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Parameters zip_path (str) – workspace_url (Optional[str]) – load()[source] Load and return documents from the Slack directory dump. Return type List[langchain.schema.Document] class langchain.document_loaders.SnowflakeLoader(query, user, password, account, warehouse, role, database, schema, parameters=None, page_con...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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password (str) – account (str) – warehouse (str) – role (str) – database (str) – schema (str) – parameters (Optional[Dict[str, Any]]) – page_content_columns (Optional[List[str]]) – metadata_columns (Optional[List[str]]) – lazy_load()[source] A lazy loader for document content. Return type Iterator[langchain.s...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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None load()[source] Load data into document objects. Return type List[langchain.schema.Document] class langchain.document_loaders.StripeLoader(resource, access_token=None)[source] Bases: langchain.document_loaders.base.BaseLoader Loader that fetches data from Stripe. Parameters resource (str) – access_token (Optiona...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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api_id (Optional[int]) – api_hash (Optional[str]) – username (Optional[str]) – file_path (str) – async fetch_data_from_telegram()[source] Fetch data from Telegram API and save it as a JSON file. Return type None load()[source] Load documents. Return type List[langchain.schema.Document] class langchain.document_lo...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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class langchain.document_loaders.TextLoader(file_path, encoding=None, autodetect_encoding=False)[source] Bases: langchain.document_loaders.base.BaseLoader Load text files. Parameters file_path (str) – Path to the file to load. encoding (Optional[str]) – File encoding to use. If None, the file will be loaded encoding. ...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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api_key (str) – lazy_load()[source] Lazily load the file. Return type Iterator[langchain.schema.Document] load()[source] Load file. Return type List[langchain.schema.Document] class langchain.document_loaders.TomlLoader(source)[source] Bases: langchain.document_loaders.base.BaseLoader A TOML document loader that in...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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Iterator[langchain.schema.Document] class langchain.document_loaders.TrelloLoader(client, board_name, *, include_card_name=True, include_comments=True, include_checklist=True, card_filter='all', extra_metadata=('due_date', 'labels', 'list', 'closed'))[source] Bases: langchain.document_loaders.base.BaseLoader Trello lo...
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Parameters board_name (str) – The name of the Trello board. api_key (Optional[str]) – Trello API key. Can also be specified as environment variable TRELLO_API_KEY. token (Optional[str]) – Trello token. Can also be specified as environment variable TRELLO_TOKEN. include_card_name – Whether to include the name of the car...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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load()[source] Loads all cards from the specified Trello board. You can filter the cards, metadata and text included by using the optional parameters. Returns:A list of documents, one for each card in the board. Return type List[langchain.schema.Document] class langchain.document_loaders.TwitterTweetLoader(auth_handle...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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number_tweets (Optional[int]) – load()[source] Load tweets. Return type List[langchain.schema.Document] classmethod from_bearer_token(oauth2_bearer_token, twitter_users, number_tweets=100)[source] Create a TwitterTweetLoader from OAuth2 bearer token. Parameters oauth2_bearer_token (str) – twitter_users (Sequence[st...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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twitter_users (Sequence[str]) – number_tweets (Optional[int]) – Return type langchain.document_loaders.twitter.TwitterTweetLoader class langchain.document_loaders.UnstructuredAPIFileIOLoader(file, mode='single', url='https://api.unstructured.io/general/v0/general', api_key='', **unstructured_kwargs)[source] Bases: l...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader Loader that uses the unstructured web API to load files. Parameters file_path (Union[str, List[str]]) – mode (str) – url (str) – api_key (str) – unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredCSVLoader(file_path, mode='...
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Loader that uses unstructured to load epub files. Parameters file_path (Union[str, List[str]]) – mode (str) – unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredEmailLoader(file_path, mode='single', **unstructured_kwargs)[source] Bases: langchain.document_loaders.unstructured.UnstructuredFileL...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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mode (str) – unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredFileIOLoader(file, mode='single', **unstructured_kwargs)[source] Bases: langchain.document_loaders.unstructured.UnstructuredBaseLoader Loader that uses unstructured to load file IO objects. Parameters file (Union[IO, Sequence[IO]])...
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unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredHTMLLoader(file_path, mode='single', **unstructured_kwargs)[source] Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader Loader that uses unstructured to load HTML files. Parameters file_path (Union[str, List[str]]) – mode (str...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredMarkdownLoader(file_path, mode='single', **unstructured_kwargs)[source] Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader Loader that uses unstructured to load markdown files. Parameters file_path (Union[str, List[str]]) – m...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredPDFLoader(file_path, mode='single', **unstructured_kwargs)[source] Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader Loader that uses unstructured to load PDF files. Parameters file_path (Union[str, List[str]]) – mode (str) ...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredRSTLoader(file_path, mode='single', **unstructured_kwargs)[source] Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader Loader that uses unstructured to load RST files. Parameters file_path (str) – mode (str) – unstructured_kw...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredURLLoader(urls, continue_on_failure=True, mode='single', show_progress_bar=False, **unstructured_kwargs)[source] Bases: langchain.document_loaders.base.BaseLoader Loader that uses unstructured to load HTML files. Parameters urls (List[str]) – c...
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Parameters file_path (Union[str, List[str]]) – mode (str) – unstructured_kwargs (Any) – class langchain.document_loaders.UnstructuredXMLLoader(file_path, mode='single', **unstructured_kwargs)[source] Bases: langchain.document_loaders.unstructured.UnstructuredFileLoader Loader that uses unstructured to load XML file...
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places (Sequence[str]) – Return type None classmethod from_params(places, *, openweathermap_api_key=None)[source] Parameters places (Sequence[str]) – openweathermap_api_key (Optional[str]) – Return type langchain.document_loaders.weather.WeatherDataLoader lazy_load()[source] Lazily load weather data for the given ...
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header_template (Optional[dict]) – verify (Optional[bool]) – requests_per_second: int = 2 Max number of concurrent requests to make. default_parser: str = 'html.parser' Default parser to use for BeautifulSoup. requests_kwargs: Dict[str, Any] = {} kwargs for requests bs_get_text_kwargs: Dict[str, Any] = {} kwargs ...
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Return type List[Any] scrape(parser=None)[source] Scrape data from webpage and return it in BeautifulSoup format. Parameters parser (Optional[str]) – Return type Any lazy_load()[source] Lazy load text from the url(s) in web_path. Return type Iterator[langchain.schema.Document] load()[source] Load text from the url(...
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Load documents. Return type List[langchain.schema.Document] class langchain.document_loaders.WikipediaLoader(query, lang='en', load_max_docs=100, load_all_available_meta=False, doc_content_chars_max=4000)[source] Bases: langchain.document_loaders.base.BaseLoader Loads a query result from www.wikipedia.org into a list ...
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Return type List[Document] class langchain.document_loaders.YoutubeAudioLoader(urls, save_dir)[source] Bases: langchain.document_loaders.blob_loaders.schema.BlobLoader Load YouTube urls as audio file(s). Parameters urls (List[str]) – save_dir (str) – yield_blobs()[source] Yield audio blobs for each url. Return type...
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translation (str) – continue_on_failure (bool) – static extract_video_id(youtube_url)[source] Extract video id from common YT urls. Parameters youtube_url (str) – Return type str classmethod from_youtube_url(youtube_url, **kwargs)[source] Given youtube URL, load video. Parameters youtube_url (str) – kwargs (Any) ...
https://api.python.langchain.com/en/latest/modules/document_loaders.html
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Experimental This module contains experimental modules and reproductions of existing work using LangChain primitives. Autonomous agents Here, we document the BabyAGI and AutoGPT classes from the langchain.experimental module. class langchain.experimental.BabyAGI(*, memory=None, callbacks=None, callback_manager=None, ...
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verbose (bool) – tags (Optional[List[str]]) – task_list (collections.deque) – task_creation_chain (langchain.chains.base.Chain) – task_prioritization_chain (langchain.chains.base.Chain) – execution_chain (langchain.chains.base.Chain) – task_id_counter (int) – vectorstore (langchain.vectorstores.base.VectorStore)...
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Parameters result (str) – task_description (str) – objective (str) – Return type List[Dict] prioritize_tasks(this_task_id, objective)[source] Prioritize tasks. Parameters this_task_id (int) – objective (str) – Return type List[Dict] execute_task(objective, task, k=5)[source] Execute a task. Parameters objective ...
https://api.python.langchain.com/en/latest/modules/experimental.html
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verbose (bool) – task_execution_chain (Optional[langchain.chains.base.Chain]) – kwargs (Dict[str, Any]) – Return type langchain.experimental.autonomous_agents.baby_agi.baby_agi.BabyAGI class langchain.experimental.AutoGPT(ai_name, memory, chain, output_parser, tools, feedback_tool=None, chat_history_memory=None)[sou...
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Generative agents Here, we document the GenerativeAgent and GenerativeAgentMemory classes from the langchain.experimental module. class langchain.experimental.GenerativeAgent(*, name, age=None, traits='N/A', status, memory, llm, verbose=False, summary='', summary_refresh_seconds=3600, last_refreshed=None, daily_summar...
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last_refreshed (datetime.datetime) – daily_summaries (List[str]) – Return type None attribute name: str [Required] The character’s name. attribute age: Optional[int] = None The optional age of the character. attribute traits: str = 'N/A' Permanent traits to ascribe to the character. attribute status: str [Required...
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How frequently to re-generate the summary. attribute last_refreshed: datetime.datetime [Optional] The last time the character’s summary was regenerated. attribute daily_summaries: List[str] [Optional] Summary of the events in the plan that the agent took. model Config[source] Bases: object Configuration for this pyd...
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React to a given observation. Parameters observation (str) – now (Optional[datetime.datetime]) – Return type Tuple[bool, str] get_summary(force_refresh=False, now=None)[source] Return a descriptive summary of the agent. Parameters force_refresh (bool) – now (Optional[datetime.datetime]) – Return type str get_full_...
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Return type str class langchain.experimental.GenerativeAgentMemory(*, llm, memory_retriever, verbose=False, reflection_threshold=None, current_plan=[], importance_weight=0.15, aggregate_importance=0.0, max_tokens_limit=1200, queries_key='queries', most_recent_memories_token_key='recent_memories_token', add_memory_key='...
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reflection_threshold (Optional[float]) – current_plan (List[str]) – importance_weight (float) – aggregate_importance (float) – max_tokens_limit (int) – queries_key (str) – most_recent_memories_token_key (str) – add_memory_key (str) – relevant_memories_key (str) – relevant_memories_simple_key (str) – most_rece...
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The retriever to fetch related memories. attribute reflection_threshold: Optional[float] = None When aggregate_importance exceeds reflection_threshold, stop to reflect. attribute current_plan: List[str] = [] The current plan of the agent. attribute importance_weight: float = 0.15 How much weight to assign the memory...
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Parameters memory_content (str) – now (Optional[datetime.datetime]) – Return type List[str] add_memory(memory_content, now=None)[source] Add an observation or memory to the agent’s memory. Parameters memory_content (str) – now (Optional[datetime.datetime]) – Return type List[str] fetch_memories(observation, now=No...
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Return type Dict[str, str] save_context(inputs, outputs)[source] Save the context of this model run to memory. Parameters inputs (Dict[str, Any]) – outputs (Dict[str, Any]) – Return type None clear()[source] Clear memory contents. Return type None
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Utilities General utilities. class langchain.utilities.ApifyWrapper(*, apify_client=None, apify_client_async=None)[source] Bases: pydantic.main.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...
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Parameters actor_id (str) – The ID or name of the Actor on the Apify platform. run_input (Dict) – The input object of the Actor that you’re trying to run. dataset_mapping_function (Callable) – A function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class. build (...
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Return type ApifyDatasetLoader call_actor(actor_id, run_input, dataset_mapping_function, *, build=None, memory_mbytes=None, timeout_secs=None)[source] Run an Actor on the Apify platform and wait for results to be ready. Parameters actor_id (str) – The ID or name of the Actor on the Apify platform. run_input (Dict) – T...
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Returns A loader that will fetch the records from theActor run’s default dataset. Return type ApifyDatasetLoader class langchain.utilities.ArxivAPIWrapper(*, arxiv_search=None, arxiv_exceptions=None, top_k_results=3, load_max_docs=100, load_all_available_meta=False, doc_content_chars_max=4000, ARXIV_MAX_QUERY_LENGTH=30...
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Parameters top_k_results (int) – number of the top-scored document used for the arxiv tool ARXIV_MAX_QUERY_LENGTH (int) – the cut limit on the query used for the arxiv tool. load_max_docs (int) – a limit to the number of loaded documents load_all_available_meta (bool) – if True: the metadata of the loaded Documents ge...
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attribute load_max_docs: int = 100 attribute top_k_results: int = 3 load(query)[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 Parameters query (str)...
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Return type str class langchain.utilities.BashProcess(strip_newlines=False, return_err_output=False, persistent=False)[source] Bases: object Executes bash commands and returns the output. Parameters strip_newlines (bool) – return_err_output (bool) – persistent (bool) – run(commands)[source] Run commands and return...
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This wrapper will use bibtexparser to load a collection of references from a bibtex file and fetch document summaries. Return type None get_metadata(entry, load_extra=False)[source] Get metadata for the given entry. Parameters entry (Mapping[str, Any]) – load_extra (bool) – Return type Dict[str, Any] load_bibtex_ent...
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https://levelup.gitconnected.com/api-tutorial-how-to-use-bing-web-search-api-in-python-4165d5592a7e Parameters bing_subscription_key (str) – bing_search_url (str) – k (int) – Return type None attribute bing_search_url: str [Required] attribute bing_subscription_key: str [Required] attribute k: int = 10 results(qu...
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run(query)[source] Run query through BingSearch and parse result. Parameters query (str) – Return type str class langchain.utilities.BraveSearchWrapper(*, api_key, search_kwargs=None)[source] Bases: pydantic.main.BaseModel Parameters api_key (str) – search_kwargs (dict) – Return type None attribute api_key: str [R...
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Wrapper for DuckDuckGo Search API. Free and does not require any setup Parameters k (int) – region (Optional[str]) – safesearch (str) – time (Optional[str]) – max_results (int) – Return type None attribute k: int = 10 attribute max_results: int = 5 attribute region: Optional[str] = 'wt-wt' attribute safesearch:...
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Parameters query (str) – The query to search for. num_results (int) – 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)[source] Parameters query (str) – ...
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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 import GooglePlacesAPIWrapper gplaceapi = GooglePlacesAPIWrapper() Parameters gplaces_api_key (Optional[str]) – goog...
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run(query)[source] Run Places search and get k number of places that exists that match. Parameters query (str) – Return type str class langchain.utilities.GoogleSearchAPIWrapper(*, search_engine=None, google_api_key=None, google_cse_id=None, k=10, siterestrict=False)[source] Bases: pydantic.main.BaseModel Wrapper fo...
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The current version of the library is 2.70.0 at this time 2. 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 3...
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4. Enable the Custom Search API - Navigate to the APIs & Servicesβ†’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 Parameters search_engine (Any) – g...
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Parameters query (str) – The query to search for. num_results (int) – 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)[source] Run query through GoogleS...
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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 import GoogleSerperAPIWrapper google_serper = GoogleSerperAPIWrapper() Parameters k (int) – ...
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attribute hl: str = 'en' attribute k: int = 10 attribute serper_api_key: Optional[str] = None attribute tbs: Optional[str] = None attribute type: Literal['news', 'search', 'places', 'images'] = 'search' async aresults(query, **kwargs)[source] Run query through GoogleSearch. Parameters query (str) – kwargs (Any) ...
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Return type Dict run(query, **kwargs)[source] Run query through GoogleSearch and parse result. Parameters query (str) – kwargs (Any) – Return type str class langchain.utilities.GraphQLAPIWrapper(*, custom_headers=None, graphql_endpoint, gql_client=None, gql_function)[source] Bases: pydantic.main.BaseModel Wrapper a...
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run(query)[source] Run a GraphQL query and get the results. Parameters query (str) – Return type str
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class langchain.utilities.JiraAPIWrapper(*, jira=None, confluence=None, jira_username=None, jira_api_token=None, jira_instance_url=None, operations=[{'mode': 'jql', 'name': 'JQL Query', 'description': '\nΒ Β Β  This tool is a wrapper around atlassian-python-api\'s Jira jql API, useful when you need to search for Jira issu...
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'}, {'mode': 'get_projects', 'name': 'Get Projects', 'description': "\nΒ Β Β  This tool is a wrapper around atlassian-python-api's Jira project API, \nΒ Β Β  useful when you need to fetch all the projects the user has access to, find out how many projects there are, or as an intermediary step that involv searching by project...
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task called "test issue" with description "test description", you would pass in the following dictionary: \nΒ Β Β  {{"summary": "test issue", "description": "test description", "issuetype": {{"name": "Task"}}, "priority": {{"name": "Low"}}}}\nΒ Β Β  '}, {'mode': 'other', 'name': 'Catch all Jira API call', 'description': '\nΒ ...
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you would pass in the following string:\nΒ Β Β  self.jira.update_issue_field(key, {{"summary": "New summary"}})\nΒ Β Β  or to find out how many projects are in the Jira instance, you would pass in the following string:\nΒ Β Β  self.jira.projects()\nΒ Β Β  For more information on the Jira API, refer to https://atlassian-python-api....
https://api.python.langchain.com/en/latest/modules/utilities.html
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DEMO space titled "This is the title" with body "This is the body. You can use \n<strong>HTML tags</strong>!", you would pass in the following dictionary: {{"space": "DEMO", "title":"This is the \ntitle","body":"This is the body. You can use <strong>HTML tags</strong>!"}} '}])[source]
https://api.python.langchain.com/en/latest/modules/utilities.html
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Bases: pydantic.main.BaseModel Wrapper for Jira API. Parameters jira (Any) – confluence (Any) – jira_username (Optional[str]) – jira_api_token (Optional[str]) – jira_instance_url (Optional[str]) – operations (List[Dict]) – Return type None attribute confluence: Any = None attribute jira_api_token: Optional[str] ...
https://api.python.langchain.com/en/latest/modules/utilities.html
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attribute operations: List[Dict] = [{'mode': 'jql', 'name': 'JQL Query', 'description': '\nΒ Β Β  This tool is a wrapper around atlassian-python-api\'s Jira jql API, useful when you need to search for Jira issues.\nΒ Β Β  The input to this tool is a JQL query string, and will be passed into atlassian-python-api\'s Jira `jql`...
https://api.python.langchain.com/en/latest/modules/utilities.html
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wrapper around atlassian-python-api's Jira project API, \nΒ Β Β  useful when you need to fetch all the projects the user has access to, find out how many projects there are, or as an intermediary step that involv searching by projects. \nΒ Β Β  there is no input to this tool.\nΒ Β Β  "}, {'mode': 'create_issue', 'name': 'Create...
https://api.python.langchain.com/en/latest/modules/utilities.html
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"test issue", "description": "test description", "issuetype": {{"name": "Task"}}, "priority": {{"name": "Low"}}}}\nΒ Β Β  '}, {'mode': 'other', 'name': 'Catch all Jira API call', 'description': '\nΒ Β Β  This tool is a wrapper around atlassian-python-api\'s Jira API.\nΒ Β Β  There are other dedicated tools for fetching all proj...
https://api.python.langchain.com/en/latest/modules/utilities.html
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or to find out how many projects are in the Jira instance, you would pass in the following string:\nΒ Β Β  self.jira.projects()\nΒ Β Β  For more information on the Jira API, refer to https://atlassian-python-api.readthedocs.io/jira.html\nΒ Β Β  '}, {'mode': 'create_page', 'name': 'Create confluence page', 'description': 'This t...
https://api.python.langchain.com/en/latest/modules/utilities.html
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you would pass in the following dictionary: {{"space": "DEMO", "title":"This is the \ntitle","body":"This is the body. You can use <strong>HTML tags</strong>!"}} '}]
https://api.python.langchain.com/en/latest/modules/utilities.html
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issue_create(query)[source] Parameters query (str) – Return type str list()[source] Return type List[Dict] other(query)[source] Parameters query (str) – Return type str page_create(query)[source] Parameters query (str) – Return type str parse_issues(issues)[source] Parameters issues (Dict) – Return type List[d...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Parameters query (str) – Return type str class langchain.utilities.LambdaWrapper(*, lambda_client=None, function_name=None, awslambda_tool_name=None, awslambda_tool_description=None)[source] Bases: pydantic.main.BaseModel Wrapper for AWS Lambda SDK. Docs for using: pip install boto3 Create a lambda function using the...
https://api.python.langchain.com/en/latest/modules/utilities.html
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run(query)[source] Invoke Lambda function and parse result. Parameters query (str) – Return type str class langchain.utilities.MaxComputeAPIWrapper(client)[source] Bases: object Interface for querying Alibaba Cloud MaxCompute tables. Parameters client (ODPS) – classmethod from_params(endpoint, project, *, access_id...
https://api.python.langchain.com/en/latest/modules/utilities.html
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directly or set as the environment variable MAX_COMPUTE_SECRET_ACCESS_KEY. Return type langchain.utilities.max_compute.MaxComputeAPIWrapper lazy_query(query)[source] Parameters query (str) – Return type Iterator[dict] query(query)[source] Parameters query (str) – Return type List[dict] class langchain.utilities.Met...
https://api.python.langchain.com/en/latest/modules/utilities.html
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results(query, num_results, include_domains=None, exclude_domains=None, start_crawl_date=None, end_crawl_date=None, start_published_date=None, end_published_date=None)[source] Run query through Metaphor Search and return metadata. Parameters query (str) – The query to search for. num_results (int) – The number of resu...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Return type A list of dictionaries with the following keys async results_async(query, num_results, include_domains=None, exclude_domains=None, start_crawl_date=None, end_crawl_date=None, start_published_date=None, end_published_date=None)[source] Get results from the Metaphor Search API asynchronously. Parameters quer...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Bases: pydantic.main.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 Parameters owm (Any) – openweathermap_api_key (Optional[str]) – Return type None attribute openweather...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Bases: pydantic.main.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 enable...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Return type None attribute aiosession: Optional[aiohttp.ClientSession] = None attribute credential: Optional[TokenCredential] = None attribute dataset_id: str [Required] attribute group_id: Optional[str] = None attribute impersonated_user_name: Optional[str] = None attribute sample_rows_in_table_info: int = 1 Con...
https://api.python.langchain.com/en/latest/modules/utilities.html
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async arun(command)[source] Execute a DAX command and return the result asynchronously. Parameters command (str) – Return type Any get_schemas()[source] Get the available schema’s. Return type str get_table_info(table_names=None)[source] Get information about specified tables. Parameters table_names (Optional[Union...
https://api.python.langchain.com/en/latest/modules/utilities.html
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property table_info: str Information about all tables in the database. class langchain.utilities.PubMedAPIWrapper(*, top_k_results=3, load_max_docs=25, doc_content_chars_max=2000, load_all_available_meta=False, email='your_email@example.com', base_url_esearch='https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Parameters top_k_results (int) – number of the top-scored document used for the PubMed tool load_max_docs (int) – a limit to the number of loaded documents load_all_available_meta (bool) – if True: the metadata of the loaded Documents gets all available meta info(see https://www.ncbi.nlm.nih.gov/books/NBK25499/#chapte...
https://api.python.langchain.com/en/latest/modules/utilities.html
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attribute load_all_available_meta: bool = False attribute load_max_docs: int = 25 attribute top_k_results: int = 3 load(query)[source] Search PubMed for documents matching the query. Return a list of dictionaries containing the document metadata. Parameters query (str) – Return type List[dict] load_docs(query)[sou...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Parameters query (str) – Return type str class langchain.utilities.PythonREPL(*, _globals=None, _locals=None)[source] Bases: pydantic.main.BaseModel Simulates a standalone Python REPL. Parameters _globals (Optional[Dict]) – _locals (Optional[Dict]) – Return type None attribute globals: Optional[Dict] [Optional] (al...
https://api.python.langchain.com/en/latest/modules/utilities.html
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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. Show JSON schema{ "title...
https://api.python.langchain.com/en/latest/modules/utilities.html
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"type": "object", "properties": { "scenex_api_key": { "title": "Scenex Api Key", "env": "SCENEX_API_KEY", "env_names": "{'scenex_api_key'}", "type": "string" }, "scenex_api_url": { "title": "Scenex Api Url", "default": "https://us-central1-causa...
https://api.python.langchain.com/en/latest/modules/utilities.html
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scenex_api_url (str) attribute scenex_api_key: str [Required] attribute scenex_api_url: str = 'https://us-central1-causal-diffusion.cloudfunctions.net/describe' run(image)[source] Run SceneXplain image explainer. Parameters image (str) – Return type str validator validate_environmentΒ  »  all fields[source] Validat...
https://api.python.langchain.com/en/latest/modules/utilities.html
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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.utilitie...
https://api.python.langchain.com/en/latest/modules/utilities.html
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params (dict) – headers (Optional[dict]) – engines (Optional[List[str]]) – categories (Optional[List[str]]) – query_suffix (Optional[str]) – k (int) – aiosession (Optional[Any]) – Return type None attribute aiosession: Optional[Any] = None attribute categories: Optional[List[str]] = [] attribute engines: Optio...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Asynchronously query with json results. Uses aiohttp. See results for more info. Parameters query (str) – num_results (int) – engines (Optional[List[str]]) – query_suffix (Optional[str]) – kwargs (Any) – Return type List[Dict] async arun(query, engines=None, query_suffix='', **kwargs)[source] Asynchronously versi...
https://api.python.langchain.com/en/latest/modules/utilities.html
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query_suffix (Optional[str]) – Extra suffix appended to the query. num_results (int) – Limit the number of results to return. engines (Optional[List[str]]) – List of engines to use for the query. categories (Optional[List[str]]) – List of categories to use for the query. **kwargs – extra parameters to pass to the searx...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Parameters query (str) – The query to search for. query_suffix (Optional[str]) – Extra suffix appended to the query. engines (Optional[List[str]]) – List of engines to use for the query. categories (Optional[List[str]]) – List of categories to use for the query. **kwargs – extra parameters to pass to the searx API. kwa...
https://api.python.langchain.com/en/latest/modules/utilities.html
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# to select the engine using `query_suffix` searx.run("what is the weather in France ?", query_suffix="!qwant") class langchain.utilities.SerpAPIWrapper(*, search_engine=None, params={'engine': 'google', 'gl': 'us', 'google_domain': 'google.com', 'hl': 'en'}, serpapi_api_key=None, aiosession=None)[source] Bases: pydan...
https://api.python.langchain.com/en/latest/modules/utilities.html
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params (dict) – serpapi_api_key (Optional[str]) – aiosession (Optional[aiohttp.client.ClientSession]) – Return type None attribute aiosession: Optional[aiohttp.client.ClientSession] = None attribute params: dict = {'engine': 'google', 'gl': 'us', 'google_domain': 'google.com', 'hl': 'en'} attribute serpapi_api_key...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Return type str get_params(query)[source] Get parameters for SerpAPI. Parameters query (str) – Return type Dict[str, str] results(query)[source] Run query through SerpAPI and return the raw result. Parameters query (str) – Return type dict run(query, **kwargs)[source] Run query through SerpAPI and parse result. Pa...
https://api.python.langchain.com/en/latest/modules/utilities.html
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schema (Optional[str]) – ignore_tables (Optional[List[str]]) – include_tables (Optional[List[str]]) – sample_rows_in_table_info (int) – classmethod from_uri(database_uri, engine_args=None, **kwargs)[source] Creating a remote Spark Session via Spark connect. For example: SparkSQL.from_uri(β€œsc://localhost:15002”) Pa...
https://api.python.langchain.com/en/latest/modules/utilities.html
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Parameters command (str) – fetch (str) – Return type str get_table_info_no_throw(table_names=None)[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 ...
https://api.python.langchain.com/en/latest/modules/utilities.html
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If the statement throws an error, the error message is returned. Parameters command (str) – fetch (str) – Return type str class langchain.utilities.TextRequestsWrapper(*, headers=None, aiosession=None)[source] Bases: pydantic.main.BaseModel Lightweight wrapper around requests library. The main purpose of this wrappe...
https://api.python.langchain.com/en/latest/modules/utilities.html
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kwargs (Any) – Return type str async aget(url, **kwargs)[source] GET the URL and return the text asynchronously. Parameters url (str) – kwargs (Any) – Return type str async apatch(url, data, **kwargs)[source] PATCH the URL and return the text asynchronously. Parameters url (str) – data (Dict[str, Any]) – kwargs ...
https://api.python.langchain.com/en/latest/modules/utilities.html