Update app.py

app.py

@@ -1,253 +1,59 @@
-"""Haqeeqat Check — Gradio interface for Hugging Face Spaces.
-
-Run locally:  python app.py
-"""
-
 import os
-import subprocess
 import sys
-from pathlib import Path
-
-# ---------------------------------------------------------------------------
-# Ensure GROQ_API_KEY is loaded from Space secrets before any module import
-# ---------------------------------------------------------------------------
-if not os.environ.get("GROQ_API_KEY"):
-    pass  # will be read at runtime by verification/config.py
-
-import gradio as gr
-
-try:
-    import spaces
-    _HAS_SPACES = True
-except ImportError:
-    _HAS_SPACES = False
-
-# ---------------------------------------------------------------------------
-# Model bootstrap — runs once at import time
-# ---------------------------------------------------------------------------
-_MODEL_FILES = ["best_norm_ED.pth", "yolov8m_UrduDoc.pt"]
-
-
-def _ensure_models():
-    """Download OCR + Whisper models if not already present."""
-    root = Path(__file__).resolve().parent
-    models_dir = root / "models"
-    if os.environ.get("SPACE_ID"):
-        models_dir = Path("/home/user/app/models")
-    if all((models_dir / name).is_file() for name in _MODEL_FILES):
-        return
-    subprocess.run(
-        [sys.executable, str(root / "download_models.py")],
-        check=True,
-    )
-
-
-_ensure_models()
-
-# ---------------------------------------------------------------------------
-# Lazy singletons — heavy imports deferred until first request
-# ---------------------------------------------------------------------------
-_ingestor = None
-_agent = None
-
-
-def _get_ingestor():
-    global _ingestor
-    if _ingestor is None:
-        from ingestion.ingestor import HaqeeqatIngestor
-        _ingestor = HaqeeqatIngestor()
-    return _ingestor
-
-
-def _get_agent():
-    global _agent
-    if _agent is None:
-        from verification.verdict_agent import VerdictAgent
-        _agent = VerdictAgent()
-    return _agent
-
-
-# ---------------------------------------------------------------------------
-# Labels
-# ---------------------------------------------------------------------------
-URDU_LABELS = {"sacha": "سچا", "jhoota": "جھوٹا", "mashkook": "مشکوک"}
-ENGLISH_LABELS = {"sacha": "True", "jhoota": "False", "mashkook": "Unverified"}
-VERDICT_ICONS = {"sacha": "✔", "jhoota": "✗", "mashkook": "?"}
-
-
-# ---------------------------------------------------------------------------
-# Core processing
-# ---------------------------------------------------------------------------
-
-if _HAS_SPACES:
-    @spaces.GPU
-    def _gpu_startup():
-        """Dummy function so Gradio 6.x detects a GPU-capable handler at startup."""
-        pass
-
-
-def _resolve_path(file_data) -> str | None:
-    """Extract a filesystem path from a Gradio FileData object or plain string."""
-    if isinstance(file_data, str):
-        return file_data
-    # Gradio 6.x FileData: object with .path or dict-like access
-    if hasattr(file_data, "path"):
-        return file_data.path
-    if isinstance(file_data, dict):
-        return file_data.get("path")
-    return None
-
-
-def _process_media_inner(file_data) -> tuple[str, str]:
-    """Ingest a media file, verify claims, return (verdict_box, reasoning_box)."""
-    if file_data is None:
-        return "کوئی فائل منتخب نہیں / No file selected.", ""
 
-    # Gradio 6.x passes a FileData object; extract the path string
-    file_path = _resolve_path(file_data)
-    if not file_path:
-        return "کوئی فائل منتخب نہیں / No file selected.", ""
+from .config import debug_enabled
+from .verdict_agent import VerdictAgent
 
-    ingestor = _get_ingestor()
-    agent = _get_agent()
 
-    report = ingestor.ingest(file_path)
-    text = report.get("combined_text", "")
-    if not text or not text.strip():
-        return "کوئی متن نکالا نہیں جا سکا / No text was extracted from the file.", ""
-
-    if report.get("metadata", {}).get("ocr_garbled"):
-        return (
-            "تصحیح OCR ناکام رہی / OCR failed to read this image properly.\n"
-            "براہ کرم واضح تصویر اپ لوڈ کریں / Please upload a clearer image."
-        ), f"استخراج شدہ متن:\n{text[:300]}"
-
-    result = agent.run(text)
-
-    if not result.is_checkworthy:
-        return "کوئی قابلِ تصدیق دعویٰ نہیں / No checkworthy claim found.", (
-            f"استخراج شدہ متن:\n{text[:500]}"
+def main(argv=None, ingestor=None, agent=None):
+    argv = list(sys.argv if argv is None else argv)
+    debug = "--debug" in argv
+    argv = [arg for arg in argv if arg != "--debug"]
+    if debug:
+        os.environ["HAQEEQAT_DEBUG"] = "1"
+    if len(argv) != 2:
+        print(
+            "Usage: python -m verification.app [--debug] <image|audio|video file>",
+            file=sys.stderr,
         )
+        return 2
+    path = argv[1]
 
-    verdict_box = _format_verdict(result)
-    reasoning_box = _format_reasoning(result)
-    return verdict_box, reasoning_box
+    if ingestor is None:
+        from ingestion.ingestor import HaqeeqatIngestor
 
+        ingestor = HaqeeqatIngestor()
+    if agent is None:
+        agent = VerdictAgent()
 
-def _process_text(text: str) -> tuple[str, str]:
-    """Verify a pasted text claim, return (verdict_box, reasoning_box)."""
-    if not text or not text.strip():
-        return "براہ کرم متن لکھیں / Please enter some text.", ""
+    report = ingestor.ingest(path)
+    text = report["combined_text"]
+    if not text.strip():
+        print("No text could be extracted from the file.", file=sys.stderr)
+        return 1
 
-    agent = _get_agent()
     result = agent.run(text)
-
+    if debug_enabled():
+        print(f"DEBUG extracted_text: {text!r}")
+        print(f"DEBUG claim_urdu: {result.claim_urdu}")
+        print(f"DEBUG claim_english: {result.claim_english}")
+        print(f"DEBUG verdict: {result.verdict.value if result.verdict else None}")
+        print(f"DEBUG confidence: {result.confidence:.2f}")
+        print(f"DEBUG evidence_count: {len(result.evidence)}")
+        for i, item in enumerate(result.evidence):
+            print(f"DEBUG evidence[{i}]: {item.source_domain} | {item.title} | {item.url}")
     if not result.is_checkworthy:
-        return "کوئی قابلِ تصدیق دعویٰ نہیں / No checkworthy claim found.", ""
-
-    verdict_box = _format_verdict(result)
-    reasoning_box = _format_reasoning(result)
-    return verdict_box, reasoning_box
-
-
-# Wrap _process_media_inner with @spaces.GPU on HF so UTRNet gets a GPU.
-if _HAS_SPACES:
-    @spaces.GPU
-    def _process_media(file_data) -> tuple[str, str]:
-        return _process_media_inner(file_data)
-else:
-    _process_media = _process_media_inner
-
-
-def _format_verdict(result) -> str:
-    key = result.verdict.value
-    icon = VERDICT_ICONS[key]
-    urdu_label = URDU_LABELS[key]
-    eng_label = ENGLISH_LABELS[key]
-    lines = [
-        f"{icon}  فیصلہ / Verdict:  {urdu_label} ({eng_label})",
-        f" Confidence: {result.confidence:.0%}",
-        "",
-        f"دعویٰ / Claim:",
-        f"  {result.claim_urdu}",
-        f"  {result.claim_english}",
-    ]
-    return "\n".join(lines)
-
-
-def _format_reasoning(result) -> str:
-    parts = [
-        "وجوہات / Reasoning:",
-        "",
-        result.reasoning_urdu,
-        "",
-        result.reasoning_english,
-    ]
-    if result.evidence:
-        parts.append("")
-        parts.append("شواہد / Sources:")
-        for item in result.evidence:
-            parts.append(f"  [{item.source_domain}] {item.title}")
-            parts.append(f"  {item.url}")
-            if item.snippet:
-                parts.append(f"  {item.snippet[:200]}")
-            parts.append("")
-    return "\n".join(parts)
-
-
-# ---------------------------------------------------------------------------
-# Gradio UI
-# ---------------------------------------------------------------------------
-def build_ui() -> gr.Blocks:
-    with gr.Blocks(
-        title="Haqeeqat Check — Urdu Misinformation Detector",
-    ) as demo:
-        gr.Markdown(
-            "# Uraan Techathon 2.0\n"
-            "# Haqeeqat Check: Urdu Misinformation Detector\n"
-            "### حقیقت چیک: اردو غلط معلومات کی جانچ پڑتال"
-        )
-
-        with gr.Tabs():
-            with gr.Tab("Image"):
-                img_input = gr.Image(label="تصویر اپ لوڈ کریں / Upload Image", type="filepath")
-                img_btn = gr.Button("Check / چیک کریں", variant="primary")
-
-            with gr.Tab("Audio"):
-                aud_input = gr.Audio(label="آڈیو اپ لوڈ کریں / Upload Audio", type="filepath")
-                aud_btn = gr.Button("Check / چیک کریں", variant="primary")
-
-            with gr.Tab("Video"):
-                vid_input = gr.Video(label="ویڈیو اپ لوڈ کریں / Upload Video")
-                vid_btn = gr.Button("Check / چیک کریں", variant="primary")
-
-            with gr.Tab("Paste Text"):
-                txt_input = gr.Textbox(
-                    label="اردو متن لکھیں یا پیسٹ کریں / Enter or paste Urdu text",
-                    lines=5,
-                )
-                txt_btn = gr.Button("Check / چیک کریں", variant="primary")
-
-        gr.Markdown("---")
-        verdict_output = gr.Textbox(
-            label="فیصلہ / Verdict",
-            lines=8,
-            interactive=False,
-        )
-        reasoning_output = gr.Textbox(
-            label="وجوہات و شواہد / Reasoning & Sources",
-            lines=14,
-            interactive=False,
-        )
-
-        img_btn.click(fn=_process_media, inputs=img_input, outputs=[verdict_output, reasoning_output])
-        aud_btn.click(fn=_process_media, inputs=aud_input, outputs=[verdict_output, reasoning_output])
-        vid_btn.click(fn=_process_media, inputs=vid_input, outputs=[verdict_output, reasoning_output])
-        txt_btn.click(fn=_process_text, inputs=txt_input, outputs=[verdict_output, reasoning_output])
+        print("کوئی قابلِ تصدیق دعویٰ نہیں")
+        return 0
 
-    return demo
+    print(f"دعویٰ: {result.claim_urdu}")
+    print(f"فیصلہ: {result.verdict_label_urdu} (confidence {result.confidence:.2f})")
+    print(f"وجوہات: {result.reasoning_urdu}")
+    print("ذرائع:")
+    for item in result.evidence[:3]:
+        print(f"  - {item.title} ({item.url})")
+    return 0
 
 
 if __name__ == "__main__":
-    demo = build_ui()
-    demo.launch(theme=gr.themes.Soft())
+    raise SystemExit(main())