Update app.py

app.py

@@ -27,60 +27,83 @@ if "history" not in st.session_state:
 if "authenticated" not in st.session_state:
     st.session_state.authenticated = False
 
-# Sidebar
+# Sidebar with BSNL logo and authentication
 with st.sidebar:
     try:
         st.image("bsnl_logo.png", width=200)
     except FileNotFoundError:
-        st.warning("Logo missing: 'bsnl_logo.png' not found.")
+        st.warning("BSNL logo not found.")
 
     st.header("RAG Control Panel")
     api_key_input = st.text_input("Enter RAG Access Key", type="password")
 
-    if st.button("Authenticate"):
-        if api_key_input == RAG_ACCESS_KEY:
-            st.session_state.authenticated = True
-            st.success("Authenticated successfully!")
-        else:
-            st.error("Invalid RAG Access Key.")
+    # Custom style for Authenticate button
+    st.markdown("""
+        <style>
+        .auth-button button {
+            background-color: #007BFF !important;
+            color: white !important;
+            font-weight: bold;
+            border-radius: 8px;
+            padding: 10px 20px;
+            border: none;
+            transition: all 0.3s ease;
+        }
+        .auth-button button:hover {
+            background-color: #0056b3 !important;
+            transform: scale(1.05);
+        }
+        </style>
+    """, unsafe_allow_html=True)
+
+    with st.container():
+        st.markdown('<div class="auth-button">', unsafe_allow_html=True)
+        if st.button("Authenticate"):
+            if api_key_input == RAG_ACCESS_KEY:
+                st.session_state.authenticated = True
+                st.success("Authentication successful!")
+            else:
+                st.error("Invalid API key.")
+        st.markdown('</div>', unsafe_allow_html=True)
 
     if st.session_state.authenticated:
-        input_data = st.file_uploader("Upload PDF file", type=["pdf"])
-
-        if input_data:
-            if input_data.type != "application/pdf":
-                st.error("Only PDF files are allowed.")
-            elif st.button("Process File"):
-                try:
-                    vector_store = process_input(input_data)
-                    st.session_state.vectorstore = vector_store
-                    st.success("File processed successfully. You can now ask questions.")
-                except (PermissionError, OSError) as e:
-                    st.error(f"File error: {str(e)}")
-                except Exception as e:
-                    if "403" in str(e):
-                        st.error("Access Denied (403): Check Hugging Face API token.")
-                    else:
-                        st.error(f"Unexpected error: {str(e)}")
-
-        # Chat History
-        st.subheader("Chat History")
-        for i, (q, a) in enumerate(st.session_state.history):
-            st.write(f"**Q{i+1}:** {q}")
-            st.write(f"**A{i+1}:** {a}")
-            st.markdown("---")
-
-# Main area
+        input_data = st.file_uploader("Upload a PDF file", type=["pdf"])
+
+        if st.button("Process File") and input_data is not None:
+            try:
+                vector_store = process_input(input_data)
+                st.session_state.vectorstore = vector_store
+                st.success("File processed successfully. You can now ask questions.")
+            except Exception as e:
+                st.error(f"Processing failed: {str(e)}")
+
+    st.subheader("Chat History")
+    for i, (q, a) in enumerate(st.session_state.history):
+        st.write(f"**Q{i+1}:** {q}")
+        st.write(f"**A{i+1}:** {a}")
+        st.markdown("---")
+
+# Main app UI
 def main():
+    st.markdown("""
+        <style>
+        .stApp {
+            font-family: 'Roboto', sans-serif;
+            background-color: #FFFFFF;
+            color: #333;
+        }
+        </style>
+    """, unsafe_allow_html=True)
+
     st.title("RAG Q&A App with Mistral AI")
-    st.markdown("Welcome to the BSNL RAG App. Upload a PDF and ask questions!")
+    st.markdown("Welcome to the BSNL RAG App! Upload a PDF and ask questions.")
 
     if not st.session_state.authenticated:
-        st.warning("Please authenticate using your RAG Access Key in the sidebar.")
+        st.warning("Please authenticate using the sidebar.")
         return
 
     if st.session_state.vectorstore is None:
-        st.info("Please upload and process a PDF file in the sidebar.")
+        st.info("Please upload and process a PDF file.")
         return
 
     query = st.text_input("Enter your question:")
@@ -91,46 +114,44 @@ def main():
                 st.session_state.history.append((query, answer))
                 st.write("**Answer:**", answer)
             except Exception as e:
-                st.error(f"Failed to generate answer: {str(e)}")
+                st.error(f"Error generating answer: {str(e)}")
 
+# PDF processing logic
 def process_input(input_data):
     os.makedirs("vectorstore", exist_ok=True)
     os.chmod("vectorstore", 0o777)
 
     progress_bar = st.progress(0)
-    status = st.status("Processing PDF...", expanded=True)
+    status = st.status("Processing PDF file...", expanded=True)
 
     status.update(label="Reading PDF file...")
     progress_bar.progress(0.2)
-
     pdf_reader = PdfReader(BytesIO(input_data.read()))
-    documents = "".join(page.extract_text() or "" for page in pdf_reader.pages)
+    documents = "".join([page.extract_text() or "" for page in pdf_reader.pages])
 
     status.update(label="Splitting text...")
     progress_bar.progress(0.4)
-
-    splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
-    texts = splitter.split_text(documents)
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
+    texts = text_splitter.split_text(documents)
 
     status.update(label="Creating embeddings...")
     progress_bar.progress(0.6)
-
-    embeddings = HuggingFaceEmbeddings(
+    hf_embeddings = HuggingFaceEmbeddings(
         model_name="sentence-transformers/all-mpnet-base-v2",
-        model_kwargs={"device": "cpu"}
+        model_kwargs={'device': 'cpu'}
     )
 
-    status.update(label="Building FAISS index...")
+    status.update(label="Building vector store...")
     progress_bar.progress(0.8)
-
-    dimension = len(embeddings.embed_query("sample text"))
+    dimension = len(hf_embeddings.embed_query("test"))
     index = faiss.IndexFlatL2(dimension)
     vector_store = FAISS(
-        embedding_function=embeddings,
+        embedding_function=hf_embeddings,
         index=index,
         docstore=InMemoryDocstore({}),
         index_to_docstore_id={}
     )
+
     uuids = [str(uuid.uuid4()) for _ in texts]
     vector_store.add_texts(texts, ids=uuids)
 
@@ -140,20 +161,22 @@ def process_input(input_data):
 
     status.update(label="Done!", state="complete")
     progress_bar.progress(1.0)
-
     return vector_store
 
+# Question-answering logic
 def answer_question(vectorstore, query):
-    llm = HuggingFaceHub(
-        repo_id="mistralai/Mistral-7B-Instruct-v0.1",
-        model_kwargs={"temperature": 0.7, "max_length": 512},
-        huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN
-    )
+    try:
+        llm = HuggingFaceHub(
+            repo_id="mistralai/Mistral-7B-Instruct-v0.1",
+            model_kwargs={"temperature": 0.7, "max_length": 512},
+            huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN
+        )
+    except Exception as e:
+        raise RuntimeError("Failed to load LLM. Check Hugging Face API key and access rights.") from e
 
     retriever = vectorstore.as_retriever(search_kwargs={"k": 3})
-
     prompt_template = PromptTemplate(
-        template="Use the provided context to answer the question concisely:\n\nContext: {context}\n\nQuestion: {question}\n\nAnswer:",
+        template="Use the context to answer the question concisely:\n\nContext: {context}\n\nQuestion: {question}\n\nAnswer:",
         input_variables=["context", "question"]
     )
 
@@ -168,5 +191,6 @@ def answer_question(vectorstore, query):
     result = qa_chain({"query": query})
     return result["result"].split("Answer:")[-1].strip()
 
+# Run the app
 if __name__ == "__main__":
     main()