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Box

BoxSearchToolSpec #

Bases: BaseToolSpec

Provides functionalities for searching Box resources.

This class allows you to search for Box resources based on various criteria specified using the BoxSearchOptions class. It utilizes the Box API search functionality and returns a list of Document objects containing information about the found resources.

Attributes:

Name Type Description
spec_functions list

A list of supported functions (always "box_search").
_box_client BoxClient

An instance of BoxClient for interacting with Box API.
_options BoxSearchOptions

An instance of BoxSearchOptions containing search options.

Methods:

Name Description
box_search

str) -> List[Document]: Performs a search for Box resources based on the provided query and configured search options. Returns a list of Document objects representing the found resources.
Source code in llama_index/tools/box/search/base.py 
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class BoxSearchToolSpec(BaseToolSpec):
    """
    Provides functionalities for searching Box resources.

    This class allows you to search for Box resources based on various criteria
    specified using the `BoxSearchOptions` class. It utilizes the Box API search
    functionality and returns a list of `Document` objects containing information
    about the found resources.

    Attributes:
        spec_functions (list): A list of supported functions (always "box_search").
        _box_client (BoxClient): An instance of BoxClient for interacting with Box API.
        _options (BoxSearchOptions): An instance of BoxSearchOptions containing search options.

    Methods:
        box_search(query: str) -> List[Document]:
            Performs a search for Box resources based on the provided query and configured
            search options. Returns a list of `Document` objects representing the found resources.

    """

    spec_functions = ["box_search"]

    _box_client: BoxClient
    _options: BoxSearchOptions

    def __init__(
        self, box_client: BoxClient, options: BoxSearchOptions = BoxSearchOptions()
    ) -> None:
        """
        Initializes a `BoxSearchToolSpec` instance.

        Args:
            box_client (BoxClient): An authenticated Box API client.
            options (BoxSearchOptions, optional): An instance of `BoxSearchOptions` containing search options.
                Defaults to `BoxSearchOptions()`.

        """
        self._box_client = add_extra_header_to_box_client(box_client)
        self._options = options

    def box_search(
        self,
        query: str,
    ) -> List[Document]:
        """
        Searches for Box resources based on the provided query and configured search options.

        This method utilizes the Box API search functionality to find resources matching the provided
        query and search options specified in the `BoxSearchOptions` object. It returns a list of
        `Document` objects containing information about the found resources.

        Args:
            query (str): The search query to use for searching Box resources.

        Returns:
            List[Document]: A list of `Document` objects representing the found Box resources.

        """
        box_check_connection(self._box_client)

        box_files = search_files(
            box_client=self._box_client,
            query=query,
            scope=self._options.scope,
            file_extensions=self._options.file_extensions,
            created_at_range=self._options.created_at_range,
            updated_at_range=self._options.updated_at_range,
            size_range=self._options.size_range,
            owner_user_ids=self._options.owner_user_ids,
            recent_updater_user_ids=self._options.recent_updater_user_ids,
            ancestor_folder_ids=self._options.ancestor_folder_ids,
            content_types=self._options.content_types,
            limit=self._options.limit,
            offset=self._options.offset,
        )

        box_files = get_box_files_details(
            box_client=self._box_client, file_ids=[file.id for file in box_files]
        )

        docs: List[Document] = []

        for file in box_files:
            doc = box_file_to_llama_document(file)
            docs.append(doc)

        return docs

box_search(query: str) -> List[Document]

Searches for Box resources based on the provided query and configured search options.

This method utilizes the Box API search functionality to find resources matching the provided query and search options specified in the BoxSearchOptions object. It returns a list of Document objects containing information about the found resources.

Parameters:

Name Type Description Default
query str

The search query to use for searching Box resources.

 required

Returns:

Type Description
List[Document]

List[Document]: A list of Document objects representing the found Box resources.
Source code in llama_index/tools/box/search/base.py 
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def box_search(
    self,
    query: str,
) -> List[Document]:
    """
    Searches for Box resources based on the provided query and configured search options.

    This method utilizes the Box API search functionality to find resources matching the provided
    query and search options specified in the `BoxSearchOptions` object. It returns a list of
    `Document` objects containing information about the found resources.

    Args:
        query (str): The search query to use for searching Box resources.

    Returns:
        List[Document]: A list of `Document` objects representing the found Box resources.

    """
    box_check_connection(self._box_client)

    box_files = search_files(
        box_client=self._box_client,
        query=query,
        scope=self._options.scope,
        file_extensions=self._options.file_extensions,
        created_at_range=self._options.created_at_range,
        updated_at_range=self._options.updated_at_range,
        size_range=self._options.size_range,
        owner_user_ids=self._options.owner_user_ids,
        recent_updater_user_ids=self._options.recent_updater_user_ids,
        ancestor_folder_ids=self._options.ancestor_folder_ids,
        content_types=self._options.content_types,
        limit=self._options.limit,
        offset=self._options.offset,
    )

    box_files = get_box_files_details(
        box_client=self._box_client, file_ids=[file.id for file in box_files]
    )

    docs: List[Document] = []

    for file in box_files:
        doc = box_file_to_llama_document(file)
        docs.append(doc)

    return docs

BoxSearchOptions #

Represents options for searching Box resources.

This class provides a way to specify various criteria for filtering search results when using the BoxSearchToolSpec class. You can define parameters like search scope, file extensions, date ranges (created/updated at), size range, owner IDs, and more to refine your search.

Attributes:

Name Type Description
scope Optional[SearchForContentScope]

The scope of the search (e.g., all content, trashed content).
file_extensions Optional[List[str]]

A list of file extensions to filter by.
created_at_range Optional[List[str]]

A list representing a date range for file creation time (format: YYYY-MM-DD).
updated_at_range Optional[List[str]]

A list representing a date range for file update time (format: YYYY-MM-DD).
size_range Optional[List[int]]

A list representing a range for file size (in bytes).
owner_user_ids Optional[List[str]]

A list of user IDs to filter by owner.
recent_updater_user_ids Optional[List[str]]

A list of user IDs to filter by recent updater.
ancestor_folder_ids Optional[List[str]]

A list of folder IDs to search within.
content_types Optional[List[SearchForContentContentTypes]]

A list of content types to filter by.
limit Optional[int]

The maximum number of search results to return.
offset Optional[int]

The offset to start results from (for pagination).
Source code in llama_index/tools/box/search/base.py 
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class BoxSearchOptions:
    """
    Represents options for searching Box resources.

    This class provides a way to specify various criteria for filtering search results
    when using the `BoxSearchToolSpec` class. You can define parameters like search
    scope, file extensions, date ranges (created/updated at), size range, owner IDs,
    and more to refine your search.

    Attributes:
        scope (Optional[SearchForContentScope]): The scope of the search (e.g., all
            content, trashed content).
        file_extensions (Optional[List[str]]): A list of file extensions to filter by.
        created_at_range (Optional[List[str]]): A list representing a date range for
            file creation time (format: YYYY-MM-DD).
        updated_at_range (Optional[List[str]]): A list representing a date range for
            file update time (format: YYYY-MM-DD).
        size_range (Optional[List[int]]): A list representing a range for file size (in bytes).
        owner_user_ids (Optional[List[str]]): A list of user IDs to filter by owner.
        recent_updater_user_ids (Optional[List[str]]): A list of user IDs to filter by
            recent updater.
        ancestor_folder_ids (Optional[List[str]]): A list of folder IDs to search within.
        content_types (Optional[List[SearchForContentContentTypes]]): A list of content
            types to filter by.
        limit (Optional[int]): The maximum number of search results to return.
        offset (Optional[int]): The offset to start results from (for pagination).

    """

    scope: Optional[SearchForContentScope] = None
    file_extensions: Optional[List[str]] = None
    created_at_range: Optional[List[str]] = None
    updated_at_range: Optional[List[str]] = None
    size_range: Optional[List[int]] = None
    owner_user_ids: Optional[List[str]] = None
    recent_updater_user_ids: Optional[List[str]] = None
    ancestor_folder_ids: Optional[List[str]] = None
    content_types: Optional[List[SearchForContentContentTypes]] = None
    limit: Optional[int] = None
    offset: Optional[int] = None

    def __init__(
        self,
        scope: Optional[SearchForContentScope] = None,
        file_extensions: Optional[List[str]] = None,
        created_at_range: Optional[List[str]] = None,
        updated_at_range: Optional[List[str]] = None,
        size_range: Optional[List[int]] = None,
        owner_user_ids: Optional[List[str]] = None,
        recent_updater_user_ids: Optional[List[str]] = None,
        ancestor_folder_ids: Optional[List[str]] = None,
        content_types: Optional[List[SearchForContentContentTypes]] = None,
        limit: Optional[int] = None,
        offset: Optional[int] = None,
    ) -> None:
        self.scope = scope
        self.file_extensions = file_extensions
        self.created_at_range = created_at_range
        self.updated_at_range = updated_at_range
        self.size_range = size_range
        self.owner_user_ids = owner_user_ids
        self.recent_updater_user_ids = recent_updater_user_ids
        self.ancestor_folder_ids = ancestor_folder_ids
        self.content_types = content_types
        self.limit = limit
        self.offset = offset

BoxSearchByMetadataToolSpec #

Bases: BaseToolSpec

Provides functionalities for searching Box resources based on metadata.

This class allows you to search for Box resources based on metadata specified using the BoxSearchByMetadataOptions class. It utilizes the Box API search functionality and returns a list of Document objects containing information about the found resources.

Attributes:

Name Type Description
spec_functions list

A list of supported functions (always "search").
_box_client BoxClient

An instance of BoxClient for interacting with Box API.
_options BoxSearchByMetadataOptions

An instance of BoxSearchByMetadataOptions containing search options.

Methods:

Name Description
search

Optional[str] = None) -> List[Document]: Performs a search for Box resources based on the configured metadata options and optional query parameters. Returns a list of Document objects representing the found resources.
Source code in llama_index/tools/box/search_by_metadata/base.py 
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class BoxSearchByMetadataToolSpec(BaseToolSpec):
    """
    Provides functionalities for searching Box resources based on metadata.

    This class allows you to search for Box resources based on metadata specified
    using the `BoxSearchByMetadataOptions` class. It utilizes the Box API search
    functionality and returns a list of `Document` objects containing information
    about the found resources.

    Attributes:
        spec_functions (list): A list of supported functions (always "search").
        _box_client (BoxClient): An instance of BoxClient for interacting with Box API.
        _options (BoxSearchByMetadataOptions): An instance of BoxSearchByMetadataOptions
            containing search options.

    Methods:
        search(query_params: Optional[str] = None) -> List[Document]:
            Performs a search for Box resources based on the configured metadata options
            and optional query parameters. Returns a list of `Document` objects representing
            the found resources.

    """

    spec_functions = ["search"]

    _box_client: BoxClient
    _options: BoxSearchByMetadataOptions

    def __init__(
        self, box_client: BoxClient, options: BoxSearchByMetadataOptions
    ) -> None:
        """
        Initializes a `BoxSearchByMetadataToolSpec` instance.

        Args:
            box_client (BoxClient): An authenticated Box API client.
            options (BoxSearchByMetadataToolSpec, optional): An instance of `BoxSearchByMetadataToolSpec` containing search options.
                Defaults to `BoxSearchByMetadataToolSpec()`.

        """
        self._box_client = add_extra_header_to_box_client(box_client)
        self._options = options

    def search(
        self,
        query_params: Optional[str] = None,
    ) -> List[Document]:
        """
        Searches for Box resources based on metadata and returns a list of documents.

        This method leverages the configured metadata options (`self._options`) to
        search for Box resources. It converts the provided JSON string (`query_params`)
        into a dictionary and uses it to refine the search based on additional
        metadata criteria. It retrieves matching Box files and then converts them
        into `Document` objects containing relevant information.

        Args:
            query_params (Optional[str]): An optional JSON string representing additional
                query parameters for filtering by metadata.

        Returns:
            List[Document]: A list of `Document` objects representing the found Box resources.

        """
        box_check_connection(self._box_client)

        # Box API accepts a dictionary of query parameters as a string, so we need to
        # convert the provided JSON string to a dictionary.
        params_dict = json.loads(query_params)

        box_files = search_files_by_metadata(
            box_client=self._box_client,
            from_=self._options.from_,
            ancestor_folder_id=self._options.ancestor_folder_id,
            query=self._options.query,
            query_params=params_dict,
            limit=self._options.limit,
        )

        box_files = get_box_files_details(
            box_client=self._box_client, file_ids=[file.id for file in box_files]
        )

        docs: List[Document] = []

        for file in box_files:
            doc = box_file_to_llama_document(file)
            docs.append(doc)

        return docs

search #

search(query_params: Optional[str] = None) -> List[Document]

Searches for Box resources based on metadata and returns a list of documents.

This method leverages the configured metadata options (self._options) to search for Box resources. It converts the provided JSON string (query_params) into a dictionary and uses it to refine the search based on additional metadata criteria. It retrieves matching Box files and then converts them into Document objects containing relevant information.

Parameters:

Name Type Description Default
query_params Optional[str]

An optional JSON string representing additional query parameters for filtering by metadata.

 None

Returns:

Type Description
List[Document]

List[Document]: A list of Document objects representing the found Box resources.
Source code in llama_index/tools/box/search_by_metadata/base.py 
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def search(
    self,
    query_params: Optional[str] = None,
) -> List[Document]:
    """
    Searches for Box resources based on metadata and returns a list of documents.

    This method leverages the configured metadata options (`self._options`) to
    search for Box resources. It converts the provided JSON string (`query_params`)
    into a dictionary and uses it to refine the search based on additional
    metadata criteria. It retrieves matching Box files and then converts them
    into `Document` objects containing relevant information.

    Args:
        query_params (Optional[str]): An optional JSON string representing additional
            query parameters for filtering by metadata.

    Returns:
        List[Document]: A list of `Document` objects representing the found Box resources.

    """
    box_check_connection(self._box_client)

    # Box API accepts a dictionary of query parameters as a string, so we need to
    # convert the provided JSON string to a dictionary.
    params_dict = json.loads(query_params)

    box_files = search_files_by_metadata(
        box_client=self._box_client,
        from_=self._options.from_,
        ancestor_folder_id=self._options.ancestor_folder_id,
        query=self._options.query,
        query_params=params_dict,
        limit=self._options.limit,
    )

    box_files = get_box_files_details(
        box_client=self._box_client, file_ids=[file.id for file in box_files]
    )

    docs: List[Document] = []

    for file in box_files:
        doc = box_file_to_llama_document(file)
        docs.append(doc)

    return docs

BoxSearchByMetadataOptions #

Represents options for searching Box resources based on metadata.

This class provides a way to specify parameters for searching Box resources using metadata. You can define the starting point for the search (from_), the ancestor folder ID to search within (ancestor_folder_id), an optional search query (query), and a limit on the number of returned results (limit).

Attributes:

Name Type Description
from_ str

The starting point for the search, such as "folder" or "file".
ancestor_folder_id str

The ID of the ancestor folder to search within.
query Optional[str]

An optional search query string to refine the search based on metadata.
limit Optional[int]

The maximum number of search results to return.
Source code in llama_index/tools/box/search_by_metadata/base.py 
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class BoxSearchByMetadataOptions:
    """
    Represents options for searching Box resources based on metadata.

    This class provides a way to specify parameters for searching Box resources
    using metadata. You can define the starting point for the search (`from_`), the
    ancestor folder ID to search within (`ancestor_folder_id`), an optional search
    query (`query`), and a limit on the number of returned results (`limit`).

    Attributes:
        from_ (str): The starting point for the search, such as "folder" or "file".
        ancestor_folder_id (str): The ID of the ancestor folder to search within.
        query (Optional[str]): An optional search query string to refine the search
            based on metadata.
        limit (Optional[int]): The maximum number of search results to return.

    """

    from_: str
    ancestor_folder_id: str
    query: Optional[str] = (None,)
    limit: Optional[int] = None

    def __init__(
        self,
        from_: str,
        ancestor_folder_id: str,
        query: Optional[str] = None,
        limit: Optional[int] = None,
    ) -> None:
        self.from_ = from_
        self.ancestor_folder_id = ancestor_folder_id
        self.query = query
        self.limit = limit

BoxTextExtractToolSpec #

Bases: BaseToolSpec

Box Text Extraction Tool Specification.

This class provides a specification for extracting text content from Box files and creating Document objects. It leverages the Box API to retrieve the text representation (if available) of specified Box files.

Attributes:

Name Type Description
_box_client BoxClient

An instance of the Box client for interacting with the Box API.
Source code in llama_index/tools/box/text_extract/base.py 
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class BoxTextExtractToolSpec(BaseToolSpec):
    """
    Box Text Extraction Tool Specification.

    This class provides a specification for extracting text content from Box files
    and creating Document objects. It leverages the Box API to retrieve the
    text representation (if available) of specified Box files.

    Attributes:
        _box_client (BoxClient): An instance of the Box client for interacting
            with the Box API.

    """

    spec_functions = ["extract"]
    _box_client: BoxClient

    def __init__(self, box_client: BoxClient) -> None:
        """
        Initializes the Box Text Extraction Tool Specification with the
        provided Box client instance.

        Args:
            box_client (BoxClient): The Box client instance.

        """
        self._box_client = add_extra_header_to_box_client(box_client)

    def extract(
        self,
        file_id: str,
    ) -> Document:
        """
        Extracts text content from Box files and creates Document objects.

        This method utilizes the Box API to retrieve the text representation
        (if available) of the specified Box files. It then creates Document
        objects containing the extracted text and file metadata.

        Args:
            file_id (str): A of Box file ID
                to extract text from.

        Returns:
            List[Document]: A list of Document objects containing the extracted
                text content and file metadata.

        """
        # Connect to Box
        box_check_connection(self._box_client)

        # get payload information
        box_file = get_box_files_details(
            box_client=self._box_client, file_ids=[file_id]
        )[0]

        box_file = get_text_representation(
            box_client=self._box_client,
            box_files=[box_file],
        )[0]

        doc = box_file_to_llama_document(box_file)
        doc.text = box_file.text_representation if box_file.text_representation else ""
        return doc

extract #

extract(file_id: str) -> Document

Extracts text content from Box files and creates Document objects.

This method utilizes the Box API to retrieve the text representation (if available) of the specified Box files. It then creates Document objects containing the extracted text and file metadata.

Parameters:

Name Type Description Default
file_id str

A of Box file ID to extract text from.

 required

Returns:

Type Description
Document

List[Document]: A list of Document objects containing the extracted text content and file metadata.
Source code in llama_index/tools/box/text_extract/base.py 
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def extract(
    self,
    file_id: str,
) -> Document:
    """
    Extracts text content from Box files and creates Document objects.

    This method utilizes the Box API to retrieve the text representation
    (if available) of the specified Box files. It then creates Document
    objects containing the extracted text and file metadata.

    Args:
        file_id (str): A of Box file ID
            to extract text from.

    Returns:
        List[Document]: A list of Document objects containing the extracted
            text content and file metadata.

    """
    # Connect to Box
    box_check_connection(self._box_client)

    # get payload information
    box_file = get_box_files_details(
        box_client=self._box_client, file_ids=[file_id]
    )[0]

    box_file = get_text_representation(
        box_client=self._box_client,
        box_files=[box_file],
    )[0]

    doc = box_file_to_llama_document(box_file)
    doc.text = box_file.text_representation if box_file.text_representation else ""
    return doc

BoxAIPromptToolSpec #

Bases: BaseToolSpec

Generates AI prompts based on a Box file.

Parameters:

Name Type Description Default
box_client BoxClient

A BoxClient instance for interacting with Box API.

 required

Attributes:

Name Type Description
spec_functions list

A list of supported functions.
_box_client BoxClient

An instance of BoxClient for interacting with Box API.

Methods:

Name Description
ai_prompt

Generates an AI prompt based on a Box file.

Parameters:

Name Type Description Default
file_id str

The ID of the Box file.

 required
ai_prompt str

The base AI prompt to use.

 required

Returns:

Name Type Description
Document

A Document object containing the generated AI prompt.
Source code in llama_index/tools/box/ai_prompt/base.py 
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class BoxAIPromptToolSpec(BaseToolSpec):
    """
    Generates AI prompts based on a Box file.

    Args:
        box_client (BoxClient): A BoxClient instance for interacting with Box API.

    Attributes:
        spec_functions (list): A list of supported functions.
        _box_client (BoxClient): An instance of BoxClient for interacting with Box API.

    Methods:
        ai_prompt(file_id, ai_prompt): Generates an AI prompt based on a Box file.

    Args:
        file_id (str): The ID of the Box file.
        ai_prompt (str): The base AI prompt to use.

    Returns:
        Document: A Document object containing the generated AI prompt.

    """

    spec_functions = ["ai_prompt"]

    _box_client: BoxClient

    def __init__(self, box_client: BoxClient) -> None:
        """
        Initializes the BoxAIPromptToolSpec with a BoxClient instance.

        Args:
            box_client (BoxClient): The BoxClient instance to use for interacting with the Box API.

        """
        self._box_client = add_extra_header_to_box_client(box_client)

    def ai_prompt(
        self,
        file_id: str,
        ai_prompt: str,
    ) -> Document:
        """
        Generates an AI prompt based on a Box file.

        Retrieves the specified Box file, constructs an AI prompt using the provided base prompt,
        and returns a Document object containing the generated prompt and file metadata.

        Args:
            file_id (str): The ID of the Box file to process.
            ai_prompt (str): The base AI prompt to use as a template.

        Returns:
            Document: A Document object containing the generated AI prompt and file metadata.

        """
        # Connect to Box
        box_check_connection(self._box_client)

        # get box files information
        box_file = get_box_files_details(
            box_client=self._box_client, file_ids=[file_id]
        )[0]

        box_file = get_ai_response_from_box_files(
            box_client=self._box_client,
            box_files=[box_file],
            ai_prompt=ai_prompt,
        )[0]

        doc = box_file_to_llama_document(box_file)
        doc.text = box_file.ai_response if box_file.ai_response else ""
        doc.metadata["ai_prompt"] = box_file.ai_prompt
        doc.metadata["ai_response"] = (
            box_file.ai_response if box_file.ai_response else ""
        )

        return doc

ai_prompt #

ai_prompt(file_id: str, ai_prompt: str) -> Document

Generates an AI prompt based on a Box file.

Retrieves the specified Box file, constructs an AI prompt using the provided base prompt, and returns a Document object containing the generated prompt and file metadata.

Parameters:

Name Type Description Default
file_id str

The ID of the Box file to process.

 required
ai_prompt str

The base AI prompt to use as a template.

 required

Returns:

Name Type Description
Document Document

A Document object containing the generated AI prompt and file metadata.
Source code in llama_index/tools/box/ai_prompt/base.py 
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def ai_prompt(
    self,
    file_id: str,
    ai_prompt: str,
) -> Document:
    """
    Generates an AI prompt based on a Box file.

    Retrieves the specified Box file, constructs an AI prompt using the provided base prompt,
    and returns a Document object containing the generated prompt and file metadata.

    Args:
        file_id (str): The ID of the Box file to process.
        ai_prompt (str): The base AI prompt to use as a template.

    Returns:
        Document: A Document object containing the generated AI prompt and file metadata.

    """
    # Connect to Box
    box_check_connection(self._box_client)

    # get box files information
    box_file = get_box_files_details(
        box_client=self._box_client, file_ids=[file_id]
    )[0]

    box_file = get_ai_response_from_box_files(
        box_client=self._box_client,
        box_files=[box_file],
        ai_prompt=ai_prompt,
    )[0]

    doc = box_file_to_llama_document(box_file)
    doc.text = box_file.ai_response if box_file.ai_response else ""
    doc.metadata["ai_prompt"] = box_file.ai_prompt
    doc.metadata["ai_response"] = (
        box_file.ai_response if box_file.ai_response else ""
    )

    return doc

BoxAIExtractToolSpec #

Bases: BaseToolSpec

Extracts AI generated content from a Box file.

Parameters:

Name Type Description Default
box_client BoxClient

A BoxClient instance for interacting with Box API.

 required

Attributes:

Name Type Description
spec_functions list

A list of supported functions.
_box_client BoxClient

An instance of BoxClient for interacting with Box API.

Methods:

Name Description
ai_extract

Extracts AI generated content from a Box file.

Parameters:

Name Type Description Default
file_id str

The ID of the Box file.

 required
ai_prompt str

The AI prompt to use for extraction.

 required

Returns:

Name Type Description
Document

A Document object containing the extracted AI content.
Source code in llama_index/tools/box/ai_extract/base.py 
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class BoxAIExtractToolSpec(BaseToolSpec):
    """
    Extracts AI generated content from a Box file.

    Args:
        box_client (BoxClient): A BoxClient instance for interacting with Box API.

    Attributes:
        spec_functions (list): A list of supported functions.
        _box_client (BoxClient): An instance of BoxClient for interacting with Box API.

    Methods:
        ai_extract(file_id, ai_prompt): Extracts AI generated content from a Box file.

    Args:
        file_id (str): The ID of the Box file.
        ai_prompt (str): The AI prompt to use for extraction.

    Returns:
        Document: A Document object containing the extracted AI content.

    """

    spec_functions = ["ai_extract"]

    _box_client: BoxClient

    def __init__(self, box_client: BoxClient) -> None:
        """
        Initializes the BoxAIExtractToolSpec with a BoxClient instance.

        Args:
            box_client (BoxClient): The BoxClient instance to use for interacting with the Box API.

        """
        self._box_client = add_extra_header_to_box_client(box_client)

    def ai_extract(
        self,
        file_id: str,
        ai_prompt: str,
    ) -> Document:
        """
        Extracts AI generated content from a Box file using the provided AI prompt.

        Args:
            file_id (str): The ID of the Box file to process.
            ai_prompt (str): The AI prompt to use for content extraction.

        Returns:
            Document: A Document object containing the extracted AI content,
            including metadata about the original Box file.

        """
        # Connect to Box
        box_check_connection(self._box_client)

        # get payload information
        box_file = get_box_files_details(
            box_client=self._box_client, file_ids=[file_id]
        )[0]

        box_file = get_files_ai_extract_data(
            box_client=self._box_client,
            box_files=[box_file],
            ai_prompt=ai_prompt,
        )[0]

        doc = box_file_to_llama_document(box_file)
        doc.text = box_file.ai_response if box_file.ai_response else ""
        doc.metadata["ai_prompt"] = box_file.ai_prompt
        doc.metadata["ai_response"] = box_file.ai_response

        return doc

ai_extract #

ai_extract(file_id: str, ai_prompt: str) -> Document

Extracts AI generated content from a Box file using the provided AI prompt.

Parameters:

Name Type Description Default
file_id str

The ID of the Box file to process.

 required
ai_prompt str

The AI prompt to use for content extraction.

 required

Returns:

Name Type Description
Document Document

A Document object containing the extracted AI content,
Document

including metadata about the original Box file.
Source code in llama_index/tools/box/ai_extract/base.py 
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def ai_extract(
    self,
    file_id: str,
    ai_prompt: str,
) -> Document:
    """
    Extracts AI generated content from a Box file using the provided AI prompt.

    Args:
        file_id (str): The ID of the Box file to process.
        ai_prompt (str): The AI prompt to use for content extraction.

    Returns:
        Document: A Document object containing the extracted AI content,
        including metadata about the original Box file.

    """
    # Connect to Box
    box_check_connection(self._box_client)

    # get payload information
    box_file = get_box_files_details(
        box_client=self._box_client, file_ids=[file_id]
    )[0]

    box_file = get_files_ai_extract_data(
        box_client=self._box_client,
        box_files=[box_file],
        ai_prompt=ai_prompt,
    )[0]

    doc = box_file_to_llama_document(box_file)
    doc.text = box_file.ai_response if box_file.ai_response else ""
    doc.metadata["ai_prompt"] = box_file.ai_prompt
    doc.metadata["ai_response"] = box_file.ai_response

    return doc

options: members: - BoxAIExtractToolSpec - BoxAIPromptToolSpec - BoxSearchByMetadataToolSpec - BoxSearchToolSpec - BoxTextExtractToolSpec