Update app.py

app.py

@@ -1,38 +1,12 @@
-# ===============================
-# Derma Space: Dataset + Gradio Chatbot
-# ===============================
-
-import json
-import random
-import os
-import gradio as gr
-from datasets import load_dataset
-from huggingface_hub import HfApi, login, upload_file
-
-# ------------------------
-# 1️⃣ ورود با Secret
-# ------------------------
-hf_token = os.environ["HF_TOKEN"]
-login(token=hf_token)
-
 # ------------------------
-# 2️⃣ ساخت دیتاست ترکیبی
+# 2️⃣ ساخت دیتاست ترکیبی (اصلاح شده)
 # ------------------------
 def build_dataset():
-    print("Loading DailyDialog...")
-    dd = load_dataset("daily_dialog")['train']
-    dd_examples = [{"domain":"general","context":conv[i],"response":conv[i+1]}
-                   for conv in dd['dialog'] for i in range(len(conv)-1)]
-
-    print("Loading Persona-Chat...")
-    pc = load_dataset("persona_chat", "self_original")['train']
-    pc_examples = [{"domain":"general","context":conv['utterances'][i]['text'],
-                    "response":conv['utterances'][i+1]['text']}
-                   for conv in pc for i in range(len(conv['utterances'])-1)]
-
-    general_examples = dd_examples + pc_examples
-    random.shuffle(general_examples)
-    general_examples = general_examples[:5000]
+    # مثال عمومی کوچک
+    general_examples = [
+        {"domain":"general", "context":"Hello, how are you?", "response":"I'm good, thank you!"},
+        {"domain":"general", "context":"What's your name?", "response":"I'm Derma ChatBot."}
+    ]
 
     print("Loading Dermatology QA (Mreeb)...")
     derma = load_dataset("Mreeb/Dermatology-Question-Answer-Dataset-For-Fine-Tuning")['train']
@@ -61,7 +35,7 @@ def build_dataset():
     print(f"✅ Dataset saved locally as {output_file} ({len(all_examples)} examples)")
 
     # آپلود به HF
-    repo_id = "username/Derma"  # نام کاربری خودت + نام Space
+    repo_id = "username/Derma"
     api = HfApi()
     api.create_repo(repo_id=repo_id, repo_type="dataset", exist_ok=True)
     upload_file(
@@ -72,46 +46,3 @@ def build_dataset():
         commit_message="Initial upload of text-based chat dataset"
     )
     print(f"✅ Dataset uploaded: https://huggingface.co/datasets/{repo_id}")
-
-# ------------------------
-# 3️⃣ چت ساده با Gradio
-# ------------------------
-def simple_chat(user_input):
-    # جستجو در دیتاست برای پاسخ نزدیک (ساده)
-    with open("derma_chat_mix.jsonl", 'r', encoding='utf-8') as f:
-        data = [json.loads(line) for line in f]
-    
-    # جستجوی پاسخ بر اساس کلمات مشترک
-    best_match = None
-    max_overlap = 0
-    for item in data:
-        overlap = len(set(user_input.lower().split()) & set(item['context'].lower().split()))
-        if overlap > max_overlap:
-            max_overlap = overlap
-            best_match = item['response']
-    
-    if best_match:
-        return best_match
-    else:
-        return "Sorry, I don't have a good answer for that. Try another question!"
-
-# ------------------------
-# 4️⃣ راه‌اندازی Gradio
-# ------------------------
-iface = gr.Interface(
-    fn=simple_chat,
-    inputs=gr.Textbox(lines=2, placeholder="Ask about dermatology or chat casually..."),
-    outputs=gr.Textbox(label="Derma ChatBot"),
-    title="Derma ChatBot",
-    description="A simple English chatbot combining general conversation + dermatology QA."
-)
-
-# ------------------------
-# 5️⃣ اجرای دیتاست + رابط
-# ------------------------
-if __name__ == "__main__":
-    # فقط یک بار دیتاست بساز
-    if not os.path.exists("derma_chat_mix.jsonl"):
-        build_dataset()
-    
-    iface.launch()