Update app.py

app.py

@@ -1,17 +1,21 @@
 import os
 import time
 from typing import List, Tuple, Optional
+
 import google.generativeai as genai
 import gradio as gr
 from PIL import Image
 
-# Environment variable for Google API Key
+print("google-generativeai:", genai.__version__)
+
 GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
 
-# Constants for image processing
+TITLE = """<h1 align="center">🕹️ Google Gemini Chatbot 🔥</h1>"""
+SUBTITLE = """<h2 align="center">🎨Create with Multimodal Gemini</h2>"""
+
+
 IMAGE_WIDTH = 512
 
-# 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
 
@@ -19,61 +23,87 @@ def preprocess_image(image: Image.Image) -> Image.Image:
     image_height = int(image.height * IMAGE_WIDTH / image.width)
     return image.resize((IMAGE_WIDTH, image_height))
 
-# Function to trigger model invocation
+def user(text_prompt: str, chatbot: List[Tuple[str, str]]):
+    return "", chatbot + [["Analyze this text for gender-based discrimination, including implicit biases and stereotypes. Provide specific examples and explain why each example demonstrates bias.  Also, suggest tips for how to address or mitigate these biases within the text.", 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.")
-    
-    # Fixed text prompt for analyzing gender-based discrimination
-    text_prompt = "Analyze this for any instances of gender-based discrimination. Consider both explicit and implicit biases, stereotypes, and unequal treatment. Provide specific examples from the text to support your analysis."
 
+    text_prompt = chatbot[-1][0]
     genai.configure(api_key=google_key)
     generation_config = genai.types.GenerationConfig(
-        temperature=0.4,
-        max_output_tokens=1024,
-        stop_sequences=preprocess_stop_sequences("STOP, END"),
-        top_k=32,
-        top_p=1.0,
+        temperature=temperature,
+        max_output_tokens=max_output_tokens,
+        stop_sequences=preprocess_stop_sequences(stop_sequences),
+        top_k=top_k,
+        top_p=top_p,
+        #instructions = "You are an expert stylist"
     )
 
     model_name = "gemini-1.5-pro-latest" 
     model = genai.GenerativeModel(model_name)
-    inputs = [text_prompt, preprocess_image(image_prompt)] if image_prompt else [text_prompt]
+    inputs = [text_prompt] if image_prompt is None else [text_prompt, preprocess_image(image_prompt)]
     
     response = model.generate_content(inputs, stream=True, generation_config=generation_config)
     response.resolve()
 
     chatbot[-1][1] = ""
     for chunk in response:
-        chatbot[-1][1] += chunk.text
-        time.sleep(0.01)
-    return chatbot
+        for i in range(0, len(chunk.text), 10):
+            chatbot[-1][1] += chunk.text[i:i + 10]
+            time.sleep(0.01)
+            yield chatbot
+
+google_key_component = gr.Textbox(
+    label="GOOGLE API KEY",
+    type="password",
+    placeholder="...",
+    visible=GOOGLE_API_KEY is None
+)
 
-# Gradio Interface Components
-google_key_component = gr.Textbox(label="GOOGLE API KEY", type="password", placeholder="...", visible=GOOGLE_API_KEY is None)
-image_prompt_component = gr.Image(type="pil")
+image_prompt_component = gr.Image(type="pil", label="Image")
 chatbot_component = gr.Chatbot(label='Gemini', bubble_full_width=False)
-run_button_component = gr.Button("Check Discrimination")
+text_prompt_component = gr.Textbox(placeholder="Write your text here", label="Ask me anything and press Enter")
+run_button_component = gr.Button("Run")
+temperature_component = gr.Slider(minimum=0, maximum=1.0, value=0.4, step=0.05, label="Temperature")
+max_output_tokens_component = gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Token limit")
+stop_sequences_component = gr.Textbox(label="Add stop sequence", placeholder="STOP, END")
+top_k_component = gr.Slider(minimum=1, maximum=40, value=32, step=1, label="Top-K")
+top_p_component = gr.Slider(minimum=0, maximum=1, value=1, step=0.01, label="Top-P")
+
+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]
 
-# Layout and Interaction
 with gr.Blocks() as demo:
+    gr.HTML(TITLE)
+    gr.HTML(SUBTITLE)
+    gr.HTML(DUPLICATE)
     with gr.Column():
         google_key_component.render()
-        image_prompt_component.render()
+        with gr.Row():
+            image_prompt_component.render()
+            chatbot_component.render()
+        text_prompt_component.render()
         run_button_component.render()
-        chatbot_component.render()
-
-    # Connect button to the bot function
-    run_button_component.click(
-        fn=bot,
-        inputs=[google_key_component, image_prompt_component, chatbot_component],
-        outputs=[chatbot_component]
-    )
+        with gr.Accordion("Parameters", open=False):
+            temperature_component.render()
+            max_output_tokens_component.render()
+            stop_sequences_component.render()
+            with gr.Accordion("Advanced", open=False):
+                top_k_component.render()
+                top_p_component.render()
 
-# Launch the app
+    run_button_component.click(fn=user, inputs=user_inputs, outputs=[text_prompt_component, chatbot_component], queue=False).then(fn=bot, inputs=bot_inputs, outputs=[chatbot_component])
+    text_prompt_component.submit(fn=user, inputs=user_inputs, outputs=[text_prompt_component, chatbot_component], queue=False).then(fn=bot, inputs=bot_inputs, outputs=[chatbot_component])
 demo.launch()