Update.py

app.py

@@ -1,204 +1,72 @@
-import os
-import time
-from typing import List, Tuple, Optional
-import google.generativeai as genai
 import gradio as gr
-from PIL import Image
-import tempfile
+from groq import Groq
 import os
 
-GOOGLE_API_KEY = os.environ.get("GEMINI_API_KEY")
-
-IMAGE_WIDTH = 512
-IMAGE_WIDTH = 512
-
-system_instruction_analysis = "You are an expert of the given topic. Analyze the provided text with a focus on the topic, identifying recent issues, recent insights, or improvements relevant to academic standards and effectiveness. Offer actionable advice for enhancing knowledge and suggest real-life examples."
-model_name = "gemini-2.0-flash-exp"
-model = genai.GenerativeModel(model_name, system_instruction=system_instruction_analysis)
-#genai.configure(api_key=google_key)
-
-# Helper Functions
-def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]:
-    return [seq.strip() for seq in stop_sequences.split(",")] if stop_sequences else None
-
-def preprocess_image(image: Image.Image) -> Image.Image:
-    image_height = int(image.height * IMAGE_WIDTH / image.width)
-    return image.resize((IMAGE_WIDTH, image_height))
-
-def user(text_prompt: str, chatbot: List[Tuple[str, str]]):
-    return "", chatbot + [[text_prompt, None]]
-
-def bot(
-    google_key: str,
-    image_prompt: Optional[Image.Image],
-    temperature: float,
-    max_output_tokens: int,
-    stop_sequences: str,
-    top_k: int,
-    top_p: float,
-    chatbot: List[Tuple[str, str]]
-):
-    google_key = google_key or GOOGLE_API_KEY
-    if not google_key:
-        raise ValueError("GOOGLE_API_KEY is not set. Please set it up.")
-
-    text_prompt = chatbot[-1][0].strip() if chatbot[-1][0] else None
-
-    # Handle cases for text and/or image input
-    if not text_prompt and not image_prompt:
-        chatbot[-1][1] = "Prompt cannot be empty. Please provide input text or an image."
-        yield chatbot
-        return
-    elif image_prompt and not text_prompt:
-        # If only an image is provided
-        text_prompt = "Describe the image"
-    elif image_prompt and text_prompt:
-        # If both text and image are provided, combine them
-        text_prompt = f"{text_prompt}. Also, analyze the provided image."
-
-    # Configure the model
-    genai.configure(api_key=google_key)
-    generation_config = genai.types.GenerationConfig(
-        temperature=temperature,
-        max_output_tokens=max_output_tokens,
-        stop_sequences=preprocess_stop_sequences(stop_sequences),
-        top_k=top_k,
-        top_p=top_p,
-    )
-
-    # Prepare inputs
-    inputs = [text_prompt] if image_prompt is None else [text_prompt, preprocess_image(image_prompt)]
-
-    # Generate response
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+
+SYSTEM_PROMPT = """You are an expert in storyboarding. Provide structured and insightful responses to queries 
+about creating and refining storyboards"""
+
+def respond(message, history, model, temperature, max_tokens):
+    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+    
+    for h in history:
+        messages.append({"role": "user", "content": h[0]})
+        if h[1]:
+            messages.append({"role": "assistant", "content": h[1]})
+    
+    messages.append({"role": "user", "content": message})
+    
     try:
-        response = model.generate_content(inputs, stream=True, generation_config=generation_config)
-        response.resolve()
+        response = client.chat.completions.create(
+            model=model,
+            messages=messages,
+            temperature=temperature,
+            max_completion_tokens=max_tokens,
+        )
+        return response.choices[0].message.content
     except Exception as e:
-        chatbot[-1][1] = f"Error occurred: {str(e)}"
-        yield chatbot
-        return
-
-    # Stream the response back to the chatbot
-    chatbot[-1][1] = ""
-    for chunk in response:
-        for i in range(0, len(chunk.text), 10):
-            chatbot[-1][1] += chunk.text[i:i + 10]
-            time.sleep(0.01)
-            yield chatbot
-# Components
-google_key_component = gr.Textbox(
-    label="Google API Key",
-    type="password",
-    placeholder="Enter your Google API Key",
-    visible=GOOGLE_API_KEY is None
-)
-
-image_prompt_component = gr.Image(type="pil", label="Input Image (Optional: Figure/Graph)")
-chatbot_component = gr.Chatbot(label="Chatbot", bubble_full_width=False)
-text_prompt_component = gr.Textbox(
-    placeholder="Type your question here...",
-    label="Ask",
-    lines=3
-)
-run_button_component = gr.Button("Submit")
-temperature_component = gr.Slider(
-    minimum=0,
-    maximum=1.0,
-    value=0.4,
-    step=0.05,
-    label="Creativity (Temperature)",
-    info="Controls the randomness of the response. Higher values result in more creative answers."
-)
-max_output_tokens_component = gr.Slider(
-    minimum=1,
-    maximum=2048,
-    value=1024,
-    step=1,
-    label="Response Length (Token Limit)",
-    info="Sets the maximum number of tokens in the output response."
-)
-stop_sequences_component = gr.Textbox(
-    label="Stop Sequences (Optional)",
-    placeholder="Enter stop sequences, e.g., STOP, END",
-    info="Specify sequences to stop the generation."
+        return f"Error: {str(e)}"
+
+# ChatInterface with additional inputs for parameters
+demo = gr.ChatInterface(
+    fn=respond,
+    title="🎬 Storyboard Generator AI",
+    description="Create professional storyboards for films, animations, and more!",
+    additional_inputs=[
+        gr.Dropdown(
+            choices=[
+                "llama-3.3-70b-versatile",
+                "llama-3.1-8b-instant",
+            ],
+            value="llama-3.3-70b-versatile",
+            label="Model",
+            info="Select the AI model to use"
+        ),
+        gr.Slider(
+            minimum=0,
+            maximum=2,
+            value=0.9,
+            step=0.1,
+            label="Temperature",
+            info="Controls randomness. Lower = more focused, Higher = more creative"
+        ),
+        gr.Slider(
+            minimum=256,
+            maximum=8192,
+            value=2048,
+            step=256,
+            label="Max Tokens",
+            info="Maximum length of the response"
+        ),
+    ],
+    examples=[
+        ["Create a storyboard for a 30-second coffee commercial"],
+        ["Generate a horror movie opening scene storyboard"],
+        ["Design a storyboard for a romantic comedy meet-cute at a bookstore"],
+    ],
+    theme="soft",
 )
-top_k_component = gr.Slider(
-    minimum=1,
-    maximum=40,
-    value=32,
-    step=1,
-    label="Top-K Sampling",
-    info="Limits token selection to the top K most probable tokens. Lower values produce conservative outputs."
-)
-top_p_component = gr.Slider(
-    minimum=0,
-    maximum=1,
-    value=1,
-    step=0.01,
-    label="Top-P Sampling",
-    info="Limits token selection to tokens with a cumulative probability up to P. Lower values produce conservative outputs."
-)
-example_scenarios = [
-    "Describe Multimodal AI",
-    "What are the difference between muliagent llm and multiagent system",
-"Why it's difficult to intgrate multimodality in prompt"]
-example_images = [["ex1.png"],["ex2.png"]]
-
-
-# Gradio Interface
-user_inputs = [text_prompt_component, chatbot_component]
-bot_inputs = [
-    google_key_component,
-    image_prompt_component,
-    temperature_component,
-    max_output_tokens_component,
-    stop_sequences_component,
-    top_k_component,
-    top_p_component,
-    chatbot_component,
-]
-
-
-with gr.Blocks(theme="earneleh/paris") as demo:
-    gr.Markdown("<h1 style='font-size: 36px; font-weight: bold; font-family: Arial;'>Gemini 2.0 Multimodal Chatbot</h1>")
-    with gr.Row():
-        google_key_component.render()
-    with gr.Row():
-        chatbot_component.render()
-    with gr.Row():
-        with gr.Column(scale=0.5):
-           text_prompt_component.render()
-        with gr.Column(scale=0.5):
-           image_prompt_component.render()
-        with gr.Column(scale=0.5):
-            run_button_component.render()
-    with gr.Accordion("🧪Example Text 💬", open=False):
-        example_radio = gr.Radio(
-        choices=example_scenarios,
-        label="Example Queries",
-        info="Select an example query.")
-        # Debug callback
-        example_radio.change(
-        fn=lambda query: query if query else "No query selected.",
-        inputs=[example_radio],
-        outputs=[text_prompt_component])
-       # Custom examples section with blue styling
-    with gr.Accordion("🧪Example Image 🩻", open=False):
-        gr.Examples(
-        examples=example_images,
-        inputs=[image_prompt_component],
-        label="Example Figures",
-        )     
-    with gr.Accordion("🛠️Customize", open=False):
-        temperature_component.render()
-        max_output_tokens_component.render()
-        stop_sequences_component.render()
-        top_k_component.render()
-        top_p_component.render()
 
-    run_button_component.click(
-        fn=user, inputs=user_inputs, outputs=[text_prompt_component, chatbot_component]
-    ).then(
-        fn=bot, inputs=bot_inputs, outputs=[chatbot_component]
-    )
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()