langchain.utilities.scenexplain.SceneXplainAPIWrapper¶
class langchain.utilities.scenexplain.SceneXplainAPIWrapper[source]¶
Bases: BaseSettings, BaseModel
Wrapper for SceneXplain API.
In order to set this up, you need API key for the SceneXplain API.
You can obtain a key by following the steps below.
- Sign up for a free account at https://scenex.jina.ai/.
- Navigate to the API Access page (https://scenex.jina.ai/api)
and create a new API key.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param scenex_api_key: str [Required]¶
param scenex_api_url: str = 'https://api.scenex.jina.ai/v1/describe'¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating


the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶


run(image: str) → str[source]¶
Run SceneXplain image explainer.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶


langchain.utilities.max_compute.MaxComputeAPIWrapper¶
class langchain.utilities.max_compute.MaxComputeAPIWrapper(client: ODPS)[source]¶
Interface for querying Alibaba Cloud MaxCompute tables.
Initialize MaxCompute document loader.
Parameters
client – odps.ODPS MaxCompute client object.
Methods
__init__(client)
Initialize MaxCompute document loader.
from_params(endpoint, project, *[, ...])
Convenience constructor that builds the odsp.ODPS MaxCompute client from
lazy_query(query)
query(query)
__init__(client: ODPS)[source]¶
Initialize MaxCompute document loader.
Parameters
client – odps.ODPS MaxCompute client object.
classmethod from_params(endpoint: str, project: str, *, access_id: Optional[str] = None, secret_access_key: Optional[str] = None) → MaxComputeAPIWrapper[source]¶
Convenience constructor that builds the odsp.ODPS MaxCompute client fromgiven parameters.
Parameters
endpoint – MaxCompute endpoint.
project – A project is a basic organizational unit of MaxCompute, which is
similar to a database.
access_id – MaxCompute access ID. Should be passed in directly or set as the
environment variable MAX_COMPUTE_ACCESS_ID.
secret_access_key – MaxCompute secret access key. Should be passed in
directly or set as the environment variable
MAX_COMPUTE_SECRET_ACCESS_KEY.
lazy_query(query: str) → Iterator[dict][source]¶
query(query: str) → List[dict][source]¶


langchain.utilities.gitlab.GitLabAPIWrapper¶
class langchain.utilities.gitlab.GitLabAPIWrapper[source]¶
Bases: BaseModel
Wrapper for GitLab API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param gitlab_base_branch: Optional[str] = None¶
The base branch in the GitLab repository, used for comparisons.
Usually ‘main’ or ‘master’. Defaults to ‘main’.
param gitlab_branch: Optional[str] = None¶
The specific branch in the GitLab repository where the bot will make
its commits. Defaults to ‘main’.
param gitlab_personal_access_token: Optional[str] = None¶
Personal access token for the GitLab service, used for authentication.
param gitlab_repository: Optional[str] = None¶
The name of the GitLab repository, in the form {username}/{repo-name}.
comment_on_issue(comment_query: str) → str[source]¶
Adds a comment to a gitlab issue
Parameters:
comment_query(str): a string which contains the issue number,
two newlines, and the comment.
for example: “1
Working on it now”
adds the comment “working on it now” to issue 1
Returns:str: A success or failure message
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values


Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
create_file(file_query: str) → str[source]¶
Creates a new file on the gitlab repo
Parameters:
file_query(str): a string which contains the file path
and the file contents. The file path is the first line
in the string, and the contents are the rest of the string.
For example, “hello_world.md
# Hello World!”
Returns:str: A success or failure message
create_pull_request(pr_query: str) → str[source]¶
Makes a pull request from the bot’s branch to the base branch
Parameters:
pr_query(str): a string which contains the PR title
and the PR body. The title is the first line
in the string, and the body are the rest of the string.
For example, “Updated README
made changes to add info”
Returns:str: A success or failure message
delete_file(file_path: str) → str[source]¶
Deletes a file from the repo
:param file_path: Where the file is
:type file_path: str
Returns
Success or failure message


:type file_path: str
Returns
Success or failure message
Return type
str
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
get_issue(issue_number: int) → Dict[str, Any][source]¶
Fetches a specific issue and its first 10 comments
:param issue_number: The number for the gitlab issue
:type issue_number: int
Returns
A dictionary containing the issue’s title,
body, and comments as a string
Return type
dict
get_issues() → str[source]¶
Fetches all open issues from the repo
Returns
A plaintext report containing the number of issues
and each issue’s title and number.
Return type
str
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().


classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
parse_issues(issues: List[Issue]) → List[dict][source]¶
Extracts title and number from each Issue and puts them in a dictionary
:param issues: A list of gitlab Issue objects
:type issues: List[Issue]
Returns
A dictionary of issue titles and numbers
Return type
List[dict]
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
read_file(file_path: str) → str[source]¶
Reads a file from the gitlab repo
:param file_path: the file path
:type file_path: str
Returns
The file decoded as a string
Return type
str
run(mode: str, query: str) → str[source]¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
update_file(file_query: str) → str[source]¶
Updates a file with new content.
:param file_query: Contains the file path and the file contents.
The old file contents is wrapped in OLD <<<< and >>>> OLD
The new file contents is wrapped in NEW <<<< and >>>> NEW
For example:
test/hello.txt
OLD <<<<
Hello Earth!
>>>> OLD
NEW <<<<
Hello Mars!
>>>> NEW
Returns
A success or failure message


NEW <<<<
Hello Mars!
>>>> NEW
Returns
A success or failure message
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using GitLabAPIWrapper¶
Gitlab


langchain.utilities.powerbi.json_to_md¶
langchain.utilities.powerbi.json_to_md(json_contents: List[Dict[str, Union[str, int, float]]], table_name: Optional[str] = None) → str[source]¶
Converts a JSON object to a markdown table.


langchain.utilities.requests.RequestsWrapper¶
langchain.utilities.requests.RequestsWrapper¶
alias of TextRequestsWrapper
Examples using RequestsWrapper¶
OpenAPI


langchain.utilities.searchapi.SearchApiAPIWrapper¶
class langchain.utilities.searchapi.SearchApiAPIWrapper[source]¶
Bases: BaseModel
Wrapper around SearchApi API.
To use, you should have the environment variable SEARCHAPI_API_KEY
set with your API key, or pass searchapi_api_key
as a named parameter to the constructor.
Example
from langchain.utilities import SearchApiAPIWrapper
searchapi = SearchApiAPIWrapper()
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param aiosession: Optional[aiohttp.client.ClientSession] = None¶
param engine: str = 'google'¶
param searchapi_api_key: Optional[str] = None¶
async aresults(query: str, **kwargs: Any) → dict[source]¶
async arun(query: str, **kwargs: Any) → str[source]¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include


exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶


classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
results(query: str, **kwargs: Any) → dict[source]¶
run(query: str, **kwargs: Any) → str[source]¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶


langchain.utilities.jira.JiraAPIWrapper¶
class langchain.utilities.jira.JiraAPIWrapper[source]¶
Bases: BaseModel
Wrapper for Jira API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param confluence: Any = None¶
param jira_api_token: Optional[str] = None¶
param jira_instance_url: Optional[str] = None¶
param jira_username: Optional[str] = None¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
issue_create(query: str) → str[source]¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
other(query: str) → str[source]¶
page_create(query: str) → str[source]¶
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
parse_issues(issues: Dict) → List[dict][source]¶
classmethod parse_obj(obj: Any) → Model¶


classmethod parse_obj(obj: Any) → Model¶
parse_projects(projects: List[dict]) → List[dict][source]¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
project() → str[source]¶
run(mode: str, query: str) → str[source]¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
search(query: str) → str[source]¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using JiraAPIWrapper¶
Jira


langchain.utilities.openapi.OpenAPISpec¶
class langchain.utilities.openapi.OpenAPISpec[source]¶
OpenAPI Model that removes mis-formatted parts of the spec.
Attributes
base_url
Get the base url.
Methods
__init__()
from_file(path)
Get an OpenAPI spec from a file path.
from_spec_dict(spec_dict)
Get an OpenAPI spec from a dict.
from_text(text)
Get an OpenAPI spec from a text.
from_url(url)
Get an OpenAPI spec from a URL.
get_cleaned_operation_id(operation, path, method)
Get a cleaned operation id from an operation id.
get_methods_for_path(path)
Return a list of valid methods for the specified path.
get_operation(path, method)
Get the operation object for a given path and HTTP method.
get_parameters_for_operation(operation)
Get the components for a given operation.
get_parameters_for_path(path)
get_referenced_schema(ref)
Get a schema (or nested reference) or err.
get_request_body_for_operation(operation)
Get the request body for a given operation.
get_schema(schema)
parse_obj(obj)
__init__()¶
classmethod from_file(path: Union[str, Path]) → OpenAPISpec[source]¶
Get an OpenAPI spec from a file path.
classmethod from_spec_dict(spec_dict: dict) → OpenAPISpec[source]¶
Get an OpenAPI spec from a dict.
classmethod from_text(text: str) → OpenAPISpec[source]¶
Get an OpenAPI spec from a text.
classmethod from_url(url: str) → OpenAPISpec[source]¶
Get an OpenAPI spec from a URL.
static get_cleaned_operation_id(operation: Operation, path: str, method: str) → str[source]¶


Get a cleaned operation id from an operation id.
get_methods_for_path(path: str) → List[str][source]¶
Return a list of valid methods for the specified path.
get_operation(path: str, method: str) → Operation[source]¶
Get the operation object for a given path and HTTP method.
get_parameters_for_operation(operation: Operation) → List[Parameter][source]¶
Get the components for a given operation.
get_parameters_for_path(path: str) → List[Parameter][source]¶
get_referenced_schema(ref: Reference) → Schema[source]¶
Get a schema (or nested reference) or err.
get_request_body_for_operation(operation: Operation) → Optional[RequestBody][source]¶
Get the request body for a given operation.
get_schema(schema: Union[Reference, Schema]) → Schema[source]¶
classmethod parse_obj(obj: dict) → OpenAPISpec[source]¶
Examples using OpenAPISpec¶
Natural Language APIs


langchain.utilities.serpapi.SerpAPIWrapper¶
class langchain.utilities.serpapi.SerpAPIWrapper[source]¶
Bases: BaseModel
Wrapper around SerpAPI.
To use, you should have the google-search-results python package installed,
and the environment variable SERPAPI_API_KEY set with your API key, or pass
serpapi_api_key as a named parameter to the constructor.
Example
from langchain.utilities import SerpAPIWrapper
serpapi = SerpAPIWrapper()
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param aiosession: Optional[aiohttp.client.ClientSession] = None¶
param params: dict = {'engine': 'google', 'gl': 'us', 'google_domain': 'google.com', 'hl': 'en'}¶
param serpapi_api_key: Optional[str] = None¶
async aresults(query: str) → dict[source]¶
Use aiohttp to run query through SerpAPI and return the results async.
async arun(query: str, **kwargs: Any) → str[source]¶
Run query through SerpAPI and parse result async.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values


Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
get_params(query: str) → Dict[str, str][source]¶
Get parameters for SerpAPI.


Get parameters for SerpAPI.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
results(query: str) → dict[source]¶
Run query through SerpAPI and return the raw result.
run(query: str, **kwargs: Any) → str[source]¶
Run query through SerpAPI and parse result.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.


Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using SerpAPIWrapper¶
SerpAPI
Bittensor
AutoGPT


langchain.utilities.searx_search.SearxSearchWrapper¶
class langchain.utilities.searx_search.SearxSearchWrapper[source]¶
Bases: BaseModel
Wrapper for Searx API.
To use you need to provide the searx host by passing the named parameter
searx_host or exporting the environment variable SEARX_HOST.
In some situations you might want to disable SSL verification, for example
if you are running searx locally. You can do this by passing the named parameter
unsecure. You can also pass the host url scheme as http to disable SSL.
Example
from langchain.utilities import SearxSearchWrapper
searx = SearxSearchWrapper(searx_host="http://localhost:8888")
Example with SSL disabled:from langchain.utilities import SearxSearchWrapper
# note the unsecure parameter is not needed if you pass the url scheme as
# http
searx = SearxSearchWrapper(searx_host="http://localhost:8888",
                                        unsecure=True)
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param aiosession: Optional[Any] = None¶
param categories: Optional[List[str]] = []¶
param engines: Optional[List[str]] = []¶
param headers: Optional[dict] = None¶
param k: int = 10¶
param params: dict [Optional]¶
param query_suffix: Optional[str] = ''¶
param searx_host: str = ''¶
param unsecure: bool = False¶
async aresults(query: str, num_results: int, engines: Optional[List[str]] = None, query_suffix: Optional[str] = '', **kwargs: Any) → List[Dict][source]¶


Asynchronously query with json results.
Uses aiohttp. See results for more info.
async arun(query: str, engines: Optional[List[str]] = None, query_suffix: Optional[str] = '', **kwargs: Any) → str[source]¶
Asynchronously version of run.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.


Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
results(query: str, num_results: int, engines: Optional[List[str]] = None, categories: Optional[List[str]] = None, query_suffix: Optional[str] = '', **kwargs: Any) → List[Dict][source]¶
Run query through Searx API and returns the results with metadata.
Parameters
query – The query to search for.
query_suffix – Extra suffix appended to the query.
num_results – Limit the number of results to return.
engines – List of engines to use for the query.
categories – List of categories to use for the query.


categories – List of categories to use for the query.
**kwargs – extra parameters to pass to the searx API.
Returns
{snippet:  The description of the result.
title:  The title of the result.
link: The link to the result.
engines: The engines used for the result.
category: Searx category of the result.
}
Return type
Dict with the following keys
run(query: str, engines: Optional[List[str]] = None, categories: Optional[List[str]] = None, query_suffix: Optional[str] = '', **kwargs: Any) → str[source]¶
Run query through Searx API and parse results.
You can pass any other params to the searx query API.
Parameters
query – The query to search for.
query_suffix – Extra suffix appended to the query.
engines – List of engines to use for the query.
categories – List of categories to use for the query.
**kwargs – extra parameters to pass to the searx API.
Returns
The result of the query.
Return type
str
Raises
ValueError – If an error occurred with the query.
Example
This will make a query to the qwant engine:
from langchain.utilities import SearxSearchWrapper
searx = SearxSearchWrapper(searx_host="http://my.searx.host")
searx.run("what is the weather in France ?", engine="qwant")
# the same result can be achieved using the `!` syntax of searx
# to select the engine using `query_suffix`
searx.run("what is the weather in France ?", query_suffix="!qwant")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶


classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using SearxSearchWrapper¶
SearxNG Search
SearxNG Search API


langchain.utilities.duckduckgo_search.DuckDuckGoSearchAPIWrapper¶
class langchain.utilities.duckduckgo_search.DuckDuckGoSearchAPIWrapper[source]¶
Bases: BaseModel
Wrapper for DuckDuckGo Search API.
Free and does not require any setup.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param max_results: int = 5¶
param region: Optional[str] = 'wt-wt'¶
param safesearch: str = 'moderate'¶
param time: Optional[str] = 'y'¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
get_snippets(query: str) → List[str][source]¶
Run query through DuckDuckGo and return concatenated results.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶


classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
results(query: str, num_results: int, backend: str = 'api') → List[Dict[str, str]][source]¶
Run query through DuckDuckGo and return metadata.
Parameters
query – The query to search for.
num_results – The number of results to return.
Returns
snippet - The description of the result.
title - The title of the result.
link - The link to the result.
Return type
A list of dictionaries with the following keys
run(query: str) → str[source]¶
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using DuckDuckGoSearchAPIWrapper¶
DuckDuckGo Search


langchain.utilities.powerbi.PowerBIDataset¶
class langchain.utilities.powerbi.PowerBIDataset[source]¶
Bases: BaseModel
Create PowerBI engine from dataset ID and credential or token.
Use either the credential or a supplied token to authenticate.
If both are supplied the credential is used to generate a token.
The impersonated_user_name is the UPN of a user to be impersonated.
If the model is not RLS enabled, this will be ignored.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param aiosession: Optional[aiohttp.ClientSession] = None¶
param credential: Optional[TokenCredential] = None¶
param dataset_id: str [Required]¶
param group_id: Optional[str] = None¶
param impersonated_user_name: Optional[str] = None¶
param sample_rows_in_table_info: int = 1¶
Constraints
exclusiveMinimum = 0
maximum = 10
param schemas: Dict[str, str] [Optional]¶
param table_names: List[str] [Required]¶
param token: Optional[str] = None¶
async aget_table_info(table_names: Optional[Union[str, List[str]]] = None) → str[source]¶
Get information about specified tables.
async arun(command: str) → Any[source]¶
Execute a DAX command and return the result asynchronously.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values


Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
get_schemas() → str[source]¶
Get the available schema’s.
get_table_info(table_names: Optional[Union[str, List[str]]] = None) → str[source]¶
Get information about specified tables.
get_table_names() → Iterable[str][source]¶
Get names of tables available.


get_table_names() → Iterable[str][source]¶
Get names of tables available.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(command: str) → Any[source]¶
Execute a DAX command and return a json representing the results.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶


classmethod validate(value: Any) → Model¶
property headers: Dict[str, str]¶
Get the token.
property request_url: str¶
Get the request url.
property table_info: str¶
Information about all tables in the database.
Examples using PowerBIDataset¶
PowerBI Dataset


langchain.utilities.python.PythonREPL¶
class langchain.utilities.python.PythonREPL[source]¶
Bases: BaseModel
Simulates a standalone Python REPL.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param globals: Optional[Dict] [Optional] (alias '_globals')¶
param locals: Optional[Dict] [Optional] (alias '_locals')¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(command: str, timeout: Optional[int] = None) → str[source]¶


run(command: str, timeout: Optional[int] = None) → str[source]¶
Run command with own globals/locals and returns anything printed.
Timeout after the specified number of seconds.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
classmethod worker(command: str, globals: Optional[Dict], locals: Optional[Dict], queue: Queue) → None[source]¶
Examples using PythonREPL¶
Dynamodb Chat Message History
Python
Code writing


langchain.utilities.pubmed.PubMedAPIWrapper¶
class langchain.utilities.pubmed.PubMedAPIWrapper[source]¶
Bases: BaseModel
Wrapper around PubMed API.
This wrapper will use the PubMed API to conduct searches and fetch
document summaries. By default, it will return the document summaries
of the top-k results of an input search.
Parameters
top_k_results – number of the top-scored document used for the PubMed tool
MAX_QUERY_LENGTH – maximum length of the query.
Default is 300 characters.
doc_content_chars_max – maximum length of the document content.
Content will be truncated if it exceeds this length.
Default is 2000 characters.
max_retry – maximum number of retries for a request. Default is 5.
sleep_time – time to wait between retries.
Default is 0.2 seconds.
email – email address to be used for the PubMed API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param MAX_QUERY_LENGTH: int = 300¶
param base_url_efetch: str = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?'¶
param base_url_esearch: str = 'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?'¶
param doc_content_chars_max: int = 2000¶
param email: str = 'your_email@example.com'¶
param max_retry: int = 5¶
param sleep_time: float = 0.2¶
param top_k_results: int = 3¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.


Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶


classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
lazy_load(query: str) → Iterator[dict][source]¶
Search PubMed for documents matching the query.
Return an iterator of dictionaries containing the document metadata.
lazy_load_docs(query: str) → Iterator[Document][source]¶
load(query: str) → List[dict][source]¶
Search PubMed for documents matching the query.
Return a list of dictionaries containing the document metadata.
load_docs(query: str) → List[Document][source]¶
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
retrieve_article(uid: str, webenv: str) → dict[source]¶
run(query: str) → str[source]¶
Run PubMed search and get the article meta information.


Run PubMed search and get the article meta information.
See https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapter4.ESearch
It uses only the most informative fields of article meta information.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶


langchain.utilities.vertexai.raise_vertex_import_error¶
langchain.utilities.vertexai.raise_vertex_import_error(minimum_expected_version: str = '1.33.0') → None[source]¶
Raise ImportError related to Vertex SDK being not available.
Parameters
minimum_expected_version – The lowest expected version of the SDK.
Raises
ImportError – an ImportError that mentions a required version of the SDK.


langchain.utilities.metaphor_search.MetaphorSearchAPIWrapper¶
class langchain.utilities.metaphor_search.MetaphorSearchAPIWrapper[source]¶
Bases: BaseModel
Wrapper for Metaphor Search API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param k: int = 10¶
param metaphor_api_key: str [Required]¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶


results(query: str, num_results: int, include_domains: Optional[List[str]] = None, exclude_domains: Optional[List[str]] = None, start_crawl_date: Optional[str] = None, end_crawl_date: Optional[str] = None, start_published_date: Optional[str] = None, end_published_date: Optional[str] = None, use_autoprompt: Optional[bool] = None) → List[Dict][source]¶
Run query through Metaphor Search and return metadata.
Parameters
query – The query to search for.
num_results – The number of results to return.
include_domains – A list of domains to include in the search. Only one of include_domains and exclude_domains should be defined.
exclude_domains – A list of domains to exclude from the search. Only one of include_domains and exclude_domains should be defined.
start_crawl_date – If specified, only pages we crawled after start_crawl_date will be returned.
end_crawl_date – If specified, only pages we crawled before end_crawl_date will be returned.
start_published_date – If specified, only pages published after start_published_date will be returned.
end_published_date – If specified, only pages published before end_published_date will be returned.
use_autoprompt – If true, we turn your query into a more Metaphor-friendly query. Adds latency.
Returns
title - The title of the page
url - The url
author - Author of the content, if applicable. Otherwise, None.
published_date - Estimated date published
in YYYY-MM-DD format. Otherwise, None.
Return type
A list of dictionaries with the following keys


Return type
A list of dictionaries with the following keys
async results_async(query: str, num_results: int, include_domains: Optional[List[str]] = None, exclude_domains: Optional[List[str]] = None, start_crawl_date: Optional[str] = None, end_crawl_date: Optional[str] = None, start_published_date: Optional[str] = None, end_published_date: Optional[str] = None, use_autoprompt: Optional[bool] = None) → List[Dict][source]¶
Get results from the Metaphor Search API asynchronously.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using MetaphorSearchAPIWrapper¶
Metaphor Search


langchain.utilities.openapi.HTTPVerb¶
class langchain.utilities.openapi.HTTPVerb(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Enumerator of the HTTP verbs.
GET = 'get'¶
PUT = 'put'¶
POST = 'post'¶
DELETE = 'delete'¶
OPTIONS = 'options'¶
HEAD = 'head'¶
PATCH = 'patch'¶
TRACE = 'trace'¶


langchain.utilities.redis.get_client¶
langchain.utilities.redis.get_client(redis_url: str, **kwargs: Any) → RedisType[source]¶
Get a redis client from the connection url given. This helper accepts
urls for Redis server (TCP with/without TLS or UnixSocket) as well as
Redis Sentinel connections.
Redis Cluster is not supported.
Before creating a connection the existence of the database driver is checked
an and ValueError raised otherwise
To use, you should have the redis python package installed.
Example
from langchain.utilities.redis import get_client
redis_client = get_client(
    redis_url="redis://username:password@localhost:6379"
    index_name="my-index",
    embedding_function=embeddings.embed_query,
)
To use a redis replication setup with multiple redis server and redis sentinels
set “redis_url” to “redis+sentinel://” scheme. With this url format a path is
needed holding the name of the redis service within the sentinels to get the
correct redis server connection. The default service name is “mymaster”. The
optional second part of the path is the redis db number to connect to.
An optional username or password is used for booth connections to the rediserver
and the sentinel, different passwords for server and sentinel are not supported.
And as another constraint only one sentinel instance can be given:
Example
from langchain.utilities.redis import get_client
redis_client = get_client(
    redis_url="redis+sentinel://username:password@sentinelhost:26379/mymaster/0"
    index_name="my-index",
    embedding_function=embeddings.embed_query,
)


langchain.utilities.dalle_image_generator.DallEAPIWrapper¶
class langchain.utilities.dalle_image_generator.DallEAPIWrapper[source]¶
Bases: BaseModel
Wrapper for OpenAI’s DALL-E Image Generator.
Docs for using:
1. pip install openai
2. save your OPENAI_API_KEY in an environment variable
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param n: int = 1¶
size of image to generate
param openai_api_key: Optional[str] = None¶
number of images to generate
param size: str = '1024x1024'¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(query: str) → str[source]¶


run(query: str) → str[source]¶
Run query through OpenAI and parse result.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using DallEAPIWrapper¶
Dall-E Image Generator


langchain.utilities.google_search.GoogleSearchAPIWrapper¶
class langchain.utilities.google_search.GoogleSearchAPIWrapper[source]¶
Bases: BaseModel
Wrapper for Google Search API.
Adapted from: Instructions adapted from https://stackoverflow.com/questions/
37083058/
programmatically-searching-google-in-python-using-custom-search
TODO: DOCS for using it
1. Install google-api-python-client
- If you don’t already have a Google account, sign up.
- If you have never created a Google APIs Console project,
read the Managing Projects page and create a project in the Google API Console.
- Install the library using pip install google-api-python-client
2. Enable the Custom Search API
- Navigate to the APIs & Services→Dashboard panel in Cloud Console.
- Click Enable APIs and Services.
- Search for Custom Search API and click on it.
- Click Enable.
URL for it: https://console.cloud.google.com/apis/library/customsearch.googleapis
.com
3. To create an API key:
- Navigate to the APIs & Services → Credentials panel in Cloud Console.
- Select Create credentials, then select API key from the drop-down menu.
- The API key created dialog box displays your newly created key.
- You now have an API_KEY
Alternatively, you can just generate an API key here:
https://developers.google.com/custom-search/docs/paid_element#api_key
4. Setup Custom Search Engine so you can search the entire web
- Create a custom search engine here: https://programmablesearchengine.google.com/.
- In What to search to search, pick the Search the entire Web option.
After search engine is created, you can click on it and find Search engine ID
on the Overview page.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.


Raises ValidationError if the input data cannot be parsed to form a valid model.
param google_api_key: Optional[str] = None¶
param google_cse_id: Optional[str] = None¶
param k: int = 10¶
param siterestrict: bool = False¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.


Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
results(query: str, num_results: int, search_params: Optional[Dict[str, str]] = None) → List[Dict][source]¶
Run query through GoogleSearch and return metadata.
Parameters
query – The query to search for.
num_results – The number of results to return.
search_params – Parameters to be passed on search
Returns
snippet - The description of the result.
title - The title of the result.
link - The link to the result.
Return type
A list of dictionaries with the following keys


Return type
A list of dictionaries with the following keys
run(query: str) → str[source]¶
Run query through GoogleSearch and parse result.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using GoogleSearchAPIWrapper¶
Google Search
Bittensor
Set env var OPENAI_API_KEY or load from a .env file:
Agents
WebResearchRetriever
Message Memory in Agent backed by a database
Memory in Agent
Shared memory across agents and tools


langchain.utilities.redis.check_redis_module_exist¶
langchain.utilities.redis.check_redis_module_exist(client: RedisType, required_modules: List[dict]) → None[source]¶
Check if the correct Redis modules are installed.


langchain.utilities.opaqueprompts.desanitize¶
langchain.utilities.opaqueprompts.desanitize(sanitized_text: str, secure_context: bytes) → str[source]¶
Restore the original sensitive data from the sanitized text.
Parameters
sanitized_text – Sanitized text.
secure_context – Secure context returned by the sanitize function.
Returns
De-sanitized text.


langchain.utilities.openweathermap.OpenWeatherMapAPIWrapper¶
class langchain.utilities.openweathermap.OpenWeatherMapAPIWrapper[source]¶
Bases: BaseModel
Wrapper for OpenWeatherMap API using PyOWM.
Docs for using:
Go to OpenWeatherMap and sign up for an API key
Save your API KEY into OPENWEATHERMAP_API_KEY env variable
pip install pyowm
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param openweathermap_api_key: Optional[str] = None¶
param owm: Any = None¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(location: str) → str[source]¶


run(location: str) → str[source]¶
Get the current weather information for a specified location.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using OpenWeatherMapAPIWrapper¶
OpenWeatherMap


langchain.utilities.bing_search.BingSearchAPIWrapper¶
class langchain.utilities.bing_search.BingSearchAPIWrapper[source]¶
Bases: BaseModel
Wrapper for Bing Search API.
In order to set this up, follow instructions at:
https://levelup.gitconnected.com/api-tutorial-how-to-use-bing-web-search-api-in-python-4165d5592a7e
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param bing_search_url: str [Required]¶
param bing_subscription_key: str [Required]¶
param k: int = 10¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
results(query: str, num_results: int) → List[Dict][source]¶


results(query: str, num_results: int) → List[Dict][source]¶
Run query through BingSearch and return metadata.
Parameters
query – The query to search for.
num_results – The number of results to return.
Returns
snippet - The description of the result.
title - The title of the result.
link - The link to the result.
Return type
A list of dictionaries with the following keys
run(query: str) → str[source]¶
Run query through BingSearch and parse result.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using BingSearchAPIWrapper¶
Bing Search


langchain.utilities.alpha_vantage.AlphaVantageAPIWrapper¶
class langchain.utilities.alpha_vantage.AlphaVantageAPIWrapper[source]¶
Bases: BaseModel
Wrapper for AlphaVantage API for Currency Exchange Rate.
Docs for using:
Go to AlphaVantage and sign up for an API key
Save your API KEY into ALPHAVANTAGE_API_KEY env variable
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param alphavantage_api_key: Optional[str] = None¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance


deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(from_currency: str, to_currency: str) → str[source]¶


run(from_currency: str, to_currency: str) → str[source]¶
Get the current exchange rate for a specified currency pair.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
property standard_currencies: List[str]¶
Examples using AlphaVantageAPIWrapper¶
Alpha Vantage


langchain.utilities.google_serper.GoogleSerperAPIWrapper¶
class langchain.utilities.google_serper.GoogleSerperAPIWrapper[source]¶
Bases: BaseModel
Wrapper around the Serper.dev Google Search API.
You can create a free API key at https://serper.dev.
To use, you should have the environment variable SERPER_API_KEY
set with your API key, or pass serper_api_key as a named parameter
to the constructor.
Example
from langchain.utilities import GoogleSerperAPIWrapper
google_serper = GoogleSerperAPIWrapper()
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param aiosession: Optional[aiohttp.client.ClientSession] = None¶
param gl: str = 'us'¶
param hl: str = 'en'¶
param k: int = 10¶
param serper_api_key: Optional[str] = None¶
param tbs: Optional[str] = None¶
param type: Literal['news', 'search', 'places', 'images'] = 'search'¶
async aresults(query: str, **kwargs: Any) → Dict[source]¶
Run query through GoogleSearch.
async arun(query: str, **kwargs: Any) → str[source]¶
Run query through GoogleSearch and parse result async.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values


Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶


classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
results(query: str, **kwargs: Any) → Dict[source]¶
Run query through GoogleSearch.
run(query: str, **kwargs: Any) → str[source]¶
Run query through GoogleSearch and parse result.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.


Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using GoogleSerperAPIWrapper¶
Google Serper
Retrieve as you generate with FLARE


langchain.utilities.google_places_api.GooglePlacesAPIWrapper¶
class langchain.utilities.google_places_api.GooglePlacesAPIWrapper[source]¶
Bases: BaseModel
Wrapper around Google Places API.
To use, you should have the googlemaps python package installed,an API key for the google maps platform,
and the environment variable ‘’GPLACES_API_KEY’’
set with your API key , or pass ‘gplaces_api_key’
as a named parameter to the constructor.
By default, this will return the all the results on the input query.You can use the top_k_results argument to limit the number of results.
Example
from langchain.utilities import GooglePlacesAPIWrapper
gplaceapi = GooglePlacesAPIWrapper()
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param gplaces_api_key: Optional[str] = None¶
param top_k_results: Optional[int] = None¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include


exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
fetch_place_details(place_id: str) → Optional[str][source]¶
format_place_details(place_details: Dict[str, Any]) → Optional[str][source]¶
classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().


classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(query: str) → str[source]¶
Run Places search and get k number of places that exists that match.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶


langchain.utilities.twilio.TwilioAPIWrapper¶
class langchain.utilities.twilio.TwilioAPIWrapper[source]¶
Bases: BaseModel
Messaging Client using Twilio.
To use, you should have the twilio python package installed,
and the environment variables TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN, and
TWILIO_FROM_NUMBER, or pass account_sid, auth_token, and from_number as
named parameters to the constructor.
Example
from langchain.utilities.twilio import TwilioAPIWrapper
twilio = TwilioAPIWrapper(
    account_sid="ACxxx",
    auth_token="xxx",
    from_number="+10123456789"
)
twilio.run('test', '+12484345508')
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param account_sid: Optional[str] = None¶
Twilio account string identifier.
param auth_token: Optional[str] = None¶
Twilio auth token.
param from_number: Optional[str] = None¶
A Twilio phone number in [E.164](https://www.twilio.com/docs/glossary/what-e164)
format, an
[alphanumeric sender ID](https://www.twilio.com/docs/sms/send-messages#use-an-alphanumeric-sender-id),
or a [Channel Endpoint address](https://www.twilio.com/docs/sms/channels#channel-addresses)
that is enabled for the type of message you want to send. Phone numbers or
[short codes](https://www.twilio.com/docs/sms/api/short-code) purchased from
Twilio also work here. You cannot, for example, spoof messages from a private
cell phone number. If you are using messaging_service_sid, this parameter
must be empty.


cell phone number. If you are using messaging_service_sid, this parameter
must be empty.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → DictStrAny¶
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶


classmethod from_orm(obj: Any) → Model¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Callable[[Any], Any]] = None, models_as_dict: bool = True, **dumps_kwargs: Any) → unicode¶
Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
run(body: str, to: str) → str[source]¶
Run body through Twilio and respond with message sid.
Parameters
body – The text of the message you want to send. Can be up to 1,600
characters in length.
to – The destination phone number in
[E.164](https://www.twilio.com/docs/glossary/what-e164) format for
SMS/MMS or
[Channel user address](https://www.twilio.com/docs/sms/channels#channel-addresses)
for other 3rd-party channels.


for other 3rd-party channels.
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
Examples using TwilioAPIWrapper¶
Twilio


langchain.utilities.sql_database.SQLDatabase¶
class langchain.utilities.sql_database.SQLDatabase(engine: Engine, schema: Optional[str] = None, metadata: Optional[MetaData] = None, ignore_tables: Optional[List[str]] = None, include_tables: Optional[List[str]] = None, sample_rows_in_table_info: int = 3, indexes_in_table_info: bool = False, custom_table_info: Optional[dict] = None, view_support: bool = False, max_string_length: int = 300)[source]¶
SQLAlchemy wrapper around a database.
Create engine from database URI.
Attributes
dialect
Return string representation of dialect to use.
table_info
Information about all tables in the database.
Methods
__init__(engine[, schema, metadata, ...])
Create engine from database URI.
from_cnosdb([url, user, password, tenant, ...])
Class method to create an SQLDatabase instance from a CnosDB connection.
from_databricks(catalog, schema[, host, ...])
Class method to create an SQLDatabase instance from a Databricks connection.
from_uri(database_uri[, engine_args])
Construct a SQLAlchemy engine from URI.
get_table_info([table_names])
Get information about specified tables.
get_table_info_no_throw([table_names])
Get information about specified tables.
get_table_names()
Get names of tables available.
get_usable_table_names()
Get names of tables available.
run(command[, fetch])
Execute a SQL command and return a string representing the results.
run_no_throw(command[, fetch])
Execute a SQL command and return a string representing the results.


Execute a SQL command and return a string representing the results.
__init__(engine: Engine, schema: Optional[str] = None, metadata: Optional[MetaData] = None, ignore_tables: Optional[List[str]] = None, include_tables: Optional[List[str]] = None, sample_rows_in_table_info: int = 3, indexes_in_table_info: bool = False, custom_table_info: Optional[dict] = None, view_support: bool = False, max_string_length: int = 300)[source]¶
Create engine from database URI.
classmethod from_cnosdb(url: str = '127.0.0.1:8902', user: str = 'root', password: str = '', tenant: str = 'cnosdb', database: str = 'public') → SQLDatabase[source]¶
Class method to create an SQLDatabase instance from a CnosDB connection.
This method requires the ‘cnos-connector’ package. If not installed, it
can be added using pip install cnos-connector.
Parameters
url (str) – The HTTP connection host name and port number of the CnosDB
service, excluding “http://” or “https://”, with a default value
of “127.0.0.1:8902”.
user (str) – The username used to connect to the CnosDB service, with a
default value of “root”.
password (str) – The password of the user connecting to the CnosDB service,
with a default value of “”.
tenant (str) – The name of the tenant used to connect to the CnosDB service,
with a default value of “cnosdb”.
database (str) – The name of the database in the CnosDB tenant.
Returns
An instance of SQLDatabase configured with the provided
CnosDB connection details.
Return type
SQLDatabase


CnosDB connection details.
Return type
SQLDatabase
classmethod from_databricks(catalog: str, schema: str, host: Optional[str] = None, api_token: Optional[str] = None, warehouse_id: Optional[str] = None, cluster_id: Optional[str] = None, engine_args: Optional[dict] = None, **kwargs: Any) → SQLDatabase[source]¶
Class method to create an SQLDatabase instance from a Databricks connection.
This method requires the ‘databricks-sql-connector’ package. If not installed,
it can be added using pip install databricks-sql-connector.
Parameters
catalog (str) – The catalog name in the Databricks database.
schema (str) – The schema name in the catalog.
host (Optional[str]) – The Databricks workspace hostname, excluding
‘https://’ part. If not provided, it attempts to fetch from the
environment variable ‘DATABRICKS_HOST’. If still unavailable and if
running in a Databricks notebook, it defaults to the current workspace
hostname. Defaults to None.
api_token (Optional[str]) – The Databricks personal access token for
accessing the Databricks SQL warehouse or the cluster. If not provided,
it attempts to fetch from ‘DATABRICKS_TOKEN’. If still unavailable
and running in a Databricks notebook, a temporary token for the current
user is generated. Defaults to None.
warehouse_id (Optional[str]) – The warehouse ID in the Databricks SQL. If
provided, the method configures the connection to use this warehouse.
Cannot be used with ‘cluster_id’. Defaults to None.
cluster_id (Optional[str]) – The cluster ID in the Databricks Runtime. If
provided, the method configures the connection to use this cluster.


provided, the method configures the connection to use this cluster.
Cannot be used with ‘warehouse_id’. If running in a Databricks notebook
and both ‘warehouse_id’ and ‘cluster_id’ are None, it uses the ID of the
cluster the notebook is attached to. Defaults to None.
engine_args (Optional[dict]) – The arguments to be used when connecting
Databricks. Defaults to None.
**kwargs (Any) – Additional keyword arguments for the from_uri method.
Returns
An instance of SQLDatabase configured with the providedDatabricks connection details.
Return type
SQLDatabase
Raises
ValueError – If ‘databricks-sql-connector’ is not found, or if both
    ‘warehouse_id’ and ‘cluster_id’ are provided, or if neither
    ‘warehouse_id’ nor ‘cluster_id’ are provided and it’s not executing
    inside a Databricks notebook.
classmethod from_uri(database_uri: str, engine_args: Optional[dict] = None, **kwargs: Any) → SQLDatabase[source]¶
Construct a SQLAlchemy engine from URI.
get_table_info(table_names: Optional[List[str]] = None) → str[source]¶
Get information about specified tables.
Follows best practices as specified in: Rajkumar et al, 2022
(https://arxiv.org/abs/2204.00498)
If sample_rows_in_table_info, the specified number of sample rows will be
appended to each table description. This can increase performance as
demonstrated in the paper.
get_table_info_no_throw(table_names: Optional[List[str]] = None) → str[source]¶
Get information about specified tables.
Follows best practices as specified in: Rajkumar et al, 2022
(https://arxiv.org/abs/2204.00498)