Update app.py

app.py

@@ -1,8 +1,27 @@
+# ===============================
+# 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
+
 # ------------------------
-# 2️⃣ ساخت دیتاست ترکیبی (اصلاح شده)
+# 1️⃣ ورود با Secret
+# ------------------------
+hf_token = os.environ.get("HF_TOKEN", None)
+if hf_token is None:
+    raise ValueError("HF_TOKEN not found in Secrets. Please add it in Space settings.")
+login(token=hf_token)
+
+# ------------------------
+# 2️⃣ ساخت دیتاست ترکیبی
 # ------------------------
 def build_dataset():
-    # مثال عمومی کوچک
+    print("Creating a small general dataset...")
     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."}
@@ -13,7 +32,7 @@ def build_dataset():
     derma_examples = [{"domain":"dermatology","context":item['question'],"response":item['answer']}
                       for item in derma]
 
-    print("Loading MedQuAD...")
+    print("Loading MedQuAD subset...")
     medquad = load_dataset("pythonafroz/MedQuAD")['train']
     derma_keywords = ["skin", "eczema", "psoriasis", "dermatitis", "melanoma", "acne", "rash"]
     medquad_derma = [{"domain":"dermatology","context":item['question'],"response":item['answer']}
@@ -35,7 +54,7 @@ def build_dataset():
     print(f"✅ Dataset saved locally as {output_file} ({len(all_examples)} examples)")
 
     # آپلود به HF
-    repo_id = "username/Derma"
+    repo_id = "username/Derma"  # تغییر بده به نام کاربری خودت
     api = HfApi()
     api.create_repo(repo_id=repo_id, repo_type="dataset", exist_ok=True)
     upload_file(
@@ -46,3 +65,43 @@ 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]
+    
+    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__":
+    if not os.path.exists("derma_chat_mix.jsonl"):
+        build_dataset()
+    iface.launch()