Update app.py

app.py

@@ -229,35 +229,83 @@ h2 {
 }
 """
 
-with gr.Blocks(title="Salamandra 7B Instruct · ZeroGPU",css=custom_css,theme=gr.themes.Soft()) as demo:
-    gr.Markdown("## Salamandra-7B-Instruct · ZeroGPU\nTexto → respuesta instruccional.")
+# App UI built with Gradio. This interface exposes several model utilities.
+with gr.Blocks(title="Salamandra 7B Instruct · ZeroGPU", css=custom_css, theme=gr.themes.Soft()) as demo:
+
+    # Section: Instruction-based text generation
+    gr.Markdown("## Salamandra-7B-Instruct · ZeroGPU\nText → resposta instruccional.")
+
     with gr.Row():
         with gr.Column(scale=1):
-            in_system = gr.Textbox(label="System (opcional)", value="")
-            in_prompt = gr.Textbox(label="Prompt", placeholder="Escribe tu instrucción…", lines=6)
-            max_new = gr.Slider(16, 2048, value=512, step=16, label="max_new_tokens")
-            temp = gr.Slider(0.0, 1.5, value=0.7, step=0.05, label="temperature")
-            top_p = gr.Slider(0.1, 1.0, value=0.95, step=0.01, label="top_p")
+            # System prompt (optional internal conditioning)
+            in_system = gr.Textbox(label="Sistema (opcional)", value="")
+
+            # User prompt to instruct the model
+            in_prompt = gr.Textbox(label="Instrucció", placeholder="Escriu la teva instrucció…", lines=6)
+
+            # Maximum number of new tokens to generate
+            max_new = gr.Slider(16, 2048, value=512, step=16, label="Màxim de tokens nous")
+
+            # Diversity parameter for randomness
+            temp = gr.Slider(0.0, 1.5, value=0.7, step=0.05, label="Temperatura")
+
+            # Nucleus sampling threshold
+            top_p = gr.Slider(0.1, 1.0, value=0.95, step=0.01, label="Top-p")
+
+            # Button to trigger text generation
             btn = gr.Button("Generar", variant="primary")
+
         with gr.Column(scale=1):
-            out = gr.Textbox(label="Respuesta", lines=18)
+            # Output box for generated text
+            out = gr.Textbox(label="Resposta", lines=18)
+
+    # Bind main generation function
+    btn.click(
+        generate_advanced,
+        [in_prompt, in_system, max_new, temp, top_p],
+        out,
+        api_name="generate",
+        concurrency_limit=1
+    )
 
-    btn.click(generate_advanced, [in_prompt, in_system, max_new, temp, top_p], out, api_name="generate", concurrency_limit=1)
+    # --------------------------------------------------------------
     gr.Markdown("---")
-    # Endpoint minimalista compatible con el ENGINE (/predict: solo prompt)
-    in_prompt_engine = gr.Textbox(label="Prompt (ENGINE)", value="Di hola en una frase.")
-    out_engine = gr.Textbox(label="Respuesta (ENGINE)")
-    gr.Button("Probar /predict").click(predict_for_engine, [in_prompt_engine], out_engine, api_name="predict", concurrency_limit=1)
+    # --------------------------------------------------------------
+
+    # Minimal endpoint for ENGINE compatibility (/predict)
+    # Only requires a prompt, returns generated text
+    in_prompt_engine = gr.Textbox(label="Instrucció (ENGINE)", value="Digues hola en una frase.")
+    out_engine = gr.Textbox(label="Resposta (ENGINE)")
+
+    gr.Button("Provar /predict").click(
+        predict_for_engine,
+        [in_prompt_engine],
+        out_engine,
+        api_name="predict",
+        concurrency_limit=1
+    )
+
+    # --------------------------------------------------------------
     gr.Markdown("---")
-    
+    # --------------------------------------------------------------
+
+    # Section: Sentence summarization
     gr.Markdown('<h2 style="text-align:center">Resumir frases</h2>')
+
     with gr.Row():
         with gr.Column(scale=1):
+            # Text to summarize
             sentence = gr.Textbox(label="Frase a resumir", value="", lines=3)
+
+            # Desired number of words in the summary
             num_words = gr.Textbox(label="Nombre de paraules del resum", value="4")
+
         with gr.Column(scale=1):
+            # Output summary
             out_resume = gr.Textbox(label="Resposta", lines=18)
+
     with gr.Row():
+        # Button to produce a summary
         btn_resume = gr.Button("Resumir", variant="primary")
 
     btn_resume.click(
@@ -267,18 +315,28 @@ with gr.Blocks(title="Salamandra 7B Instruct · ZeroGPU",css=custom_css,theme=gr
         api_name="resume",
         concurrency_limit=1
     )
+
+    # --------------------------------------------------------------
     gr.Markdown("---")
-    
+    # --------------------------------------------------------------
+
+    # Section: Inclusion of identities inside text
     gr.Markdown('<h2 style="text-align:center">Inclusió d’identitats</h2>')
+
     with gr.Row():
         with gr.Column(scale=1):
+            # Sentence to modify
             sentence = gr.Textbox(label="Frase a modificar", value="", lines=3)
+
+            # Identity mapping provided by the user
             person = gr.Textbox(label="Persones reconegudes", value='"Mireia Martí": 4, "Xavier Busquets": 5')
+
         with gr.Column(scale=1):
             out_modificat = gr.Textbox(label="Resposta", lines=18)
+
     with gr.Row():
         btn_modify = gr.Button("Modificar frase", variant="primary")
-        
+
     btn_modify.click(
         identity_manager,
         inputs=[sentence, person],
@@ -287,11 +345,24 @@ with gr.Blocks(title="Salamandra 7B Instruct · ZeroGPU",css=custom_css,theme=gr
         concurrency_limit=1
     )
 
+    # --------------------------------------------------------------
+    gr.Markdown("---")
+    # --------------------------------------------------------------
+
+    # Section: Free narration generation from SRT-like audio description
     gr.Markdown('<h2 style="text-align:center">Narració lliure</h2>')
+
     with gr.Row():
         with gr.Column(scale=1):
-            srt = gr.Textbox(label="Audiodescripció", value="(AD)\nTOTS CANTANT: avui celebrem la nostra festa major\nAINA: som hi tots a ballar", lines=3)
+            # SRT-like structured description
+            srt = gr.Textbox(
+                label="Audiodescripció",
+                value="(AD)\nTOTS CANTANT: avui celebrem la nostra festa major\nAINA: som hi tots a ballar",
+                lines=3
+            )
+
             btn_modify = gr.Button("Generar narració lliure", variant="primary")
+
         with gr.Column(scale=1):
             narració_lliure = gr.Textbox(label="Narració lliure", lines=18)
 
@@ -303,15 +374,33 @@ with gr.Blocks(title="Salamandra 7B Instruct · ZeroGPU",css=custom_css,theme=gr
         concurrency_limit=1
     )
 
+    # --------------------------------------------------------------
+    gr.Markdown("---")
+    # --------------------------------------------------------------
+
+    # Section: Raw model output from a prompt (JSON)
     gr.Markdown('<h2 style="text-align:center">Sortida del model Salamandra a partir d’una petició</h2>')
+
     with gr.Row():
-        prompt = gr.Textbox(label="prompt", lines=10)
+        prompt = gr.Textbox(label="Prompt", lines=10)
+
     with gr.Row():
         btn2 = gr.Button("Generar", variant="primary")
+
     with gr.Row():
-        out2 = gr.JSON(label="Salida")
+        out2 = gr.JSON(label="Sortida")
+
+    btn2.click(
+        salamandra_chat_endpoint,
+        [prompt],
+        out2,
+        api_name="generate_out_from_prompt",
+        concurrency_limit=1
+    )
 
-    btn2.click(salamandra_chat_endpoint, [prompt], out2, api_name="generate_out_from_prompt", concurrency_limit=1)
+    # --------------------------------------------------------------
     gr.Markdown("---")
+    # --------------------------------------------------------------
 
+# Queue to handle multiple requests safely
 demo.queue(max_size=16).launch()