mirror of
https://github.com/hwchase17/langchain
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dcd0392423
Minor lint dependency version upgrade to pick up latest functionality. Ruff's new v0.1 version comes with lots of nice features, like fix-safety guarantees and a preview mode for not-yet-stable features: https://astral.sh/blog/ruff-v0.1.0
271 lines
4.4 KiB
Python
271 lines
4.4 KiB
Python
# ruff: noqa: E501
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# fmt: off
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template = (
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"""
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Transform the narrative_input into an SQL expression. If you are
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unsure, then do not guess, instead add a llm_error_msg that explains why you are unsure.
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{format_instructions}
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narrative_input: how much money will boris have?
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# JSON:
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{{
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"narrative_input": "how much money will boris have?",
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"llm_error_msg": "",
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"expression": "SELECT name, value FROM df WHERE name = 'boris'"
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}}
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narrative_input: How much money does ted have?
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# JSON:
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{{
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"narrative_input": "How much money does ted have?",
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"llm_error_msg": "",
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"expression": "SELECT name, value FROM df WHERE name = 'ted'"
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}}
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narrative_input: what is the sum of pet count for all the people?
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# JSON:
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{{
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"narrative_input": "what is the sum of pet count for all the people?",
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"llm_error_msg": "",
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"expression": "SELECT SUM(value) FROM df"
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}}
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narrative_input: what's the average of the pet counts for all the people?
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# JSON:
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{{
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"narrative_input": "what's the average of the pet counts for all the people?",
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"llm_error_msg": "",
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"expression": "SELECT AVG(value) FROM df"
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}}
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narrative_input: what's the maximum of the pet counts for all the people?
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# JSON:
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{{
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"narrative_input": "what's the maximum of the pet counts for all the people?",
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"llm_error_msg": "",
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"expression": "SELECT MAX(value) FROM df"
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}}
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narrative_input: what's the minimum of the pet counts for all the people?
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# JSON:
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{{
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"narrative_input": "what's the minimum of the pet counts for all the people?",
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"llm_error_msg": "",
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"expression": "SELECT MIN(value) FROM df"
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}}
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narrative_input: what's the number of people with pet counts greater than 10?
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# JSON:
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{{
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"narrative_input": "what's the number of people with pet counts greater than 10?",
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"llm_error_msg": "",
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"expression": "SELECT COUNT(*) FROM df WHERE value > 10"
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}}
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narrative_input: what's the pet count for boris?
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# JSON:
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{{
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"narrative_input": "what's the pet count for boris?",
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"llm_error_msg": "",
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"expression": "SELECT name, value FROM df WHERE name = 'boris'"
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}}
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narrative_input: what's the pet count for cindy and marcia?
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# JSON:
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{{
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"narrative_input": "what's the pet count for cindy and marcia?",
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"llm_error_msg": "",
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"expression": "SELECT name, value FROM df WHERE name IN ('cindy', 'marcia')"
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}}
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narrative_input: what's the total pet count for cindy and marcia?
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# JSON:
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{{
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"narrative_input": "what's the total pet count for cindy and marcia?",
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"llm_error_msg": "",
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"expression": "SELECT SUM(value) FROM df WHERE name IN ('cindy', 'marcia')"
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}}
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narrative_input: what's the total pet count for TED?
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# JSON:
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{{
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"narrative_input": "what's the total pet count for TED?",
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"llm_error_msg": "",
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"expression": "SELECT SUM(value) FROM df WHERE name = 'TED'"
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}}
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narrative_input: what's the total dollar count for TED and cindy?
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# JSON:
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{{
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"narrative_input": "what's the total dollar count for TED and cindy?",
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"llm_error_msg": "",
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"expression": "SELECT SUM(value) FROM df WHERE name IN ('TED', 'cindy')"
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}}
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narrative_input: what's the total pet count for TED and cindy?
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# JSON:
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{{
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"narrative_input": "what's the total pet count for TED and cindy?",
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"llm_error_msg": "",
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"expression": "SELECT SUM(value) FROM df WHERE name IN ('TED', 'cindy')"
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}}
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narrative_input: what's the best for TED and cindy?
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# JSON:
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{{
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"narrative_input": "what's the best for TED and cindy?",
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"llm_error_msg": "ambiguous narrative_input, not sure what 'best' means",
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"expression": ""
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}}
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narrative_input: what's the value?
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# JSON:
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{{
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"narrative_input": "what's the value?",
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"llm_error_msg": "ambiguous narrative_input, not sure what entity is being asked about",
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"expression": ""
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}}
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narrative_input: how many total pets do the three have?
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# JSON:
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{{
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"narrative_input": "how many total pets do the three have?",
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"llm_error_msg": "",
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"expression": "SELECT SUM(value) FROM df"
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}}
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narrative_input: {narrative_input}
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# JSON:
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""".strip()
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+ "\n\n\n"
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)
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# fmt: on
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