Update app.py

app.py

@@ -1,24 +1,22 @@
-# app.py
 """
-AnyCoder / Shasha AI – Gradio back‑end
+AnyCoder / Shasha AI – Gradio back‑end
 
-• Shows the custom front‑end shipped in index.html (plus static/style.css & static/index.js).
-• Exposes one JSON endpoint (`POST  /run/predict`) that the JS front‑end
+• Serves the custom front‑end shipped in index.html (+ static/style.css & static/index.js).
+• Exposes one JSON endpoint (`POST /run/predict`) that the JS front‑end
   calls to run model inference.
-• Keeps all existing helpers (hf_client, inference, utils, deploy …).
 """
 
 from pathlib import Path
-from typing import List, Tuple, Dict, Any
+from typing import List, Tuple
 
 import gradio as gr
 
-# ---- local helpers (unchanged) --------------------------------------------
-from inference   import chat_completion
-from tavily_search import enhance_query_with_search
-from deploy      import send_to_sandbox
-from models      import AVAILABLE_MODELS, find_model, ModelInfo
-from utils       import (
+# ---- local helpers --------------------------------------------------------
+from inference       import chat_completion
+from tavily_search   import enhance_query_with_search
+from deploy          import send_to_sandbox
+from models          import AVAILABLE_MODELS, find_model, ModelInfo
+from utils           import (
     extract_text_from_file,
     extract_website_content,
     history_to_messages,
@@ -52,10 +50,10 @@ def generate(
     enable_search: bool,
     history: History | None,
 ) -> Tuple[str, History]:
-    """Called by the JS front‑end via fetch('/run/predict')."""
+    """Called by the JS front‑end via POST /run/predict."""
     history = history or []
 
-    # --- build system + messages ------------------------------------------
+    # ----- build system + messages -----------------------------------------
     system_prompt = SYSTEM_PROMPTS.get(language, f"You are an expert {language} developer.")
     messages      = history_to_messages(history, system_prompt)
 
@@ -65,20 +63,20 @@ def generate(
         ctx_parts.append("[File]")
         ctx_parts.append(extract_text_from_file(file_path)[:5000])
     if website_url:
-        html = extract_website_content(website_url)
-        if not html.startswith("Error"):
+        site_html = extract_website_content(website_url)
+        if not site_html.startswith("Error"):
             ctx_parts.append("[Website]")
-            ctx_parts.append(html[:8000])
+            ctx_parts.append(site_html[:8000])
 
     user_query = "\n\n".join(filter(None, ctx_parts))
     user_query = enhance_query_with_search(user_query, enable_search)
     messages.append({"role": "user", "content": user_query})
 
-    # --- run model ---------------------------------------------------------
+    # ----- run model --------------------------------------------------------
     model: ModelInfo = find_model(model_id) or AVAILABLE_MODELS[0]
     answer = chat_completion(model.id, messages)
 
-    # --- post‑process ------------------------------------------------------
+    # ----- post‑process output ---------------------------------------------
     if language == "transformers.js":
         files = parse_transformers_js_output(answer)
         code  = format_transformers_js_output(files)
@@ -96,8 +94,8 @@ HTML_SOURCE = Path("index.html").read_text(encoding="utf‑8")
 
 # ------------------- Gradio UI ---------------------------------------------
 with gr.Blocks(css="body{margin:0}", title="AnyCoder AI") as demo:
-    # 1 visible: your own UI
-    gr.HTML(HTML_SOURCE, sanitize=False)
+    # 1 visible: your custom front‑end
+    gr.HTML(HTML_SOURCE)              # <- sanitize=False removed
 
     # 2 hidden: API inputs / outputs
     with gr.Group(visible=False) as api: