterprise RAG Assistant", page_icon="🤖", layout="centered")
+st.set_page_config(
+    page_title="Enterprise RAG Assistant",
+    page_icon="🤖",
+    layout="centered"
+)
+
 st.title("📚 Enterprise Document Assistant")
-st.markdown("Upload a PDF to the knowledge base and ask questions about it.")
+st.markdown(
+    "Upload a PDF to the knowledge base and ask questions about it."
+)
 
-# 2. SESSION STATE INITIALIZATION (The Memory Bank)
 if "user_id" not in st.session_state:
     st.session_state.user_id = str(uuid.uuid4())
 
@@ -17,76 +22,105 @@ if "thread_id" not in st.session_state:
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
-# 3. SIDEBAR: PDF UPLOAD (The Handoff to FastAPI)
 with st.sidebar:
     st.header("Document Ingestion")
-    uploaded_file = st.file_uploader("Upload a PDF", type="pdf")
-    
+
+    uploaded_file = st.file_uploader(
+        "Upload a PDF",
+        type="pdf"
+    )
+
     if st.button("Process Document"):
         if uploaded_file:
             with st.spinner("Transmitting to backend..."):
-                # Package the file as multipart/form-data
-                files = {"file": (uploaded_file.name, uploaded_file.getvalue(), "application/pdf")}
+                files = {
+                    "file": (
+                        uploaded_file.name,
+                        uploaded_file.getvalue(),
+                        "application/pdf"
+                    )
+                }
+
+                payload_data = {
+                    "user_id": st.session_state.user_id
+                }
 
-                payload_data = {"user_id": st.session_state.user_id}
-                
-                # Send the POST request to your local FastAPI server
                 try:
                     response = requests.post(
-                        "http://127.0.0.1:8000/upload", 
+                        "http://127.0.0.1:8000/upload",
                         files=files,
                         data=payload_data
                     )
+
                     if response.status_code == 200:
-                        st.success("File uploaded! The AI is reading it in the background.")
+                        st.success(
+                            "File uploaded! The AI is reading it in the background."
+                        )
                     else:
-                        st.error(f"Upload failed: {response.text}")
+                        st.error(
+                            f"Upload failed: {response.text}"
+                        )
+
                 except requests.exceptions.ConnectionError:
-                    st.error("Cannot connect to backend. Is FastAPI running?")
+                    st.error(
+                        "Cannot connect to backend. Is FastAPI running?"
+                    )
         else:
             st.warning("Please select a file first.")
 
-# 4. CHAT HISTORY RENDERING
 for msg in st.session_state.messages:
-    # This creates a chat bubble. role is either 'user' or 'assistant'
     with st.chat_message(msg["role"]):
         st.markdown(msg["content"])
 
-# 5. CHAT INPUT & BACKEND COMMUNICATION
-if prompt := st.chat_input("Ask a question about your documents..."):
-    
-    # Immediately render the user's new message to the UI
-    st.session_state.messages.append({"role": "user", "content": prompt})
+if prompt := st.chat_input(
+    "Ask a question about your documents..."
+):
+    st.session_state.messages.append({
+        "role": "user",
+        "content": prompt
+    })
+
     with st.chat_message("user"):
         st.markdown(prompt)
 
-    # Show a loading indicator while we wait for FastAPI and LangGraph
     with st.chat_message("assistant"):
         message_placeholder = st.empty()
-        message_placeholder.markdown("*(Thinking...)*")
-        
-        # Prepare the JSON payload for FastAPI
+
+        message_placeholder.markdown(
+            "*(Thinking...)*"
+        )
+
         payload = {
             "message": prompt,
             "user_id": st.session_state.user_id,
             "thread_id": st.session_state.thread_id
         }
-        
+
         try:
-            # Send the question to your LangGraph backend
-            chat_response = requests.post("http://127.0.0.1:8000/chat", json=payload)
-            
+            chat_response = requests.post(
+                "http://127.0.0.1:8000/chat",
+                json=payload
+            )
+
             if chat_response.status_code == 200:
-                # Extract the answer from the JSON response
-                answer = chat_response.json().get("response", "No response found.")
-                
-                # Update the UI placeholder with the actual answer
+                answer = chat_response.json().get(
+                    "response",
+                    "No response found."
+                )
+
                 message_placeholder.markdown(answer)
-                
-                # Save the AI's answer to the session state memory
-                st.session_state.messages.append({"role": "assistant", "content": answer})
+
+                st.session_state.messages.append({
+                    "role": "assistant",
+                    "content": answer
+                })
+
             else:
-                message_placeholder.error(f"Error: {chat_response.text}")
-                
+                message_placeholder.error(
+                    f"Error: {chat_response.text}"
+                )
+
         except requests.exceptions.ConnectionError:
-            message_placeholder.error("Cannot connect to backend. Is FastAPI running?")
+            message_placeholder.error(
+                "Cannot connect to backend. Is FastAPI running?"
+            )

docker-compose.yaml

@@ -9,7 +9,6 @@ services:
       - "8000:8000"
     env_file:
       - .env
-    # This prevents the container from crashing immediately if it hits a tiny error
     restart: always 
 
   frontend:
@@ -20,7 +19,6 @@ services:
       - "8501:8501"
     env_file:
       - .env
-    # Tells Docker to start the backend BEFORE it starts the frontend
     depends_on:
       - backend
     restart: always

frontend.Dockerfile

@@ -7,8 +7,6 @@ RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .
 
-# Expose the port Streamlit runs on
 EXPOSE 8501
 
-# The command to start the UI
 CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]