Update app.py

app.py

@@ -1,9 +1,14 @@
 import gradio as gr
 from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+import csv
+import os
+from datetime import datetime
 
 # --- CONFIGURATION ---
-MODEL_K2H_REPO = "ankitklakra/kurukh-to-hindi"  
-MODEL_H2K_REPO = "ankitklakra/hindi-to-kurukh"  
+
+MODEL_K2H_REPO = "ankitklakra/kurukh-to-hindi"
+MODEL_H2K_REPO = "ankitklakra/hindi-to-kurukh"
+FEEDBACK_FILE = "feedback_log.csv"
 
 # --- LOAD RESOURCES ---
 print("Loading Tokenizer...")
@@ -13,53 +18,96 @@ print("Loading Models...")
 model_k2h = AutoModelForSeq2SeqLM.from_pretrained(MODEL_K2H_REPO)
 model_h2k = AutoModelForSeq2SeqLM.from_pretrained(MODEL_H2K_REPO)
 
-# Create Pipelines
 pipe_k2h = pipeline("text2text-generation", model=model_k2h, tokenizer=tokenizer)
 pipe_h2k = pipeline("text2text-generation", model=model_h2k, tokenizer=tokenizer)
 
-# --- TRANSLATION FUNCTION ---
+# --- HELPER FUNCTIONS ---
 def translate_text(text, direction):
     if not text:
         return ""
-    
     target_pipeline = pipe_k2h if direction == "Kurukh -> Hindi" else pipe_h2k
-    
     try:
         results = target_pipeline(text, max_length=128)
         return results[0]['generated_text']
     except Exception as e:
         return f"Error: {str(e)}"
 
-# --- THE UI ---
-
-with gr.Blocks() as demo:
+def save_feedback(original_text, translation, corrected_text, direction):
+    """Saves user corrections to a CSV file"""
+    if not corrected_text:
+        return "⚠️ Please enter a correction before submitting."
     
-    gr.Markdown("# 🇮🇳 AI Kurukh (Kurux) Translator")
-    gr.Markdown("### Preserving Tribal Languages with Artificial Intelligence")
+    file_exists = os.path.isfile(FEEDBACK_FILE)
     
-    with gr.Row():
-        direction = gr.Radio(
-            ["Kurukh -> Hindi", "Hindi -> Kurukh"], 
-            label="Translation Mode", 
-            value="Kurukh -> Hindi"
-        )
+    with open(FEEDBACK_FILE, mode='a', newline='', encoding='utf-8') as file:
+        writer = csv.writer(file)
+        # Write header if file is new
+        if not file_exists:
+            writer.writerow(["Timestamp", "Direction", "Original", "AI_Translation", "User_Correction"])
+        
+        writer.writerow([datetime.now(), direction, original_text, translation, corrected_text])
     
-    with gr.Row():
-        input_text = gr.Textbox(label="Input Text", lines=5, placeholder="Type here...")
-        output_text = gr.Textbox(label="Translation Result", lines=5)
-            
-    translate_btn = gr.Button("Translate 🚀", variant="primary")
+    return "✅ Thank you! Your correction has been saved to improve the model."
+
+# --- THE UI ---
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
     
-    gr.Examples(
-        examples=[
-            ["निघै नामे इन्द्रा हिकै?", "Kurukh -> Hindi"],
-            ["इन्गे अम्मो चि'आ।", "Kurukh -> Hindi"],
-            ["तुम्हारा नाम क्या है?", "Hindi -> Kurukh"],
-            ["मुझे पानी दो।", "Hindi -> Kurukh"]
-        ],
-        inputs=[input_text, direction]
+    gr.Markdown(
+        """
+        # 🇮🇳 AI Kurukh (Kurux) Translator
+        ### Preserving Tribal Languages with Artificial Intelligence
+        """
     )
+    
+    with gr.Tabs():
+        # TAB 1: TRANSLATOR
+        with gr.TabItem("🗣️ Translator"):
+            with gr.Row():
+                direction = gr.Radio(
+                    ["Kurukh -> Hindi", "Hindi -> Kurukh"], 
+                    label="Translation Mode", 
+                    value="Kurukh -> Hindi"
+                )
+            
+            with gr.Row():
+                with gr.Column():
+                    input_text = gr.Textbox(label="Input Text", placeholder="Type here...", lines=4)
+                    translate_btn = gr.Button("Translate 🚀", variant="primary")
+                
+                with gr.Column():
+                    output_text = gr.Textbox(label="AI Translation", lines=4, interactive=False)
+            
+            translate_btn.click(fn=translate_text, inputs=[input_text, direction], outputs=output_text)
+            
+            gr.Examples(
+                examples=[
+                    ["निघै नामे इन्द्रा हिकै?", "Kurukh -> Hindi"],
+                    ["इन्गे अम्मो चि'आ।", "Kurukh -> Hindi"],
+                    ["तुम्हारा नाम क्या है?", "Hindi -> Kurukh"]
+                ],
+                inputs=[input_text, direction]
+            )
 
-    translate_btn.click(fn=translate_text, inputs=[input_text, direction], outputs=output_text)
+        # TAB 2: FEEDBACK (THE NEW FEATURE)
+        with gr.TabItem("📝 Improve the AI"):
+            gr.Markdown("### Help us make this model better!")
+            gr.Markdown("If the AI made a mistake, please paste the text below and tell us the correct translation.")
+            
+            with gr.Row():
+                fb_direction = gr.Radio(["Kurukh -> Hindi", "Hindi -> Kurukh"], label="Direction", value="Kurukh -> Hindi")
+            
+            with gr.Row():
+                fb_original = gr.Textbox(label="Original Text")
+                fb_ai_output = gr.Textbox(label="What the AI said (Optional)")
+                fb_user_correct = gr.Textbox(label="What it SHOULD be (Your Correction)", lines=2)
+            
+            submit_fb_btn = gr.Button("Submit Correction ✅")
+            fb_status = gr.Label(label="Status")
+            
+            submit_fb_btn.click(
+                fn=save_feedback,
+                inputs=[fb_original, fb_ai_output, fb_user_correct, fb_direction],
+                outputs=fb_status
+            )
 
 demo.launch()