Tony20100/langchain_full huggingface dataset:
langchain_community.agent_toolkits.openapi.toolkit.OpenAPIToolkit¶
class langchain_community.agent_toolkits.openapi.toolkit.OpenAPIToolkit[source]¶
Bases: BaseToolkit
Toolkit for interacting with an OpenAPI API.
Security Note: This toolkit contains tools that can read and modifythe state of a service; e.g., by creating, deleting, or updating,
reading underlying data.
For example, this toolkit can be used to delete data exposed via
an OpenAPI compliant 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 allow_dangerous_requests: bool = False¶
Allow dangerous requests. See documentation for details.
param json_agent: Any = None¶
param requests_wrapper: TextRequestsWrapper [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
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
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.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
Return type
DictStrAny
classmethod from_llm(llm: BaseLanguageModel, json_spec: JsonSpec, requests_wrapper: TextRequestsWrapper, allow_dangerous_requests: bool = False, **kwargs: Any) → OpenAPIToolkit[source]¶
Create json agent from llm, then initialize.
Parameters
llm (BaseLanguageModel) – 
json_spec (JsonSpec) – 
requests_wrapper (TextRequestsWrapper) – 
allow_dangerous_requests (bool) –
allow_dangerous_requests (bool) – 
kwargs (Any) – 
Return type
OpenAPIToolkit
classmethod from_orm(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
get_tools() → List[BaseTool][source]¶
Get the tools in the toolkit.
Return type
List[BaseTool]
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().
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
encoder (Optional[Callable[[Any], Any]]) – 
models_as_dict (bool) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
Parameters
path (Union[str, Path]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod parse_obj(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using OpenAPIToolkit¶
OpenAPI
langchain_community.agent_toolkits.github.toolkit.CommentOnIssue¶
class langchain_community.agent_toolkits.github.toolkit.CommentOnIssue[source]¶
Bases: BaseModel
Schema for operations that require a comment as input.
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 input: str [Required]¶
Follow the required formatting.
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
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
langchain_community.agent_toolkits.jira.toolkit.JiraToolkit¶
class langchain_community.agent_toolkits.jira.toolkit.JiraToolkit[source]¶
Bases: BaseToolkit
Jira Toolkit.
Security Note: This toolkit contains tools that can read and modifythe state of a service; e.g., by creating, deleting, or updating,
reading underlying data.
See https://python.langchain.com/docs/security for more information.
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 tools: List[BaseTool] = []¶
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
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
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.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
Return type
DictStrAny
classmethod from_jira_api_wrapper(jira_api_wrapper: JiraAPIWrapper) → JiraToolkit[source]¶
Parameters
jira_api_wrapper (JiraAPIWrapper) – 
Return type
JiraToolkit
classmethod from_orm(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
get_tools() → List[BaseTool][source]¶
Get the tools in the toolkit.
Return type
List[BaseTool]
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using JiraToolkit¶
Jira
langchain_community.agent_toolkits.github.toolkit.SearchCode¶
class langchain_community.agent_toolkits.github.toolkit.SearchCode[source]¶
Bases: BaseModel
Schema for operations that require a search query as input.
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 search_query: str [Required]¶
A keyword-focused natural language searchquery for code, e.g. MyFunctionName().
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
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
langchain_community.agent_toolkits.github.toolkit.GitHubToolkit¶
class langchain_community.agent_toolkits.github.toolkit.GitHubToolkit[source]¶
Bases: BaseToolkit
GitHub Toolkit.
Security Note: This toolkit contains tools that can read and modifythe state of a service; e.g., by creating, deleting, or updating,
reading underlying data.
For example, this toolkit can be used to create issues, pull requests,
and comments on GitHub.
See [Security](https://python.langchain.com/docs/security) for more information.
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 tools: List[BaseTool] = []¶
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
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
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.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
Return type
DictStrAny
classmethod from_github_api_wrapper(github_api_wrapper: GitHubAPIWrapper) → GitHubToolkit[source]¶
Parameters
github_api_wrapper (GitHubAPIWrapper) – 
Return type
GitHubToolkit
classmethod from_orm(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
get_tools() → List[BaseTool][source]¶
Get the tools in the toolkit.
Return type
List[BaseTool]
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using GitHubToolkit¶
Github
langchain_community.agent_toolkits.azure_ai_services.AzureAiServicesToolkit¶
class langchain_community.agent_toolkits.azure_ai_services.AzureAiServicesToolkit[source]¶
Bases: BaseToolkit
Toolkit for Azure AI Services.
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.
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
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using AzureAiServicesToolkit¶
Azure AI Services
langchain_community.agent_toolkits.openapi.planner.RequestsGetToolWithParsing¶
class langchain_community.agent_toolkits.openapi.planner.RequestsGetToolWithParsing[source]¶
Bases: BaseRequestsTool, BaseTool
Requests GET tool with LLM-instructed extraction of truncated responses.
Initialize the tool.
param allow_dangerous_requests: bool = False¶
param args_schema: Optional[Type[BaseModel]] = None¶
Pydantic model class to validate and parse the tool’s input arguments.
param callback_manager: Optional[BaseCallbackManager] = None¶
Deprecated. Please use callbacks instead.
param callbacks: Callbacks = None¶
Callbacks to be called during tool execution.
param description: str = 'Use this to GET content from a website.\nInput to the tool should be a json string with 3 keys: "url", "params" and "output_instructions".\nThe value of "url" should be a string. \nThe value of "params" should be a dict of the needed and available parameters from the OpenAPI spec related to the endpoint. \nIf parameters are not needed, or not available, leave it empty.\nThe value of "output_instructions" should be instructions on what information to extract from the response, \nfor example the id(s) for a resource(s) that the GET request fetches.\n'¶
Tool description.
param handle_tool_error: Optional[Union[bool, str, Callable[[ToolException], str]]] = False¶
Handle the content of the ToolException thrown.
param handle_validation_error: Optional[Union[bool, str, Callable[[ValidationError], str]]] = False¶
Handle the content of the ValidationError thrown.
param llm_chain: Any [Optional]¶
LLMChain used to extract the response.
param metadata: Optional[Dict[str, Any]] = None¶
langchain_community.agent_toolkits.github.toolkit.DirectoryPath¶
class langchain_community.agent_toolkits.github.toolkit.DirectoryPath[source]¶
Bases: BaseModel
Schema for operations that require a directory path as input.
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 input: str = ''¶
The path of the directory, e.g. some_dir/inner_dir. Only input a string, do not include the parameter name.
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
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
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 (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data