Create app.py

app.py

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+import gradio as gr
+import google.generativeai as genai
+import base64
+from PIL import Image
+import io
+import time
+
+def encode_image(image):
+    if isinstance(image, dict) and 'path' in image:
+        image_path = image['path']
+    elif isinstance(image, str):
+        image_path = image
+    else:
+        raise ValueError("Unsupported image format")
+    
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+def bot_streaming(message, history, api_key, model, system_prompt, temperature, max_tokens, top_p, top_k, harassment, hate_speech, sexually_explicit, dangerous_content):
+    genai.configure(api_key=api_key)
+    
+    messages = []
+    images = []
+
+    if system_prompt:
+        messages.append({"role": "system", "content": system_prompt})
+
+    for i, msg in enumerate(history):
+        if isinstance(msg[0], tuple):
+            # This is a message with an image
+            image, text = msg[0]
+            base64_image = encode_image(image)
+            messages.append({
+                "role": "user",
+                "parts": [
+                    {"text": text},
+                    {"inline_data": {"mime_type": "image/jpeg", "data": base64_image}}
+                ]
+            })
+            images.append(Image.open(image['path'] if isinstance(image, dict) else image).convert("RGB"))
+        else:
+            # This is a text-only message
+            messages.append({"role": "user", "parts": [{"text": str(msg[0])}]})
+        
+        # Add the model's response
+        messages.append({"role": "model", "parts": [{"text": str(msg[1])}]})
+
+    # Handle the current message
+    if isinstance(message, dict) and "files" in message and message["files"]:
+        # This is a message with an image
+        image = message["files"][0]
+        base64_image = encode_image(image)
+        content = [
+            {"text": message["text"]},
+            {"inline_data": {"mime_type": "image/jpeg", "data": base64_image}}
+        ]
+        images.append(Image.open(image['path'] if isinstance(image, dict) else image).convert("RGB"))
+    else:
+        # This is a text-only message
+        content = [{"text": message["text"] if isinstance(message, dict) else str(message)}]
+
+    messages.append({"role": "user", "parts": content})
+
+    model = genai.GenerativeModel(model_name=model)
+    
+    safety_settings = [
+        {"category": genai.types.HarmCategory.HARM_CATEGORY_HARASSMENT, "threshold": getattr(genai.types.HarmBlockThreshold, harassment)},
+        {"category": genai.types.HarmCategory.HARM_CATEGORY_HATE_SPEECH, "threshold": getattr(genai.types.HarmBlockThreshold, hate_speech)},
+        {"category": genai.types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, "threshold": getattr(genai.types.HarmBlockThreshold, sexually_explicit)},
+        {"category": genai.types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, "threshold": getattr(genai.types.HarmBlockThreshold, dangerous_content)}
+    ]
+    
+    chat = model.start_chat(history=messages)
+    
+    response = chat.send_message(
+        content,
+        stream=True,
+        generation_config=genai.types.GenerationConfig(
+            temperature=temperature,
+            max_output_tokens=max_tokens,
+            top_p=top_p,
+            top_k=top_k
+        ),
+        safety_settings=safety_settings
+    )
+
+    buffer = ""
+    for chunk in response:
+        if hasattr(chunk, 'text') and chunk.text:
+            buffer += chunk.text
+            yield buffer
+            time.sleep(0.01)
+        if hasattr(chunk, 'finish_reason') and chunk.finish_reason:
+            break
+
+    if buffer:
+        yield buffer
+
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # 🤖 Google Gemini API Multimodal Chat
+
+    Chat with Google Gemini AI models. Supports text and image interactions.
+
+    ## 🚀 Quick Start:
+    1. Enter your Google AI API key
+    2. Choose a model
+    3. Start chatting!
+
+    Enjoy your AI-powered conversation!
+    """)
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            api_key = gr.Textbox(label="API Key", type="password", placeholder="Enter your Google AI API key")
+            model = gr.Dropdown(
+                label="Select Model",
+                choices=[
+                    "gemini-1.5-pro",
+                    "gemini-1.5-pro-001",
+                    "gemini-1.5-pro-vision-latest",
+                    "gemini-1.5-pro-latest",
+                    "gemini-1.5-flash",
+                    "gemini-1.5-flash-002",
+                    "gemini-1.0-pro",
+                    "gemini-1.0-pro-001",
+                    "gemini-1.0-pro-vision-latest",
+                    "gemini-1.0-pro-latest"
+                ],
+                value="gemini-1.5-pro",
+            )
+            system_prompt = gr.Textbox(label="System Prompt", placeholder="Enter a system prompt (optional)")
+            
+            with gr.Accordion("Common Settings", open=False):
+                temperature = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Temperature")
+                max_tokens = gr.Slider(minimum=1, maximum=2048, value=1000, step=1, label="Max Tokens")
+                top_p = gr.Slider(minimum=0, maximum=1, value=0.95, step=0.01, label="Top P")
+                top_k = gr.Slider(minimum=1, maximum=40, value=40, step=1, label="Top K")
+            
+            with gr.Accordion("Safety Settings", open=False):
+                harassment = gr.Dropdown(label="Harassment", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE")
+                hate_speech = gr.Dropdown(label="Hate Speech", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE")
+                sexually_explicit = gr.Dropdown(label="Sexually Explicit", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE")
+                dangerous_content = gr.Dropdown(label="Dangerous Content", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE")
+
+        with gr.Column(scale=2):
+            chatbot = gr.ChatInterface(
+                fn=bot_streaming,
+                additional_inputs=[
+                    api_key, model, system_prompt, temperature, max_tokens, top_p, top_k,
+                    harassment, hate_speech, sexually_explicit, dangerous_content
+                ],
+                title="💬 Chat with Google Gemini AI",
+                description="Upload images or type your message to start the conversation.",
+                retry_btn="🔄 Retry",
+                undo_btn="↩️ Undo",
+                clear_btn="🗑️ Clear",
+                multimodal=True,
+                cache_examples=False,
+                fill_height=True,
+            )
+
+    gr.Markdown("""
+    ## 🔧 Settings:
+    - Adjust basic parameters in the "Common Settings" section
+    - Fine-tune safety options in the "Safety Settings" section
+    - Upload images for multimodal interactions
+    """)
+
+demo.launch(debug=True, share=True)