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deepshield

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2026-04-22 18:24:59.601 | INFO     | main:lifespan:83 - Starting DeepShield backend
2026-04-22 18:24:59.655 | INFO     | main:lifespan:85 - Database initialized
2026-04-22 18:24:59.656 | INFO     | models.model_loader:load_image_model:43 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-22 18:25:06.201 | INFO     | models.model_loader:load_image_model:51 - Image model loaded
2026-04-22 18:25:06.206 | INFO     | services.report_service:cleanup_expired:151 - Cleaned up 1 expired reports
2026-04-22 18:26:20.263 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-22 18:26:22.700 | INFO     | services.efficientnet_service:__init__:97 - EfficientNetDetector ready: EfficientNetAutoAttB4/DFDC on cpu | calibrator=no
2026-04-22 18:26:23.034 | INFO     | services.image_service:classify_image:152 - Image classify (average_vit_eff) → Real | vit=0.078 ffpp=n/a eff=0.18335410952568054 → 0.131
2026-04-22 18:26:28.349 | INFO     | models.model_loader:load_face_detector:142 - Loading MediaPipe FaceMesh
2026-04-22 18:26:28.390 | INFO     | models.model_loader:load_face_detector:150 - MediaPipe FaceMesh loaded
2026-04-22 18:26:29.238 | INFO     | models.heatmap_generator:generate_heatmap_base64:186 - Heatmap generated (224x224) source=gradcam++
2026-04-22 18:26:29.277 | INFO     | services.ela_service:generate_ela_base64:60 - ELA map generated (256x256)
2026-04-22 18:26:30.141 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 5 regions
2026-04-22 18:26:30.327 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-22 18:26:30.347 | INFO     | api.v1.analyze:analyze_image:214 - Saved AnalysisRecord id=19 score=13 verdict=Very Likely Fake
2026-04-22 18:26:30.349 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: No module named 'google.generativeai'
2026-04-22 18:26:30.349 | ERROR    | services.vlm_breakdown:generate_vlm_breakdown:104 - VLM breakdown failed: No module named 'google.generativeai'
2026-04-22 18:27:58.805 | INFO     | main:lifespan:93 - Shutting down DeepShield backend
2026-04-22 18:28:09.692 | INFO     | main:lifespan:83 - Starting DeepShield backend
2026-04-22 18:28:09.698 | INFO     | main:lifespan:85 - Database initialized
2026-04-22 18:28:09.698 | INFO     | models.model_loader:load_image_model:43 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-22 18:28:11.556 | INFO     | models.model_loader:load_image_model:51 - Image model loaded
2026-04-24 01:50:58.220 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-24 01:51:03.592 | INFO     | services.efficientnet_service:__init__:97 - EfficientNetDetector ready: EfficientNetAutoAttB4/DFDC on cpu | calibrator=no
2026-04-24 01:51:03.887 | INFO     | services.image_service:classify_image:152 - Image classify (vit_only) → Fake | vit=0.597 ffpp=n/a eff=n/a → 0.597
2026-04-24 01:51:12.975 | INFO     | models.model_loader:load_face_detector:142 - Loading MediaPipe FaceMesh
2026-04-24 01:51:13.089 | INFO     | models.model_loader:load_face_detector:150 - MediaPipe FaceMesh loaded
2026-04-24 01:51:13.255 | INFO     | models.heatmap_generator:generate_heatmap_base64:176 - EfficientNet heatmap skipped — no face detected
2026-04-24 01:51:13.320 | INFO     | services.ela_service:generate_ela_base64:60 - ELA map generated (640x427)
2026-04-24 01:51:14.648 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 1 regions
2026-04-24 01:51:14.933 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-24 01:51:14.979 | INFO     | api.v1.analyze:analyze_image:215 - Saved AnalysisRecord id=20 score=40 verdict=Likely Fake
2026-04-24 01:51:14.982 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: No module named 'google.generativeai'
2026-04-24 01:51:14.984 | ERROR    | services.vlm_breakdown:generate_vlm_breakdown:104 - VLM breakdown failed: No module named 'google.generativeai'
2026-04-24 07:35:53.458 | INFO     | models.model_loader:load_text_model:57 - Loading text model: jy46604790/Fake-News-Bert-Detect
2026-04-24 07:36:02.194 | INFO     | models.model_loader:load_text_model:65 - Text model loaded
2026-04-24 07:36:03.057 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.999 fake_p=0.999
2026-04-24 07:36:03.058 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 68 (High) excl=4 caps=3 cb=1 emo=1
2026-04-24 07:36:03.061 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 3 found
2026-04-24 07:36:05.585 | WARNING  | models.model_loader:load_spacy_nlp:98 - spaCy model 'en_core_web_sm' not found. Run: python -m spacy download en_core_web_sm
2026-04-24 07:36:06.959 | INFO     | api.v1.analyze:analyze_text_endpoint:550 - Saved AnalysisRecord id=21 text score=15 verdict=Very Likely Fake
2026-04-24 07:36:08.561 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
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* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
Please retry in 51.884484839s. [links {
  description: "Learn more about Gemini API quotas"
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2026-04-24 07:36:41.979 | INFO     | models.model_loader:load_image_model:43 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-24 07:36:47.524 | INFO     | models.model_loader:load_image_model:51 - Image model loaded
2026-04-24 07:36:48.484 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-24 07:36:49.759 | INFO     | services.efficientnet_service:__init__:97 - EfficientNetDetector ready: EfficientNetAutoAttB4/DFDC on cpu | calibrator=no
2026-04-24 07:36:49.848 | INFO     | services.image_service:classify_image:152 - Image classify (vit_only) → Fake | vit=0.521 ffpp=n/a eff=n/a → 0.521
2026-04-24 07:36:51.638 | INFO     | models.model_loader:load_face_detector:142 - Loading MediaPipe FaceMesh
2026-04-24 07:36:51.638 | WARNING  | services.artifact_detector:detect_face_based_artifacts:213 - Face-based artifact detection failed: module 'mediapipe' has no attribute 'solutions'
2026-04-24 07:36:51.649 | INFO     | models.heatmap_generator:generate_heatmap_base64:176 - EfficientNet heatmap skipped — no face detected
2026-04-24 07:36:51.696 | INFO     | services.ela_service:generate_ela_base64:60 - ELA map generated (512x512)
2026-04-24 07:36:52.470 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 5 regions
2026-04-24 07:36:52.519 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-24 07:36:52.542 | INFO     | api.v1.analyze:analyze_image:215 - Saved AnalysisRecord id=22 score=48 verdict=Possibly Manipulated
2026-04-24 07:36:53.674 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
Please retry in 6.748563195s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
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, retry_delay {
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2026-04-24 07:36:54.760 | ERROR    | services.vlm_breakdown:generate_vlm_breakdown:104 - VLM breakdown failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
Please retry in 5.653927512s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
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2026-04-24 15:16:36.138 | INFO     | models.model_loader:load_text_model:57 - Loading text model: jy46604790/Fake-News-Bert-Detect
2026-04-24 15:16:43.946 | INFO     | models.model_loader:load_text_model:65 - Text model loaded
2026-04-24 15:16:44.719 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.998 fake_p=0.998
2026-04-24 15:16:44.721 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 67 (High) excl=3 caps=2 cb=1 emo=1
2026-04-24 15:16:44.723 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 3 found
2026-04-24 15:16:45.864 | WARNING  | models.model_loader:load_spacy_nlp:98 - spaCy model 'en_core_web_sm' not found. Run: python -m spacy download en_core_web_sm
2026-04-24 15:16:47.113 | INFO     | api.v1.analyze:analyze_text_endpoint:549 - Saved AnalysisRecord id=23 text score=15 verdict=Very Likely Fake
2026-04-24 15:16:48.348 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
Please retry in 12.294521515s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
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2026-04-24 15:16:48.553 | INFO     | models.model_loader:load_image_model:43 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-24 15:16:50.111 | INFO     | models.model_loader:load_image_model:51 - Image model loaded
2026-04-24 15:16:51.265 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-24 15:16:52.685 | INFO     | services.efficientnet_service:__init__:97 - EfficientNetDetector ready: EfficientNetAutoAttB4/DFDC on cpu | calibrator=no
2026-04-24 15:16:52.723 | INFO     | services.image_service:classify_image:152 - Image classify (vit_only) → Fake | vit=0.517 ffpp=n/a eff=n/a → 0.517
2026-04-24 15:16:52.735 | INFO     | models.model_loader:load_face_detector:142 - Loading MediaPipe FaceMesh
2026-04-24 15:16:54.934 | WARNING  | services.artifact_detector:detect_face_based_artifacts:211 - Face-based artifact detection failed: module 'mediapipe' has no attribute 'solutions'
2026-04-24 15:16:54.949 | INFO     | models.heatmap_generator:generate_heatmap_base64:176 - EfficientNet heatmap skipped — no face detected
2026-04-24 15:16:54.965 | INFO     | services.ela_service:generate_ela_base64:59 - ELA map generated (256x256)
2026-04-24 15:16:55.916 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 5 regions
2026-04-24 15:16:55.975 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-24 15:16:55.989 | INFO     | api.v1.analyze:analyze_image:214 - Saved AnalysisRecord id=24 score=48 verdict=Possibly Manipulated
2026-04-24 15:16:56.236 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
Please retry in 4.477916448s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
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, retry_delay {
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2026-04-24 15:16:57.419 | ERROR    | services.vlm_breakdown:generate_vlm_breakdown:104 - VLM breakdown failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
Please retry in 3.282459328s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
  quota_id: "GenerateContentInputTokensPerModelPerDay-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerDayPerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerMinutePerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
  quota_id: "GenerateContentInputTokensPerModelPerMinute-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
, retry_delay {
  seconds: 3
}
]
2026-04-24 15:16:57.445 | INFO     | models.model_loader:load_ocr_engine:130 - Loading EasyOCR reader (langs: ['en', 'hi'])
2026-04-24 15:17:27.399 | INFO     | models.model_loader:load_ocr_engine:136 - EasyOCR loaded
2026-04-24 15:17:27.870 | INFO     | services.screenshot_service:run_ocr:48 - OCR extracted 0 text regions
2026-04-24 15:17:27.881 | INFO     | api.v1.analyze:analyze_screenshot_endpoint:726 - Saved AnalysisRecord id=25 screenshot score=50 verdict=Possibly Manipulated
2026-04-24 15:17:28.066 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
Please retry in 32.593323033s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
  quota_id: "GenerateContentInputTokensPerModelPerDay-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
  quota_id: "GenerateContentInputTokensPerModelPerMinute-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerMinutePerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerDayPerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
, retry_delay {
  seconds: 32
}
]
2026-04-24 15:17:54.819 | INFO     | models.model_loader:load_text_model:57 - Loading text model: jy46604790/Fake-News-Bert-Detect
2026-04-24 15:18:00.795 | INFO     | models.model_loader:load_text_model:65 - Text model loaded
2026-04-24 15:18:00.888 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.998 fake_p=0.998
2026-04-24 15:18:00.889 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 67 (High) excl=3 caps=2 cb=1 emo=1
2026-04-24 15:18:00.891 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 3 found
2026-04-24 15:18:01.659 | WARNING  | models.model_loader:load_spacy_nlp:98 - spaCy model 'en_core_web_sm' not found. Run: python -m spacy download en_core_web_sm
2026-04-24 15:18:02.878 | INFO     | api.v1.analyze:analyze_text_endpoint:549 - Saved AnalysisRecord id=26 text score=15 verdict=Very Likely Fake
2026-04-24 15:18:03.994 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_input_token_count, limit: 0, model: gemini-2.5-pro
Please retry in 56.638939454s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerDayPerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerMinutePerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
  quota_id: "GenerateContentInputTokensPerModelPerMinute-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_input_token_count"
  quota_id: "GenerateContentInputTokensPerModelPerDay-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-pro"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
}
, retry_delay {
  seconds: 56
}
]
2026-04-24 15:20:38.285 | INFO     | models.model_loader:load_text_model:57 - Loading text model: jy46604790/Fake-News-Bert-Detect
2026-04-24 15:20:43.929 | INFO     | models.model_loader:load_text_model:65 - Text model loaded
2026-04-24 15:20:44.034 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.998 fake_p=0.998
2026-04-24 15:20:44.035 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 67 (High) excl=3 caps=2 cb=1 emo=1
2026-04-24 15:20:44.037 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 3 found
2026-04-24 15:20:44.806 | WARNING  | models.model_loader:load_spacy_nlp:98 - spaCy model 'en_core_web_sm' not found. Run: python -m spacy download en_core_web_sm
2026-04-24 15:20:46.001 | INFO     | api.v1.analyze:analyze_text_endpoint:549 - Saved AnalysisRecord id=27 text score=15 verdict=Very Likely Fake
2026-04-24 15:20:56.376 | INFO     | services.llm_explainer:generate_llm_summary:175 - LLM summary generated via gemini/gemini-2.5-flash
2026-04-24 15:33:56.592 | INFO     | api.v1.auth:register:33 - Registered user id=3 email=***@example.com
2026-04-24 15:33:57.227 | INFO     | api.v1.auth:login:42 - Login user id=3 email=***@example.com
2026-04-24 15:33:57.553 | INFO     | models.model_loader:load_text_model:57 - Loading text model: jy46604790/Fake-News-Bert-Detect
2026-04-24 15:34:06.986 | INFO     | models.model_loader:load_text_model:65 - Text model loaded
2026-04-24 15:34:07.731 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.997 fake_p=0.997
2026-04-24 15:34:07.733 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:34:07.736 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:34:09.017 | WARNING  | models.model_loader:load_spacy_nlp:98 - spaCy model 'en_core_web_sm' not found. Run: python -m spacy download en_core_web_sm
2026-04-24 15:34:10.285 | INFO     | api.v1.analyze:analyze_text_endpoint:549 - Saved AnalysisRecord id=28 text score=30 verdict=Likely Fake
2026-04-24 15:34:41.718 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 5, model: gemini-2.5-flash
Please retry in 19.188761533s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerMinutePerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-flash"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
  quota_value: 5
}
, retry_delay {
  seconds: 19
}
]
2026-04-24 15:34:41.788 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.997 fake_p=0.997
2026-04-24 15:34:41.788 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 76 (High) excl=3 caps=2 cb=1 emo=3
2026-04-24 15:34:41.789 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:34:41.791 | WARNING  | models.model_loader:load_spacy_nlp:98 - spaCy model 'en_core_web_sm' not found. Run: python -m spacy download en_core_web_sm
2026-04-24 15:34:43.147 | INFO     | api.v1.analyze:analyze_text_endpoint:549 - Saved AnalysisRecord id=29 text score=15 verdict=Very Likely Fake
2026-04-24 15:34:43.555 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 5, model: gemini-2.5-flash
Please retry in 17.333464233s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerMinutePerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-flash"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
  quota_value: 5
}
, retry_delay {
  seconds: 17
}
]
2026-04-24 15:34:43.615 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.996 fake_p=0.996
2026-04-24 15:34:43.616 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:34:43.616 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:34:43.618 | WARNING  | models.model_loader:load_spacy_nlp:98 - spaCy model 'en_core_web_sm' not found. Run: python -m spacy download en_core_web_sm
2026-04-24 15:34:44.924 | INFO     | api.v1.analyze:analyze_text_endpoint:549 - Saved AnalysisRecord id=30 text score=30 verdict=Likely Fake
2026-04-24 15:34:45.353 | ERROR    | services.llm_explainer:generate_llm_summary:186 - LLM explainer failed: 429 You exceeded your current quota, please check your plan and billing details. For more information on this error, head to: https://ai.google.dev/gemini-api/docs/rate-limits. To monitor your current usage, head to: https://ai.dev/rate-limit. 
* Quota exceeded for metric: generativelanguage.googleapis.com/generate_content_free_tier_requests, limit: 5, model: gemini-2.5-flash
Please retry in 15.553103918s. [links {
  description: "Learn more about Gemini API quotas"
  url: "https://ai.google.dev/gemini-api/docs/rate-limits"
}
, violations {
  quota_metric: "generativelanguage.googleapis.com/generate_content_free_tier_requests"
  quota_id: "GenerateRequestsPerMinutePerProjectPerModel-FreeTier"
  quota_dimensions {
    key: "model"
    value: "gemini-2.5-flash"
  }
  quota_dimensions {
    key: "location"
    value: "global"
  }
  quota_value: 5
}
, retry_delay {
  seconds: 15
}
]
2026-04-24 15:43:27.438 | INFO     | api.v1.auth:register:33 - Registered user id=4 email=***@example.com
2026-04-24 15:43:27.463 | INFO     | models.model_loader:load_text_model:57 - Loading text model: jy46604790/Fake-News-Bert-Detect
2026-04-24 15:43:33.684 | INFO     | models.model_loader:load_text_model:65 - Text model loaded
2026-04-24 15:43:33.796 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.991 fake_p=0.991
2026-04-24 15:43:33.797 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:43:33.799 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:43:35.106 | INFO     | models.model_loader:load_spacy_nlp:96 - spaCy en_core_web_sm loaded
2026-04-24 15:43:35.120 | INFO     | services.text_service:extract_entities:253 - NER extracted 3 entities: ['India', 'Elon Musk', 'New Delhi']
2026-04-24 15:43:36.284 | INFO     | api.v1.analyze:analyze_text_endpoint:550 - Saved AnalysisRecord id=31 text score=31 verdict=Likely Fake
2026-04-24 15:43:36.352 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.991 fake_p=0.991
2026-04-24 15:43:36.352 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:43:36.353 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:43:36.370 | INFO     | services.text_service:extract_entities:253 - NER extracted 3 entities: ['India', 'Elon Musk', 'New Delhi']
2026-04-24 15:43:37.567 | INFO     | api.v1.analyze:analyze_text_endpoint:550 - Saved AnalysisRecord id=32 text score=31 verdict=Likely Fake
2026-04-24 15:43:47.549 | INFO     | services.llm_explainer:generate_llm_summary:207 - LLM summary generated via gemini/gemini-2.5-flash
2026-04-24 15:43:47.614 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.991 fake_p=0.991
2026-04-24 15:43:47.614 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:43:47.615 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:43:47.630 | INFO     | services.text_service:extract_entities:253 - NER extracted 3 entities: ['India', 'Elon Musk', 'New Delhi']
2026-04-24 15:43:49.134 | INFO     | api.v1.analyze:analyze_text_endpoint:550 - Saved AnalysisRecord id=33 text score=31 verdict=Likely Fake
2026-04-24 15:44:11.346 | WARNING  | services.llm_explainer:mark_rate_limited:42 - LLM rate-limited — pausing all LLM calls for 300s
2026-04-24 15:44:11.346 | WARNING  | services.llm_explainer:generate_llm_summary:220 - LLM quota hit (ResourceExhausted) — circuit open for 300s
2026-04-24 15:44:11.352 | WARNING  | services.llm_explainer:mark_rate_limited:42 - LLM rate-limited — pausing all LLM calls for 5s
2026-04-24 15:44:11.404 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.999 fake_p=0.999
2026-04-24 15:44:11.404 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:44:11.405 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:44:12.724 | INFO     | api.v1.analyze:analyze_text_endpoint:550 - Saved AnalysisRecord id=34 text score=30 verdict=Likely Fake
2026-04-24 15:57:39.916 | INFO     | api.v1.auth:register:33 - Registered user id=5 email=***@example.com
2026-04-24 15:57:39.958 | INFO     | models.model_loader:load_text_model:57 - Loading text model: jy46604790/Fake-News-Bert-Detect
2026-04-24 15:57:46.475 | INFO     | models.model_loader:load_text_model:65 - Text model loaded
2026-04-24 15:57:46.582 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.999 fake_p=0.999
2026-04-24 15:57:46.584 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:57:46.586 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:57:47.954 | INFO     | models.model_loader:load_spacy_nlp:96 - spaCy en_core_web_sm loaded
2026-04-24 15:57:49.166 | INFO     | api.v1.analyze:analyze_text_endpoint:555 - Saved AnalysisRecord id=35 text score=30 verdict=Likely Fake
2026-04-24 15:57:58.130 | INFO     | services.llm_explainer:generate_llm_summary:271 - LLM summary generated via gemini/gemini-2.5-flash
2026-04-24 15:57:58.196 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.999 fake_p=0.999
2026-04-24 15:57:58.197 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:57:58.197 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:57:59.705 | INFO     | api.v1.analyze:analyze_text_endpoint:555 - Saved AnalysisRecord id=36 text score=30 verdict=Likely Fake
2026-04-24 15:58:02.948 | ERROR    | services.llm_explainer:generate_llm_summary:287 - LLM explainer failed: 503 UNAVAILABLE. {'error': {'code': 503, 'message': 'This model is currently experiencing high demand. Spikes in demand are usually temporary. Please try again later.', 'status': 'UNAVAILABLE'}}
2026-04-24 15:58:03.008 | INFO     | services.text_service:classify_text:159 - Text classify [en] → LABEL_0 @ 0.999 fake_p=0.999
2026-04-24 15:58:03.008 | INFO     | services.text_service:score_sensationalism:193 - Sensationalism → 0 (Low) excl=0 caps=0 cb=0 emo=0
2026-04-24 15:58:03.009 | INFO     | services.text_service:detect_manipulation_indicators:213 - Manipulation indicators → 0 found
2026-04-24 15:58:04.488 | INFO     | api.v1.analyze:analyze_text_endpoint:555 - Saved AnalysisRecord id=37 text score=30 verdict=Likely Fake
2026-04-24 15:59:52.694 | INFO     | services.llm_explainer:_get_provider:176 - LLM chain initialized: gemini/gemini-2.5-flash → groq/llama-3.3-70b-versatile
2026-04-24 15:59:52.695 | INFO     | services.llm_explainer:generate:161 - gemini/gemini-2.5-flash quota hit — failing over to groq/llama-3.3-70b-versatile
2026-04-24 23:15:36.409 | INFO     | main:lifespan:108 - Starting DeepShield backend
2026-04-24 23:15:36.470 | INFO     | main:lifespan:110 - Database initialized
2026-04-24 23:15:36.470 | INFO     | models.model_loader:load_image_model:43 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-24 23:15:46.404 | INFO     | models.model_loader:load_image_model:51 - Image model loaded
2026-04-24 23:15:57.188 | INFO     | api.v1.analyze:analyze_image:118 - cache hit image sha=6de55b9fc5bd record=19
2026-04-24 23:16:59.860 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-24 23:17:03.920 | INFO     | services.efficientnet_service:__init__:97 - EfficientNetDetector ready: EfficientNetAutoAttB4/DFDC on cpu | calibrator=no
2026-04-24 23:17:04.519 | INFO     | services.image_service:classify_image:152 - Image classify (average_vit_eff) → Real | vit=0.868 ffpp=n/a eff=0.03269108012318611 → 0.450
2026-04-24 23:17:04.569 | INFO     | models.model_loader:load_face_detector:142 - Loading MediaPipe FaceMesh
2026-04-24 23:17:13.315 | INFO     | models.model_loader:load_face_detector:150 - MediaPipe FaceMesh loaded
2026-04-24 23:17:16.988 | INFO     | models.heatmap_generator:generate_heatmap_base64:186 - Heatmap generated (224x224) source=gradcam++
2026-04-24 23:17:17.131 | INFO     | services.ela_service:generate_ela_base64:59 - ELA map generated (800x450)
2026-04-24 23:17:18.394 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 5 regions
2026-04-24 23:17:18.714 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-24 23:17:18.757 | INFO     | api.v1.analyze:analyze_image:230 - Saved AnalysisRecord id=38 score=45 verdict=Possibly Manipulated
2026-04-24 23:29:04.622 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-24 23:29:05.312 | INFO     | services.image_service:classify_image:152 - Image classify (average_vit_eff) → Fake | vit=0.767 ffpp=n/a eff=0.36121347546577454 → 0.564
2026-04-24 23:29:06.604 | INFO     | models.heatmap_generator:generate_heatmap_base64:186 - Heatmap generated (224x224) source=gradcam++
2026-04-24 23:29:10.091 | INFO     | services.ela_service:generate_ela_base64:59 - ELA map generated (2393x4096)
2026-04-24 23:29:11.326 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 5 regions
2026-04-24 23:29:11.344 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-24 23:29:11.436 | INFO     | api.v1.analyze:analyze_image:230 - Saved AnalysisRecord id=39 score=44 verdict=Possibly Manipulated
2026-04-24 23:30:58.303 | ERROR    | api.v1.report:generate:51 - Report generation failed: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback (most recent call last):

  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.11_3.11.2544.0_x64__qbz5n2kfra8p0\Lib\threading.py", line 1002, in _bootstrap
    self._bootstrap_inner()
    │    └ <function Thread._bootstrap_inner at 0x000001A73BF11A80>
    └ <WorkerThread(AnyIO worker thread, started 18584)>
  File "C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.11_3.11.2544.0_x64__qbz5n2kfra8p0\Lib\threading.py", line 1045, in _bootstrap_inner
    self.run()
    │    └ <function WorkerThread.run at 0x000001A7030349A0>
    └ <WorkerThread(AnyIO worker thread, started 18584)>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\anyio\_backends\_asyncio.py", line 1002, in run
    result = context.run(func, *args)
             │       │   │      └ ()
             │       │   └ functools.partial(<function generate at 0x000001A7011BA0C0>, db=<sqlalchemy.orm.session.Session object at 0x000001A70D16E390>...
             │       └ <method 'run' of '_contextvars.Context' objects>
             └ <_contextvars.Context object at 0x000001A70D16CD40>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\slowapi\extension.py", line 766, in sync_wrapper
    response = func(*args, **kwargs)
               │     │       └ {'db': <sqlalchemy.orm.session.Session object at 0x000001A70D16E390>, 'user': None, 'analysis_id': 39, 'request': <starlette....
               │     └ ()
               └ <function generate at 0x000001A7011BA160>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\slowapi\extension.py", line 766, in sync_wrapper
    response = func(*args, **kwargs)
               │     │       └ {'db': <sqlalchemy.orm.session.Session object at 0x000001A70D16E390>, 'user': None, 'analysis_id': 39, 'request': <starlette....
               │     └ ()
               └ <function generate at 0x000001A7011BA020>

> File "C:\Users\athar\Desktop\minor2\backend\api\v1\report.py", line 49, in generate
    path = generate_report(record)
           │               └ <db.models.AnalysisRecord object at 0x000001A70D17A2D0>
           └ <function generate_report at 0x000001A7011B9D00>

  File "C:\Users\athar\Desktop\minor2\backend\services\report_service.py", line 119, in generate_report
    html_to_pdf(html, out_path)
    │           │     └ WindowsPath('temp_reports/deepshield_39_c2b71295.pdf')
    │           └ '<!DOCTYPE html>\n<html>\n<head>\n  <meta charset="utf-8" />\n  <title>DeepShield Analysis Report — c9f44067-528d-4e96-9365-2...
    └ <function html_to_pdf at 0x000001A7011B9C60>

  File "C:\Users\athar\Desktop\minor2\backend\services\report_service.py", line 107, in html_to_pdf
    result = pisa.CreatePDF(html, dest=f)
             │    │         │          └ <_io.BufferedWriter name='temp_reports\\deepshield_39_c2b71295.pdf'>
             │    │         └ '<!DOCTYPE html>\n<html>\n<head>\n  <meta charset="utf-8" />\n  <title>DeepShield Analysis Report — c9f44067-528d-4e96-9365-2...
             │    └ <function pisaDocument at 0x000001A7011B9440>
             └ <module 'xhtml2pdf.pisa' from 'C:\\Users\\athar\\Desktop\\minor2\\backend\\.venv\\Lib\\site-packages\\xhtml2pdf\\pisa.py'>

  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\xhtml2pdf\document.py", line 196, in pisaDocument
    doc.build(context.story)
    │   │     │       └ [PmlParagraph(
    │   │     │           'dir'
    │   │     │               'dir'
    │   │     │           'caseSensitive'
    │   │     │               'caseSensitive'
    │   │     │           'encoding'
    │   │     │               'encoding'
    │   │     │           'text'
    │   │     │               'text...
    │   │     └ <xhtml2pdf.context.pisaContext object at 0x000001A703A22990>
    │   └ <function BaseDocTemplate.build at 0x000001A77EFA8E00>
    └ <xhtml2pdf.xhtml2pdf_reportlab.PmlBaseDoc object at 0x000001A703756C10>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\doctemplate.py", line 1083, in build
    self.handle_flowable(flowables)
    │    │               └ [PmlParagraph(
    │    │                   'dir'
    │    │                       'dir'
    │    │                   'caseSensitive'
    │    │                       'caseSensitive'
    │    │                   'encoding'
    │    │                       'encoding'
    │    │                   'text'
    │    │                       'text...
    │    └ <function BaseDocTemplate.handle_flowable at 0x000001A77EFA8B80>
    └ <xhtml2pdf.xhtml2pdf_reportlab.PmlBaseDoc object at 0x000001A703756C10>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\doctemplate.py", line 932, in handle_flowable
    if frame.add(f, canv, trySplit=self.allowSplitting):
       │     │   │  │              │    └ 1
       │     │   │  │              └ <xhtml2pdf.xhtml2pdf_reportlab.PmlBaseDoc object at 0x000001A703756C10>
       │     │   │  └ <reportlab.pdfgen.canvas.Canvas object at 0x000001A70D1DED50>
       │     │   └ PmlTable(
       │     │      rowHeights=[None],
       │     │      colWidths=[4.93228346456693, 488.29606299212605],
       │     │     [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
       │     └ <function Frame._add at 0x000001A77EECDF80>
       └ <reportlab.platypus.frames.Frame object at 0x000001A70344D6D0>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\frames.py", line 158, in _add
    w, h = flowable.wrap(aW, h)
           │        │    │   └ 751.1811023622049
           │        │    └ 493.228346456693
           │        └ <function PmlTable.wrap at 0x000001A7011719E0>
           └ PmlTable(
              rowHeights=[None],
              colWidths=[4.93228346456693, 488.29606299212605],
             [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\xhtml2pdf\xhtml2pdf_reportlab.py", line 858, in wrap
    return Table.wrap(self, availWidth, availHeight)
           │     │    │     │           └ 751.1811023622049
           │     │    │     └ 493.228346456693
           │     │    └ PmlTable(
           │     │       rowHeights=[None],
           │     │       colWidths=[4.93228346456693, 488.29606299212605],
           │     │      [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
           │     └ <function Table.wrap at 0x000001A77EFAC400>
           └ <class 'reportlab.platypus.tables.Table'>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\tables.py", line 1354, in wrap
    self._calc(availWidth, availHeight)
    │    │     │           └ 751.1811023622049
    │    │     └ 493.228346456693
    │    └ <function Table._calc at 0x000001A77EFAB600>
    └ PmlTable(
       rowHeights=[None],
       colWidths=[4.93228346456693, 488.29606299212605],
      [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\tables.py", line 740, in _calc
    self._calc_height(availHeight,availWidth,W=W)
    │    │            │           │            └ None
    │    │            │           └ 493.228346456693
    │    │            └ 751.1811023622049
    │    └ <function Table._calc_height at 0x000001A77EFAB560>
    └ PmlTable(
       rowHeights=[None],
       colWidths=[4.93228346456693, 488.29606299212605],
      [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\tables.py", line 664, in _calc_height
    dW,t = self._listCellGeom(v,w or self._listValueWidth(v),s)
           │    │             │ │    │    │               │  └ <CellStyle '(0, 0)'>
           │    │             │ │    │    │               └ (<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInFrame object at 0x000001A70D1F4950>,)
           │    │             │ │    │    └ <function Table._listValueWidth at 0x000001A77EFAB380>
           │    │             │ │    └ PmlTable(
           │    │             │ │       rowHeights=[None],
           │    │             │ │       colWidths=[4.93228346456693, 488.29606299212605],
           │    │             │ │      [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
           │    │             │ └ 4.93228346456693
           │    │             └ (<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInFrame object at 0x000001A70D1F4950>,)
           │    └ <function PmlTable._listCellGeom at 0x000001A701171940>
           └ PmlTable(
              rowHeights=[None],
              colWidths=[4.93228346456693, 488.29606299212605],
             [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\xhtml2pdf\xhtml2pdf_reportlab.py", line 810, in _listCellGeom
    return Table._listCellGeom(self, V, w, s, W=W, H=H, aH=aH)
           │     │             │     │  │  │    │    │     └ 751.1811023622049
           │     │             │     │  │  │    │    └ None
           │     │             │     │  │  │    └ None
           │     │             │     │  │  └ <CellStyle '(0, 0)'>
           │     │             │     │  └ 4.93228346456693
           │     │             │     └ (<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInFrame object at 0x000001A70D1F4950>,)
           │     │             └ PmlTable(
           │     │                rowHeights=[None],
           │     │                colWidths=[4.93228346456693, 488.29606299212605],
           │     │               [[(<xhtml2pdf.xhtml2pdf_reportlab.PmlKeepInF...
           │     └ <function Table._listCellGeom at 0x000001A77EFAB2E0>
           └ <class 'reportlab.platypus.tables.Table'>
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\tables.py", line 490, in _listCellGeom
    raise ValueError(f'{self.identity()}: flowable given negative availWidth={aW} == width={w} - leftPadding={s.leftPadding} - rightPadding={s.rightPadding}')
  File "C:\Users\athar\Desktop\minor2\backend\.venv\Lib\site-packages\reportlab\platypus\tables.py", line 440, in identity
    tallest = '(tallest row %d)' % int(max(rh))
                                           └ [None]

TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
2026-04-24 23:44:20.465 | INFO     | api.v1.auth:register:33 - Registered user id=6 email=***@gmail.com
2026-04-24 23:45:54.152 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-24 23:45:54.595 | INFO     | services.image_service:classify_image:152 - Image classify (average_vit_eff) → Real | vit=0.668 ffpp=n/a eff=0.00913542602211237 → 0.339
2026-04-24 23:45:55.772 | INFO     | models.heatmap_generator:generate_heatmap_base64:186 - Heatmap generated (224x224) source=gradcam++
2026-04-24 23:45:58.926 | INFO     | services.ela_service:generate_ela_base64:59 - ELA map generated (2268x4032)
2026-04-24 23:46:00.276 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 2 regions
2026-04-24 23:46:00.291 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=Google, model=Pixel 7 Pro, adjustment=-20 (valid camera metadata (Make/Model/DateTime); GPS coordinates present)
2026-04-24 23:46:00.379 | INFO     | api.v1.analyze:analyze_image:230 - Saved AnalysisRecord id=40 score=14 verdict=Very Likely Fake
2026-04-24 23:46:00.382 | ERROR    | services.llm_explainer:generate_llm_summary:296 - LLM explainer failed: cannot import name 'genai' from 'google' (unknown location)
2026-04-24 23:46:00.386 | ERROR    | services.vlm_breakdown:generate_vlm_breakdown:114 - VLM breakdown failed: cannot import name 'genai' from 'google' (unknown location)
2026-04-24 23:47:37.291 | INFO     | services.report_service:generate_report:120 - Report generated id=40 path=temp_reports\deepshield_40_3f0f8ff7.pdf size=14978B
2026-04-24 23:50:59.570 | INFO     | api.v1.auth:login:42 - Login user id=6 email=***@gmail.com
2026-04-25 02:48:29.295 | INFO     | services.report_service:cleanup_expired:149 - Cleaned up 2 expired reports
2026-04-25 02:48:29.419 | WARNING  | services.report_service:cleanup_expired:149 - Cleanup failed for temp_reports\deepshield_40_3f0f8ff7.pdf: [WinError 2] The system cannot find the file specified: 'temp_reports\\deepshield_40_3f0f8ff7.pdf'
2026-04-25 21:48:15.075 | INFO     | main:lifespan:108 - Starting DeepShield backend
2026-04-25 21:48:15.082 | INFO     | main:lifespan:110 - Database initialized
2026-04-25 21:48:15.082 | INFO     | models.model_loader:load_image_model:43 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-25 21:48:18.709 | INFO     | models.model_loader:load_image_model:51 - Image model loaded
2026-04-25 21:48:18.712 | INFO     | main:lifespan:118 - Shutting down DeepShield backend
2026-04-25 21:52:02.663 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-25 21:52:03.239 | INFO     | services.image_service:classify_image:152 - Image classify (average_vit_eff) → Real | vit=0.870 ffpp=n/a eff=0.0529196597635746 → 0.462
2026-04-25 21:52:04.390 | INFO     | models.heatmap_generator:generate_heatmap_base64:186 - Heatmap generated (224x224) source=gradcam++
2026-04-25 21:52:04.682 | INFO     | services.ela_service:generate_ela_base64:59 - ELA map generated (1223x640)
2026-04-25 21:52:05.863 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 5 regions
2026-04-25 21:52:05.883 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-25 21:52:05.927 | INFO     | api.v1.analyze:analyze_image:230 - Saved AnalysisRecord id=41 score=46 verdict=Possibly Manipulated
2026-04-25 22:02:22.021 | INFO     | main:lifespan:108 - Starting DeepShield backend
2026-04-25 22:02:22.057 | INFO     | main:lifespan:110 - Database initialized
2026-04-25 22:02:22.057 | INFO     | models.model_loader:load_image_model:43 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-25 22:02:30.014 | INFO     | models.model_loader:load_image_model:51 - Image model loaded
2026-04-25 22:13:05.431 | INFO     | api.v1.auth:login:42 - Login user id=6 email=***@gmail.com
2026-04-25 22:13:28.224 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-25 22:13:28.471 | INFO     | services.image_service:classify_image:152 - Image classify (vit_only) → Fake | vit=0.694 ffpp=n/a eff=n/a → 0.694
2026-04-25 22:13:28.859 | INFO     | models.heatmap_generator:generate_heatmap_base64:176 - EfficientNet heatmap skipped — no face detected
2026-04-25 22:13:31.674 | INFO     | services.ela_service:generate_ela_base64:59 - ELA map generated (2268x4032)
2026-04-25 22:13:33.044 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 2 regions
2026-04-25 22:13:33.062 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=Apple, model=iPhone 16 Pro, adjustment=-20 (valid camera metadata (Make/Model/DateTime); GPS coordinates present)
2026-04-25 22:13:33.166 | INFO     | api.v1.analyze:analyze_image:230 - Saved AnalysisRecord id=42 score=11 verdict=Very Likely Fake
2026-04-25 22:13:33.169 | ERROR    | services.llm_explainer:generate_llm_summary:296 - LLM explainer failed: cannot import name 'genai' from 'google' (unknown location)
2026-04-25 22:13:33.171 | ERROR    | services.vlm_breakdown:generate_vlm_breakdown:114 - VLM breakdown failed: cannot import name 'genai' from 'google' (unknown location)
2026-04-26 22:05:50.626 | INFO     | main:lifespan:108 - Starting DeepShield backend
2026-04-26 22:05:50.640 | INFO     | main:lifespan:110 - Database initialized
2026-04-26 22:05:50.641 | INFO     | models.model_loader:load_image_model:44 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-26 22:05:58.170 | INFO     | models.model_loader:load_image_model:52 - Image model loaded
2026-04-26 22:07:47.526 | WARNING  | models.model_loader:load_ffpp_model:193 - FFPP ViT checkpoint not found at C:\Users\athar\Desktop\trained_models — skipping
2026-04-26 22:07:48.484 | INFO     | services.image_service:classify_image:152 - Image classify (average_vit_eff) → Real | vit=0.834 ffpp=n/a eff=0.02755815163254738 → 0.431
2026-04-26 22:07:50.164 | INFO     | models.heatmap_generator:generate_heatmap_base64:186 - Heatmap generated (224x224) source=gradcam++
2026-04-26 22:07:50.584 | INFO     | services.ela_service:generate_ela_base64:59 - ELA map generated (1290x1290)
2026-04-26 22:07:52.661 | INFO     | models.heatmap_generator:generate_boxes_base64:232 - Bounding boxes generated: 1 regions
2026-04-26 22:07:52.670 | INFO     | services.exif_service:extract_exif:127 - EXIF extracted: make=None, model=None, adjustment=0 (no EXIF metadata found)
2026-04-26 22:07:52.747 | INFO     | api.v1.analyze:analyze_image:230 - Saved AnalysisRecord id=43 score=43 verdict=Possibly Manipulated
2026-04-26 22:07:52.752 | ERROR    | services.llm_explainer:generate_llm_summary:296 - LLM explainer failed: cannot import name 'genai' from 'google' (unknown location)
2026-04-26 22:07:52.756 | ERROR    | services.vlm_breakdown:generate_vlm_breakdown:114 - VLM breakdown failed: cannot import name 'genai' from 'google' (unknown location)
2026-04-26 22:09:45.469 | INFO     | services.report_service:generate_report:120 - Report generated id=43 path=temp_reports\deepshield_43_262befa5.pdf size=15602B
2026-04-26 23:15:58.262 | INFO     | services.report_service:cleanup_expired:149 - Cleaned up 2 expired reports
2026-04-27 01:22:14.691 | INFO     | services.report_service:cleanup_expired:149 - Cleaned up 2 expired reports
2026-04-28 21:11:45.835 | INFO     | main:lifespan:108 - Starting DeepShield backend
2026-04-28 21:11:45.871 | INFO     | main:lifespan:110 - Database initialized
2026-04-28 21:11:45.871 | INFO     | models.model_loader:load_image_model:48 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-28 21:11:51.313 | INFO     | models.model_loader:load_image_model:56 - Image model loaded
2026-04-28 21:34:27.293 | INFO     | main:lifespan:118 - Shutting down DeepShield backend
2026-04-28 21:34:41.654 | INFO     | main:lifespan:108 - Starting DeepShield backend
2026-04-28 21:34:41.668 | INFO     | main:lifespan:110 - Database initialized
2026-04-28 21:34:41.668 | INFO     | models.model_loader:load_image_model:48 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-04-28 21:34:44.266 | INFO     | models.model_loader:load_image_model:56 - Image model loaded
2026-05-01 19:46:26.537 | INFO     | main:lifespan:123 - Starting DeepShield backend
2026-05-01 19:46:26.560 | INFO     | main:lifespan:125 - Database initialized
2026-05-01 19:46:26.560 | INFO     | models.model_loader:load_image_model:48 - Loading image model: prithivMLmods/Deep-Fake-Detector-v2-Model
2026-05-01 19:46:33.087 | INFO     | models.model_loader:load_image_model:56 - Image model loaded