Add raw output

app.py

@@ -146,7 +146,9 @@ def generate(features, image, garment_type, structure, reference, model, tempera
     chat_response = chat.invoke(messages, temperature=temperature)
     print(messages[0].content)
     alt_texts_str = '\n\n### Alt text\n\n' + '\n- ' + '\n- '.join(alt_texts) if len(alt_texts) > 0 else ""
-    return chat_response.content + alt_texts_str + '\n'.join([f'![Product photo](data:image/png;base64,{base64_image} "{alt_text}")' if base64_image != "" else "" for (base64_image, alt_text) in zip(base64_images, alt_texts)])
+    result_text = chat_response.content
+    result_md = chat_response.content + alt_texts_str + '\n'.join([f'![Product photo](data:image/png;base64,{base64_image} "{alt_text}")' if base64_image != "" else "" for (base64_image, alt_text) in zip(base64_images, alt_texts)])
+    return result_md, result_text
 
 
 demo = gr.Interface(
@@ -158,7 +160,7 @@ demo = gr.Interface(
             gr.Textbox(reference, label="Reference copy"),
             gr.Dropdown(["gpt-4-turbo", "gpt-3.5-turbo", "claude-3-sonnet-20240229", "claude-3-opus-20240229", "llama3-70b-8192"], value="llama3-70b-8192", label="Model"),
             gr.Slider(minimum=0., maximum=1.0, value=0.5, label="Temperature")],
-    outputs=["markdown"],
+    outputs=[gr.Markdown(label="Markdown"), gr.Textbox(label="Raw text")],
 )
 
 # demo.launch()

requirements.txt

@@ -1,3 +1,4 @@
+gradio
 langchain
 langchain_openai
 langchain_anthropic