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""" |
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AnyCoder / Shasha AI – Gradio back‑end |
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• Hosts the custom HTML/JS/CSS in /static |
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• Exposes POST /run/predict for the browser‑side fetch() |
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""" |
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from __future__ import annotations |
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from pathlib import Path |
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from typing import List, Tuple |
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import gradio as gr |
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from inference import chat_completion |
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from tavily_search import enhance_query_with_search |
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from models import AVAILABLE_MODELS, find_model, ModelInfo |
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from utils import ( |
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extract_text_from_file, extract_website_content, |
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history_to_messages, history_to_chatbot_messages, |
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apply_search_replace_changes, remove_code_block, |
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parse_transformers_js_output, format_transformers_js_output, |
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) |
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SYSTEM_PROMPTS = { |
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"html": "ONLY USE HTML, CSS & JS. Return ONE file wrapped in ```html```.", |
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"transformers.js":"Generate THREE files (index.html / index.js / style.css) as fenced blocks." |
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} |
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History = List[Tuple[str, str]] |
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def generate(prompt:str, |
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file_path:str|None, |
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website_url:str|None, |
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model_id:str, |
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language:str, |
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enable_search:bool, |
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history:History|None) -> Tuple[str,History]: |
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"""Invoked by the JS front‑end.""" |
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history = history or [] |
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sys_prompt = SYSTEM_PROMPTS.get(language, f"You are an expert {language} developer.") |
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messages = history_to_messages(history, sys_prompt) |
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ctx: list[str] = [prompt.strip()] |
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if file_path: |
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ctx.append("[File]\n" + extract_text_from_file(file_path)[:5_000]) |
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if website_url: |
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html = extract_website_content(website_url) |
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if not html.startswith("Error"): |
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ctx.append("[Website]\n" + html[:8_000]) |
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user_q = "\n\n".join(filter(None, ctx)) |
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user_q = enhance_query_with_search(user_q, enable_search) |
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messages.append({"role": "user", "content": user_q}) |
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model: ModelInfo = find_model(model_id) or AVAILABLE_MODELS[0] |
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answer = chat_completion(model.id, messages) |
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if language == "transformers.js": |
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files = parse_transformers_js_output(answer) |
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code = format_transformers_js_output(files) |
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else: |
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cleaned = remove_code_block(answer) |
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if history and not history[-1][1].startswith("❌"): |
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cleaned = apply_search_replace_changes(history[-1][1], cleaned) |
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code = cleaned |
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history.append((prompt, code)) |
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return code, history |
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HTML_SOURCE = Path("static/index.html").read_text(encoding="utf-8") |
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with gr.Blocks(css="body{margin:0}", title="AnyCoder AI") as demo: |
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gr.HTML(HTML_SOURCE) |
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with gr.Group(visible=False): |
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prompt_in = gr.Textbox() |
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file_in = gr.File() |
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url_in = gr.Textbox() |
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model_in = gr.Textbox() |
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lang_in = gr.Textbox() |
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search_in = gr.Checkbox() |
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hist_state = gr.State([]) |
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code_out, hist_out = gr.Textbox(), gr.State([]) |
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gr.Button(visible=False).click( |
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generate, |
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[prompt_in, file_in, url_in, |
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model_in, lang_in, search_in, hist_state], |
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[code_out, hist_out], |
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api_name="predict", |
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) |
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if __name__ == "__main__": |
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demo.queue().launch() |
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