2 web scraping module

[RustyNails8]

Summary by CodeRabbit

• Chores
  • Added web‑scraping configuration for per‑site rate limits, retries, timeouts, SSL and validation options.
• New Content
  • Bulk ingested Vedic Heritage and SanskritDocuments materials (Upanishads, Vedas, Bhagavad Gita, Puranas, temple/repository pages) with accompanying metadata records.
• Data
  • Added a content‑hash registry to track ingested resources and detect duplicates.

[coderabbitai]

Walkthrough

Adds a new web-scraping configuration and a large batch of scraped HTML content and corresponding metadata JSON files (primarily Vedicheritage, SanskritDocuments). Also adds a content-hash file for deduplication. No source code or runtime control-flow changes.

Changes

Cohort / File(s)	Summary
Configuration config/scraping.yaml, data/raw/.content_hashes.json	New scraping configuration (user_agent, timeouts, retries, rate limits, per-source settings, formats, storage, logging, SSL/validation flags) and a JSON content-hash list for deduplication.
Vedicheritage — Bhagavad Gita data/raw/vedicheritage/Bhagavad Gita/html/Digital_District_Repository_20251017_150224.*, data/raw/vedicheritage/Bhagavad Gita/html/Home_20251017_150630.*	Added scraped HTML pages and their metadata JSON records for Bhagavad Gita / portal pages.
Vedicheritage — Upanishads data/raw/vedicheritage/Upanishads/html/*Aitareyopanishad*.*, .../Arsheyopanishad*.*, .../Brihadaranyakopanishad*.*, .../Chandogyopanishad*.*, .../Ishavasyopanishad*.*, .../Kathopanishad*.*, .../Kenopanisad*.*, .../Maitrayani_*.*, .../Mandukyopanishad*.*, .../Mundakopanishad*.*, .../Prashnopanishad*.*, .../Shwetashwataropanishad*.*, .../TAITTIRIYA_*.*, .../Upanishads_*.{html,json}, .../उपनषद_*.{html,json}	Many new HTML content files and paired metadata JSON files containing scraped Upanishads texts and standardized metadata (title, url, source, format, language, category, encoding, scraped_at, file_size, processing metrics).
Vedicheritage — Vedas & Vedangas data/raw/vedicheritage/Vedas/html/*Ashvalayana_Samhita*.*, .../Atharvaveda_*.*, .../Chanda*.*, .../Continuity_of_oral_and_textual_traditions_*.*, .../Ghana_Patha_*.*, .../Jaiminiya_Samhita*.*, .../Jyotisha*.*	Added scraped Vedas/Vedanga HTML pages and their metadata JSON records following the same schema as above.
SanskritDocuments — Bhagavad Gita & Puranas data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_*.{html,json}, data/raw/sanskritdocuments/Puranas/html/purana_*.{html,json}	Added scraped HTML and metadata JSON files for Bhagavad Gita and Purana listings.
SanskritDocuments — Uncategorized data/raw/sanskritdocuments/uncategorized/html/Bookstores_for_Sanskrit_resources_*.{html,json}	Added scraped bookstore listings HTML and accompanying metadata JSON.

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~12 minutes

Poem

🐰 I hopped through configs, hashes tight and neat,

Gathered Upanishads, mantras, every sheet;
JSON breadcrumbs lined each ancient door,
HTML treasures piled across the floor.
A rabbit's cheer — our harvest is complete!

Pre-merge checks and finishing touches

❌ Failed checks (1 inconclusive)

Check name	Status	Explanation	Resolution
Title Check	❓ Inconclusive	The title "2 web scraping module" relates to content present in the changeset, as the PR does introduce web scraping capabilities including a configuration file and scraped data artifacts. However, the title is problematic due to vague and unclear terminology. The leading "2" is ambiguous—it could refer to an issue number, version, or feature identifier, but this is not evident from the title alone. Additionally, "web scraping module" is generic and does not clearly convey the scope of changes, which encompasses configuration setup, multiple data sources, and infrastructure initialization. A teammate scanning the pull request history would struggle to understand the primary purpose and extent of the changes from this title alone.	Consider revising the title to be more specific and self-contained. For example: "Add web scraping configuration and initial data collection infrastructure" or "Initialize web scraping module with source configuration" would better convey the primary changes without requiring external context. Remove or clarify the leading "2" and replace generic phrasing with descriptive language that explains what is being added and why.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Docstring Coverage	✅ Passed	No functions found in the changes. Docstring coverage check skipped.

✨ Finishing touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment
• Commit unit tests in branch 2-web-scraping-module

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[coderabbitai]

Actionable comments posted: 11

♻️ Duplicate comments (2)

data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_143818.html (1)

1-193: Duplicate Ishavasyopanishad file flagged in previous comment.

See comment on file Ishavasyopanishad__Vedic_Heritage_Portal_20251017_150616.html regarding the two versions with different timestamps.

data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_143420_metadata.json (1)

1-19: Redundant text duplication issue (same as Kenopanishad metadata file).

The metadata JSON unnecessarily duplicates the full page text. Additionally, the extracted text includes UI scaffolding ("Top", "Social Sidebar", "Please enable JavaScript") that should be filtered during scraping.

Recommendation: Separate data and metadata; clean extracted text of UI elements.

🧹 Nitpick comments (11)

data/raw/vedicheritage/Bhagavad Gita/html/Digital_District_Repository_20251017_150224_metadata.json (1)

14-14: Enhance metadata completeness: zero processing_time and empty tags.

The processing_time (line 14) is 0.0, which is unrealistic for scraping, parsing, and encoding operations. Additionally, tags (line 17) is empty, missing semantic classification that could aid discoverability and organization of content.

• Review and correct the processing_time capture logic to accurately reflect scraping/processing duration.
• Consider extracting semantic tags from content (e.g., "history", "heritage", "india", "freedom-struggle") to enrich metadata and improve searchability.

Also applies to: 15-15, 17-17

data/raw/vedicheritage/Bhagavad Gita/html/Digital_District_Repository_20251017_150224.html (1)

1-68: Ensure raw scraped data includes source metadata and validation context.

This file appears to be extracted content from the Digital District Repository. For maintainability and auditability of scraped datasets, consider:

1. Metadata alongside data: Store source URL, scrape timestamp, checksum, and last-verified date in an accompanying .json metadata file.
2. Original HTML preservation: If available, preserve the raw HTML in a separate directory alongside cleaned text to enable future re-extraction or validation.
3. Data freshness tracking: Add a manifest or index that tracks which sources have been scraped and when, to support incremental updates.

The file naming convention (Digital_District_Repository_20251017_150224.html) includes a helpful timestamp. Pairing this with structured metadata will improve reproducibility and data governance.

data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150353_metadata.json (1)

10-10: Standardize timestamp format to ISO 8601.

The scraped_at field uses a non-standard format ("2025-10-17 15:03:53.644120"). For consistency and interoperability, use ISO 8601 format with timezone information (e.g., "2025-10-17T15:03:53.644120Z" or "2025-10-17T15:03:53.644120+00:00").

data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150539.html (1)

226-232: Consider post-processing to separate content from navigation.

Lines 226–232 contain navigation elements and UI prompts ("Samhita", "Shaunaka Samhita", "Top", "Social Sidebar", "Please enable JavaScript…") that appear to be artifacts of web page scraping rather than core content. For cleaner data consumption, consider:

• Stripping or flagging UI/navigation boilerplate in a post-processing step.
• Documenting which lines represent actual content vs. page chrome.
• Creating a structured extraction that separates content sections (e.g., mantras/verses) from metadata.

config/scraping.yaml (1)

10-11: Clarify rate-limit semantics in documentation.

The default_rate_limit: 1.0 and source-level rate_limit values lack a unit designation (e.g., requests/second). Ensure this is clearly documented so maintainers and operators can understand throttling behavior and configure appropriately per-source policy.

Consider adding an inline comment or schema annotation to clarify the unit:

# Rate limiting in requests per second
default_rate_limit: 1.0  # requests/second
...
    rate_limit: 1.0      # requests/second

data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150400.html (1)

1-49: Data-only resource addition—no code review needed; assess data quality and storage strategy.

This file contains raw HTML/text scraped from Vedicheritage.gov.in. While the content appears complete with proper Unicode Devanagari encoding and structural markers, note that web scrapes typically include boilerplate UI elements (lines 38–49: "Samhita", "Top", "Social Sidebar", "Please enable JavaScript") that could be stripped in preprocessing to reduce file size and improve data cleanliness.

Considerations:

• Storage: ~197 KB per file for repeated markup/boilerplate is inefficient. Consider extracting and storing just the canonical text.
• Metadata alignment: Verify the file_size field in the associated metadata JSON matches the actual file size on disk.
• Duplication: Multiple language variants (en-US, hi-in) of the same content create storage overhead—ensure this aligns with project requirements.

Would you like me to help design a preprocessing pipeline to extract canonical text and standardize file storage?

data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150353.html (1)

37-48: Consistent pattern: UI chrome and JavaScript warning at end of all HTML files.

This larger HTML file follows the same pattern as prior files: substantive content (lines 1–36) is followed by navigation metadata and UI elements (lines 37–48), culminating in the JavaScript fallback warning (line 48). While the actual Vedic text content appears intact, the UI artifacts should be systematically removed during preprocessing.

Recommend adding a post-processing cleanup step to strip these boilerplate elements (Top, Social Sidebar, JavaScript prompts) before persisting raw HTML data.

I can help design and implement a data-cleaning pipeline to automatically strip these UI elements during scraping or post-processing if needed.

data/raw/vedicheritage/Upanishads/html/Mundakopanishad__Vedic_Heritage_Portal_20251017_150348_metadata.json (1)

1-19: Metadata Schema Consistency: Timestamp Format Mismatch

The metadata JSON uses ISO datetime format (2025-10-17 15:03:48.538372), but the corresponding filename uses a compact timestamp (20251017_150348). While both are valid, consider standardizing to a single format across filenames and metadata to ensure consistency and simplify parsing.

Minor observation: tags and properties are empty. For future discoverability, consider populating these fields during scraping (e.g., add category tags or scraping metadata properties).

data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_143818_metadata.json (1)

1-19: Data Quality Check: Timestamp Inconsistency

The filename timestamp (143818 = 14:38:18) does not match the scraped_at timestamp (15:06:16). This ~28-minute discrepancy could indicate:

• Timezone conversion issue
• Multiple scrape attempts with misaligned timestamps
• File renamed after scraping

Ensure scraping pipeline synchronizes filename timestamps with metadata scraped_at values for auditability.

data/raw/vedicheritage/Upanishads/html/Chandogyopanishad__Vedic_Heritage_Portal_20251017_150448.html (1)

1-30: Consider post-processing scraped HTML to separate content from UI navigation artifacts.

The scraped content includes website navigation elements (Samhita sections, Top, Social Sidebar, JavaScript notices) intermingled with the actual textual content. While complete, this pattern may reduce content usability downstream for indexing or transformation pipelines.

For improved data quality, consider adding a post-processing step in the scraper to extract and separate the primary content blocks from UI/navigation boilerplate, or document the expected format so downstream consumers know to filter these elements.

data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_143420.html (1)

1-17: Inconsistent content depth across files.

Some files contain full text (Mundakopanishad, Ishavasyopanishad with 100+ lines), while others contain only descriptions (Maitrayani, Aitareya with ~15-25 lines). Clarify content strategy:

• Are overview pages and full texts both intentionally collected?
• Should metadata distinguish between "overview" vs "full_text" content types?

Consider adding a content_type field to metadata for consistency.

📜 Review details

Configuration used: CodeRabbit UI

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between b284182 and 930a7e0.

📒 Files selected for processing (86)

• config/scraping.yaml (1 hunks)
• data/raw/.content_hashes.json (1 hunks)
• data/raw/vedicheritage/Bhagavad Gita/html/Digital_District_Repository_20251017_150224.html (1 hunks)
• data/raw/vedicheritage/Bhagavad Gita/html/Digital_District_Repository_20251017_150224_metadata.json (1 hunks)
• data/raw/vedicheritage/Bhagavad Gita/html/Home_20251017_150630.html (1 hunks)
• data/raw/vedicheritage/Bhagavad Gita/html/Home_20251017_150630_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150433.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150433_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150455.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150455_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150500.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150500_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Arsheyopanishad__Vedic_Heritage_Portal_20251017_150426.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Arsheyopanishad__Vedic_Heritage_Portal_20251017_150426_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Arsheyopanishad__Vedic_Heritage_Portal_20251017_150523.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Arsheyopanishad__Vedic_Heritage_Portal_20251017_150523_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Brihadaranyakopanishad__Vedic_Heritage_Portal_20251017_150339.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Brihadaranyakopanishad__Vedic_Heritage_Portal_20251017_150339_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Brihadaranyakopanishad__Vedic_Heritage_Portal_20251017_150525.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Brihadaranyakopanishad__Vedic_Heritage_Portal_20251017_150525_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Chandogyopanishad__Vedic_Heritage_Portal_20251017_150445.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Chandogyopanishad__Vedic_Heritage_Portal_20251017_150445_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Chandogyopanishad__Vedic_Heritage_Portal_20251017_150448.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Chandogyopanishad__Vedic_Heritage_Portal_20251017_150448_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/English_Mundakopanishad__Vedic_Heritage_Portal_20251017_150325.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/English_Mundakopanishad__Vedic_Heritage_Portal_20251017_150325_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_143818.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_143818_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_150616.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_150616_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kathopanishad__Vedic_Heritage_Portal_20251017_150358.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kathopanishad__Vedic_Heritage_Portal_20251017_150358_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kathopanishad__Vedic_Heritage_Portal_20251017_150431.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kathopanishad__Vedic_Heritage_Portal_20251017_150431_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kenopanisad__Vedic_Heritage_Portal_20251017_150441.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kenopanisad__Vedic_Heritage_Portal_20251017_150441_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kenopanisad__Vedic_Heritage_Portal_20251017_150535.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Kenopanisad__Vedic_Heritage_Portal_20251017_150535_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_143420.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_143420_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_150514.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_150514_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Mandukyopanishad__Vedic_Heritage_Portal_20251017_150259.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Mandukyopanishad__Vedic_Heritage_Portal_20251017_150259_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Mandukyopanishad__Vedic_Heritage_Portal_20251017_150507.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Mandukyopanishad__Vedic_Heritage_Portal_20251017_150507_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Mundakopanishad__Vedic_Heritage_Portal_20251017_150348.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Mundakopanishad__Vedic_Heritage_Portal_20251017_150348_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150539.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150539_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150624.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150624_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150327.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150327_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150559.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150559_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150353.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150353_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150400.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150400_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Upanishads_20251017_150637.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/Upanishads_20251017_150637_metadata.json (1 hunks)
• data/raw/vedicheritage/Upanishads/html/उपनषद_20251017_150417.html (1 hunks)
• data/raw/vedicheritage/Upanishads/html/उपनषद_20251017_150417_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Ashvalayana_Samhita__Vedic_Heritage_Portal_20251017_150541.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Ashvalayana_Samhita__Vedic_Heritage_Portal_20251017_150541_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Atharvaveda_Samhitas__Vedic_Heritage_Portal_20251017_150355.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Atharvaveda_Samhitas__Vedic_Heritage_Portal_20251017_150355_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150331.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150331_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150641.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150641_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Chanda__Vedic_Heritage_Portal_20251017_150551.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Chanda__Vedic_Heritage_Portal_20251017_150551_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150620.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150620_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150632.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150632_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Ghana_Patha_of_Select_Mantras_from_Krishna_Yajurveda__Vedic_Heritage_Portal_20251017_150316.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Ghana_Patha_of_Select_Mantras_from_Krishna_Yajurveda__Vedic_Heritage_Portal_20251017_150316_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150346.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150346_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150403.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150403_metadata.json (1 hunks)
• data/raw/vedicheritage/Vedas/html/Jyotisha__Vedic_Heritage_Portal_20251017_150228.html (1 hunks)
• data/raw/vedicheritage/Vedas/html/Jyotisha__Vedic_Heritage_Portal_20251017_150228_metadata.json (1 hunks)

🔇 Additional comments (48)

data/raw/vedicheritage/Bhagavad Gita/html/Digital_District_Repository_20251017_150224.html (1)

4-13: Verify against original source: Contact information blocks are duplicated with minor variations.

Lines 4–8 and 9–13 contain near-identical submission instructions with slight differences ("teams" vs. "team", different closing statements). Confirm whether this duplication exists in the original Digital District Repository website or if it's a scraping artifact that should be deduplicated in the raw data file.

data/raw/vedicheritage/Upanishads/html/Brihadaranyakopanishad__Vedic_Heritage_Portal_20251017_150339_metadata.json (1)

1-19: Verify handling of duplicate language variants in data pipeline.

Files 3 and 4 represent the same text content scraped from different language variants of the same page (/upanishads/brihadaranyakopanishad/ vs /hi/upanishads/brihadaranyakopanishad/). Both files contain nearly identical metadata except for language and URL.

Clarify the data handling strategy:

1. Is duplication of language variants intentional, or should there be language-agnostic deduplication?
2. How does the downstream data pipeline (indexing, retrieval, analysis) handle these variants?
3. Does the config/scraping.yaml include logic to avoid scraping duplicate language paths for the same content?

This is especially important if the dataset grows to include many languages per text, which could significantly inflate storage and processing overhead without clear benefit.

data/raw/.content_hashes.json (1)

1-98: Clarify the purpose and integration of the content hashes file.

The file contains 98 SHA-256 hashes but lacks context on how these hashes are used—whether for content validation, deduplication, or integrity checks. This should be documented.

Can you confirm:

• How these hashes are validated or consumed by the scraping/data pipeline?
• Whether they correspond to the HTML/metadata files being added in this PR?
• If this mechanism is already integrated into the existing codebase or if it's pending implementation?

data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150346.html (1)

1-28: LGTM — Scraped content preserved correctly.

The HTML content is properly extracted with Devanagari and Latin scripts preserved. No structural or encoding issues detected.

data/raw/vedicheritage/Vedas/html/Jyotisha__Vedic_Heritage_Portal_20251017_150228_metadata.json (1)

1-19: Well-structured metadata with consistent schema.

Metadata is properly formed with all expected fields. Data values (source, category, language, encoding) are consistent and appropriate for the scraped Vedicheritage content.

data/raw/vedicheritage/Upanishads/html/Mandukyopanishad__Vedic_Heritage_Portal_20251017_150259_metadata.json (1)

1-19: Schema and data consistency verified.

Metadata matches the established pattern with correct source/category/language alignment and valid timestamp. No issues detected.

data/raw/vedicheritage/Upanishads/html/Mandukyopanishad__Vedic_Heritage_Portal_20251017_150259.html (1)

1-28: Content extraction and encoding correct.

Sanskrit verses preserved with proper diacritics. Scraped content is well-formed with expected navigation artifacts.

data/raw/vedicheritage/Upanishads/html/Chandogyopanishad__Vedic_Heritage_Portal_20251017_150448_metadata.json (1)

1-19: Language variant properly captured.

The language: "hi-in" field correctly matches the /hi/ URL path segment, showing proper handling of language-specific content variants.

data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150331.html (1)

1-21: LGTM — Content properly extracted.

Atharvaveda section headings and structure preserved correctly with Devanagari text intact.

data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150353_metadata.json (1)

14-14: Verify processing_time and confidence_score values.

All metadata files show processing_time: 0.0 and confidence_score: 1.0. These appear to be placeholder or default values rather than actual metrics. Clarify whether these represent real measurements or should be documented as such. If they're defaults, consider documenting the scraper configuration that produces these values.

data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150641_metadata.json (1)

1-19: Consistent metadata structure across files is good; align timestamp formats per previous comment.

This file follows the same well-defined metadata structure as the Taittiriya Upanishads file, which is good for consistency. However, the timestamp format issue noted in the previous file applies here as well.

data/raw/vedicheritage/Upanishads/html/उपनषद_20251017_150417.html (1)

1-123: Excellent structured reference content; ensure attribution is preserved.

This file contains well-organized educational content about Upanishads with proper author attribution (Line 117: Dr. Shashi Tiwari, Delhi University). The bilingual structure (Hindi/English) and clear sectioning make it valuable reference material. Ensure:

• Author/source attribution is preserved in any downstream processing or publication.
• License or usage rights for this content are documented (see data governance comment in File 1).

data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_150514_metadata.json (1)

1-19: Metadata structure consistent; timestamp format alignment recommended.

This metadata file maintains the established structure and consistency with Files 1–2. Align the timestamp format per recommendations in File 1.

data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150632.html (1)

1-41: Well-organized seminar proceedings; maintain author and event attribution.

This file documents the "Continuity of oral and textual traditions of the Vedas" seminar with clear author and title information for each paper. Ensure attribution is preserved in any derived works or publications.

data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150620.html (1)

1-41: Investigate duplicate/variant scraping of same page.

This file appears to be a variant of the previous Continuity page (File 6, timestamp 150632), with the same event content but different navigation language/formatting. The two files were captured 12 minutes apart (150620 vs. 150632). Clarify:

• Whether this is intentional (e.g., bilingual variants of the same page).
• Or an unintended duplicate from scraper retry/error handling logic.
• If duplicates exist, consider deduplication or consolidation before publication.

data/raw/vedicheritage/Vedas/html/Ghana_Patha_of_Select_Mantras_from_Krishna_Yajurveda__Vedic_Heritage_Portal_20251017_150316_metadata.json (1)

1-19: Metadata structure consistent; finalize timestamp standardization across PR.

This final metadata file maintains consistency with the established structure. Recommend applying the timestamp format standardization (ISO 8601) as a single refactor across all metadata files in this PR rather than file-by-file changes.

data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150624_metadata.json (1)

1-19: Metadata schema is well-formed and consistent.

The JSON structure follows a clean, standardized metadata schema across all fields. All required provenance and processing information is captured. No data integrity issues detected.

Minor observations:

• page_count: null and processing_time: 0.0 suggest minimal post-processing—consider whether additional context is needed.
• author: null is expected for scraped content; confirm this is intentional.
• tags: [] and properties: {} are empty—consider populating these for discoverability and future extensibility.

Verify that the text field content is consistent with the corresponding HTML source file and that the file_size matches the actual HTML file on disk.

data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150539_metadata.json (1)

1-19: Language variant metadata—properly structured but raises storage duplication question.

This file represents the Hindi-language (hi-in) variant of the Prashnopanishad resource. The metadata is correctly structured and URL path reflects the language variant appropriately.

Observation: The PR now contains both English and Hindi versions of the same content (compare with File 2). This increases storage footprint by ~9% but enables multi-language support. Confirm this aligns with project goals—if so, consider automating metadata generation for language variants to reduce maintenance burden.

Clarify the multi-language strategy: are all resources being scraped in multiple languages? If yes, consider a naming convention or directory structure to make language variants explicit.

data/raw/vedicheritage/Upanishads/html/Prashnopanishad__Vedic_Heritage_Portal_20251017_150624.html (1)

1-232: Raw web scrape content—properly encoded but contains boilerplate overhead.

The HTML content is complete and correctly encoded in UTF-8 with proper Devanagari Unicode rendering. However, lines 226–232 contain non-content boilerplate (navigation, sidebars, JavaScript notices) that should ideally be stripped during preprocessing to improve data quality and reduce storage footprint.

Recommendation: Implement a post-scraping cleanup step to remove <div id="Samhita">, navigation elements, and footer notices before storing canonical text.

Cross-check that the text content in this file matches the text field in the associated metadata JSON (File 2). Verify file size matches: expected ~205 KB if metadata is accurate.

data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150400_metadata.json (1)

1-19: Metadata schema consistent; aligns with Taittiriya Upanishads HTML content file.

The metadata correctly references the Taittiriya Upanishads resource with proper provenance information. Structure and content quality match previous metadata files.

data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150632_metadata.json (1)

1-19: Outreach/reference content metadata—properly structured but raises scope question.

This metadata documents an informational/outreach page listing conference presentations and scholarly resources, rather than canonical Vedic text. While the metadata schema is correct, consider whether reference/outreach materials should be stored separately from primary text resources for better data organization and discoverability.

Clarify the content scope: should this PR include only canonical Vedic texts, or also secondary resources like outreach pages and conference materials?

data/raw/vedicheritage/Vedas/html/Continuity_of_oral_and_textual_traditions_of_the_Vedas__Vedic_Heritage_Portal_20251017_150620_metadata.json (1)

1-19: Language variant of outreach content—consistent metadata but reinforces multi-language duplication pattern.

Another Hindi-language variant following the same pattern as previous files. This confirms the scraping strategy includes multiple language versions. Ensure this is documented and intentional.

data/raw/vedicheritage/Vedas/html/Ashvalayana_Samhita__Vedic_Heritage_Portal_20251017_150541_metadata.json (1)

1-19: Metadata for reference content—structurally sound but represents secondary rather than canonical material.

This metadata documents a scholarly reference page about the Ashvalayana Samhita rather than the text itself. Consistent with File 6's pattern of including reference/outreach materials alongside canonical content.

data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150346_metadata.json (1)

1-19: Metadata structure is valid; flag potential duplicate scraping.

The metadata JSON is well-formed with all expected fields. However, this file appears to be a duplicate scrape of the same Vedic text (Jaiminiya Samhita) captured at a different timestamp (15:03:46 vs 15:04:03 in the companion file). Different metadata shows different URLs and language codes for what appears to be the same resource (compare language: "hi-in" with URL path /hi/ here vs language: "en-US" with no language path in the next file).

This pattern suggests either intentional multi-language scraping or accidental duplication.

Clarify: Are duplicate Jaiminiya_Samhita scrapes with different language variants intended, or is this redundant? If intentional, consider explicit naming to distinguish variants (e.g., ...jaiminiya-samhita-hi and ...jaiminiya-samhita-en).

data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150331_metadata.json (1)

1-19: Valid metadata but processing statistics appear unrealistic.

The metadata JSON is well-formed with proper Unicode escaping for Devanagari text. However, across all metadata files in this review set, processing_time is uniformly 0.0 and retry_count is uniformly 0. For real web scraping operations, especially of files >180 KB, these statistics should reflect actual network latency and any retry behavior.

Questions:

1. Are processing times being collected by the scraper? A 195 KB file (line 11) should have non-zero processing time.
2. Are retry stats being tracked? Zero retries suggests either perfect network conditions or incomplete instrumentation.
3. Should these fields be populated with actual measurements, or are they placeholders?

Verify that the scraper is properly instrumenting and recording actual processing_time and retry_count metrics. If these are intentionally placeholders, document that expectation.

data/raw/vedicheritage/Upanishads/html/Mandukyopanishad__Vedic_Heritage_Portal_20251017_150507.html (1)

1-28: No action required—metadata file exists and is properly paired.

The verification confirms that the metadata file Mandukyopanishad__Vedic_Heritage_Portal_20251017_150507_metadata.json exists in the repository at data/raw/vedicheritage/Upanishads/html/. All 29 HTML files in the Upanishads directory have corresponding metadata files with matching timestamps, demonstrating a consistent 1:1 pairing strategy across the entire dataset.

Likely an incorrect or invalid review comment.

data/raw/vedicheritage/Upanishads/html/Kenopanisad__Vedic_Heritage_Portal_20251017_150441.html (1)

113-128: ****

The review comment contains factual errors. Verification shows:

1. Metadata file exists: Kenopanisad__Vedic_Heritage_Portal_20251017_150441_metadata.json is present and properly paired with the HTML file.

2. Ashvalayana_Samhita naming is mischaracterized: It uses Ashvalayana_Samhita__Vedic_Heritage_Portal_20251017_150541 (double underscore with portal name), not "single underscores and timestamps only" as claimed. This is the same pattern as Kenopanisad.

3. Actual naming variance: The codebase exhibits mixed patterns—some files include __Vedic_Heritage_Portal (Kenopanisad, Ashvalayana, most resources), others omit it (Jaiminiya_Samhita, TAITTIRIYA_UPANISHADS). All HTML files have corresponding _metadata.json pairs.

The review's claims about missing metadata and inconsistent naming relative to Ashvalayana_Samhita are incorrect.

Likely an incorrect or invalid review comment.

data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150403_metadata.json (1)

1-19: The URLs are distinct language variants, not duplicates.

The review comment's premise is incorrect. The two files represent intentional language variants of the same resource at different endpoints:

• Prior file (150346): Hindi (hi-in) at https://vedicheritage.gov.in/**hi**/samhitas/samaveda-samhitas/jaiminiya-samhita-2/
• Current file (150403): English (en-US) at https://vedicheritage.gov.in/samhitas/samaveda-samhitas/jaiminiya-samhita-2/

The file size discrepancy (188,558 vs 181,887 bytes) is expected due to Unicode encoding overhead in the Hindi variant's text field. The language codes, URLs, and scraped content are all correct and intentionally distinct.

The concern about processing_time: 0.0 and retry_count: 0 may warrant separate investigation, but these files themselves are legitimate and not accidental duplicates.

Likely an incorrect or invalid review comment.

data/raw/vedicheritage/Vedas/html/Ashvalayana_Samhita__Vedic_Heritage_Portal_20251017_150541.html (1)

1-13: The review comment's premise is incorrect—files contain text extractions, not HTML markup.

The "Please enable JavaScript" warning is not evidence of a no-JS fallback capture. These files are plain text extractions (0 HTML tags present), and the warning appears because it's part of the rendered text content on the target pages. The systematic presence of this string in 95% of files indicates it's expected behavior, not a scraping failure.

The separate concern about including UI chrome ("Top", "Social Sidebar", navigation elements) in raw extracts may be valid as a data-cleaning suggestion, but it's unrelated to the JavaScript warning issue.

Likely an incorrect or invalid review comment.

data/raw/vedicheritage/Upanishads/html/उपनषद_20251017_150417_metadata.json (1)

1-19: Flag unrealistic processing_time value across all scraped records.

Line 14 shows "processing_time": 0.0 for a ~196KB file scraped from a live website. This pattern repeats identically across all metadata files in this PR, suggesting either:

1. A bug in the scraper that's not capturing actual timing
2. An intentional placeholder that wasn't replaced with real metrics

Verify the scraper implementation logs actual elapsed time and that these values are not hardcoded defaults. This is important for monitoring scrape performance and diagnosing network issues.

data/raw/vedicheritage/Upanishads/html/Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150327_metadata.json (1)

4-4: Verify intentional duplicate Shwetashwataropanishad entries.

This PR includes two separate scraped records for Shwetashwataropanishad with different timestamps and URLs:

• Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150327_metadata.json → https://vedicheritage.gov.in/upanishads/shwetashwataropanishad/ (en-US, 15:03:27)
• Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150559_metadata.json → https://vedicheritage.gov.in/hi/upanishads/shwetashwataropanishad/ (hi-in, 15:05:59)

These appear to be language variants (English vs Hindi), which is sensible. Confirm this is the intended deduplication strategy and document if these represent the same source or different page versions.

data/raw/vedicheritage/Upanishads/html/Arsheyopanishad__Vedic_Heritage_Portal_20251017_150426_metadata.json (1)

3-4: Verify URL spelling inconsistency for Arsheyopanishad.

Line 3 shows title "Arsheyopanishad" but Line 4 URL is https://vedicheritage.gov.in/upanishads/aarsheyopanishad/ (note the double 'a' in "aarsheyopanishad"). This mismatch between the metadata fields and the actual scraped URL should be verified:

• Is this the correct URL from the Vedic Heritage Portal source?
• Or is this a scraper bug that captured an incorrect URL slug?

Document the expected URL format to prevent downstream lookup failures or link rot issues.

data/raw/vedicheritage/Upanishads/html/Kathopanishad__Vedic_Heritage_Portal_20251017_150358.html (1)

1-341: Data File Addition: Kathopanishad HTML Content

Static data file containing scraped Vedic text. Content is well-structured with clear section markers (Part I/II, Cantos). Ensure accompanying metadata JSON file exists for proper indexing.

data/raw/vedicheritage/Upanishads/html/Maitrayani_Upanishad__Vedic_Heritage_Portal_20251017_150514.html (1)

1-17: Data File Addition: Maitrayani Upanishad HTML Content

Static HTML data file with descriptive content and taxonomy classification. No functional review applicable.

data/raw/vedicheritage/Upanishads/html/Kathopanishad__Vedic_Heritage_Portal_20251017_150431.html (1)

1-341: Data Quality: Potential Duplicate Content

This file appears nearly identical to Kathopanishad__Vedic_Heritage_Portal_20251017_150358.html (scraped ~33 minutes earlier). Verify whether both versions are intentional (e.g., capturing content drift) or unintentional duplicates. If unintentional, consolidate to a single canonical version to avoid storage/maintenance overhead.

data/raw/vedicheritage/Upanishads/html/Chandogyopanishad__Vedic_Heritage_Portal_20251017_150445.html (1)

1-30: Data File Addition: Chandogya Upanishad HTML Content

Static HTML overview content. Structure and encoding appropriate. Ensure corresponding metadata JSON exists.

data/raw/vedicheritage/Upanishads/html/Shwetashwataropanishad__Vedic_Heritage_Portal_20251017_150559.html (1)

1-23: Data File Addition: Shwetashwatar Upanishad HTML Content

Static HTML overview content with appropriate taxonomy structure. No functional review applicable.

data/raw/vedicheritage/Vedas/html/Atharvaveda_Shaunaka_Samhita__Vedic_Heritage_Portal_20251017_150641.html (1)

1-21: Consistent with prior HTML file pattern.

This file follows the same HTML structure and content/navigation intermingling pattern noted in the previous file. No additional concerns beyond the already-flagged architectural consideration about UI boilerplate.

data/raw/vedicheritage/Upanishads/html/Upanishads_20251017_150637_metadata.json (1)

1-19: Well-structured metadata with complete schema.

The metadata JSON follows a consistent, complete schema with all expected provenance fields (title, url, source, format, language, category, scraped_at, file_size, encoding, processing_time, retry_count, confidence_score). File size and timestamp appear reasonable.

data/raw/vedicheritage/Upanishads/html/Kenopanisad__Vedic_Heritage_Portal_20251017_150535.html (1)

1-128: Substantial Sanskrit content properly preserved.

The Kenopanisad HTML contains extensive primary textual content in Sanskrit/Devanagari with appropriate sectional markers. Standard website navigation boilerplate is present at the end (already noted as architectural pattern in prior review).

data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150433_metadata.json (1)

1-19: Metadata schema consistent; language field properly reflects content language.

This metadata file maintains the same well-structured schema as prior JSON artifacts. The language field is appropriately set to "hi-in" and the URL path confirms Hindi-language content (.../hi/upanishads/...), showing proper localization tracking.

data/raw/vedicheritage/Upanishads/html/Arsheyopanishad__Vedic_Heritage_Portal_20251017_150426.html (1)

1-26: Content follows established HTML structure pattern.

data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_150616_metadata.json (1)

1-19: Metadata schema consistent across all JSON files in batch.

This file maintains the established schema and shows appropriate variation in file_size (216083 bytes) reflecting the larger textual content volume. Language and localization tracking remain consistent.

data/raw/vedicheritage/Upanishads/html/Mundakopanishad__Vedic_Heritage_Portal_20251017_150348.html (1)

1-175: Extensive primary content with clear structural organization.

The Mundakopanishad file contains comprehensive Sanskrit verse content with well-preserved sectional organization (Mundaks and Khandas). Navigation boilerplate follows the established pattern noted in prior reviews.

data/raw/vedicheritage/Upanishads/html/Aitareyopanishad__Vedic_Heritage_Portal_20251017_150455.html (1)

1-27: File format inconsistency: plain text with .html extension.

Same issue as Mundakopanishad—this file lacks HTML document structure. Apply consistent formatting across all files.

data/raw/vedicheritage/Upanishads/html/Upanishads_20251017_150637.html (1)

1-123: Attribution preserved but consider documenting source provenance.

The content attribution to Dr. Shashi Tiwari is appreciated. However, ensure source URLs/publication details are captured in metadata for proper citation tracking and compliance with original source attribution requirements.

Verify that config/scraping.yaml (mentioned in PR summary) includes proper attribution/citation rules for scraped content.

data/raw/vedicheritage/Upanishads/html/Ishavasyopanishad__Vedic_Heritage_Portal_20251017_150616.html (1)

1-193: Multiple versions of same text detected: potential data duplication.

This PR includes two Ishavasyopanishad files with different timestamps:

• Ishavasyopanishad__Vedic_Heritage_Portal_20251017_143818.html
• Ishavasyopanishad__Vedic_Heritage_Portal_20251017_150616.html

Are these intentional variants (different recensions) or accidental duplicates? Clarify in PR description or consolidate if redundant.

Verify the content differences between the two Ishavasyopanishad files to confirm they are distinct variants rather than duplicates.

data/raw/vedicheritage/Vedas/html/Chanda__Vedic_Heritage_Portal_20251017_150551.html (1)

1-33: Verify encoding and metadata consistency.

The file correctly includes both English and Devanagari script content (lines 1–33). Ensure that:

1. The encoding is explicitly declared as UTF-8 in the accompanying metadata JSON
2. The encoding field in the metadata JSON matches the actual file encoding
3. Any page_count and file_size fields in the metadata are accurate

Also confirm that the scraping configuration (config/scraping.yaml) documents the expected content structure and any transformations applied.

[coderabbitai]

⚠️ Potential issue | 🟠 Major

Upgrade GRETIL source to HTTPS.

Line 58 configures gretil with http:// instead of https://. This exposes potential man-in-the-middle attacks on Vedic heritage content, which is particularly sensitive in an open-source context.

Apply this fix:

  gretil:
    name: "gretil"
-   base_url: "http://gretil.sub.uni-goettingen.de"
+   base_url: "https://gretil.sub.uni-goettingen.de"
    description: "Göttingen Register of Electronic Texts"
    language: "en"
    encoding: "utf-8"
-   robots_txt_url: "http://gretil.sub.uni-goettingen.de/robots.txt"
+   robots_txt_url: "https://gretil.sub.uni-goettingen.de/robots.txt"

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change

	gretil:
	name: "gretil"
	base_url: "http://gretil.sub.uni-goettingen.de"
	description: "Göttingen Register of Electronic Texts"
	language: "en"
	encoding: "utf-8"
	robots_txt_url: "http://gretil.sub.uni-goettingen.de/robots.txt"
	rate_limit: 0.5
	max_pages: 500
	supported_formats:
	- html
	- plaintext
	- xml
	gretil:
	name: "gretil"
	base_url: "https://gretil.sub.uni-goettingen.de"
	description: "Göttingen Register of Electronic Texts"
	language: "en"
	encoding: "utf-8"
	robots_txt_url: "https://gretil.sub.uni-goettingen.de/robots.txt"
	rate_limit: 0.5
	max_pages: 500
	supported_formats:
	- html
	- plaintext
	- xml

🤖 Prompt for AI Agents

In config/scraping.yaml around lines 56 to 68, the gretil source is configured
with http URLs; update the base_url and robots_txt_url to use https (change
"http://gretil.sub.uni-goettingen.de" to "https://gretil.sub.uni-goettingen.de"
and "http://gretil.sub.uni-goettingen.de/robots.txt" to
"https://gretil.sub.uni-goettingen.de/robots.txt") leaving all other fields
unchanged.

[coderabbitai]

⚠️ Potential issue | 🟠 Major

Incomplete HTML parsing in extracted text.

The text field (line 2) contains HTML form elements and navigation markup (e.g., "Select State", "Select District", dropdown options), indicating that the HTML extraction did not properly isolate content from navigation/UI elements. This pollutes the semantic content and reduces usefulness for downstream text analysis or search indexing.

Refine the HTML parsing and content extraction logic to remove or properly separate navigation elements from the primary article/page content.

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

Critical: Category and source metadata mismatch.

The metadata contains inconsistencies:

• Source mismatch: source is set to "vedicheritage" but the url points to amritkaal.nic.in (Amrit Kaal achievements portal), not vedicheritage.gov.in.
• Category mismatch: category is set to "Bhagavad Gita", but the actual content is the "Digital District Repository" about Indian historical narratives and freedom struggle, which has no relation to the Bhagavad Gita.

These discrepancies degrade data quality and could break downstream filtering, categorization, or retrieval logic.

Verify and correct the source (line 5) and category (line 8) fields to match the actual content source and semantic category.

Also applies to: 8-8

🤖 Prompt for AI Agents

In data/raw/vedicheritage/Bhagavad
Gita/html/Digital_District_Repository_20251017_150224_metadata.json around lines
5 and 8, update the mismatched metadata: change "source" on line 5 from
"vedicheritage" to a value matching the URL host (e.g., "amritkaal" or
"amritkaal.nic.in"), and change "category" on line 8 from "Bhagavad Gita" to a
semantically correct category such as "Digital District Repository", "Indian
history", or "Freedom struggle" that reflects the actual content.

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Critical: Data integrity issue — content misclassified.

The metadata contains a fundamental inconsistency:

• URL: https://amritmahotsav.nic.in/... (NIC government independence portal)
• Source: "vedicheritage" (claims Vedicheritage source)
• Category: "Bhagavad Gita" (but content is about India's 75-year independence commemoration)
• Actual content: "Azadi Ka Amrit Mahotsav" — unrelated to Vedic texts

This appears to be either a scraper configuration error or misconfigured metadata. The URL, source, and category do not match the actual page content.

Please verify:

1. Should this file be included in a Vedicheritage dataset?
2. Is the URL correct, or was a wrong URL added to the scraping configuration?
3. Should the source be "amritmahotsav" and category "Government" or similar instead?
4. Can you share config/scraping.yaml (referenced in the AI summary but not provided) to verify the source configuration?

---

---

🏁 Script executed:

#!/bin/bash

# Find scraping configuration files
echo "=== Searching for scraping configuration files ==="
find . -type f \( -name "*scraping*" -o -name "*config*" \) -path "*/config/*" 2>/dev/null | head -20

# Check directory structure
echo -e "\n=== Vedicheritage directory structure ==="
find data/raw/vedicheritage -type d | head -20

# Count files in Bhagavad Gita category
echo -e "\n=== Files in Bhagavad Gita category ==="
find data/raw/vedicheritage/Bhagavad* -type f 2>/dev/null | wc -l

# Sample other metadata files from same directory
echo -e "\n=== Other metadata files in Bhagavad Gita directory ==="
find data/raw/vedicheritage -name "*metadata.json" -type f 2>/dev/null | head -5

# Show the source field from multiple metadata files
echo -e "\n=== Source field from metadata files ==="
find data/raw/vedicheritage -name "*metadata.json" -type f 2>/dev/null | head -3 | xargs -I {} sh -c 'echo "File: {}"; jq -r ".source" {} 2>/dev/null'

Length of output: 1318

---

🏁 Script executed:

#!/bin/bash

# Verify URL domain for the flagged file
echo "=== Analyzing the flagged metadata file ==="
cat data/raw/vedicheritage/Bhagavad\ Gita/Home_20251017_150630_metadata.json | jq '{url: .url, source: .source, category: .category, title: .title}' 2>/dev/null

# Check if URL content matches classification
echo -e "\n=== URL domain analysis ==="
cat data/raw/vedicheritage/Bhagavad\ Gita/Home_20251017_150630_metadata.json | jq -r '.url' | grep -oP '(?:https?://)?(?:www\.)?[^/]+' || echo "Could not extract domain"

# Show content snippet analysis
echo -e "\n=== Content snippet (first 200 chars) ==="
cat data/raw/vedicheritage/Bhagavad\ Gita/Home_20251017_150630_metadata.json | jq -r '.text' | head -c 200

Length of output: 458

---

🏁 Script executed:

#!/bin/bash

# Check if this pattern exists in other vedicheritage files
echo "=== Checking for other files with amritmahotsav URLs ==="
find data/raw/vedicheritage -name "*metadata.json" -type f -exec grep -l "amritmahotsav" {} \; 2>/dev/null | wc -l

# Check if there are URLs mismatched with categories
echo -e "\n=== Sample metadata files structure ==="
find data/raw/vedicheritage -name "*metadata.json" -type f 2>/dev/null | head -3 | while read file; do
  echo "File: $file"
  jq '{source, category, url: (.url | split("/")[2])}' "$file" 2>/dev/null | head -5
  echo "---"
done

Length of output: 696

---

---

🏁 Script executed:

#!/bin/bash

# Inspect scraping configuration
echo "=== Scraping Configuration ==="
cat config/scraping.yaml

# Check if there are more NIC domain URLs
echo -e "\n=== All NIC domain URLs in vedicheritage ==="
find data/raw/vedicheritage -name "*metadata.json" -type f -exec grep -H "\.nic\.in" {} \;

# Check full URLs to understand scope
echo -e "\n=== Full URLs in Bhagavad Gita metadata files ==="
find data/raw/vedicheritage/Bhagavad\ Gita -name "*metadata.json" -type f -exec sh -c 'echo "=== $1 ==="; jq -r ".url" "$1"' _ {} \;

Length of output: 2438

---

Critical: Data integrity issue confirmed — URLs do not match configured sources.

Verification of scraping configuration reveals a definitive misconfiguration:

• Configuration: config/scraping.yaml defines vedicheritage source with base_url: "https://vedicheritage.gov.in" only. NIC domains (amritmahotsav.nic.in, amritkaal.nic.in) are not listed.
• Actual files:
  • Home_20251017_150630_metadata.json → https://amritmahotsav.nic.in/digital-district-repository
  • Digital_District_Repository_20251017_150224_metadata.json → https://amritkaal.nic.in/digital-district-repository
• Content mismatch: Both URLs serve government independence initiatives (Azadi Ka Amrit Mahotsav, Amrit Kaal), not Vedic heritage content.

Action required:

1. Remove these two files from the vedicheritage/Bhagavad Gita directory, OR
2. Reclassify them under a separate government source (if intended)
3. Verify scraper configuration to prevent recurrence

🤖 Prompt for AI Agents

In data/raw/vedicheritage/Bhagavad Gita/Home_20251017_150630_metadata.json
(lines 1-19) the scraped URL (amritmahotsav.nic.in) does not match the
configured vedicheritage base_url (vedicheritage.gov.in) and the content is from
a different government initiative; fix by either (A) remove
Home_20251017_150630_metadata.json and
Digital_District_Repository_20251017_150224_metadata.json from the
vedicheritage/Bhagavad Gita folder, or (B) move/reclassify those two files into
a new or existing government-source directory (e.g., amritmahotsav or amritkaal)
and update their metadata.source and category accordingly, then update
config/scraping.yaml to add the correct base_url(s) for the source(s) or correct
the source-to-domain mapping so the scraper stores pages under the proper
source, and finally run the scraper validation (or a test scrape) to confirm no
further domain-to-source mismatches occur.

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Unrealistic processing_time metric across scraped data.

A processing_time of 0.0 seconds is implausible for web scraping operations, which necessarily involve network I/O, parsing, and file operations. This indicates either missing instrumentation or a data recording issue that could impair debugging and performance monitoring.

Please verify:

1. Whether timing instrumentation is properly implemented in the scraper
2. Whether this pattern occurs across all scraped files (not just this one)
3. Whether the configuration files (e.g., config/scraping.yaml) enable timing metrics

Run this verification to check the pattern across all metadata files:

---

🏁 Script executed:

#!/bin/bash
# Check processing_time values across all metadata files
find data/raw/vedicheritage -name "*_metadata.json" -type f | head -20 | xargs -I {} sh -c 'echo "File: {}"; jq ".processing_time" {}'

Length of output: 2716

---

Fix broken timing instrumentation in scraper—processing_time is 0 across all metadata files.

Verification confirms all scraped metadata files record processing_time: 0, indicating the timing instrumentation is not working. This prevents monitoring scraper performance and diagnosing bottlenecks. Update the scraper to properly measure and record wall-clock time for each operation, including network I/O, parsing, and file writing.

[coderabbitai]

⚠️ Potential issue | 🟠 Major

Architectural concern: Full text duplicated in metadata JSON.

The "text" field contains the entire Kenopanishad content (189KB). This creates maintenance burden and sync risks:

• If the HTML and JSON versions diverge, there's no single source of truth
• Storage inefficiency (same content in two files)
• Risk of inconsistency during future updates

Recommendation: Store only reference metadata in JSON; keep full text in HTML files only.

Consider refactoring to separate concerns:

{
  "title": "...",
  "url": "...",
  "source": "vedicheritage",
  "format": "html",
  "language": "en-US",
  "category": "Upanishads",
  "file_path": "English_Kenopanishad__Vedic_Heritage_Portal_20251017_150441.html",
  "file_size": 189168,
  "encoding": "UTF-8",
  "scraped_at": "2025-10-17 15:05:35.175855"
}

🤖 Prompt for AI Agents

In
data/raw/vedicheritage/Upanishads/html/Kenopanisad__Vedic_Heritage_Portal_20251017_150535_metadata.json
lines 1-19, the "text" field redundantly contains the full Kenopanishad HTML
content (large ~189KB) which duplicates the HTML file and causes storage and
consistency issues; remove the "text" field and replace it with reference-only
metadata (retain title, url, source, format, language, category, file_path or
filename, file_size, encoding, scraped_at, confidence_score, etc.), ensure
file_path points to the existing HTML file, update any ingestion/consumption
code to read the content from that HTML file instead of expecting "text" in the
JSON, and run a quick validation that consumers still find content via the new
file_path key.

[coderabbitai]

🛠️ Refactor suggestion | 🟠 Major

Add data governance documentation.

This PR adds multiple data files with metadata but lacks documentation about data sourcing, licensing, attribution, and maintenance. Consider adding:

• A DATA_SOURCES.md documenting each source (vedicheritage.gov.in), licensing terms, and update frequency.
• A .gitattributes file to mark large data files appropriately.
• A .gitignore policy for generated or temporary data artifacts (if applicable).

🤖 Prompt for AI Agents

In
data/raw/vedicheritage/Upanishads/html/TAITTIRIYA_UPANISHADS_20251017_150353_metadata.json
around lines 1-19, the PR adds raw metadata files but lacks data governance
documentation; add a DATA_SOURCES.md that lists each source
(vedicheritage.gov.in) with exact source URLs, licensing terms, required
attribution text, contact/maintainer info, and update frequency; add a
.gitattributes file marking large/binary or generated data files (e.g., *.json,
*.csv) with appropriate attributes (e.g., export-ignore or linguist-generated)
and indicating any files tracked via Git LFS; and add/extend .gitignore to
exclude generated/temp artifacts (e.g., tmp/, .cache/, *.ndjson.tmp) and
document the policy in DATA_SOURCES.md or README with maintainers and refresh
procedures.

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Verify licensing and copyright clearance for scraped content.

This HTML file contains content directly scraped from vedicheritage.gov.in. Before including this in the repository, confirm that:

1. The source website permits redistribution and archival of their content
2. Appropriate attribution or licensing headers are included
3. The data collection has legal/ethical clearance

This is especially important for content that may be restricted or require specific attribution.

---

I'll verify the review comment's concerns about licensing and data quality. Let me search for information about the source website and examine the repository structure.

---

🏁 Script executed:

#!/bin/bash
# Check for LICENSE files and scraping documentation
echo "=== Looking for LICENSE and documentation files ==="
fd -e LICENSE -e "license*" -e "terms*" -e "SCRAPING*" -e "scraping*" -e "README*" | head -20

echo ""
echo "=== Checking data/raw directory structure ==="
fd --type f --type d data/raw/ | grep -E "(vedicheritage|meta|config)" | head -20

echo ""
echo "=== Looking for scraping configuration files ==="
fd -e yaml -e yml -e json . -x grep -l "vedicheritage\|scraping" {} \; 2>/dev/null | head -10

echo ""
echo "=== Checking root and config directories for guidance ==="
ls -la config/ 2>/dev/null || echo "No config directory"
ls -la | grep -iE "(license|scraping|attribution)"

Length of output: 1311

---

🌐 Web query:

vedicheritage.gov.in terms of use licensing content redistribution

💡 Result:

Short answer: vedicheritage.gov.in does not offer an open re-use license. Its Copyright Policy says content "cannot be reproduced partially or fully, without written permission from Indira Gandhi National Center for the Arts or the contributor" and must be acknowledged and not used in a misleading/objectionable context. The Terms & Conditions reiterate disclaimers and a linking policy (direct linking allowed; framing not permitted). [1][2]

If you need to redistribute material, request written permission from IGNCA (contact information is on the portal). [1][2]

Sources:

• Vedic Heritage — Copyright Policy. [1]
• Vedic Heritage — Terms & Conditions (linking, disclaimers). [2]

---

Let me verify the scraping configuration and metadata structure to see if licensing is properly documented.

---

🏁 Script executed:

```shell
#!/bin/bash
# Examine scraping configuration for licensing guidance
echo "=== Content of scraping.yaml ==="
cat ./git/config/scraping.yaml 2>/dev/null || echo "File not found"

echo ""
echo "=== Sample metadata JSON structure ==="
cat ./git/data/raw/vedicheritage/Vedas/html/Chanda__Vedic_Heritage_Portal_20251017_150551_metadata.json 2>/dev/null | head -30 || echo "Metadata file not found"

echo ""
echo "=== Checking for IGNCA permission or license reference ==="
rg -i "ignca|permission|copyright|license" ./git/config/ ./git/data/raw/ --type json --type yaml 2>/dev/null | head -15

Length of output: 147

---

Let me search for the files without the path prefix to locate them correctly.

---

🏁 Script executed:

```shell
#!/bin/bash
# Search for the actual files without ./git/ prefix
echo "=== Looking for scraping.yaml ==="
find . -name "scraping.yaml" -type f 2>/dev/null

echo ""
echo "=== Looking for Chanda metadata/HTML files ==="
find . -name "*Chanda*" -type f 2>/dev/null

echo ""
echo "=== Check data/raw/vedicheritage structure ==="
find data/raw/vedicheritage -type f 2>/dev/null | head -20

echo ""
echo "=== Look for any LICENSE or ATTRIBUTION files ==="
find . -iname "*license*" -o -iname "*attribution*" -o -iname "*terms*" 2>/dev/null | grep -v ".git"

Length of output: 2426

---

Let me examine the LICENSE file, scraping configuration, and metadata to determine if licensing compliance is documented.

---

🏁 Script executed:

```shell
#!/bin/bash
echo "=== LICENSE file content ==="
cat LICENSE

echo ""
echo "=== scraping.yaml content ==="
cat config/scraping.yaml

echo ""
echo "=== Chanda metadata.json structure ==="
cat data/raw/vedicheritage/Vedas/html/Chanda__Vedic_Heritage_Portal_20251017_150551_metadata.json

echo ""
echo "=== Search for any permission/licensing documentation ==="
find . -type f \( -name "*.md" -o -name "*.txt" -o -name "*.rst" \) ! -path "./.git/*" -exec grep -l "vedicheritage\|IGNCA\|permission\|copyright" {} \;

Length of output: 6655

---

Let me check the documentation files to see if licensing is addressed.

---

🏁 Script executed:

```shell
#!/bin/bash
echo "=== README.md ==="
head -50 README.md

echo ""
echo "=== docs/scraping/README.md ==="
cat docs/scraping/README.md 2>/dev/null || echo "File not found"

echo ""
echo "=== Check for licensing disclaimers in documentation ==="
grep -r "copyright\|permission\|IGNCA\|vedicheritage.*license\|data.*license" README.md docs/ project-management/ 2>/dev/null | head -10

Length of output: 9503

---

Copyright compliance violation: IGNCA written permission required but not documented.

The source website's Copyright Policy explicitly prohibits reproduction of content without written permission from the Indira Gandhi National Centre for the Arts (IGNCA). The repository contains no documented evidence that this permission has been obtained:

• No permission documentation: The repository lacks any IGNCA written permission letters or compliance records
• Metadata gaps: The metadata structure (metadata.json) does not track permission status or licensing compliance
• Known unresolved risk: The project's risk register identifies this as risk R1 ("Scraping copyrighted texts without permission") with action item "Document copyright verification process" — not yet completed
• Policy contradiction: The project charter states "Respect copyright and use only public domain or openly licensed texts," yet vedicheritage.gov.in is neither public domain nor openly licensed

Required action: Before merging, obtain and document written permission from IGNCA for redistributing vedicheritage.gov.in content, or remove all vedicheritage-sourced files from the repository. Update metadata.json to include a permission_status field and populate it for all scraped content.

🤖 Prompt for AI Agents

In
data/raw/vedicheritage/Vedas/html/Chanda__Vedic_Heritage_Portal_20251017_150551.html
lines 1-36: this file (and other vedicheritage-sourced files) appear to be
copyrighted content requiring written IGNCA permission which is not documented;
either obtain and add the IGNCA written permission letter(s) into the repository
(e.g., add a permissions/IGNCA/<date>-permission.pdf) and reference them in the
dataset metadata, or remove all vedicheritage.gov.in files from the repo. Also
update the project's metadata.json schema to include a permission_status field
(e.g., values: "unknown", "requested", "granted", "denied") and populate
permission_status for every scraped record from vedicheritage, and update the
risk register entry R1 to reflect the new status and actions taken.

[coderabbitai]

⚠️ Potential issue | 🟠 Major

Remove UI cruft from scraped content.

The file includes non-content elements like "Top" (line 34), "Social Sidebar" (line 35), and "Please enable JavaScript in your browser to view the content" (line 36). These are navigation and UI hints from the source website, not the actual educational content.

For a clean dataset, the scraper should filter out these UI elements during ingestion. Consider post-processing the scraped HTML to extract and normalize only the actual content (lines 1–33 appear to contain the substantive Vedanga material).

🤖 Prompt for AI Agents

In
data/raw/vedicheritage/Vedas/html/Chanda__Vedic_Heritage_Portal_20251017_150551.html
around lines 34–36, the scraped HTML contains UI/navigation cruft ("Top",
"Social Sidebar", "Please enable JavaScript in your browser to view the
content") that should be excluded from the dataset; update the scraper or add a
post-processing step to detect and remove common UI strings and sidebar blocks
(by CSS selectors, role attributes, or exact text matches) and normalize the
output to include only substantive content (e.g., keep lines 1–33), ensuring
these phrases are filtered out before saving the cleaned HTML/text.

[coderabbitai]

⚠️ Potential issue | 🟠 Major

Same JavaScript and UI chrome issues as prior HTML files.

Lines 8-9 again include UI navigation ("Social Sidebar") and the JavaScript fallback message. This confirms a systemic issue across all scraped HTML files: UI elements and no-JS fallback messages are being retained in the raw data.

See prior review comment for details. Recommend implementing a consistent data-cleaning/post-processing step.

🤖 Prompt for AI Agents

In data/raw/vedicheritage/Vedas/html/Jaiminiya_Samhita_20251017_150403.html
lines 1-9 the file contains UI chrome and no-JS fallback text ("Top", "Social
Sidebar", "Please enable JavaScript in your browser to view the content") that
should not be in raw data; implement a consistent post-processing step in the
scraper pipeline that parses the HTML (e.g., with jsdom/BeautifulSoup), removes
known UI elements and fallback messages by selector/text patterns (e.g.,
elements with classes/ids matching sidebar, social, top, or containing "Please
enable JavaScript"), and trims leftover standalone strings like "Top"; make the
cleaning configurable (list of selectors/phrases) and idempotent, add a unit
test or sample assertion to verify these specific strings are stripped from
newly scraped files.

[coderabbitai]

Actionable comments posted: 5

♻️ Duplicate comments (1)

config/scraping.yaml (1)

60-72: Upgrade GRETIL source from HTTP to HTTPS.

The GRETIL source uses unencrypted HTTP on both base_url and robots_txt_url, creating a MITM vulnerability. This issue was flagged in the previous review and should be fixed.

Apply this diff to upgrade to HTTPS:

  gretil:
    name: "gretil"
-   base_url: "http://gretil.sub.uni-goettingen.de"
+   base_url: "https://gretil.sub.uni-goettingen.de"
    description: "Göttingen Register of Electronic Texts"
    language: "en"
    encoding: "utf-8"
-   robots_txt_url: "http://gretil.sub.uni-goettingen.de/robots.txt"
+   robots_txt_url: "https://gretil.sub.uni-goettingen.de/robots.txt"
    rate_limit: 0.5
    max_pages: 500
    supported_formats:
      - html
      - plaintext
      - xml

🧹 Nitpick comments (2)

data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257_metadata.json (2)

10-10: Use ISO 8601 timestamp format.

The scraped_at field uses a non-standard format: "2025-10-17 17:12:57.457958". Adopt ISO 8601 format for consistency: "2025-10-17T17:12:57.457958Z" (or with explicit timezone offset).

---

17-18: Document or populate empty metadata fields.

The "tags": [] and "properties": {} fields are empty. Clarify whether these are intentionally unused, or if they should be populated with categorization tags or domain-specific metadata (e.g., author names, chapter structure, linguistic properties). Add inline documentation if these are to remain empty.

📜 Review details

Configuration used: CodeRabbit UI

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 930a7e0 and 951647e.

📒 Files selected for processing (8)

• config/scraping.yaml (1 hunks)
• data/raw/.content_hashes.json (1 hunks)
• data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257.html (1 hunks)
• data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257_metadata.json (1 hunks)
• data/raw/sanskritdocuments/Puranas/html/purana_20251017_171255.html (1 hunks)
• data/raw/sanskritdocuments/Puranas/html/purana_20251017_171255_metadata.json (1 hunks)
• data/raw/sanskritdocuments/uncategorized/html/Bookstores_for_Sanskrit_resources_20251017_171253.html (1 hunks)
• data/raw/sanskritdocuments/uncategorized/html/Bookstores_for_Sanskrit_resources_20251017_171253_metadata.json (1 hunks)

✅ Files skipped from review due to trivial changes (2)

• data/raw/sanskritdocuments/Puranas/html/purana_20251017_171255_metadata.json
• data/raw/sanskritdocuments/Puranas/html/purana_20251017_171255.html

🚧 Files skipped from review as they are similar to previous changes (1)

• data/raw/.content_hashes.json

🔇 Additional comments (4)

data/raw/sanskritdocuments/uncategorized/html/Bookstores_for_Sanskrit_resources_20251017_171253.html (1)

1-97: Data artifact is complete and well-formed.

The HTML content captures bookstore listings with contact information across multiple locations, and the encoding preserves special characters (Devanagari script for Hindi text). No issues detected in the scraped data.

data/raw/sanskritdocuments/uncategorized/html/Bookstores_for_Sanskrit_resources_20251017_171253_metadata.json (1)

1-19: Metadata structure is consistent and complete.

The JSON metadata properly documents the scraped HTML resource with appropriate schema fields, timestamps, and encoding information. All values are consistent with the companion data artifact.

config/scraping.yaml (1)

1-39: Configuration structure and defaults look sound.

The general settings, rate limiting, content filtering, logging, validation, and performance tuning are all reasonable and well-calibrated for respectful scraping of academic Sanskrit resources. Source configurations (excluding HTTP protocol issues above) are properly structured with per-source rate limits and format constraints.

data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257.html (1)

54-57: Verify licensing compliance with SanskritDocuments.org before merging.

SanskritDocuments.org explicitly prohibits copying and reposting without permission, and requires contacting maintainers (sanskrit at cheerful dot com) for reuse beyond personal study/research. The file's copyright notice (lines 54-57) correctly reflects this restriction.

Confirm that:

• This repository's use case qualifies as personal study/research, OR
• Express permission has been obtained from SanskritDocuments.org maintainers
• Proper attribution and source links are maintained

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

Critical: Disable SSL verification should be environment-based, not hardcoded.

Disabling SSL verification in a committed configuration file creates a MITM attack surface that could accidentally propagate to production. The comment says "for development" but config files are not development-only artifacts.

Recommend one of these approaches:

Option 1 (preferred): Enable SSL verification and use environment variable overrides for development:

-verify_ssl: false  # Disable SSL verification for development
-ssl_warnings: false  # Disable SSL warnings
+verify_ssl: ${VERIFY_SSL:-true}
+ssl_warnings: ${SSL_WARNINGS:-true}

Option 2: Move to a separate .env.development file that is .gitignore-d and loaded only during local testing, keeping production configs secure by default.

This aligns with the principle of secure-by-default configurations.

Committable suggestion skipped: line range outside the PR's diff.

🤖 Prompt for AI Agents

In config/scraping.yaml around lines 41-43, the file hardcodes verify_ssl: false
and ssl_warnings: false which is insecure; change the defaults to enable SSL
verification (verify_ssl: true and keep ssl_warnings true/omit) and update the
application to read an environment variable (e.g. SCRAPING_VERIFY_SSL) to allow
overriding to false only in local/dev environments, or alternatively move the
false settings into a separate .env.development/.yaml file that is .gitignore-d
and loaded only in local runs; ensure documentation and config loading logic
prefer the secure default and allow explicit, non-committed overrides for
development.

[coderabbitai]

⚠️ Potential issue | 🟠 Major

Upgrade sanskritlinguistics source from HTTP to HTTPS.

The sanskritlinguistics source uses unencrypted HTTP for both base_url and robots_txt_url. All other sources in this configuration use HTTPS. Upgrade to HTTPS for consistency and security.

Apply this diff:

  sanskritlinguistics:
    name: "sanskritlinguistics"
-   base_url: "http://www.sanskrit-linguistics.org"
+   base_url: "https://www.sanskrit-linguistics.org"
    description: "Sanskrit Linguistics Digital Corpus"
    language: "en"
    encoding: "utf-8"
-   robots_txt_url: "http://www.sanskrit-linguistics.org/robots.txt"
+   robots_txt_url: "https://www.sanskrit-linguistics.org/robots.txt"
    rate_limit: 0.3
    max_pages: 400
    supported_formats:
      - html
      - xml
      - plaintext

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change

	sanskritlinguistics:
	name: "sanskritlinguistics"
	base_url: "http://www.sanskrit-linguistics.org"
	description: "Sanskrit Linguistics Digital Corpus"
	language: "en"
	encoding: "utf-8"
	robots_txt_url: "http://www.sanskrit-linguistics.org/robots.txt"
	rate_limit: 0.3
	max_pages: 400
	supported_formats:
	- html
	- xml
	- plaintext
	sanskritlinguistics:
	name: "sanskritlinguistics"
	base_url: "https://www.sanskrit-linguistics.org"
	description: "Sanskrit Linguistics Digital Corpus"
	language: "en"
	encoding: "utf-8"
	robots_txt_url: "https://www.sanskrit-linguistics.org/robots.txt"
	rate_limit: 0.3
	max_pages: 400
	supported_formats:
	- html
	- xml
	- plaintext

🤖 Prompt for AI Agents

In config/scraping.yaml around lines 154 to 166, the sanskritlinguistics source
uses unencrypted HTTP for base_url and robots_txt_url; update both values to use
HTTPS (change "http://www.sanskrit-linguistics.org" to
"https://www.sanskrit-linguistics.org" and
"http://www.sanskrit-linguistics.org/robots.txt" to
"https://www.sanskrit-linguistics.org/robots.txt"), then verify the HTTPS
endpoints are reachable and adjust any trailing slashes or site-specific
redirects as needed.

[coderabbitai]

⚠️ Potential issue | 🟠 Major

Fix inaccurate language classification.

The "language": "en" is incorrect. The content is primarily Sanskrit (Devanagari script) with English labels and translations. Update to reflect the actual language composition, either as "sa" (Sanskrit) or "multi" (multilingual).

🤖 Prompt for AI Agents

In data/raw/sanskritdocuments/Bhagavad
Gita/html/bhagavadgItA_20251017_171257_metadata.json around line 7, the
"language": "en" field is incorrect; update the value to reflect Sanskrit
content with English elements by setting "language" to "multi" (multilingual) —
if you prefer to mark the primary language only, set it to "sa" for Sanskrit;
ensure the JSON value is properly quoted and valid.

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Investigate zero processing time.

A "processing_time": 0.0 is unrealistic for a web scraping operation (network I/O, HTML parsing, encoding conversion). This suggests either incomplete logging, cached data, or a measurement error. Verify the actual processing time is being captured accurately.

---

I'll help verify this review comment about the zero processing time. Let me investigate the metadata file and the code that generates it.

---

🏁 Script executed:

#!/bin/bash
# First, find and examine the metadata file
find . -name "*bhagavadgItA_20251017_171257_metadata.json" -type f 2>/dev/null | head -20

Length of output: 90

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🏁 Script executed:

#!/bin/bash
# Search for files related to sanskritdocuments metadata generation
find . -type f \( -name "*.py" -o -name "*.js" -o -name "*.ts" \) | xargs grep -l "processing_time" 2>/dev/null | head -20

Length of output: 70

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🏁 Script executed:

#!/bin/bash
# Look for the directory structure
find . -type d -name "sanskritdocuments" 2>/dev/null

Length of output: 28

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🏁 Script executed:

#!/bin/bash
# Search for code that might be creating this metadata
rg -n "processing_time" --type py --type js -C 3 2>/dev/null | head -50

Length of output: 3377

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🏁 Script executed:

#!/bin/bash
# Look for any scrapers or metadata generation scripts
find . -type f \( -name "*scrap*" -o -name "*metadata*" \) 2>/dev/null | grep -E "\.(py|js|ts)$"

Length of output: 866

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🏁 Script executed:

#!/bin/bash
# Check if the file actually exists and examine its content
if [ -d "data/raw/sanskritdocuments" ]; then
  find "data/raw/sanskritdocuments" -name "*metadata.json" -type f 2>/dev/null | head -5 | xargs cat 2>/dev/null
fi

Length of output: 4742

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🏁 Script executed:

#!/bin/bash
# More specific search for metadata generation in Python
rg -n "def.*metadata|\"processing_time\"" --type py -C 2 2>/dev/null | head -100

Length of output: 7081

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🏁 Script executed:

#!/bin/bash
# Look for timing measurements
rg -n "time\(\)|timeit|perf_counter|datetime\.now" --type py -C 2 2>/dev/null | head -50

Length of output: 3225

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🏁 Script executed:

#!/bin/bash
# Check project structure and find main scripts
ls -la | head -20
find . -maxdepth 2 -type f -name "*.py" 2>/dev/null | head -20

Length of output: 1287

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🏁 Script executed:

#!/bin/bash
# Search for where metadata is written
rg -n "json\.dump|to_json|metadata" --type py -C 2 2>/dev/null | head -100

Length of output: 6762

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🏁 Script executed:

#!/bin/bash
# Look for any timing context in processing
rg -n "\.elapsed|\.total_seconds|time\.time" --type py -C 2 2>/dev/null | head -100

Length of output: 5618

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🏁 Script executed:

#!/bin/bash
# Direct check for content in the data directory
if [ -f "data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257_metadata.json" ]; then
  cat "data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257_metadata.json"
else
  echo "File not found at expected path"
  find . -name "*metadata.json" -type f 2>/dev/null | head -10
fi

Length of output: 3706

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🏁 Script executed:

#!/bin/bash
# Search for scraping-related code patterns
rg -n "requests\.|urllib|BeautifulSoup|parse|scrape" --type py -C 3 2>/dev/null | head -150

Length of output: 10278

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🏁 Script executed:

#!/bin/bash
# Look for the exact pattern of how processing_time gets set
rg -n "'processing_time'|\"processing_time\"" --type py -B 5 -A 5 2>/dev/null

Length of output: 0

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#!/bin/bash
# Check for any initialization of processing_time to 0.0
rg -n "processing_time.*=.*0" --type py -C 3 2>/dev/null

Length of output: 1214

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🏁 Script executed:

#!/bin/bash
# Look for imports and overall file structure - find main entry points
find . -maxdepth 3 -type f \( -name "main.py" -o -name "run*.py" -o -name "*scrape*.py" \) 2>/dev/null

Length of output: 0

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🏁 Script executed:

#!/bin/bash
# Try to understand the project structure better
find . -name "*.json" -path "*/data/*" -type f 2>/dev/null | head -10

Length of output: 937

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🏁 Script executed:

#!/bin/bash
# Check recent files to see the PR changes
git diff HEAD~1 --name-only 2>/dev/null | head -20

Length of output: 1047

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🏁 Script executed:

#!/bin/bash
# Look at what changed in the metadata file
git show HEAD:"data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257_metadata.json" 2>/dev/null || echo "File might be new in this commit"

Length of output: 3706

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#!/bin/bash
# Check git status to see added files
git status 2>/dev/null | head -50

Length of output: 465

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#!/bin/bash
# List all files in PR
git diff --name-only 2>/dev/null | grep -E "\.(py|json)$" | head -30

Length of output: 0

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#!/bin/bash
# Look at metadata in all formats
ls -la "data/raw/sanskritdocuments/Bhagavad Gita/html/" 2>/dev/null | head -20

Length of output: 285

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🏁 Script executed:

#!/bin/bash
# Check what's actually changed in this commit
git log --oneline -1 2>/dev/null
git diff HEAD 2>/dev/null | head -200

Length of output: 569

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#!/bin/bash
# Get the entire diff context
git diff 2>/dev/null | head -300

Length of output: 530

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🏁 Script executed:

#!/bin/bash
# Look at file sizes to see what we're dealing with
find . -name "*metadata.json" -type f -exec ls -lh {} \; 2>/dev/null

Length of output: 15295

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🏁 Script executed:

#!/bin/bash
# Simple check - does the file exist?
test -f "data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257_metadata.json" && echo "File exists" || echo "File does not exist in sandbox"

Length of output: 11

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🏁 Script executed:

#!/bin/bash
# Look for any Python scripts that might be generating metadata
find . -type f -name "*.py" -exec grep -l "metadata" {} \; 2>/dev/null | head -10

Length of output: 457

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🏁 Script executed:

#!/bin/bash
# Trace the actual imports and code
rg -n "import.*time|from.*time" --type py 2>/dev/null | head -30

Length of output: 507

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🏁 Script executed:

#!/bin/bash
# Check if this is a data-only PR
find . -type f \( -name "*.py" -o -name "*.js" \) | wc -l
ls -la | head -30

Length of output: 1835

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🏁 Script executed:

#!/bin/bash
# Find where metadata JSON is written/created
rg -n "get_metadata_filename|_metadata\.json|json\.dump|\.dict\(\)|\.model_dump" --type py -B 3 -A 3 2>/dev/null | head -150

Length of output: 8376

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#!/bin/bash
# Look at ScrapedContent and ScrapingResult to understand the relationship
cat src/code4ved/scraping/models.py | head -250

Length of output: 9407

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🏁 Script executed:

#!/bin/bash
# Search for where ScrapedContent is created from scrapers
rg -n "ScrapedContent\(" --type py -B 2 -A 2 2>/dev/null | head -100

Length of output: 7205

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🏁 Script executed:

#!/bin/bash
# Look for storage/export code
find . -type f -name "*.py" -exec grep -l "store\|save\|export\|write.*json" {} \; 2>/dev/null | head -10

Length of output: 168

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🏁 Script executed:

#!/bin/bash
# Look at a specific scraper to see how metadata gets created
cat src/code4ved/scraping/python/sanskritdocuments_scraper.py

Length of output: 12325

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🏁 Script executed:

#!/bin/bash
# Check base scraper class for any timing measurement
cat src/code4ved/scraping/base.py | grep -A 50 "async def scrape"

Length of output: 2072

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🏁 Script executed:

#!/bin/bash
# Look for where scrapers are invoked and if timing is measured there
rg -n "scrape_url|ScrapingResult" --type py -B 3 -A 3 2>/dev/null | head -200

Length of output: 13646

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🏁 Script executed:

#!/bin/bash
# Check orchestrator to see how scraping is executed
cat src/code4ved/scraping/orchestrator.py | head -300

Length of output: 11637

---

Processing time not being captured in stored metadata.

The timing calculation exists in ScrapingResult.complete() (line 225 in src/code4ved/scraping/models.py), which correctly calculates processing_time = (self.completed_at - self.started_at).total_seconds(). However, in Orchestrator._store_results() (line 267 in src/code4ved/scraping/orchestrator.py), only result.content (the ScrapedContent object) is stored via self.storage.store_content(result.content). The ScrapedContent model has no mechanism to receive or set the timing data from ScrapingResult, leaving processing_time at its default value of 0.0 in the persisted metadata.

Transfer the calculated processing_time from ScrapingResult to the ScrapedContent object before storing:

# In orchestrator.py, _store_results() method around line 267
if result.content and result.status == ScrapingStatus.COMPLETED:
    result.content.processing_time = result.processing_time
    self.storage.store_content(result.content)

🤖 Prompt for AI Agents

In src/code4ved/scraping/orchestrator.py around line 267, the
ScrapingResult.processing_time is calculated but never copied into the
ScrapedContent before storage, so persisted metadata shows processing_time 0.0;
update _store_results() to, when result.status == ScrapingStatus.COMPLETED and
result.content exists, set result.content.processing_time =
result.processing_time prior to calling
self.storage.store_content(result.content) so the timing is persisted.

[coderabbitai]

⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

Clarify confidence score semantics and validation.

A perfect "confidence_score": 1.0 lacks context. Define what this score measures (e.g., extraction quality, OCR accuracy, content validity) and justify why the score is always perfect. If this is a placeholder, document the validation thresholds or mark the field as null until proper scoring is implemented.

---

🏁 Script executed:

#!/bin/bash
# Inspect the target metadata file
cat "data/raw/sanskritdocuments/Bhagavad Gita/html/bhagavadgItA_20251017_171257_metadata.json"

Length of output: 3706

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🏁 Script executed:

#!/bin/bash
# Find all metadata JSON files and check confidence_score pattern
fd -e json -p "metadata" | head -20 | while read f; do
  if grep -q "confidence_score" "$f" 2>/dev/null; then
    echo "=== $f ==="
    grep "confidence_score" "$f"
  fi
done

Length of output: 2797

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🏁 Script executed:

#!/bin/bash
# Search codebase for confidence_score definitions, generation, or validation logic
rg -n "confidence_score" -C3 --type json --type ts --type js --type py 2>/dev/null | head -50

Length of output: 6013

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🏁 Script executed:

#!/bin/bash
# Look for any documentation, comments, or READMEs about scoring
find . -type f \( -name "README*" -o -name "*.md" -o -name "*.txt" \) | xargs grep -l "confidence" 2>/dev/null | head -10

Length of output: 335

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🏁 Script executed:

#!/bin/bash
# Check README for confidence_score context
head -100 README.md && echo -e "\n\n--- Searching for confidence in README ---\n" && grep -n -i "confidence" README.md

Length of output: 4769

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🏁 Script executed:

#!/bin/bash
# Check data model specification
grep -n -A5 -B5 "confidence" project-management/03_specifications/data_model.md | head -60

Length of output: 1148

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🏁 Script executed:

#!/bin/bash
# Find Python/JavaScript code that generates metadata files
fd -e py -e js -e ts | xargs grep -l "metadata\|confidence" | grep -v node_modules | grep -v ".json" | head -20

Length of output: 947

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🏁 Script executed:

#!/bin/bash
# Look for scraper or data processing scripts
fd -e py | grep -E "(scrape|metadata|process|extract)" | head -10

Length of output: 483

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🏁 Script executed:

#!/bin/bash
# Check metadata field definitions in scraping models
grep -n -A20 -B5 "confidence" src/code4ved/scraping/models.py

Length of output: 1158

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🏁 Script executed:

#!/bin/bash
# Inspect a scraper to see how metadata is created and confidence_score is set
cat src/code4ved/scraping/python/sanskritdocuments_scraper.py | head -150

Length of output: 4487

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🏁 Script executed:

#!/bin/bash
# Search for where confidence_score is assigned in scraper code
rg -n "confidence_score" --type py -A2 -B2

Length of output: 941

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🏁 Script executed:

#!/bin/bash
# Check storage.py to see metadata schema and confidence_score handling
grep -n -A10 -B5 "confidence" src/code4ved/scraping/storage.py

Length of output: 0

---

Implement or document confidence_score field semantics.

The confidence_score is hardcoded to 1.0 across all metadata because no scraper assigns an actual value. The field definition (scraping/models.py, line 86) describes it as "Content quality score" but provides no scoring logic or validation thresholds. Either:

1. Implement actual scoring logic in scrapers to calculate meaningful scores based on extraction success, content completeness, or source reliability, OR
2. Remove the field if unused, OR
3. Change the default to null and document it as a future feature with validation rules to be defined.

🤖 Prompt for AI Agents

In data/raw/sanskritdocuments/Bhagavad
Gita/html/bhagavadgItA_20251017_171257_metadata.json around line 16 the
confidence_score is hardcoded to 1.0 across metadata; update the implementation
or schema: either implement scoring in scrapers (compute based on extraction
completeness, source trust, and parsing errors), or remove the field from output
if unused, or set default to null and add clear schema documentation and
validation rules (e.g., range 0–1 with null allowed) in scraping/models.py so
downstream consumers know the intended semantics and validators enforce it.