Update app.py

app.py

@@ -1,155 +1,79 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-# Load model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("aaliyaan/t5-small-finetuned-career")
-model = AutoModelForSeq2SeqLM.from_pretrained("aaliyaan/t5-small-finetuned-career")
-
-# Function to generate a response from the model and maintain chat history
-def chat_with_gpt(user_input, chat_history):
-    # Tokenize the user input and generate response
-    inputs = tokenizer(user_input, return_tensors="pt", padding=True, truncation=True, max_length=512)
-    outputs = model.generate(**inputs, max_length=150, num_beams=5, early_stopping=True)
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
-    # Update chat history with the new user input and response
-    chat_history += f"You: {user_input}\nJobMatch AI: {response}\n"
-
-    # Return updated chat history and clear input box
-    return chat_history, ""
-
-# Define the Gradio interface
-def launch_gradio_interface():
-    # Create the Gradio Blocks for the layout
-    with gr.Blocks() as demo:
-        # Title and description section
-        gr.Markdown("<h1 style='color: #3A9FD6; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; font-weight: bold; text-align: center;'>JobMatch AI</h1>")
-        gr.Markdown("<p style='font-size: 18px; color: #333; text-align: center;'>Your trusted career assistant. Ask any job-related question, and get expert advice!</p>")
-
-        # Chat history display (above the input box)
-        chat_history = gr.Textbox(
-            label="Chat History",
-            interactive=False,
-            show_label=False,
-            placeholder="Chat history will appear here...",
-            lines=10,
-            max_lines=20,
-            elem_id="chat-history",
-            value="",  # Initial empty chat history
-            container=False  # To avoid any extra padding around this area
-        )
-
-        # User input and output textboxes
-        with gr.Row():
-            with gr.Column():
-                user_input = gr.Textbox(
-                    label="Ask JobMatch AI",
-                    placeholder="Type your job-related question here...",
-                    lines=2,
-                    max_lines=4,
-                    interactive=True,
-                    elem_id="user-input-textbox",
-                    show_label=False,
-                    container=False
-                )
-
-        # Button to submit input
-        submit_button = gr.Button("Submit", variant="primary")
-
-        # Link the button with the function (updates chat history and clears input)
-        submit_button.click(fn=chat_with_gpt, inputs=[user_input, chat_history], outputs=[chat_history, user_input])
-
-        # Custom CSS styling
-        demo.css = """
-        /* Body and Container Styling */
-        .gradio-container {
-            background: linear-gradient(135deg, #FF9A8B, #FF6A00);  /* Gradient background with warm colors */
-            border-radius: 15px;
-            box-shadow: 0px 6px 30px rgba(0, 0, 0, 0.1); /* Soft shadow for depth */
-            padding: 50px;
-            width: 70%;  /* Adjust width for centering */
-            margin: 0 auto;  /* Centering the container */
-            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; /* Professional font */
-        }
-
-        /* Title Styling */
-        .gradio-title {
-            font-size: 36px;
-            font-weight: 700;
-            color: #ffffff;  /* White color for contrast */
-            text-align: center;
-            margin-bottom: 20px;
-        }
-
-        /* Description Styling */
-        .gradio-description {
-            font-size: 18px;
-            color: #eeeeee;  /* Light gray text for description */
-            text-align: center;
-            margin-bottom: 30px;
-        }
-
-        /* Chat History Box Styling */
-        #chat-history {
-            font-size: 16px;
-            border-radius: 12px;
-            border: none;
-            padding: 14px;
-            background: rgba(255, 255, 255, 0.9);  /* Slight transparent white background */
-            color: #444;
-            margin-bottom: 20px;
-            height: 300px;
-            overflow-y: auto;
-            font-family: 'Roboto', sans-serif;
-            box-shadow: 0px 4px 12px rgba(0, 0, 0, 0.1);  /* Soft shadow for chat history */
-        }
-
-        /* Input Textbox Styling */
-        #user-input-textbox {
-            font-size: 16px;
-            border-radius: 10px;
-            border: none;
-            padding: 12px;
-            width: 100%;
-            margin-bottom: 15px;
-            background-color: #FFFFFF;
-            font-family: 'Roboto', sans-serif;
-            transition: background-color 0.3s ease;  /* Smooth transition for hover effect */
-        }
-
-        #user-input-textbox:focus {
-            background-color: #FFFFFF;  /* Light gray background on focus */
-            border-color: #FF6A00;  /* Orange border on focus */
-        }
-
-        /* Submit Button Styling */
-        .gradio-button {
-            background-color: #3A9FD6;  /* Blue color for submit button */
-            color: white;
-            padding: 14px 28px;
-            border-radius: 8px;
-            box-shadow: 0px 6px 30px H000000; /* Soft shadow for depth */
-            border: none;
-            font-size: 18px;
-            font-weight: 600;
-            cursor: pointer;
-            transition: all 0.3s ease-in-out;
-        }
-
-        .gradio-button:hover {
-            background-color: #FF6A00;  /* Orange color on hover */
-            transform: scale(1.05);  /* Slight button scaling on hover */
-        }
-
-        /* Adjust padding and margins */
-        .gradio-block {
-            padding: 0;
-        }
-        .gradio-row {
-            margin-bottom: 25px;
-        }
-        """
-
-    demo.launch()
-
-launch_gradio_interface()
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+import PyPDF2
+
+# Load Models
+model1_name = "t5-small"  # Model 1
+model2_name = "codeparrot/codeparrot-small"  # Model 2
+model3_name = "Salesforce/blip-image-captioning"  # Model 3
+
+# Load Pipelines
+model1 = pipeline("text2text-generation", model=model1_name, tokenizer=model1_name)
+model2 = pipeline("text-generation", model=model2_name, tokenizer=model2_name)
+model3 = pipeline("image-to-text", model=model3_name)  # We'll adapt this for PDF processing
+
+# Helper: Extract text from PDF
+def extract_text_from_pdf(pdf_file):
+    pdf_reader = PyPDF2.PdfReader(pdf_file)
+    text = ""
+    for page in pdf_reader.pages:
+        text += page.extract_text()
+    return text
+
+# Function for Model 1
+def model1_func(input_text):
+    try:
+        result = model1(input_text, max_length=50, num_return_sequences=1)
+        answer = result[0]["generated_text"]
+        return f"Model 1 Output: {answer}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Function for Model 2
+def model2_func(input_text):
+    try:
+        result = model2(input_text, max_length=50, num_return_sequences=1)
+        answer = result[0]["generated_text"]
+        return f"Model 2 Output: {answer}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Function for Model 3
+def model3_func(pdf_file):
+    try:
+        extracted_text = extract_text_from_pdf(pdf_file)
+        if not extracted_text.strip():
+            return "No text found in the PDF. Please upload a valid file."
+        result = model3(extracted_text)
+        answer = result[0]["generated_text"]
+        return f"Model 3 Output: {answer}"
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("<h1>Multi-Model NLP Tool</h1>")
+    
+    with gr.Tab("Model 1"):
+        gr.Markdown("**Model 1: Text-to-Text (e.g., Summarization)**")
+        model1_input = gr.Textbox(label="Enter Text", placeholder="Type here...")
+        model1_output = gr.Textbox(label="Output")
+        model1_button = gr.Button("Generate")
+        model1_button.click(model1_func, inputs=model1_input, outputs=model1_output)
+    
+    with gr.Tab("Model 2"):
+        gr.Markdown("**Model 2: Text Generation (e.g., Code Generation)**")
+        model2_input = gr.Textbox(label="Enter Text", placeholder="Type here...")
+        model2_output = gr.Textbox(label="Output")
+        model2_button = gr.Button("Generate")
+        model2_button.click(model2_func, inputs=model2_input, outputs=model2_output)
+    
+    with gr.Tab("Model 3"):
+        gr.Markdown("**Model 3: Document Reader (PDF Input)**")
+        pdf_input = gr.File(label="Upload PDF")
+        model3_output = gr.Textbox(label="Output")
+        model3_button = gr.Button("Process PDF")
+        model3_button.click(model3_func, inputs=pdf_input, outputs=model3_output)
+
+# Launch the app
+demo.launch()