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Upload a block to a signed URL and return the public URL. langchain.tools.render¶ Different methods for rendering Tools to be passed to LLMs. Depending on the LLM you are using and the prompting strategy you are using, you may want Tools to be rendered in a different way. This module contains various ways to render too...
lang/api.python.langchain.com/en/latest/api_reference.html
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Wrapper around ArxivAPI. utilities.awslambda.LambdaWrapper Wrapper for AWS Lambda SDK. utilities.bibtex.BibtexparserWrapper Wrapper around bibtexparser. utilities.bing_search.BingSearchAPIWrapper Wrapper for Bing Search API. utilities.brave_search.BraveSearchWrapper Wrapper around the Brave search engine. utilities.cli...
lang/api.python.langchain.com/en/latest/api_reference.html
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Wrapper around the Serper.dev Google Search API. utilities.graphql.GraphQLAPIWrapper Wrapper around GraphQL API. utilities.jira.JiraAPIWrapper Wrapper for Jira API. utilities.max_compute.MaxComputeAPIWrapper(client) Interface for querying Alibaba Cloud MaxCompute tables. utilities.metaphor_search.MetaphorSearchAPIWrapp...
lang/api.python.langchain.com/en/latest/api_reference.html
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SparkSQL is a utility class for interacting with Spark SQL. utilities.sql_database.SQLDatabase(engine[, ...]) SQLAlchemy wrapper around a database. utilities.tavily_search.TavilySearchAPIWrapper Wrapper for Tavily Search API. utilities.tensorflow_datasets.TensorflowDatasets Access to the TensorFlow Datasets. utilities....
lang/api.python.langchain.com/en/latest/api_reference.html
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utilities.opaqueprompts.sanitize(input) Sanitize input string or dict of strings by replacing sensitive data with placeholders. utilities.powerbi.fix_table_name(table) Add single quotes around table names that contain spaces. utilities.powerbi.json_to_md(json_contents) Converts a JSON object to a markdown table. utilit...
lang/api.python.langchain.com/en/latest/api_reference.html
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Functions¶ utils.aiter.py_anext(iterator[, default]) Pure-Python implementation of anext() for testing purposes. utils.aiter.tee_peer(iterator, buffer, ...) An individual iterator of a tee() utils.env.get_from_dict_or_env(data, key, ...) Get a value from a dictionary or an environment variable. utils.env.get_from_env(k...
lang/api.python.langchain.com/en/latest/api_reference.html
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utils.openai_functions.convert_pydantic_to_openai_function(...) Converts a Pydantic model to a function description for the OpenAI API. utils.openai_functions.convert_pydantic_to_openai_tool(...) Converts a Pydantic model to a function description for the OpenAI API. utils.pydantic.get_pydantic_major_version() Get the ...
lang/api.python.langchain.com/en/latest/api_reference.html
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BaseRetriever --> VectorStoreRetriever --> <name>Retriever # Example: VespaRetriever Main helpers: Embeddings, Document Classes¶ vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearch(...) Alibaba Cloud OpenSearch vector store. vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearchSettings(...) Alibaba Cloud...
lang/api.python.langchain.com/en/latest/api_reference.html
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vectorstores.chroma.Chroma([...]) ChromaDB vector store. vectorstores.clarifai.Clarifai([user_id, ...]) Clarifai AI vector store. vectorstores.clickhouse.Clickhouse(embedding) ClickHouse VectorSearch vector store. vectorstores.clickhouse.ClickhouseSettings ClickHouse client configuration. vectorstores.dashvector.DashVe...
lang/api.python.langchain.com/en/latest/api_reference.html
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Wrapper around Epsilla vector database. vectorstores.faiss.FAISS(embedding_function, ...) Meta Faiss vector store. vectorstores.hippo.Hippo(embedding_function) Hippo vector store. vectorstores.hologres.Hologres(...[, ndims, ...]) Hologres API vector store. vectorstores.hologres.HologresWrapper(...) Hologres API wrapper...
lang/api.python.langchain.com/en/latest/api_reference.html
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vectorstores.nucliadb.NucliaDB(...[, ...]) NucliaDB vector store. vectorstores.opensearch_vector_search.OpenSearchVectorSearch(...) Amazon OpenSearch Vector Engine vector store. vectorstores.pgembedding.BaseModel(**kwargs) Base model for all SQL stores. vectorstores.pgembedding.CollectionStore(...) Collection store. ve...
lang/api.python.langchain.com/en/latest/api_reference.html
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vectorstores.redis.filters.RedisNum(field) A RedisFilterField representing a numeric field in a Redis index. vectorstores.redis.filters.RedisTag(field) A RedisFilterField representing a tag in a Redis index. vectorstores.redis.filters.RedisText(field) A RedisFilterField representing a text field in a Redis index. vecto...
lang/api.python.langchain.com/en/latest/api_reference.html
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vectorstores.sklearn.SKLearnVectorStore(...) Simple in-memory vector store based on the scikit-learn library NearestNeighbors implementation. vectorstores.sklearn.SKLearnVectorStoreException Exception raised by SKLearnVectorStore. vectorstores.sqlitevss.SQLiteVSS(table, ...) Wrapper around SQLite with vss extension as ...
lang/api.python.langchain.com/en/latest/api_reference.html
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Initialize vearch vector store flag 1 for cluster,0 for standalone vectorstores.vectara.Vectara([...]) Vectara API vector store. vectorstores.vectara.VectaraRetriever Retriever class for Vectara. vectorstores.vespa.VespaStore(app[, ...]) Vespa vector store. vectorstores.weaviate.Weaviate(client, ...) Weaviate vector st...
lang/api.python.langchain.com/en/latest/api_reference.html
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Check if Redis index exists. vectorstores.redis.filters.check_operator_misuse(func) Decorator to check for misuse of equality operators. vectorstores.redis.schema.read_schema(...) Reads in the index schema from a dict or yaml file. vectorstores.scann.dependable_scann_import() Import scann if available, otherwise raise ...
lang/api.python.langchain.com/en/latest/api_reference.html
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langchain_experimental API Reference¶ langchain_experimental.agents¶ Functions¶ agents.agent_toolkits.csv.base.create_csv_agent(...) Create csv agent by loading to a dataframe and using pandas agent. agents.agent_toolkits.pandas.base.create_pandas_dataframe_agent(llm, df) Construct a pandas agent from an LLM and datafr...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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autonomous_agents.baby_agi.task_prioritization.TaskPrioritizationChain Chain to prioritize tasks. autonomous_agents.hugginggpt.hugginggpt.HuggingGPT(...) autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerationChain Chain to execute tasks. autonomous_agents.hugginggpt.repsonse_generator.ResponseGenerator(...)...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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an interface where “chat messages” are the inputs and outputs. Class hierarchy: BaseLanguageModel --> BaseChatModel --> <name> # Examples: ChatOpenAI, ChatGooglePalm Main helpers: AIMessage, BaseMessage, HumanMessage Classes¶ chat_models.llm_wrapper.ChatWrapper Create a new model by parsing and validating input data f...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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comprehend_moderation.base_moderation_exceptions.ModerationPiiError([...]) Exception raised if PII entities are detected. comprehend_moderation.base_moderation_exceptions.ModerationPromptSafetyError([...]) Exception raised if Intention entities are detected. comprehend_moderation.base_moderation_exceptions.ModerationTo...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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cpal.models.StoryModel Create a new model by parsing and validating input data from keyword arguments. cpal.models.SystemSettingModel Initial global conditions for the system. langchain_experimental.fallacy_removal¶ The Chain runs a self-review of logical fallacies as determined by this paper categorizing and defining...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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llm_bash.bash.BashProcess([strip_newlines, ...]) Wrapper class for starting subprocesses. llm_bash.prompt.BashOutputParser Parser for bash output. langchain_experimental.llm_symbolic_math¶ Chain that interprets a prompt and executes python code to do math. Heavily borrowed from llm_math, wrapper for SymPy Classes¶ llm_...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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langchain_experimental.pal_chain¶ Implements Program-Aided Language Models. As in https://arxiv.org/pdf/2211.10435.pdf. This is vulnerable to arbitrary code execution: https://github.com/langchain-ai/langchain/issues/5872 Classes¶ pal_chain.base.PALChain Implements Program-Aided Language Models (PAL). pal_chain.base.PA...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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Classes¶ retrievers.vector_sql_database.VectorSQLDatabaseChainRetriever Retriever that uses SQLDatabase as Retriever langchain_experimental.rl_chain¶ Classes¶ rl_chain.base.AutoSelectionScorer Create a new model by parsing and validating input data from keyword arguments. rl_chain.base.Embedder(*args, **kwargs) rl_chai...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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rl_chain.base.embed(to_embed, model[, namespace]) Embeds the actions or context using the SentenceTransformer model (or a model that has an encode function) rl_chain.base.embed_dict_type(item, model) Helper function to embed a dictionary item. rl_chain.base.embed_list_type(item, model[, ...]) rl_chain.base.embed_string...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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Output Parser for Vector SQL 1. sql.vector_sql.VectorSQLRetrieveAllOutputParser Based on VectorSQLOutputParser It also modify the SQL to get all columns Functions¶ sql.vector_sql.get_result_from_sqldb(db, cmd) langchain_experimental.tabular_synthetic_data¶ Classes¶ tabular_synthetic_data.base.SyntheticDataGenerator Gen...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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tot.thought_generation.BaseThoughtGenerationStrategy Base class for a thought generation strategy. tot.thought_generation.ProposePromptStrategy Propose thoughts sequentially using a "propose prompt". tot.thought_generation.SampleCoTStrategy Sample thoughts from a Chain-of-Thought (CoT) prompt. langchain_experimental.ut...
lang/api.python.langchain.com/en/latest/experimental_api_reference.html
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langchain.utilities.dataforseo_api_search.DataForSeoAPIWrapper¶ class langchain.utilities.dataforseo_api_search.DataForSeoAPIWrapper[source]¶ Bases: BaseModel Wrapper around the DataForSeo API. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data canno...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.dataforseo_api_search.DataForSeoAPIWrapper.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.dataforseo_api_search.DataForSeoAPIWrapper.html
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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_n...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.dataforseo_api_search.DataForSeoAPIWrapper.html
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classmethod validate(value: Any) → Model¶ Examples using DataForSeoAPIWrapper¶ DataForSeo DataForSEO
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.dataforseo_api_search.DataForSeoAPIWrapper.html
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langchain.utilities.portkey.Portkey¶ class langchain.utilities.portkey.Portkey[source]¶ Portkey configuration. base¶ The base URL for the Portkey API. Default: “https://api.portkey.ai/v1/proxy” Attributes base Methods Config(api_key[, trace_id, environment, ...]) __init__() static Config(api_key: str, trace_id: Optiona...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.portkey.Portkey.html
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langchain.utilities.opaqueprompts.sanitize¶ langchain.utilities.opaqueprompts.sanitize(input: Union[str, Dict[str, str]]) → Dict[str, Union[str, Dict[str, str]]][source]¶ Sanitize input string or dict of strings by replacing sensitive data with placeholders. It returns the sanitized input string or dict of strings and ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.opaqueprompts.sanitize.html
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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 fr...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.scenexplain.SceneXplainAPIWrapper.html
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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[boo...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.scenexplain.SceneXplainAPIWrapper.html
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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_f...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.scenexplain.SceneXplainAPIWrapper.html
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langchain.utilities.serpapi.HiddenPrints¶ class langchain.utilities.serpapi.HiddenPrints[source]¶ Context manager to hide prints. Methods __init__() __init__()¶
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.serpapi.HiddenPrints.html
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langchain.utilities.arcee.ArceeDocumentSource¶ class langchain.utilities.arcee.ArceeDocumentSource[source]¶ Bases: BaseModel Source of an Arcee document. 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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arcee.ArceeDocumentSource.html
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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, ex...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arcee.ArceeDocumentSource.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arcee.ArceeDocumentSource.html
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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'¶ TR...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.openapi.HTTPVerb.html
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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 variab...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.google_places_api.GooglePlacesAPIWrapper.html
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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(*, i...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.google_places_api.GooglePlacesAPIWrapper.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.google_places_api.GooglePlacesAPIWrapper.html
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langchain.utilities.requests.RequestsWrapper¶ langchain.utilities.requests.RequestsWrapper¶ alias of TextRequestsWrapper Examples using RequestsWrapper¶ OpenAPI
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.requests.RequestsWrapper.html
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langchain.utilities.arcee.DALMFilter¶ class langchain.utilities.arcee.DALMFilter[source]¶ Bases: BaseModel Filters available for a DALM retrieval and generation. Parameters field_name – The field to filter on. Can be ‘document’ or ‘name’ to filter on your document’s raw text or title. Any other field will be presumed t...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arcee.DALMFilter.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arcee.DALMFilter.html
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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_n...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arcee.DALMFilter.html
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langchain.utilities.clickup.load_query¶ langchain.utilities.clickup.load_query(query: str, fault_tolerant: bool = False) → Tuple[Optional[Dict], Optional[str]][source]¶ Attempts to parse a JSON string and return the parsed object. If parsing fails, returns an error message. Parameters query – The JSON string to parse. ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.load_query.html
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langchain.utilities.awslambda.LambdaWrapper¶ class langchain.utilities.awslambda.LambdaWrapper[source]¶ Bases: BaseModel Wrapper for AWS Lambda SDK. To use, you should have the boto3 package installed and a lambda functions built from the AWS Console or CLI. Set up your AWS credentials with aws configure Example pip in...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.awslambda.LambdaWrapper.html
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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(*, i...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.awslambda.LambdaWrapper.html
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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]¶ Invokes the lambda function and returns the result. Parameters query – an input to...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.awslambda.LambdaWrapper.html
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langchain.utilities.arxiv.ArxivAPIWrapper¶ class langchain.utilities.arxiv.ArxivAPIWrapper[source]¶ Bases: BaseModel Wrapper around ArxivAPI. To use, you should have the arxiv python package installed. https://lukasschwab.me/arxiv.py/index.html This wrapper will use the Arxiv API to conduct searches and fetch document ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arxiv.ArxivAPIWrapper.html
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) arxiv.run("tree of thought llm) 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 ARXIV_MAX_QUERY_LENGTH: int = 300¶ param arxiv_exceptions: Any = None¶ param doc_content_chars_max: Optional[int] = 400...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arxiv.ArxivAPIWrapper.html
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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, ex...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arxiv.ArxivAPIWrapper.html
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load(query: str) → List[Document][source]¶ Run Arxiv search and get the article texts plus the article meta information. See https://lukasschwab.me/arxiv.py/index.html#Search Returns: a list of documents with the document.page_content in text format Performs an arxiv search, downloads the top k results as PDFs, loads t...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arxiv.ArxivAPIWrapper.html
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classmethod validate(value: Any) → Model¶ Examples using ArxivAPIWrapper¶ ArXiv
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arxiv.ArxivAPIWrapper.html
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langchain.utilities.google_scholar.GoogleScholarAPIWrapper¶ class langchain.utilities.google_scholar.GoogleScholarAPIWrapper[source]¶ Bases: BaseModel Wrapper for Google Scholar API You can create serpapi key by signing up at: https://serpapi.com/users/sign_up. The wrapper uses the serpapi python package: https://serpa...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.google_scholar.GoogleScholarAPIWrapper.html
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param lr: str = 'lang_en'¶ param serp_api_key: Optional[str] = None¶ param top_k_results: 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 v...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.google_scholar.GoogleScholarAPIWrapper.html
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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_n...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.google_scholar.GoogleScholarAPIWrapper.html
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langchain.utilities.clickup.fetch_team_id¶ langchain.utilities.clickup.fetch_team_id(access_token: str) → Optional[int][source]¶ Fetch the team id.
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.fetch_team_id.html
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langchain.utilities.clickup.ClickupAPIWrapper¶ class langchain.utilities.clickup.ClickupAPIWrapper[source]¶ Bases: BaseModel Wrapper for Clickup 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 acc...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.ClickupAPIWrapper.html
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Returns new model instance create_folder(query: str) → Dict[source]¶ Creates a new folder. create_list(query: str) → Dict[source]¶ Creates a new list. create_task(query: str) → Dict[source]¶ Creates a new task. dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[Abstrac...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.ClickupAPIWrapper.html
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Retrieve a specific task. get_task_attribute(query: str) → Dict[source]¶ Update an attribute of a specified task. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = No...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.ClickupAPIWrapper.html
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classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and localns. update_task(query: str) → Dict[source]¶ Update an attribute of a specified task. update_task_assignees(query: str) → Dict[source]¶ Add or remove assignees of a specified task. classmeth...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.ClickupAPIWrapper.html
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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_...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.sql_database.SQLDatabase.html
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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, ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.sql_database.SQLDatabase.html
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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 met...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.sql_database.SQLDatabase.html
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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 u...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.sql_database.SQLDatabase.html
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(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_names() → Iterable[str][source]¶ Get names of tables available. get_usable_table_names() → Iterable[str][...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.sql_database.SQLDatabase.html
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langchain.utilities.wikipedia.WikipediaAPIWrapper¶ class langchain.utilities.wikipedia.WikipediaAPIWrapper[source]¶ Bases: BaseModel Wrapper around WikipediaAPI. To use, you should have the wikipedia python package installed. This wrapper will use the Wikipedia API to conduct searches and fetch page summaries. By defau...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.wikipedia.WikipediaAPIWrapper.html
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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, ex...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.wikipedia.WikipediaAPIWrapper.html
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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 Wikipedia search and get page summaries. classmethod schema(by_alias: bool = T...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.wikipedia.WikipediaAPIWrapper.html
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langchain.utilities.clickup.parse_dict_through_component¶ langchain.utilities.clickup.parse_dict_through_component(data: dict, component: Type[Component], fault_tolerant: bool = False) → Dict[source]¶ Parse a dictionary by creating a component and then turning it back into a dictionary. This helps with two things 1. Ex...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.parse_dict_through_component.html
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langchain.utilities.vertexai.get_client_info¶ langchain.utilities.vertexai.get_client_info(module: Optional[str] = None) → ClientInfo[source]¶ Returns a custom user agent header. Parameters module (Optional[str]) – Optional. The module for a custom user agent header. Returns google.api_core.gapic_v1.client_info.ClientI...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.vertexai.get_client_info.html
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langchain.utilities.golden_query.GoldenQueryAPIWrapper¶ class langchain.utilities.golden_query.GoldenQueryAPIWrapper[source]¶ Bases: BaseModel Wrapper for Golden. Docs for using: Go to https://golden.com and sign up for an account Get your API Key from https://golden.com/settings/api Save your API Key into GOLDEN_API_K...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.golden_query.GoldenQueryAPIWrapper.html
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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, ex...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.golden_query.GoldenQueryAPIWrapper.html
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run(query: str) → str[source]¶ Run query through Golden Query API and return the JSON raw 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: An...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.golden_query.GoldenQueryAPIWrapper.html
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langchain.utilities.clickup.fetch_space_id¶ langchain.utilities.clickup.fetch_space_id(team_id: int, access_token: str) → Optional[int][source]¶ Fetch the space id.
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.fetch_space_id.html
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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 accoun...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.twilio.TwilioAPIWrapper.html
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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 i...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.twilio.TwilioAPIWrapper.html
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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_n...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.twilio.TwilioAPIWrapper.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.twilio.TwilioAPIWrapper.html
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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 impers...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.powerbi.PowerBIDataset.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.powerbi.PowerBIDataset.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.powerbi.PowerBIDataset.html
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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
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.powerbi.PowerBIDataset.html
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langchain.utilities.redis.TokenEscaper¶ class langchain.utilities.redis.TokenEscaper(escape_chars_re: Optional[Pattern] = None)[source]¶ Escape punctuation within an input string. Attributes DEFAULT_ESCAPED_CHARS Methods __init__([escape_chars_re]) escape(value) __init__(escape_chars_re: Optional[Pattern] = None)[sourc...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.redis.TokenEscaper.html
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langchain.utilities.anthropic.get_token_ids_anthropic¶ langchain.utilities.anthropic.get_token_ids_anthropic(text: str) → List[int][source]¶ Get the token ids for a string of text.
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.anthropic.get_token_ids_anthropic.html
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langchain.utilities.anthropic.get_num_tokens_anthropic¶ langchain.utilities.anthropic.get_num_tokens_anthropic(text: str) → int[source]¶ Get the number of tokens in a string of text.
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.anthropic.get_num_tokens_anthropic.html
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langchain.utilities.clickup.fetch_data¶ langchain.utilities.clickup.fetch_data(url: str, access_token: str, query: Optional[dict] = None) → dict[source]¶ Fetch data from a URL.
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.fetch_data.html
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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 name...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.serpapi.SerpAPIWrapper.html
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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...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.serpapi.SerpAPIWrapper.html
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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 = ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.serpapi.SerpAPIWrapper.html
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Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶ Examples using SerpAPIWrapper¶ SerpAPI Bittensor AutoGPT
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.serpapi.SerpAPIWrapper.html
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langchain.utilities.arcee.DALMFilterType¶ class langchain.utilities.arcee.DALMFilterType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶ Filter types available for a DALM retrieval as enumerator. fuzzy_search = 'fuzzy_search'¶ strict_search = 'strict_search'¶
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.arcee.DALMFilterType.html
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langchain.utilities.clickup.Space¶ class langchain.utilities.clickup.Space(id: int, name: str, private: bool, enabled_features: Dict[str, Any])[source]¶ Component class for a space. Attributes id name private enabled_features Methods __init__(id, name, private, enabled_features) from_data(data) __init__(id: int, name: ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.clickup.Space.html
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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 = ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.jira.JiraAPIWrapper.html
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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, ex...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.jira.JiraAPIWrapper.html
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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) → ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.jira.JiraAPIWrapper.html
d8c216c9cf77-0
langchain.utilities.apify.ApifyWrapper¶ class langchain.utilities.apify.ApifyWrapper[source]¶ Bases: BaseModel Wrapper around Apify. To use, you should have the apify-client python package installed, and the environment variable APIFY_API_TOKEN set with your API key, or pass apify_api_token as a named parameter to the ...
lang/api.python.langchain.com/en/latest/utilities/langchain.utilities.apify.ApifyWrapper.html