Update app.py

app.py

@@ -25,7 +25,7 @@ if not os.path.exists(FAISS_INDEX_DIR):
 # Dictionary to store user-specific vectorstores
 user_vectorstores = {}
 
-# Custom CSS with adjustments for chatbot height, scrollability, and resizability
+# Custom CSS with green theme and modern chatbot
 custom_css = """
 :root {
     --primary-green: #10B981;
@@ -80,16 +80,14 @@ body {
     border-top: 1px solid var(--border-grey); 
     box-shadow: 0 -2px 10px rgba(0,0,0,0.1); 
     padding: 10px; 
-    height: 300px;  /* Reduced initial height */
+    height: 40vh; 
     display: flex; 
     flex-direction: column; 
     z-index: 1000; 
-    resize: vertical;  /* Allows manual resizing */
-    overflow: hidden;  /* Prevents overflow during resizing */
 }
 .chatbot { 
     flex-grow: 1; 
-    overflow-y: auto;  /* Ensures history is scrollable */
+    overflow-y: auto; 
     padding: 10px; 
 }
 .message-user { 
@@ -165,14 +163,102 @@ body {
 }
 """
 
-# [Functions process_pdf, generate_response, update_pdf_viewer, update_image remain unchanged]
+# Function to process PDF files
+def process_pdf(pdf_file):
+    if pdf_file is None:
+        return None, "No file uploaded", {"page_images": [], "total_pages": 0, "total_words": 0}
+    try:
+        session_id = str(uuid.uuid4())
+        with tempfile.NamedTemporaryFile(suffix=".pdf", delete=False) as temp_file:
+            temp_file.write(pdf_file)
+            pdf_path = temp_file.name
+        
+        doc = fitz.open(pdf_path)
+        texts = [page.get_text() for page in doc]
+        page_images = []
+        for page in doc:
+            pix = page.get_pixmap()
+            img_bytes = pix.tobytes("png")
+            img_base64 = base64.b64encode(img_bytes).decode("utf-8")
+            page_images.append(img_base64)
+        total_pages = len(doc)
+        total_words = sum(len(text.split()) for text in texts)
+        doc.close()
+
+        text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
+        chunks = text_splitter.create_documents(texts)
+        
+        vectorstore = FAISS.from_documents(chunks, embeddings)
+        index_path = os.path.join(FAISS_INDEX_DIR, session_id)
+        vectorstore.save_local(index_path)
+        user_vectorstores[session_id] = vectorstore
+
+        os.unlink(pdf_path)
+        pdf_state = {"page_images": page_images, "total_pages": total_pages, "total_words": total_words}
+        return session_id, f"✅ Successfully processed {len(chunks)} text chunks from your PDF", pdf_state
+    except Exception as e:
+        if "pdf_path" in locals() and os.path.exists(pdf_path):
+            os.unlink(pdf_path)
+        return None, f"Error processing PDF: {str(e)}", {"page_images": [], "total_pages": 0, "total_words": 0}
+
+# Function to generate chatbot responses
+def generate_response(message, session_id, model_name, history):
+    if not message:
+        return history
+    try:
+        context = ""
+        if session_id and session_id in user_vectorstores:
+            vectorstore = user_vectorstores[session_id]
+            docs = vectorstore.similarity_search(message, k=3)
+            if docs:
+                context = "\n\nRelevant information from uploaded PDF:\n" + "\n".join(f"- {doc.page_content}" for doc in docs)
+        system_prompt = "You are a financial analyst adept at summarizing reports and extracting key metrics."
+        if context:
+            system_prompt += " Use the following context to answer the question if relevant: " + context
+        completion = client.chat.completions.create(
+            model=model_name,
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": message}
+            ],
+            temperature=0.7,
+            max_tokens=1024
+        )
+        response = completion.choices[0].message.content
+        history.append((message, response))
+        return history
+    except Exception as e:
+        history.append((message, f"Error generating response: {str(e)}"))
+        return history
+
+# Function to update the PDF viewer with the first page
+def update_pdf_viewer(pdf_state):
+    if not pdf_state["total_pages"]:
+        return 0, None, "No PDF uploaded yet"
+    try:
+        img_data = base64.b64decode(pdf_state["page_images"][0])
+        img = Image.open(io.BytesIO(img_data))
+        return pdf_state["total_pages"], img, f"**Total Pages:** {pdf_state['total_pages']}\n**Total Words:** {pdf_state['total_words']}"
+    except Exception as e:
+        print(f"Error decoding image: {e}")
+        return 0, None, "Error displaying PDF"
+
+# Function to update the displayed PDF page based on the slider value
+def update_image(page_num, pdf_state):
+    if not pdf_state["total_pages"] or page_num < 1 or page_num > pdf_state["total_pages"]:
+        return None
+    try:
+        img_data = base64.b64decode(pdf_state["page_images"][page_num - 1])
+        img = Image.open(io.BytesIO(img_data))
+        return img
+    except Exception as e:
+        print(f"Error decoding image: {e}")
+        return None
 
 # Gradio interface
 with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
     current_session_id = gr.State(None)
     pdf_state = gr.State({"page_images": [], "total_pages": 0, "total_words": 0})
-    chat_height = gr.State(300)  # Initial chatbot height in pixels
-
     gr.HTML("""
     <div class="header">
         <div class="header-title">Fin-Vision</div>
@@ -191,8 +277,6 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
                 value="llama3-70b-8192",
                 label="Select Groq Model"
             )
-            # Add a slider to adjust chatbot height
-            height_slider = gr.Slider(minimum=100, maximum=600, step=10, value=300, label="Chatbot Height (px)")
         with gr.Column(scale=2, min_width=600):
             with gr.Tabs():
                 with gr.TabItem("PDF Viewer"):
@@ -203,7 +287,7 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
 
     # Chatbot at the bottom
     with gr.Column(elem_classes="chat-container"):
-        chatbot = gr.Chatbot(elem_classes="chatbot", height=chat_height.value, bubble_full_width=False, show_copy_button=True)
+        chatbot = gr.Chatbot(elem_classes="chatbot", height="100%", bubble_full_width=False, show_copy_button=True)
         with gr.Row(elem_classes="input-area"):
             msg = gr.Textbox(show_label=False, placeholder="Ask about your financial report...", elem_classes="input-box")
             send_btn = gr.Button("Send", elem_classes="send-btn")
@@ -243,13 +327,6 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
         inputs=[page_slider, pdf_state],
         outputs=[pdf_image]
     )
-    
-    # Update chatbot height dynamically with the slider
-    height_slider.change(
-        lambda height: gr.update(height=height),
-        inputs=[height_slider],
-        outputs=[chatbot]
-    )
 
 # Launch the app
 if __name__ == "__main__":