Update app.py

app.py

@@ -1,176 +1,176 @@
-# Requirement: !pip install gradio, groq
-
-# 1. Imports and API setup
-import gradio as gr
-from groq import Groq
-import base64
-import os
-import spaces
-
-# Image encoding function
-def encode_image(image_path):
-    with open(image_path, "rb") as image_file:
-        return base64.b64encode(image_file.read()).decode('utf-8')
-
-# Image to text function
-def image_to_text(client, model, base64_image, prompt):
-    try:
-        chat_completion = client.chat.completions.create(
-            messages=[
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "text", "text": prompt},
-                        {
-                            "type": "image_url",
-                            "image_url": {
-                                "url": f"data:image/jpeg;base64,{base64_image}",
-                            },
-                        },
-                    ],
-                }
-            ],
-            model=model
-        )
-        return chat_completion.choices[0].message.content
-    except Exception as e:
-        if 'Invalid API Key' in str(e):
-            return "Please enter a correct API key and try again."
-        return f"Error generating text from image: {str(e)}"
-
-# Technical review generation function
-def technical_review_generation(client, image_description):
-    keywords = ["econometrics", "finance", "marketing", "stock", "prediction", "chart", "graph", "time series"]
-    if not any(keyword in image_description.lower() for keyword in keywords):
-        return "The image is not related to the area this app covers. Please input a relevant image."
-
-    try:
-        chat_completion = client.chat.completions.create(
-            messages=[
-                {
-                    "role": "system",
-                    "content": "You are a professional econometrics. Write a complete review and report about the scene depicted in this image.",
-                },
-                {
-                    "role": "user",
-                    "content": image_description,
-                }
-            ],
-            model=llama31_model
-        )
-        return chat_completion.choices[0].message.content
-    except Exception as e:
-        return f"Error generating report: {str(e)}"
-
-# Main function for Gradio interface
-def process_image(api_key, image, prompt="Describe this image in detail."):
-    # Set the API key
-    try:
-        os.environ["GROQ_API_KEY"] = api_key
-        client = Groq()  # Initialize the Groq client with the provided key
-    except Exception as e:
-        return "Please enter a correct API key and try again.", ""
-
-    # Encode the image
-    base64_image = encode_image(image)
-
-    # Get image description from the model
-    image_description = image_to_text(client, llava_model, base64_image, prompt)
-
-    # If API key was invalid, only return the API key error message
-    if "Please enter a correct API key and try again." in image_description:
-        return image_description, ""
-
-    # Generate the econometrics report based on the image description
-    report = technical_review_generation(client, image_description)
-
-    # Return both image description and the econometrics report
-    return f"--- Image Description ---\n{image_description}", f"--- GroqLLaVA EconoMind Report ---\n{report}"
-
-# Define CSS for centering elements and footer styling
-css = """
-    #title, #description {
-        text-align: center;
-        margin: 20px;
-    }
-    #footer {
-        text-align: center;
-        margin-top: 30px;
-        padding: 10px;
-        font-size: 14px;
-    }
-    .gradio-container {
-        display: flex;
-        flex-direction: column;
-        align-items: center;
-    }
-    .gradio-row {
-        width: 100%;
-        display: flex;
-        justify-content: center;
-    }
-    .clear-button {
-        margin-top: 10px;
-    }
-"""
-
-# Gradio Interface
-@spaces.GPU()
-def gradio_interface():
-    # Define the footer HTML
-    footer = """
-    <div id="footer">
-        <a href="https://www.linkedin.com/in/pejman-ebrahimi-4a60151a7/" target="_blank">LinkedIn</a> |
-        <a href="https://github.com/arad1367" target="_blank">GitHub</a> |
-        <a href="https://arad1367.pythonanywhere.com/" target="_blank">Live demo of my PhD defense</a> |
-        <a href="https://groq.com/introducing-llava-v1-5-7b-on-groqcloud-unlocking-the-power-of-multimodal-ai/" target="_blank">Introducing LLaVA V1.5 7B on GroqCloud</a>
-        <br>
-        Made with 💖 by Pejman Ebrahimi
-    </div>
-    """
-
-    with gr.Blocks(theme="gradio/soft", css=css) as demo:
-        gr.HTML("<h1 id='title'>GroqLLaVA Econometrics Agent</h1>")
-        gr.HTML("<p id='description'>Upload an economic chart and get a detailed analysis using Groq + LLaVA V1.5 7B multimodal.</p>")
-        
-        with gr.Row():
-            api_key_input = gr.Textbox(label="GROQ API Key", placeholder="Enter your GROQ API Key", type="password")
-        with gr.Row():
-            image_input = gr.Image(type="filepath", label="Upload an Image")  # Changed type to 'filepath'
-        with gr.Row():
-            report_button = gr.Button("Generate Report")
-        with gr.Row():
-            output_description = gr.Textbox(label="Image Description", lines=10, elem_id="description-box")
-            output_report = gr.Textbox(label="Report", lines=10, elem_id="report-box")
-
-        # Define the interaction between inputs and outputs
-        report_button.click(
-            fn=process_image,
-            inputs=[api_key_input, image_input],
-            outputs=[output_description, output_report]
-        )
-
-        # Add footer HTML
-        gr.HTML(footer)
-        
-        # Add clear button
-        def clear_inputs():
-            return "", None, "", ""
-
-        with gr.Row():
-            clear_button = gr.Button("Clear", elem_id="clear-button")
-            clear_button.click(
-                fn=clear_inputs,
-                inputs=[],
-                outputs=[api_key_input, image_input, output_description, output_report]
-            )
-
-    # Launch the interface
-    demo.launch()
-
-# Define models used in the process
-llava_model = 'llava-v1.5-7b-4096-preview'
-llama31_model = 'llama-3.1-70b-versatile'
-
-# Start the Gradio interface
+# Requirement: !pip install gradio, groq
+
+# 1. Imports and API setup
+import gradio as gr
+from groq import Groq
+import base64
+import os
+import spaces
+
+# Define models used in the process
+llava_model = 'llava-v1.5-7b-4096-preview'
+llama31_model = 'llama-3.1-70b-versatile'
+
+# Image encoding function
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+# Image to text function
+def image_to_text(client, model, base64_image, prompt):
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": prompt},
+                        {
+                            "type": "image_url",
+                            "image_url": {
+                                "url": f"data:image/jpeg;base64,{base64_image}",
+                            },
+                        },
+                    ],
+                }
+            ],
+            model=model
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        if 'Invalid API Key' in str(e):
+            return "Please enter a correct API key and try again."
+        return f"Error generating text from image: {str(e)}"
+
+# Technical review generation function
+def technical_review_generation(client, image_description):
+    keywords = ["econometrics", "finance", "marketing", "stock", "prediction", "chart", "graph", "time series"]
+    if not any(keyword in image_description.lower() for keyword in keywords):
+        return "The image is not related to the area this app covers. Please input a relevant image."
+
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a professional econometrics. Write a complete review and report about the scene depicted in this image.",
+                },
+                {
+                    "role": "user",
+                    "content": image_description,
+                }
+            ],
+            model=llama31_model
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        return f"Error generating report: {str(e)}"
+
+# Main function for Gradio interface
+def process_image(api_key, image, prompt="Describe this image in detail."):
+    # Set the API key
+    try:
+        os.environ["GROQ_API_KEY"] = api_key
+        client = Groq()  # Initialize the Groq client with the provided key
+    except Exception as e:
+        return "Please enter a correct API key and try again.", ""
+
+    # Encode the image
+    base64_image = encode_image(image)
+
+    # Get image description from the model
+    image_description = image_to_text(client, llava_model, base64_image, prompt)
+
+    # If API key was invalid, only return the API key error message
+    if "Please enter a correct API key and try again." in image_description:
+        return image_description, ""
+
+    # Generate the econometrics report based on the image description
+    report = technical_review_generation(client, image_description)
+
+    # Return both image description and the econometrics report
+    return f"--- Image Description ---\n{image_description}", f"--- GroqLLaVA EconoMind Report ---\n{report}"
+
+# Define CSS for centering elements and footer styling
+css = """
+    #title, #description {
+        text-align: center;
+        margin: 20px;
+    }
+    #footer {
+        text-align: center;
+        margin-top: 30px;
+        padding: 10px;
+        font-size: 14px;
+    }
+    .gradio-container {
+        display: flex;
+        flex-direction: column;
+        align-items: center;
+    }
+    .gradio-row {
+        width: 100%;
+        display: flex;
+        justify-content: center;
+    }
+    .clear-button {
+        margin-top: 10px;
+    }
+"""
+
+# Gradio Interface
+
+def gradio_interface():
+    # Define the footer HTML
+    footer = """
+    <div id="footer">
+        <a href="https://www.linkedin.com/in/pejman-ebrahimi-4a60151a7/" target="_blank">LinkedIn</a> |
+        <a href="https://github.com/arad1367" target="_blank">GitHub</a> |
+        <a href="https://arad1367.pythonanywhere.com/" target="_blank">Live demo of my PhD defense</a> |
+        <a href="https://groq.com/introducing-llava-v1-5-7b-on-groqcloud-unlocking-the-power-of-multimodal-ai/" target="_blank">Introducing LLaVA V1.5 7B on GroqCloud</a>
+        <br>
+        Made with 💖 by Pejman Ebrahimi
+    </div>
+    """
+    @spaces.GPU()
+    with gr.Blocks(theme="gradio/soft", css=css) as demo:
+        gr.HTML("<h1 id='title'>GroqLLaVA Econometrics Agent</h1>")
+        gr.HTML("<p id='description'>Upload an economic chart and get a detailed analysis using Groq + LLaVA V1.5 7B multimodal.</p>")
+        
+        with gr.Row():
+            api_key_input = gr.Textbox(label="GROQ API Key", placeholder="Enter your GROQ API Key", type="password")
+        with gr.Row():
+            image_input = gr.Image(type="filepath", label="Upload an Image")  # Changed type to 'filepath'
+        with gr.Row():
+            report_button = gr.Button("Generate Report")
+        with gr.Row():
+            output_description = gr.Textbox(label="Image Description", lines=10, elem_id="description-box")
+            output_report = gr.Textbox(label="Report", lines=10, elem_id="report-box")
+
+        # Define the interaction between inputs and outputs
+        report_button.click(
+            fn=process_image,
+            inputs=[api_key_input, image_input],
+            outputs=[output_description, output_report]
+        )
+
+        # Add footer HTML
+        gr.HTML(footer)
+        
+        # Add clear button
+        def clear_inputs():
+            return "", None, "", ""
+
+        with gr.Row():
+            clear_button = gr.Button("Clear", elem_id="clear-button")
+            clear_button.click(
+                fn=clear_inputs,
+                inputs=[],
+                outputs=[api_key_input, image_input, output_description, output_report]
+            )
+
+    # Launch the interface
+    demo.launch()
+
+# Start the Gradio interface
 gradio_interface()