# app.py # ──────────────────────────────────────────────────────────────── """ AnyCoder / Shasha AI – single‑file Gradio interface • Pick a model (registry in models.py) • Give context (prompt, file upload, or website URL) • Choose from 25+ target languages • Optional Tavily web‑search enrichment • Generate code, preview HTML, see conversation history """ from __future__ import annotations from typing import List, Tuple, Dict, Any import gradio as gr # ── local modules ─────────────────────────────────────────────── from models import AVAILABLE_MODELS, find_model, ModelInfo from inference import chat_completion from tavily_search import enhance_query_with_search 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, ) from deploy import send_to_sandbox # ── constants ─────────────────────────────────────────────────── SUPPORTED_LANGUAGES = [ "python", "c", "cpp", "markdown", "latex", "json", "html", "css", "javascript", "jinja2", "typescript", "yaml", "dockerfile", "shell", "r", "sql", "sql-msSQL", "sql-mySQL", "sql-mariaDB", "sql-sqlite", "sql-cassandra", "sql-plSQL", "sql-hive", "sql-pgSQL", "sql-gql", "sql-gpSQL", "sql-sparkSQL", "sql-esper", ] SYSTEM_PROMPTS = { "html": ( "ONLY USE HTML, CSS AND JAVASCRIPT. " "Return exactly one complete HTML page wrapped in ```html ...```." ), "transformers.js": ( "Generate THREE fenced blocks: " "`index.html`, `index.js`, and `style.css` for a transformers.js web‑app." ), } History = List[Tuple[str, str]] # ── back‑end callback ─────────────────────────────────────────── def generate_code( prompt: str, file_path: str | None, website_url: str | None, model_name: str, enable_search: bool, language: str, hist: History | None, ) -> Tuple[str, History, str, List[Dict[str, str]]]: """Runs on **Generate Code** click.""" hist = hist or [] prompt = (prompt or "").strip() # 1 build message list sys_prompt = SYSTEM_PROMPTS.get(language, f"You are an expert {language} developer.") msgs = history_to_messages(hist, sys_prompt) ctx: List[str] = [prompt] if prompt else [] if file_path: ctx += ["[File]", extract_text_from_file(file_path)[:5000]] if website_url: site_html = extract_website_content(website_url) if not site_html.startswith("Error"): ctx += ["[Website]", site_html[:8000]] user_query = enhance_query_with_search("\n\n".join(ctx), enable_search) msgs.append({"role": "user", "content": user_query}) # 2 call model through inference.py model: ModelInfo = find_model(model_name) or AVAILABLE_MODELS[0] try: raw = chat_completion(model.id, msgs) except Exception as exc: # pragma: no cover err = f"❌ **Error**\n```{exc}```" hist.append((prompt, err)) return "", hist, "", history_to_chatbot_messages(hist) # 3 post‑process response if language == "transformers.js": files = parse_transformers_js_output(raw) code = format_transformers_js_output(files) preview = send_to_sandbox(files.get("index.html", "")) else: cleaned = remove_code_block(raw) if hist and not hist[-1][1].startswith("❌"): cleaned = apply_search_replace_changes(hist[-1][1], cleaned) code = cleaned preview = send_to_sandbox(cleaned) if language == "html" else "" hist.append((prompt, code)) chat_display = history_to_chatbot_messages(hist) return code, hist, preview, chat_display # ── Gradio UI ─────────────────────────────────────────────────── THEME = gr.themes.Soft(primary_hue="indigo") CSS = """ body {font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Arial,sans-serif} #title {text-align:center;font-size:2.3rem;margin-top:1rem} #subtitle {text-align:center;color:#55606d;margin-bottom:2rem} """ with gr.Blocks(theme=THEME, css=CSS, title="AnyCoder AI") as demo: state_hist: gr.State[History] = gr.State([]) gr.Markdown("## 🚀 AnyCoder AI", elem_id="title") gr.Markdown("Your AI partner for generating, modifying & understanding code.", elem_id="subtitle") with gr.Row(): # ── sidebar (inputs) with gr.Column(scale=1): gr.Markdown("#### 1 · Model") model_dd = gr.Dropdown( choices=[m.name for m in AVAILABLE_MODELS], value=AVAILABLE_MODELS[0].name, label="AI Model", ) gr.Markdown("#### 2 · Context") with gr.Tabs(): with gr.Tab("Prompt"): prompt_box = gr.Textbox(lines=6, placeholder="Describe what you want to build…") with gr.Tab("File"): file_box = gr.File(type="filepath") with gr.Tab("Website"): url_box = gr.Textbox(placeholder="https://example.com") gr.Markdown("#### 3 · Output") lang_dd = gr.Dropdown(SUPPORTED_LANGUAGES, value="html", label="Target Language") search_ck = gr.Checkbox(label="Enable Tavily Web Search") with gr.Row(): clear_btn = gr.Button("Clear Session", variant="secondary") gen_btn = gr.Button("Generate Code", variant="primary") # ── main panel (outputs) with gr.Column(scale=2): with gr.Tabs(): with gr.Tab("Code"): code_out = gr.Code(interactive=True, label=None) with gr.Tab("Live Preview"): preview_out = gr.HTML() with gr.Tab("History"): chat_out = gr.Chatbot(type="messages") # wiring gen_btn.click( generate_code, inputs=[prompt_box, file_box, url_box, model_dd, search_ck, lang_dd, state_hist], outputs=[code_out, state_hist, preview_out, chat_out], ) clear_btn.click( lambda: ("", None, "", "html", False, [], [], "", ""), outputs=[prompt_box, file_box, url_box, lang_dd, search_ck, state_hist, code_out, preview_out, chat_out], queue=False, ) if __name__ == "__main__": demo.queue().launch()