chore(wren-ai-service): improve sql prompt #1819
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WalkthroughThe SQL generation rules documentation was updated to forbid the use of the EXTRACT() function with INTERVAL data types. Additionally, the function for constructing ask history messages was modified to accept both AskHistory objects and dictionaries, adjusting its logic to handle both data structures accordingly. Changes
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Warning There were issues while running some tools. Please review the errors and either fix the tool's configuration or disable the tool if it's a critical failure. 🔧 Pylint (3.3.7)wren-ai-service/src/pipelines/generation/utils/sql.py✨ Finishing Touches
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Actionable comments posted: 0
🧹 Nitpick comments (1)
wren-ai-service/src/pipelines/generation/utils/sql.py (1)
468-485: Consider improving type safety and error handling.The function modification adds flexibility to handle both
AskHistoryobjects and dictionaries, but the current implementation has some potential issues:
- Mixed list handling: The function doesn't explicitly handle cases where the list contains both
AskHistoryobjects and dictionaries- Error handling: If an item is neither an
AskHistoryobject nor a dictionary with the required keys, it will raise aKeyError- Type safety: Using
hasattrfor duck typing works butisinstancechecks would be more explicitConsider this more robust implementation:
def construct_ask_history_messages( histories: list[AskHistory] | list[dict], ) -> list[ChatMessage]: messages = [] for history in histories: - messages.append( - ChatMessage.from_user( - history.question - if hasattr(history, "question") - else history["question"] - ) - ) - messages.append( - ChatMessage.from_assistant( - history.sql if hasattr(history, "sql") else history["sql"] - ) - ) + if isinstance(history, AskHistory): + question = history.question + sql = history.sql + elif isinstance(history, dict): + question = history["question"] + sql = history["sql"] + else: + raise TypeError(f"Expected AskHistory or dict, got {type(history)}") + + messages.append(ChatMessage.from_user(question)) + messages.append(ChatMessage.from_assistant(sql)) return messages
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wren-ai-service/src/pipelines/generation/utils/sql.py(2 hunks)
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🧠 Learnings (2)
📓 Common learnings
Learnt from: wwwy3y3
PR: Canner/WrenAI#1585
File: wren-ui/src/pages/api/v1/generate_sql.ts:98-106
Timestamp: 2025-04-24T16:10:43.308Z
Learning: In the generate_sql API, allow users to specify language codes not predefined in the WrenAILanguage enum, passing them through directly rather than strictly validating against the enum.
wren-ai-service/src/pipelines/generation/utils/sql.py (1)
Learnt from: wwwy3y3
PR: Canner/WrenAI#1585
File: wren-ui/src/pages/api/v1/generate_sql.ts:98-106
Timestamp: 2025-04-24T16:10:43.308Z
Learning: In the generate_sql API, allow users to specify language codes not predefined in the WrenAILanguage enum, passing them through directly rather than strictly validating against the enum.
🧬 Code Graph Analysis (1)
wren-ai-service/src/pipelines/generation/utils/sql.py (1)
wren-ai-service/src/web/v1/services/ask.py (1)
AskHistory(16-18)
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🔇 Additional comments (1)
wren-ai-service/src/pipelines/generation/utils/sql.py (1)
209-209: LGTM! Good addition to SQL constraints.The new rule appropriately forbids the use of
EXTRACT()function with INTERVAL data types, which aligns with the existing constraint pattern and helps prevent potential SQL generation issues.
yichieh-lu
approved these changes
Jul 3, 2025
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Summary by CodeRabbit
Documentation
New Features