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=============
AI / LLM
=============

The AI module provides integration with large language models (LLMs) for tasks such as
classification, sentiment analysis, text extraction, translation, summarization, PII masking,
and embedding generation. Access these functions through the ``df.llm`` accessor on a
:class:`~pyflink.dataframe.DataFrame`.

Example:
::

    >>> import pyflink.dataframe as pf
    >>> pf.set_provider("openai", api_key="...", model="gpt-4o")
    >>> df = pf.from_dict({"text": ["Hello world", "Bonjour le monde"]})
    >>> df.llm.ai_translate("text", source_lang="auto", target_lang="en").collect()


Providers
---------

Register and manage LLM providers.

.. currentmodule:: pyflink.dataframe.ai.llm

.. autosummary::
    :toctree: api/

    set_provider
    set_default_provider
    list_providers


Provider
--------

Base class and built-in provider implementations.

.. currentmodule:: pyflink.dataframe.ai.providers

.. autosummary::
    :toctree: api/

    Provider
    OpenAICompatProvider
    DashScopeProvider
    TritonProvider
    GenericProvider


LLMAccessor
-----------

Accessed via the ``df.llm`` property on a :class:`~pyflink.dataframe.DataFrame`.
Provides methods for common AI tasks.

.. currentmodule:: pyflink.dataframe.ai.llm

.. autosummary::
    :toctree: api/

    LLMAccessor.predict
    LLMAccessor.ai_classify
    LLMAccessor.ai_sentiment
    LLMAccessor.ai_extract
    LLMAccessor.ai_translate
    LLMAccessor.ai_summarize
    LLMAccessor.ai_mask
    LLMAccessor.ai_embed