[Doc] Add more Python integrations documents (#299)

This commit is contained in:
Lei Xu
2023-07-13 17:09:39 -07:00
committed by GitHub
parent 0590413b96
commit 8c9edafccc
3 changed files with 85 additions and 6 deletions

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@@ -60,6 +60,9 @@ nav:
- Python integrations:
- Pandas and PyArrow: python/arrow.md
- DuckDB: python/duckdb.md
- LangChain 🦜️🔗: https://python.langchain.com/en/latest/modules/indexes/vectorstores/examples/lancedb.html
- LlamaIndex 🦙: https://gpt-index.readthedocs.io/en/latest/examples/vector_stores/LanceDBIndexDemo.html
- Pydantic: python/pydantic.md
- Python examples:
- YouTube Transcript Search: notebooks/youtube_transcript_search.ipynb
- Documentation QA Bot using LangChain: notebooks/code_qa_bot.ipynb

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@@ -0,0 +1,35 @@
# Pydantic
[Pydantic](https://docs.pydantic.dev/latest/) is a data validation library in Python.
## Schema
LanceDB supports to create Apache Arrow Schema from a
[Pydantic BaseModel](https://docs.pydantic.dev/latest/api/main/#pydantic.main.BaseModel)
via [pydantic_to_schema()](python.md##lancedb.pydantic.pydantic_to_schema) method.
::: lancedb.pydantic.pydantic_to_schema
## Vector Field
LanceDB provides a [`vector(dim)`](python.md#lancedb.pydantic.vector) method to define a
vector Field in a Pydantic Model.
::: lancedb.pydantic.vector
## Type Conversion
LanceDB automatically convert Pydantic fields to
[Apache Arrow DataType](https://arrow.apache.org/docs/python/generated/pyarrow.DataType.html#pyarrow.DataType).
Current supported type conversions:
| Pydantic Field Type | PyArrow Data Type |
| ------------------- | ----------------- |
| `int` | `pyarrow.int64` |
| `float` | `pyarrow.float64` |
| `bool` | `pyarrow.bool` |
| `str` | `pyarrow.utf8()` |
| `list` | `pyarrow.List` |
| `BaseModel` | `pyarrow.Struct` |
| `vector(n)` | `pyarrow.FixedSizeList(float32, n)` |

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@@ -41,9 +41,15 @@ def vector(
) -> Type[FixedSizeListMixin]:
"""Pydantic Vector Type.
Note
----
Experimental feature.
!!! warning
Experimental feature.
Parameters
----------
dim : int
The dimension of the vector.
value_type : pyarrow.DataType, optional
The value type of the vector, by default pa.float32()
Examples
--------
@@ -52,9 +58,15 @@ def vector(
>>> from lancedb.pydantic import vector
...
>>> class MyModel(pydantic.BaseModel):
... vector: vector(756)
... id: int
... description: str
... url: str
... embeddings: vector(768)
>>> schema = pydantic_to_schema(MyModel)
>>> assert schema == pa.schema([
... pa.field("id", pa.int64(), False),
... pa.field("url", pa.utf8(), False),
... pa.field("embeddings", pa.list_(pa.float32(), 768), False)
... ])
"""
# TODO: make a public parameterized type.
@@ -163,7 +175,36 @@ def pydantic_to_schema(model: Type[pydantic.BaseModel]) -> pa.Schema:
Returns
-------
A PyArrow Schema.
pyarrow.Schema
Examples
--------
>>> from typing import List, Optional
>>> import pydantic
>>> from lancedb.pydantic import pydantic_to_schema
...
>>> class InnerModel(pydantic.BaseModel):
... a: str
... b: Optional[float]
>>>
>>> class FooModel(pydantic.BaseModel):
... id: int
... s: Optional[str] = None
... vec: List[float]
... li: List[int]
... inner: InnerModel
>>> schema = pydantic_to_schema(FooModel)
>>> assert schema == pa.schema([
... pa.field("id", pa.int64(), False),
... pa.field("s", pa.utf8(), True),
... pa.field("vec", pa.list_(pa.float64()), False),
... pa.field("li", pa.list_(pa.int64()), False),
... pa.field("inner", pa.struct([
... pa.field("a", pa.utf8(), False),
... pa.field("b", pa.float64(), True),
... ]), False),
... ])
"""
fields = _pydantic_model_to_fields(model)
return pa.schema(fields)