Upload app.py

app.py

@@ -41,7 +41,7 @@ def respond(
     top_p: float = 1.0,
 ):
     # Preprocess the input message
-    input_text = "translate English to French: " + message
+    input_text = system_message + " " + message
     input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 
     # Set up the streamer
@@ -62,10 +62,8 @@ def respond(
     generation_thread.start()
 
     # Stream the output progressively
-    generated_text = ""
-    for token in streamer:
-        generated_text += token  # Append each token to the accumulated text
-        yield generated_text
+    for token in streamer:  # Append each token to the accumulated text
+        yield token
 
 
 """
@@ -87,6 +85,27 @@ For information on how to customize the ChatInterface, peruse the gradio docs: h
 #     ],
 # )
 
+# Function to process translation
+def respond_google_translate(
+    source_text,
+    system_message,
+    max_tokens,
+    temperature,
+    top_p
+):
+    # Call the respond function and collect the final response
+    result = ""
+    for token in respond(
+        message=source_text,
+        history=[],
+        system_message=system_message,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        result += token  # Accumulate the tokens
+    return result
+
 # Define the interface
 with gr.Blocks() as demo:
     gr.Markdown("# Google Translate-like Interface")
@@ -110,7 +129,7 @@ with gr.Blocks() as demo:
 
     with gr.Accordion("Advanced Settings", open=False):
         system_message_input = gr.Textbox(
-            value="You are a friendly Chatbot.",
+            value="translate English to French:",
             label="System message",
         )
         max_tokens_slider = gr.Slider(
@@ -125,7 +144,7 @@ with gr.Blocks() as demo:
 
     # Define functionality
     translate_button.click(
-        respond,
+        respond_google_translate,
         inputs=[
             source_textbox,
             system_message_input,