Update app.py

app.py

@@ -3,23 +3,23 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-model = "meta-llama/Llama-3.2-3B-Instruct"
+model = "meta-llama/Llama-3.2-11B-Vision-Instruct"
 client = InferenceClient(model)
 
-def fn(
+def fn_text(
     prompt,
     history,
     system_prompt,
     max_tokens,
     temperature,
     top_p,
-):  
-    messages = [{"role": "system", "content": system_prompt}]
+):
+    messages = [{"role": "system", "content": [{"type": "text", "text": system_prompt}]}]
     history.append(messages[0])
     
-    messages.append({"role": "user", "content": prompt})
+    messages.append({"role": "user", "content": [{"type": "text", "text": prompt}]})
     history.append(messages[1])
-
+    
     stream = client.chat.completions.create(
         model = model,
         messages = history,
@@ -28,14 +28,14 @@ def fn(
         top_p = top_p,
         stream = True
     )
-
+    
     chunks = []
     for chunk in stream:
         chunks.append(chunk.choices[0].delta.content or "")
         yield "".join(chunks)
 
-app = gr.ChatInterface(
-    fn = fn,
+app_text = gr.ChatInterface(
+    fn = fn_text,
     type = "messages",
     additional_inputs = [
         gr.Textbox(value="You are a helpful assistant.", label="System Prompt"),
@@ -47,5 +47,56 @@ app = gr.ChatInterface(
     description = model,
 )
 
-if __name__ == "__main__":
-    app.launch()
+def fn_vision(
+    prompt,
+    image_url,
+    #system_prompt,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "user", "content": [{"type": "text", "text": prompt}]}]
+    
+    if image_url:
+        messages[0]["content"].append({"type": "image_url", "image_url": {"url": image_url}})
+    
+    stream = client.chat.completions.create(
+        model = model,
+        messages = messages,
+        max_tokens = max_tokens,
+        temperature = temperature,
+        top_p = top_p,
+        stream = True
+    )
+    
+    chunks = []
+    for chunk in stream:
+        chunks.append(chunk.choices[0].delta.content or "")
+        yield "".join(chunks)
+
+app_vision = gr.Interface(
+    fn = fn_vision,
+    inputs = [
+        gr.Textbox(label="Prompt"),
+        gr.Textbox(label="Image URL")
+    ],
+    outputs = [
+        gr.Textbox(label="Output")
+    ],
+    additional_inputs = [
+        #gr.Textbox(value="You are a helpful assistant.", label="System Prompt"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max Tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P"),
+    ],
+    title = "Meta Llama",
+    description = model,
+)
+
+app = gr.TabbedInterface(
+    [app_text, app_vision],
+    ["Text", "Vision"]
+).launch()
+
+#if __name__ == "__main__":
+#    app.launch()