feat: updated the max returned reference counts!#229
Conversation
WalkthroughAdded a global constant Changes
Sequence Diagram(s)sequenceDiagram
autonumber
participant Client
participant MediaWikiTool as MediaWikiSearchTool
participant Executor as ThreadPoolExecutor
participant Fetch as _fetch_page_content
Note over Client,MediaWikiTool: New flow: collect titles, fetch concurrently
Client->>MediaWikiTool: mediawiki_search(query)
MediaWikiTool->>MediaWikiTool: gather page titles (up to max_pages)
MediaWikiTool->>Executor: submit fetch tasks for each title
Executor->>Fetch: run _fetch_page_content(title) [concurrent]
Fetch-->>Executor: return content or error
Executor-->>MediaWikiTool: as_completed yields results (title -> content/error)
MediaWikiTool->>Client: aggregated results (content OR error markers)
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes
Possibly related PRs
Poem
Pre-merge checks and finishing touches❌ Failed checks (1 warning)
✅ Passed checks (2 passed)
✨ Finishing touches
🧪 Generate unit tests (beta)
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Actionable comments posted: 2
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (1)
utils/query_engine/media_wiki.py(3 hunks)
🧰 Additional context used
🪛 Ruff (0.14.2)
utils/query_engine/media_wiki.py
162-162: Do not catch blind exception: Exception
(BLE001)
163-163: Use logging.exception instead of logging.error
Replace with exception
(TRY400)
164-164: Use explicit conversion flag
Replace with conversion flag
(RUF010)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)
- GitHub Check: ci / test / Test
🔇 Additional comments (1)
utils/query_engine/media_wiki.py (1)
6-6: LGTM! Clean import for parallel processing.The import of
ThreadPoolExecutorandas_completedproperly supports the parallel fetching implementation introduced later in the file.
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| def _create_mediawiki_search_tool(api_url: str, max_pages: int = 10): | ||
| def _create_mediawiki_search_tool(api_url: str, max_pages: int = 30): |
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🧩 Analysis chain
Verify the impact of the 3x increase in default max_pages.
The increase from 10 to 30 pages aligns with the PR objectives and is reasonable given the new parallel fetching. However, ensure this doesn't hit MediaWiki API rate limits or cause performance issues in production.
🏁 Script executed:
#!/bin/bash
# Description: Check if there are any rate limiting configurations or concerns in the codebase
# Search for rate limit related code or configuration
rg -n -i -C3 'rate.?limit|throttle|api.?limit' --type=py
# Check for any MediaWiki API configuration or documentation
fd -e md -e txt -e yaml -e yml | xargs rg -l -i 'mediawiki|api.?url'Length of output: 512
🏁 Script executed:
#!/bin/bash
# Description: Examine MediaWiki implementation and understand max_pages usage
# Find and display the media_wiki.py file content, focusing on how max_pages is used
fd -n 'media_wiki\.py' --type f -x cat {}
# Search for any MediaWiki API documentation or configuration files
fd -e md -e rst -e txt | xargs grep -l -i 'mediawiki.*api.*limit\|api.*rate\|max.*page' 2>/dev/null | head -20Length of output: 230
🏁 Script executed:
#!/bin/bash
# Description: Examine MediaWiki implementation and understand max_pages usage
# Find and display the media_wiki.py file
fd 'media_wiki\.py' --type f -exec cat {} \;
# Also check how max_pages is referenced in the codebase
rg -n 'max_pages' --type py -B2 -A5Length of output: 3632
🏁 Script executed:
#!/bin/bash
# Description: Examine parallel fetching implementation and check for API concerns
# Look for parallel fetching implementation
rg -n 'parallel|asyncio|concurrent|ThreadPool|ProcessPool' utils/query_engine/media_wiki.py -A3 -B1
# Check the actual fetching logic to see how many concurrent requests are made
rg -n 'fetch_content|gather|map_async' utils/query_engine/media_wiki.py -A5 -B1
# Check if MediaWikiQueryEngine class max_pages default should also be updated
rg -n 'class MediaWikiQueryEngine' utils/query_engine/media_wiki.py -A30 | head -50Length of output: 2030
Update MediaWikiQueryEngine class to match function default for consistency.
The increase to max_pages=30 in the function (line 84) is safe because parallel fetches are capped at 10 concurrent workers (line 148). However, the MediaWikiQueryEngine class (line 195) still defaults to max_pages=10, creating an inconsistency. Update the class default to 30 to match the function and ensure consistent behavior across the codebase.
🤖 Prompt for AI Agents
In utils/query_engine/media_wiki.py around lines 84 and 195, the top-level
function _create_mediawiki_search_tool sets max_pages=30 while the
MediaWikiQueryEngine class still defaults max_pages to 10, causing inconsistent
behavior; update the MediaWikiQueryEngine class default for max_pages to 30 to
match the function, and ensure any constructor/type hints/docstrings reflect the
new default so both code paths use the same max_pages value.
| # 2. Fetch content for each page in parallel | ||
| pages_content = {} | ||
| for result in results[:max_pages]: | ||
| title = result.get("title") | ||
| if not title: | ||
| continue | ||
| titles_to_fetch = [ | ||
| result.get("title") | ||
| for result in results[:max_pages] | ||
| if result.get("title") | ||
| ] | ||
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| logger.info(f"Fetching content for {len(titles_to_fetch)} pages in parallel...") | ||
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| # Use ThreadPoolExecutor for parallel fetching | ||
| with ThreadPoolExecutor(max_workers=min(10, len(titles_to_fetch))) as executor: | ||
| # Submit all fetch tasks | ||
| future_to_title = { | ||
| executor.submit(_fetch_page_content, api_url, title): title | ||
| for title in titles_to_fetch | ||
| } | ||
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| logger.info(f"Fetching content for: {title}") | ||
| content = _fetch_page_content(api_url, title) | ||
| pages_content[title] = content | ||
| # Collect results as they complete | ||
| for future in as_completed(future_to_title): | ||
| title = future_to_title[future] | ||
| try: | ||
| content = future.result() | ||
| pages_content[title] = content | ||
| logger.info(f"Successfully fetched content for: {title}") | ||
| except Exception as e: | ||
| logger.error(f"Error fetching content for '{title}': {e}") | ||
| pages_content[title] = f"(Error: Failed to fetch content - {str(e)})" | ||
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🛠️ Refactor suggestion | 🟠 Major
Use logging.exception for better error diagnostics.
The parallel fetching implementation is solid and follows best practices with proper resource management and error handling. However, line 163 should use logging.exception instead of logging.error to automatically include the stack trace, which aids debugging.
Apply this diff:
try:
content = future.result()
pages_content[title] = content
logger.info(f"Successfully fetched content for: {title}")
except Exception as e:
- logger.error(f"Error fetching content for '{title}': {e}")
+ logger.exception(f"Error fetching content for '{title}'")
pages_content[title] = f"(Error: Failed to fetch content - {str(e)})"Optional: Consider extracting the magic number for max_workers.
The hardcoded max_workers=10 on line 148 could be extracted as a module-level or class-level constant for better maintainability.
For example, at the module level:
MAX_PARALLEL_FETCH_WORKERS = 10Then use it as:
with ThreadPoolExecutor(max_workers=min(MAX_PARALLEL_FETCH_WORKERS, len(titles_to_fetch))) as executor:Based on static analysis hints.
🧰 Tools
🪛 Ruff (0.14.2)
162-162: Do not catch blind exception: Exception
(BLE001)
163-163: Use logging.exception instead of logging.error
Replace with exception
(TRY400)
164-164: Use explicit conversion flag
Replace with conversion flag
(RUF010)
🤖 Prompt for AI Agents
In utils/query_engine/media_wiki.py around lines 137 to 165, change the error
logging inside the parallel fetch loop to use logger.exception(...) instead of
logger.error(...) so the stack trace is captured automatically when an exception
occurs; also consider extracting the hardcoded max_workers=10 into a
module-level constant (e.g., MAX_PARALLEL_FETCH_WORKERS) and use
min(MAX_PARALLEL_FETCH_WORKERS, len(titles_to_fetch)) when creating the
ThreadPoolExecutor for better maintainability.
1 participant
Summary by CodeRabbit
Chores
Refactor