Update app.py

app.py

@@ -1,127 +1,37 @@
-"""
-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.
-"""
-
+# app.py  (root)
 from pathlib import Path
-from typing import List, Tuple
-
 import gradio as gr
-
-# ---------- imports that actually do the work ----------
-from inference import chat_completion                # runs the model
+from inference import chat_completion           # your back‑end helpers
 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 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]]
-
-# ------------------------------------------------------------------
-# /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.")
-    msgs = history_to_messages(history, sys_prompt)
-
-    parts = [prompt.strip()]
-
-    if file_path:
-        parts.append(extract_text_from_file(file_path)[:5_000])
-
-    if website_url:
-        html = extract_website_content(website_url)
-        if not html.startswith("Error"):
-            parts.append(html[:8_000])
-
-    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]
-    reply = chat_completion(model.id, msgs)
-
-    # 3 · post‑process
-    if language == "transformers.js":
-        files = parse_transformers_js_output(reply)
-        code = format_transformers_js_output(files)
-    else:
-        cleaned = remove_code_block(reply)
-        if history and not history[-1][1].startswith("❌"):
-            cleaned = apply_search_replace_changes(history[-1][1], cleaned)
-        code = cleaned
-
-    history.append((prompt, code))
+from utils import (extract_text_from_file, extract_website_content,
+                   history_to_messages, apply_search_replace_changes,
+                   remove_code_block, parse_transformers_js_output,
+                   format_transformers_js_output)
+from models import AVAILABLE_MODELS, find_model
+from deploy import send_to_sandbox
+
+# ---------- backend callback -------------
+def generate(payload):
+    prompt  = payload["prompt"]
+    model   = find_model(payload["model_id"])
+    lang    = payload["language"]
+    history = payload.get("history", [])
+    # … same logic as before, returns {"code": ..., "history": [...] }
+    # (keep your existing generate() from the compact app.py)
     return code, history
 
-
-# ------------------------------------------------------------------
-# Serve static UI
-# ------------------------------------------------------------------
-HTML_SOURCE = Path("static/index.html").read_text(encoding="utf‑8")
+# ---------- UI ---------------------------
+INDEX = Path("static/index.html").read_text(encoding="utf-8")
 
 with gr.Blocks(css="body{margin:0}", title="AnyCoder AI") as demo:
-    # 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([])
+    # custom front‑end
+    gr.HTML(INDEX, unsafe_allow_html=True)
 
-    # 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,
-    )
+    # hidden API endpoints
+    generator = gr.JSON(
+        label="hidden",
+        visible=False
+    ).api(generate, path="/run/predict", methods=["POST"])
 
 if __name__ == "__main__":
-    demo.queue().launch()
+    demo.launch()