Update app.py

app.py

@@ -1,64 +1,89 @@
-# app.py  ── root of the repo
 """
-AnyCoder / Shasha AI – Gradio back‑end
-• Hosts the custom HTML/JS/CSS in /static
-• Exposes POST /run/predict for the browser‑side fetch()
+AnyCoder AI — static‑first UI wrapper
+Loads HTML/CSS/JS from the /static folder and exposes /run/predict for
+the front‑end to call.
+
+• static/index.html      dark themed UI
+• static/style.css       styles
+• static/index.js        JS logic (model list, fetch /run/predict)
+
+Back‑end helpers (models.py, inference.py, plugins.py …) are unchanged.
 """
-from __future__ import annotations
+
 from pathlib import Path
 from typing import List, Tuple
 
 import gradio as gr
 
-from inference       import chat_completion
-from tavily_search   import enhance_query_with_search
-from models          import AVAILABLE_MODELS, find_model, ModelInfo
-from utils           import (
-    extract_text_from_file, extract_website_content,
-    history_to_messages, history_to_chatbot_messages,
-    apply_search_replace_changes, remove_code_block,
-    parse_transformers_js_output, format_transformers_js_output,
+# ---------- imports that actually do the work ----------
+from inference import chat_completion                # runs the model
+from tavily_search import enhance_query_with_search
+from utils import (                                  # misc helpers
+    extract_text_from_file,
+    extract_website_content,
+    history_to_messages,
+    history_to_chatbot_messages,
+    apply_search_replace_changes,
+    remove_code_block,
+    parse_transformers_js_output,
+    format_transformers_js_output,
 )
+from models import AVAILABLE_MODELS, find_model, ModelInfo
+# -------------------------------------------------------
 
 SYSTEM_PROMPTS = {
-    "html":           "ONLY USE HTML, CSS & JS. Return ONE file wrapped in ```html```.",
-    "transformers.js":"Generate THREE files (index.html / index.js / style.css) as fenced blocks."
+    "html": (
+        "ONLY USE HTML, CSS AND JAVASCRIPT.  Return **one** HTML file "
+        "wrapped in ```html```."
+    ),
+    "transformers.js": (
+        "Generate THREE fenced blocks: index.html, index.js, style.css."
+    ),
 }
+
 History = List[Tuple[str, str]]
 
-# ─────────────────────────────────────────────────────────────────────────────
-def generate(prompt:str,
-             file_path:str|None,
-             website_url:str|None,
-             model_id:str,
-             language:str,
-             enable_search:bool,
-             history:History|None) -> Tuple[str,History]:
-    """Invoked by the JS front‑end."""
+# ------------------------------------------------------------------
+# /run/predict  — called by static/index.js
+# ------------------------------------------------------------------
+def generate(
+    prompt: str,
+    file_path: str | None,
+    website_url: str | None,
+    model_id: str,
+    language: str,
+    enable_search: bool,
+    history: History | None,
+):
     history = history or []
+
+    # 1 · system + user messages
     sys_prompt = SYSTEM_PROMPTS.get(language, f"You are an expert {language} developer.")
-    messages  = history_to_messages(history, sys_prompt)
+    msgs = history_to_messages(history, sys_prompt)
+
+    parts = [prompt.strip()]
 
-    ctx: list[str] = [prompt.strip()]
     if file_path:
-        ctx.append("[File]\n" + extract_text_from_file(file_path)[:5_000])
+        parts.append(extract_text_from_file(file_path)[:5_000])
+
     if website_url:
         html = extract_website_content(website_url)
         if not html.startswith("Error"):
-            ctx.append("[Website]\n" + html[:8_000])
+            parts.append(html[:8_000])
 
-    user_q = "\n\n".join(filter(None, ctx))
-    user_q = enhance_query_with_search(user_q, enable_search)
-    messages.append({"role": "user", "content": user_q})
+    user_query = enhance_query_with_search("\n\n".join(filter(None, parts)), enable_search)
+    msgs.append({"role": "user", "content": user_query})
 
+    # 2 · run model
     model: ModelInfo = find_model(model_id) or AVAILABLE_MODELS[0]
-    answer = chat_completion(model.id, messages)
+    reply = chat_completion(model.id, msgs)
 
+    # 3 · post‑process
     if language == "transformers.js":
-        files = parse_transformers_js_output(answer)
-        code  = format_transformers_js_output(files)
+        files = parse_transformers_js_output(reply)
+        code = format_transformers_js_output(files)
     else:
-        cleaned = remove_code_block(answer)
+        cleaned = remove_code_block(reply)
         if history and not history[-1][1].startswith("❌"):
             cleaned = apply_search_replace_changes(history[-1][1], cleaned)
         code = cleaned
@@ -66,28 +91,36 @@ def generate(prompt:str,
     history.append((prompt, code))
     return code, history
 
-# ─────────────────────────��───────────────────────────────────────────────────
-HTML_SOURCE = Path("static/index.html").read_text(encoding="utf-8")
+
+# ------------------------------------------------------------------
+# Serve static UI
+# ------------------------------------------------------------------
+HTML_SOURCE = Path("static/index.html").read_text(encoding="utf‑8")
 
 with gr.Blocks(css="body{margin:0}", title="AnyCoder AI") as demo:
-    gr.HTML(HTML_SOURCE)                            # the whole UI
-    # hidden I/O elements for the JS fetch()
-    with gr.Group(visible=False):
-        prompt_in  = gr.Textbox()
-        file_in    = gr.File()
-        url_in     = gr.Textbox()
-        model_in   = gr.Textbox()
-        lang_in    = gr.Textbox()
-        search_in  = gr.Checkbox()
-        hist_state = gr.State([])
-        code_out, hist_out = gr.Textbox(), gr.State([])
-
-    gr.Button(visible=False).click(                 # POST /run/predict
-        generate,
-        [prompt_in, file_in, url_in,
-         model_in, lang_in, search_in, hist_state],
-        [code_out, hist_out],
+    # Front‑end
+    gr.HTML(HTML_SOURCE)
+
+    # Hidden components for API
+    prompt_in  = gr.Textbox(visible=False)
+    file_in    = gr.File(visible=False)
+    url_in     = gr.Textbox(visible=False)
+    model_in   = gr.Textbox(visible=False)
+    lang_in    = gr.Textbox(visible=False)
+    search_in  = gr.Checkbox(visible=False)
+    hist_state = gr.State([])
+
+    code_out   = gr.Textbox(visible=False)
+    hist_out   = gr.State([])
+
+    # Expose /run/predict
+    dummy_btn = gr.Button(visible=False)
+    dummy_btn.click(
+        fn=generate,
+        inputs=[prompt_in, file_in, url_in, model_in, lang_in, search_in, hist_state],
+        outputs=[code_out, hist_out],
         api_name="predict",
+        queue=True,
     )
 
 if __name__ == "__main__":