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Download app.py from Ghada-99-Ragab/Amanah_AI: direct link, hf CLI and curl.
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- Download file 6.9 kB
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https://huggingface.co/spaces/Ghada-99-Ragab/Amanah_AI/resolve/main/app.py
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hf download hf://spaces/Ghada-99-Ragab/Amanah_AI/app.py
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curl -L -o app.py https://huggingface.co/spaces/Ghada-99-Ragab/Amanah_AI/resolve/main/app.py
6.9 kB
| from __future__ import annotations | |
| import json | |
| import logging | |
| import os | |
| import threading | |
| from pathlib import Path | |
| from typing import List, Optional | |
| import ui | |
| from camelbert_adapter import analyze_hybrid, entities_to_spans, query_hosted_model | |
| from llm_client import LLMError, generate, sanitize_answer | |
| from verifier import MAX_INPUT_CHARS, IslamicContentVerifier | |
| logger = logging.getLogger(__name__) | |
| EXAMPLES_PATH = Path(__file__).resolve().parent / "demo" / "examples.json" | |
| _pipeline: Optional[IslamicContentVerifier] = None | |
| _lock = threading.Lock() | |
| def get_pipeline() -> IslamicContentVerifier: | |
| global _pipeline | |
| with _lock: | |
| if _pipeline is None: | |
| _pipeline = IslamicContentVerifier() | |
| return _pipeline | |
| def warm_in_background() -> None: | |
| threading.Thread(target=lambda: get_pipeline().retriever.warm(), daemon=True).start() | |
| def load_examples(path: Path = EXAMPLES_PATH) -> List[dict]: | |
| try: | |
| with open(path, encoding="utf-8") as handle: | |
| return json.load(handle) | |
| except (OSError, json.JSONDecodeError): | |
| logger.exception("Could not load demo examples from %s", path) | |
| return [] | |
| def _analyze(text: str, entities_json: str = "") -> dict: | |
| pipeline = get_pipeline() | |
| model_spans: list = [] | |
| try: | |
| if entities_json: | |
| model_spans = entities_to_spans(text, json.loads(entities_json)) | |
| elif os.environ.get("ICV_HF_MODEL", "").strip(): | |
| model_spans = query_hosted_model(text, os.environ["ICV_HF_MODEL"].strip(), os.environ.get("HF_TOKEN", "")) | |
| except (RuntimeError, ValueError, TypeError): | |
| logger.warning("Hosted model unavailable; using the bundled detector only") | |
| model_spans = [] | |
| return analyze_hybrid(pipeline, text, model_spans) | |
| def verify_text(text: str, entities_json: str = "") -> str: | |
| if not text or not text.strip(): | |
| return ui.render_message("الرجاء إدخال نص للتحقق منه.", "warn") | |
| try: | |
| return ui.render_results(_analyze(text, entities_json)) | |
| except ValueError: | |
| return ui.render_message(f"النص طويل جدًا (الحد الأقصى {MAX_INPUT_CHARS} حرف).", "warn") | |
| except Exception: | |
| logger.exception("Verification failed") | |
| return ui.render_message("حدث خطأ غير متوقع أثناء التحقق.", "bad") | |
| def verify_generated_answer(answer: str, entities_json: str = "") -> str: | |
| try: | |
| answer = sanitize_answer(answer) | |
| return ui.render_results(_analyze(answer, entities_json), generated_answer=answer) | |
| except ValueError: | |
| return ui.render_message(f"الإجابة طويلة جدًا (الحد الأقصى {MAX_INPUT_CHARS} حرف).", "warn") | |
| except Exception: | |
| logger.exception("Verification of the generated answer failed") | |
| return ui.render_message("تعذّر التحقق من إجابة النموذج.", "bad") | |
| def ask_then_verify(prompt: str) -> str: | |
| try: | |
| answer = generate(None, prompt) | |
| except LLMError as exc: | |
| return ui.render_message(str(exc), "warn") | |
| return verify_generated_answer(answer) | |
| def build_interface(): | |
| import gradio as gr | |
| examples = load_examples() | |
| def next_example(index: int): | |
| if not examples: | |
| return "", 0 | |
| return examples[index % len(examples)]["text"], (index + 1) % len(examples) | |
| samples = [e for e in examples if e.get("question")] | |
| def next_ask_example(index: int): | |
| if not samples: | |
| return "", 0 | |
| return samples[index % len(samples)]["question"], (index + 1) % len(samples) | |
| def saved_answer_check(question: str): | |
| for sample in samples: | |
| if sample["question"] == question: | |
| return verify_generated_answer(sample["text"]) | |
| return ui.render_message("اختر مثالًا أولًا.", "warn") | |
| theme = gr.themes.Base(primary_hue="emerald", neutral_hue="stone") | |
| with gr.Blocks(title=ui.APP_TITLE, css=ui.CSS, theme=theme, head=f"<script>{ui.COPY_JS}</script>") as demo: | |
| gr.HTML(ui.HERO) | |
| with gr.Tabs(): | |
| with gr.Tab("تحقّق مباشر"): | |
| example_index = gr.State(0) | |
| text_input = gr.Textbox(label="النص المراد التحقق منه", lines=9, max_lines=24, placeholder=ui.PLACEHOLDER, | |
| rtl=True, elem_classes="input-area") | |
| with gr.Row(): | |
| verify_button = gr.Button("تحقّق من النص", variant="primary", scale=3) | |
| example_button = gr.Button("جرّب مثالًا", variant="secondary", scale=2) | |
| results = gr.HTML(elem_classes="results") | |
| verify_button.click(verify_text, inputs=text_input, outputs=results) | |
| example_button.click(next_example, inputs=example_index, outputs=[text_input, example_index]).then( | |
| verify_text, inputs=text_input, outputs=results) | |
| with gr.Tab("اسأل ثم تحقّق"): | |
| gr.HTML('<div class="icv"><div class="notice">اكتب سؤالًا، وسيجيب عنه النظام مباشرةً، ثم يفحص كل آية ' | |
| 'وحديث ورد في الإجابة ويعرض الأخطاء والتصحيحات.</div></div>') | |
| prompt = gr.Textbox(label="سؤالك", lines=3, placeholder=ui.PROMPT_PLACEHOLDER, rtl=True, elem_classes="input-area") | |
| with gr.Row(): | |
| ask_button = gr.Button("اسأل ثم تحقّق", variant="primary", scale=3) | |
| ask_example_button = gr.Button("جرّب مثالًا", variant="secondary", scale=2) | |
| answer_results = gr.HTML(elem_classes="results") | |
| ask_button.click(ask_then_verify, inputs=prompt, outputs=answer_results) | |
| ask_example_state = gr.State(0) | |
| ask_example_button.click(next_ask_example, inputs=ask_example_state, outputs=[prompt, ask_example_state]).then( | |
| saved_answer_check, inputs=prompt, outputs=answer_results) | |
| gr.HTML(ui.DISCLAIMER) | |
| return demo | |
| def _load_dotenv(path: Path = Path(__file__).resolve().parent / ".env") -> None: | |
| try: | |
| lines = path.read_text(encoding="utf-8").splitlines() | |
| except OSError: | |
| return | |
| for line in lines: | |
| name, sep, value = line.strip().partition("=") | |
| if sep and name and not name.startswith("#") and value.strip(): | |
| os.environ.setdefault(name.strip(), value.strip().strip('"').strip("'")) | |
| def main() -> None: | |
| logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s: %(message)s") | |
| _load_dotenv() | |
| get_pipeline() | |
| warm_in_background() | |
| build_interface().queue().launch(share=os.environ.get("ICV_SHARE") == "1") | |
| if __name__ == "__main__": | |
| main() | |