Update app.py

app.py

@@ -31,83 +31,112 @@ def encode_image(image_path, max_size=(800, 800), quality=85):
         img.save(buffered, format="JPEG", quality=quality)
         return base64.b64encode(buffered.getvalue()).decode('utf-8')
 
-def bot_streaming(message, history, together_api_key, max_new_tokens=250, max_history=5):
+def bot_streaming(message, history, together_api_key, max_new_tokens=250, temperature=0.7, max_history=5):
     if client is None:
-        initialize_client(together_api_key)
+        try:
+            initialize_client(together_api_key)
+        except Exception as e:
+            yield f"Error initializing client: {str(e)}"
+            return
 
-    txt = message["text"]
+    txt = message.get("text", "")
     messages = []
     images = []
 
-    for i, msg in enumerate(history[-max_history:]):
-        if isinstance(msg[0], tuple):
-            messages.append({"role": "user", "content": [{"type": "text", "text": history[i+1][0]}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encode_image(msg[0][0])}"}}]})
-            messages.append({"role": "assistant", "content": [{"type": "text", "text": history[i+1][1]}]})
-        elif isinstance(history[i-1], tuple) and isinstance(msg[0], str):
-            pass
-        elif isinstance(history[i-1][0], str) and isinstance(msg[0], str):
-            messages.append({"role": "user", "content": [{"type": "text", "text": msg[0]}]})
-            messages.append({"role": "assistant", "content": [{"type": "text", "text": msg[1]}]})
+    try:
+        for i, msg in enumerate(history[-max_history:]):
+            if isinstance(msg[0], tuple):
+                messages.append({"role": "user", "content": [{"type": "text", "text": history[i+1][0]}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encode_image(msg[0][0])}"}}]})
+                messages.append({"role": "assistant", "content": [{"type": "text", "text": history[i+1][1]}]})
+            elif isinstance(history[i-1][0], tuple) and isinstance(msg[0], str):
+                pass
+            elif isinstance(history[i-1][0], str) and isinstance(msg[0], str):
+                messages.append({"role": "user", "content": [{"type": "text", "text": msg[0]}]})
+                messages.append({"role": "assistant", "content": [{"type": "text", "text": msg[1]}]})
 
-    if len(message["files"]) == 1:
-        if isinstance(message["files"][0], str):  # examples
-            image_path = message["files"][0]
-        else:  # regular input
-            image_path = message["files"][0]["path"]
-        messages.append({"role": "user", "content": [{"type": "text", "text": txt}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encode_image(image_path)}"}}]})
-    else:
-        messages.append({"role": "user", "content": [{"type": "text", "text": txt}]})
+        if "files" in message and len(message["files"]) == 1:
+            if isinstance(message["files"][0], str):  # examples
+                image_path = message["files"][0]
+            else:  # regular input
+                image_path = message["files"][0]["path"]
+            messages.append({"role": "user", "content": [{"type": "text", "text": txt}, {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encode_image(image_path)}"}}]})
+        else:
+            messages.append({"role": "user", "content": [{"type": "text", "text": txt}]})
 
-    try:
         stream = client.chat.completions.create(
             model="meta-llama/Llama-Vision-Free",
             messages=messages,
             max_tokens=max_new_tokens,
+            temperature=temperature,
             stream=True,
         )
 
         buffer = ""
         for chunk in stream:
-            if chunk.choices[0].delta.content is not None:
+            if chunk.choices and chunk.choices[0].delta and chunk.choices[0].delta.content is not None:
                 buffer += chunk.choices[0].delta.content
                 time.sleep(0.01)
                 yield buffer
 
+        if not buffer:
+            yield "No response generated. Please try again."
+
     except Exception as e:
         if "Request Entity Too Large" in str(e):
             yield "The image is too large. Please try with a smaller image or compress the existing one."
         else:
             yield f"An error occurred: {str(e)}"
 
-with gr.Blocks() as demo:
+css = """
+#chatbot-container {
+    height: calc(100vh - 230px);
+    overflow-y: auto;
+}
+#chatbot-textbox {
+    position: fixed;
+    bottom: 20px;
+    left: 20px;
+    right: 20px;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
     gr.Markdown("# Meta Llama-3.2-11B-Vision-Instruct (FREE)")
-    gr.Markdown("Try the new Llama 3.2 11B Vision API by Meta for free through Together AI. Upload an image, and start chatting about it. Just paste in your [Together AI API key](https://api.together.xyz/settings/api-keys) and get started!")
+    gr.Markdown("Try the new Llama 3.2 11B Vision API by Meta for free through Together AI. Upload an image, and start chatting about it. Just paste in your Together AI API key and get started!")
     
-    together_api_key = gr.Textbox(
-        label="Together API Key",
-        placeholder="Enter your TOGETHER_API_KEY here",
-        type="password"
-    )
+    with gr.Row():
+        together_api_key = gr.Textbox(
+            label="Together API Key",
+            placeholder="Enter your TOGETHER_API_KEY here",
+            type="password"
+        )
     
-    chatbot = gr.ChatInterface(
-        fn=bot_streaming,
-        textbox=gr.MultimodalTextbox(),
-        additional_inputs=[
-            gr.Slider(
-                minimum=10,
-                maximum=500,
-                value=250,
-                step=10,
-                label="Maximum number of new tokens to generate",
-            )
-        ],
-        cache_examples=False,
-        stop_btn="Stop Generation",
-        fill_height=True,
-        multimodal=True
-    )
+    with gr.Row():
+        max_new_tokens = gr.Slider(
+            minimum=10,
+            maximum=500,
+            value=250,
+            step=10,
+            label="Maximum number of new tokens",
+        )
+        temperature = gr.Number(
+            value=0.7,
+            minimum=0,
+            maximum=1,
+            step=0.1,
+            label="Temperature"
+        )
     
-    together_api_key.change(lambda x: x, inputs=[together_api_key], outputs=[chatbot.additional_inputs[0]])
+    with gr.Column(elem_id="chatbot-container"):
+        chatbot = gr.ChatInterface(
+            fn=bot_streaming,
+            textbox=gr.MultimodalTextbox(elem_id="chatbot-textbox"),
+            additional_inputs=[together_api_key, max_new_tokens, temperature],
+            cache_examples=False,
+            stop_btn="Stop Generation",
+            fill_height=True,
+            multimodal=True
+        )
 
 if __name__ == "__main__":
     demo.launch(debug=True)