langchain/libs/community/tests/unit_tests/tools/test_few_shot.py
Christophe Bornet 6ddd5dbb1e
community: Add FewShotSQLTool (#28232)
The `FewShotSQLTool` gets some SQL query examples from a
`BaseExampleSelector` for a given question.
This is useful to provide [few-shot
examples](https://python.langchain.com/docs/how_to/sql_prompting/#few-shot-examples)
capability to an SQL agent.

Example usage:
```python
from langchain.agents.agent_toolkits.sql.prompt import SQL_PREFIX

embeddings = OpenAIEmbeddings()

example_selector = SemanticSimilarityExampleSelector.from_examples(
    examples,
    embeddings,
    AstraDB,
    k=5,
    input_keys=["input"],
    collection_name="lc_few_shots",
    token=ASTRA_DB_APPLICATION_TOKEN,
    api_endpoint=ASTRA_DB_API_ENDPOINT,
)

few_shot_sql_tool = FewShotSQLTool(
    example_selector=example_selector,
    description="Input to this tool is the input question, output is a few SQL query examples related to the input question. Always use this tool before checking the query with sql_db_query_checker!"
)

agent = create_sql_agent(
    llm=llm, 
    db=db, 
    prefix=SQL_PREFIX + "\nYou MUST get some example queries before creating the query.", 
    extra_tools=[few_shot_sql_tool]
)

result = agent.invoke({"input": "How many artists are there?"})
```

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-12-16 15:37:21 +00:00

64 lines
1.8 KiB
Python

from typing import Type
from langchain_core.embeddings.fake import DeterministicFakeEmbedding
from langchain_core.example_selectors import SemanticSimilarityExampleSelector
from langchain_core.vectorstores import InMemoryVectorStore
from langchain_tests.integration_tests import ToolsIntegrationTests
from langchain_tests.unit_tests import ToolsUnitTests
from langchain_community.tools.few_shot.tool import FewShotSQLTool
EXAMPLES = [
{
"input": "Number of rows in artist table",
"output": "select count(*) from Artist",
},
{
"input": "Number of rows in album table",
"output": "select count(*) from Album",
},
]
EMBEDDINGS = DeterministicFakeEmbedding(size=10)
EXAMPLE_SELECTOR = SemanticSimilarityExampleSelector.from_examples(
EXAMPLES,
EMBEDDINGS,
InMemoryVectorStore,
k=5,
input_keys=["input"],
)
class TestFewShotSQLToolUnit(ToolsUnitTests):
@property
def tool_constructor(self) -> Type[FewShotSQLTool]:
return FewShotSQLTool
@property
def tool_constructor_params(self) -> dict:
return {
"example_selector": EXAMPLE_SELECTOR,
"description": "Use this tool to select examples.",
}
@property
def tool_invoke_params_example(self) -> dict:
return {"question": "How many rows are in the customer table?"}
class TestFewShotSQLToolIntegration(ToolsIntegrationTests):
@property
def tool_constructor(self) -> Type[FewShotSQLTool]:
return FewShotSQLTool
@property
def tool_constructor_params(self) -> dict:
return {
"example_selector": EXAMPLE_SELECTOR,
"description": "Use this tool to select examples.",
}
@property
def tool_invoke_params_example(self) -> dict:
return {"question": "How many rows are in the customer table?"}