id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 49 117 |
|---|---|---|
e8f04845209a-2 | Instantiate the toolkit from an OpenAPI Spec URL
get_tools() β List[langchain.tools.base.BaseTool][source]#
Get the tools for all the API operations.
pydantic model langchain.agents.agent_toolkits.OpenAPIToolkit[source]#
Toolkit for interacting with a OpenAPI api.
field json_agent: langchain.agents.agent.AgentExecutor ... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-3 | field max_iterations: int = 5#
field powerbi: langchain.utilities.powerbi.PowerBIDataset [Required]#
get_tools() β List[langchain.tools.base.BaseTool][source]#
Get the tools in the toolkit.
pydantic model langchain.agents.agent_toolkits.SQLDatabaseToolkit[source]#
Toolkit for interacting with SQL databases.
field db: l... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-4 | Get the tools in the toolkit.
pydantic model langchain.agents.agent_toolkits.VectorStoreToolkit[source]#
Toolkit for interacting with a vector store.
field llm: langchain.base_language.BaseLanguageModel [Optional]#
field vectorstore_info: langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreInfo [Required]#
g... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-5 | langchain.agents.agent_toolkits.create_json_agent(llm: langchain.base_language.BaseLanguageModel, toolkit: langchain.agents.agent_toolkits.json.toolkit.JsonToolkit, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManager] = None, prefix: str = 'You are an agent designed to interact with JSON.\nYour goal... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-6 | you cannot use it.\nYou should only add one key at a time to the path. You cannot add multiple keys at once.\nIf you encounter a "KeyError", go back to the previous key, look at the available keys, and try again.\n\nIf the question does not seem to be related to the JSON, just return "I don\'t know" as the answer.\nAlw... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-7 | str = 'Begin!"\n\nQuestion: {input}\nThought: I should look at the keys that exist in data to see what I have access to\n{agent_scratchpad}', format_instructions: str = 'Use the following format:\n\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to ta... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-8 | Construct a json agent from an LLM and tools. | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-9 | langchain.agents.agent_toolkits.create_openapi_agent(llm: langchain.base_language.BaseLanguageModel, toolkit: langchain.agents.agent_toolkits.openapi.toolkit.OpenAPIToolkit, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManager] = None, prefix: str = "You are an agent designed to answer questions by m... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-10 | checking which parameters are required. For parameters with a fixed set of values, please use the spec to look at which values are allowed.\n\nUse the exact parameter names as listed in the spec, do not make up any names or abbreviate the names of parameters.\nIf you get a not found error, ensure that you are using a p... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-11 | None, max_iterations: Optional[int] = 15, max_execution_time: Optional[float] = None, early_stopping_method: str = 'force', verbose: bool = False, return_intermediate_steps: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Dict[str, Any]) β langchain.agents.agent.AgentExecutor[source]# | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-12 | Construct a json agent from an LLM and tools.
langchain.agents.agent_toolkits.create_pandas_dataframe_agent(llm: langchain.base_language.BaseLanguageModel, df: Any, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManager] = None, prefix: Optional[str] = None, suffix: Optional[str] = None, input_variable... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-13 | langchain.agents.agent_toolkits.create_pbi_agent(llm: langchain.base_language.BaseLanguageModel, toolkit: Optional[langchain.agents.agent_toolkits.powerbi.toolkit.PowerBIToolkit], powerbi: Optional[langchain.utilities.powerbi.PowerBIDataset] = None, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManage... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-14 | easily readible format for a human, also make sure to represent numbers in readable ways, like 1M instead of 1000000. Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.\n', suffix: str = 'Begin!\n\nQuestion: {input}\nThought: I can first ask ... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-15 | None, input_variables: Optional[List[str]] = None, top_k: int = 10, verbose: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Dict[str, Any]) β langchain.agents.agent.AgentExecutor[source]# | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-16 | Construct a pbi agent from an LLM and tools. | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-17 | langchain.agents.agent_toolkits.create_pbi_chat_agent(llm: langchain.chat_models.base.BaseChatModel, toolkit: Optional[langchain.agents.agent_toolkits.powerbi.toolkit.PowerBIToolkit], powerbi: Optional[langchain.utilities.powerbi.PowerBIDataset] = None, callback_manager: Optional[langchain.callbacks.base.BaseCallbackMa... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-18 | multiple rows are asked find a way to write that in a easily readible format for a human, also make sure to represent numbers in readable ways, like 1M instead of 1000000. Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.\n', suffix: str = "... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-19 | Construct a pbi agent from an Chat LLM and tools.
If you supply only a toolkit and no powerbi dataset, the same LLM is used for both.
langchain.agents.agent_toolkits.create_python_agent(llm: langchain.base_language.BaseLanguageModel, tool: langchain.tools.python.tool.PythonREPLTool, callback_manager: Optional[langchain... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-20 | Construct a python agent from an LLM and tool.
langchain.agents.agent_toolkits.create_spark_dataframe_agent(llm: langchain.llms.base.BaseLLM, df: Any, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManager] = None, prefix: str = '\nYou are working with a spark dataframe in Python. The name of the dataf... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-21 | langchain.agents.agent_toolkits.create_spark_sql_agent(llm: langchain.base_language.BaseLanguageModel, toolkit: langchain.agents.agent_toolkits.spark_sql.toolkit.SparkSQLToolkit, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManager] = None, prefix: str = 'You are an agent designed to interact with Sp... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-22 | a query, rewrite the query and try again.\n\nDO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n\nIf the question does not seem related to the database, just return "I don\'t know" as the answer.\n', suffix: str = 'Begin!\n\nQuestion: {input}\nThought: I should look at the tables in th... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-23 | early_stopping_method: str = 'force', verbose: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Dict[str, Any]) β langchain.agents.agent.AgentExecutor[source]# | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-24 | Construct a sql agent from an LLM and tools. | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-25 | langchain.agents.agent_toolkits.create_sql_agent(llm: langchain.base_language.BaseLanguageModel, toolkit: langchain.agents.agent_toolkits.sql.toolkit.SQLDatabaseToolkit, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManager] = None, prefix: str = 'You are an agent designed to interact with a SQL datab... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-26 | query, rewrite the query and try again.\n\nDO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n\nIf the question does not seem related to the database, just return "I don\'t know" as the answer.\n', suffix: str = 'Begin!\n\nQuestion: {input}\nThought: I should look at the tables in the ... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-27 | early_stopping_method: str = 'force', verbose: bool = False, agent_executor_kwargs: Optional[Dict[str, Any]] = None, **kwargs: Dict[str, Any]) β langchain.agents.agent.AgentExecutor[source]# | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-28 | Construct a sql agent from an LLM and tools.
langchain.agents.agent_toolkits.create_vectorstore_agent(llm: langchain.base_language.BaseLanguageModel, toolkit: langchain.agents.agent_toolkits.vectorstore.toolkit.VectorStoreToolkit, callback_manager: Optional[langchain.callbacks.base.BaseCallbackManager] = None, prefix: ... | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
e8f04845209a-29 | Construct a vectorstore router agent from an LLM and tools.
previous
Tools
next
Utilities
By Harrison Chase
Β© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/reference/modules/agent_toolkits.html |
caedbaa7fe5e-0 | .rst
.pdf
Document Loaders
Document Loaders#
All different types of document loaders.
class langchain.document_loaders.AZLyricsLoader(web_path: Union[str, List[str]], header_template: Optional[dict] = None)[source]#
Loader that loads AZLyrics webpages.
load() β List[langchain.schema.Document][source]#
Load webpage.
cla... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-1 | Loading logic for loading documents from Azure Blob Storage.
load() β List[langchain.schema.Document][source]#
Load documents.
class langchain.document_loaders.AzureBlobStorageFileLoader(conn_str: str, container: str, blob_name: str)[source]#
Loading logic for loading documents from Azure Blob Storage.
load() β List[la... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-2 | load() β List[langchain.schema.Document][source]#
Load bibtex file documents from the given bibtex file path.
See https://bibtexparser.readthedocs.io/en/master/
Parameters
file_path β the path to the bibtex file
Returns
a list of documents with the document.page_content in text format
class langchain.document_loaders.B... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-3 | cookie by logging into the course and then copying the value of the
BbRouter cookie from the browserβs developer tools.
Example
from langchain.document_loaders import BlackboardLoader
loader = BlackboardLoader(
blackboard_course_url="https://blackboard.example.com/webapps/blackboard/execute/announcement?method=sear... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-4 | The Loader uses the Alchemy API to interact with the blockchain.
ALCHEMY_API_KEY environment variable must be set to use this loader.
The API returns 100 NFTs per request and can be paginated using the
startToken parameter.
If get_all_tokens is set to True, the loader will get all tokens
on the contract. Note that for... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-5 | column3: value3
load() β List[langchain.schema.Document][source]#
Load data into document objects.
class langchain.document_loaders.ChatGPTLoader(log_file: str, num_logs: int = - 1)[source]#
Loader that loads conversations from exported ChatGPT data.
load() β List[langchain.schema.Document][source]#
Load data into docu... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-6 | is set to False by default, if set to True all attachments will be downloaded and
ConfluenceReader will extract the text from the attachments and add it to the
Document object. Currently supported attachment types are: PDF, PNG, JPEG/JPG,
SVG, Word and Excel.
Hint: space_key and page_id can both be found in the URL of ... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-7 | Check if a page is publicly accessible.
load(space_key: Optional[str] = None, page_ids: Optional[List[str]] = None, label: Optional[str] = None, cql: Optional[str] = None, include_restricted_content: bool = False, include_archived_content: bool = False, include_attachments: bool = False, include_comments: bool = False,... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-8 | doesnβt match the limit value. If limit is >100 confluence
seems to cap the response to 100. Also, due to the Atlassian Python
package, we donβt get the βnextβ values from the β_linksβ key because
they only return the value from the results key. So here, the pagination
starts from 0 and goes until the max_pages, getti... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-9 | Validates proper combinations of init arguments
class langchain.document_loaders.DataFrameLoader(data_frame: Any, page_content_column: str = 'text')[source]#
Load Pandas DataFrames.
load() β List[langchain.schema.Document][source]#
Load from the dataframe.
class langchain.document_loaders.DiffbotLoader(api_token: str, ... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-10 | load() β List[langchain.schema.Document][source]#
Load all chat messages.
pydantic model langchain.document_loaders.DocugamiLoader[source]#
Loader that loads processed docs from Docugami.
To use, you should have the lxml python package installed.
field access_token: Optional[str] = None#
field api: str = 'https://api.d... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-11 | are written into the page_content and none into the metadata.
load() β List[langchain.schema.Document][source]#
Load data into document objects.
class langchain.document_loaders.EverNoteLoader(file_path: str, load_single_document: bool = True)[source]#
EverNote Loader.
Loads an EverNote notebook export file e.g. my_not... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-12 | load() β List[langchain.schema.Document][source]#
Load documents.
class langchain.document_loaders.GCSFileLoader(project_name: str, bucket: str, blob: str)[source]#
Loading logic for loading documents from GCS.
load() β List[langchain.schema.Document][source]#
Load documents.
class langchain.document_loaders.GitLoader(... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-13 | A Generic Google Api Client.
To use, you should have the google_auth_oauthlib,youtube_transcript_api,google
python package installed.
As the google api expects credentials you need to set up a google account and
register your Service. βhttps://developers.google.com/docs/api/quickstart/pythonβ
Example
from langchain.doc... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-14 | from langchain.document_loaders import GoogleApiYoutubeLoader
google_api_client = GoogleApiClient(
service_account_path=Path("path_to_your_sec_file.json")
)
loader = GoogleApiYoutubeLoader(
google_api_client=google_api_client,
channel_name = "CodeAesthetic"
)
load.load()
add_video_info: bool = True#
caption... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-15 | class langchain.document_loaders.GutenbergLoader(file_path: str)[source]#
Loader that uses urllib to load .txt web files.
load() β List[langchain.schema.Document][source]#
Load file.
class langchain.document_loaders.HNLoader(web_path: Union[str, List[str]], header_template: Optional[dict] = None)[source]#
Load Hacker N... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-16 | class langchain.document_loaders.IFixitLoader(web_path: str)[source]#
Load iFixit repair guides, device wikis and answers.
iFixit is the largest, open repair community on the web. The site contains nearly
100k repair manuals, 200k Questions & Answers on 42k devices, and all the data is
licensed under CC-BY.
This loader... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-17 | Load from a list of image files
class langchain.document_loaders.JSONLoader(file_path: Union[str, pathlib.Path], jq_schema: str, content_key: Optional[str] = None, metadata_func: Optional[Callable[[Dict, Dict], Dict]] = None, text_content: bool = True)[source]#
Loads a JSON file and references a jq schema provided to l... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-18 | Load MediaWiki dump from XML file
.. rubric:: Example
from langchain.document_loaders import MWDumpLoader
loader = MWDumpLoader(
file_path="myWiki.xml",
encoding="utf8"
)
docs = loader.load()
from langchain.text_splitter import RecursiveCharacterTextSplitter
text_splitter = RecursiveCharacterTextSplitter(
c... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-19 | property url: str#
wait_for_processing(pdf_id: str) β None[source]#
class langchain.document_loaders.ModernTreasuryLoader(resource: str, organization_id: Optional[str] = None, api_key: Optional[str] = None)[source]#
load() β List[langchain.schema.Document][source]#
Load data into document objects.
class langchain.docum... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-20 | Loader that loads Obsidian files from disk.
FRONT_MATTER_REGEX = re.compile('^---\\n(.*?)\\n---\\n', re.MULTILINE|re.DOTALL)#
load() β List[langchain.schema.Document][source]#
Load documents.
pydantic model langchain.document_loaders.OneDriveLoader[source]#
field auth_with_token: bool = False#
field drive_id: str [Requ... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-21 | Eagerly load the content.
class langchain.document_loaders.PDFMinerPDFasHTMLLoader(file_path: str)[source]#
Loader that uses PDFMiner to load PDF files as HTML content.
load() β List[langchain.schema.Document][source]#
Load file.
class langchain.document_loaders.PDFPlumberLoader(file_path: str, text_kwargs: Optional[Ma... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-22 | load() β List[langchain.schema.Document][source]#
Load documents.
class langchain.document_loaders.PyMuPDFLoader(file_path: str)[source]#
Loader that uses PyMuPDF to load PDF files.
load(**kwargs: Optional[Any]) β List[langchain.schema.Document][source]#
Load file.
class langchain.document_loaders.PyPDFDirectoryLoader(... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-23 | Load Python files, respecting any non-default encoding if specified.
class langchain.document_loaders.ReadTheDocsLoader(path: Union[str, pathlib.Path], encoding: Optional[str] = None, errors: Optional[str] = None, custom_html_tag: Optional[Tuple[str, dict]] = None, **kwargs: Optional[Any])[source]#
Loader that loads Re... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-24 | Loader for .srt (subtitle) files.
load() β List[langchain.schema.Document][source]#
Load using pysrt file.
class langchain.document_loaders.SeleniumURLLoader(urls: List[str], continue_on_failure: bool = True, browser: Literal['chrome', 'firefox'] = 'chrome', binary_location: Optional[str] = None, executable_path: Optio... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-25 | Loader that fetches a sitemap and loads those URLs.
load() β List[langchain.schema.Document][source]#
Load sitemap.
parse_sitemap(soup: Any) β List[dict][source]#
Parse sitemap xml and load into a list of dicts.
class langchain.document_loaders.SlackDirectoryLoader(zip_path: str, workspace_url: Optional[str] = None)[so... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-26 | Load documents.
langchain.document_loaders.TelegramChatLoader#
alias of langchain.document_loaders.telegram.TelegramChatFileLoader
class langchain.document_loaders.TextLoader(file_path: str, encoding: Optional[str] = None, autodetect_encoding: bool = False)[source]#
Load text files.
Parameters
file_path β Path to the f... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-27 | Twitter tweets loader.
Read tweets of user twitter handle.
First you need to go to
https://developer.twitter.com/en/docs/twitter-api
/getting-started/getting-access-to-the-twitter-api
to get your token. And create a v2 version of the app.
classmethod from_bearer_token(oauth2_bearer_token: str, twitter_users: Sequence[s... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-28 | Loader that uses unstructured to load epub files.
class langchain.document_loaders.UnstructuredEmailLoader(file_path: Union[str, List[str]], mode: str = 'single', **unstructured_kwargs: Any)[source]#
Loader that uses unstructured to load email files.
class langchain.document_loaders.UnstructuredFileIOLoader(file: Union... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-29 | Loader that uses unstructured to load PDF files.
class langchain.document_loaders.UnstructuredPowerPointLoader(file_path: Union[str, List[str]], mode: str = 'single', **unstructured_kwargs: Any)[source]#
Loader that uses unstructured to load powerpoint files.
class langchain.document_loaders.UnstructuredRTFLoader(file_... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-30 | Load weather data for the given locations.
class langchain.document_loaders.WebBaseLoader(web_path: Union[str, List[str]], header_template: Optional[dict] = None)[source]#
Loader that uses urllib and beautiful soup to load webpages.
aload() β List[langchain.schema.Document][source]#
Load text from the urls in web_path ... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
caedbaa7fe5e-31 | load() β List[langchain.schema.Document][source]#
Load data into document objects.
class langchain.document_loaders.YoutubeLoader(video_id: str, add_video_info: bool = False, language: str = 'en', continue_on_failure: bool = False)[source]#
Loader that loads Youtube transcripts.
static extract_video_id(youtube_url: str... | https://python.langchain.com/en/latest/reference/modules/document_loaders.html |
25bb7d146e71-0 | .rst
.pdf
Document Transformers
Document Transformers#
Transform documents
pydantic model langchain.document_transformers.EmbeddingsRedundantFilter[source]#
Filter that drops redundant documents by comparing their embeddings.
field embeddings: langchain.embeddings.base.Embeddings [Required]#
Embeddings to use for embed... | https://python.langchain.com/en/latest/reference/modules/document_transformers.html |
98a4fcd9b56e-0 | .rst
.pdf
LLMs
LLMs#
Wrappers on top of large language models APIs.
pydantic model langchain.llms.AI21[source]#
Wrapper around AI21 large language models.
To use, you should have the environment variable AI21_API_KEY
set with your API key.
Example
from langchain.llms import AI21
ai21 = AI21(model="j2-jumbo-instruct")
V... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-1 | field numResults: int = 1#
How many completions to generate for each prompt.
field presencePenalty: langchain.llms.ai21.AI21PenaltyData = AI21PenaltyData(scale=0, applyToWhitespaces=True, applyToPunctuations=True, applyToNumbers=True, applyToStopwords=True, applyToEmojis=True)#
Penalizes repeated tokens.
field temperat... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-2 | Predict text from text.
async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β Model#
Creates a new model setting __dict__ a... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-3 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-4 | Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.AlephAlpha[source... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-5 | True: apply control by adding the log(control_factor) to attention scores.
False: (attention_scores - - attention_scores.min(-1)) * control_factor
field echo: bool = False#
Echo the prompt in the completion.
field frequency_penalty: float = 0.0#
Penalizes repeated tokens according to frequency.
field log_probs: Optiona... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-6 | field stop_sequences: Optional[List[str]] = None#
Stop sequences to use.
field temperature: float = 0.0#
A non-negative float that tunes the degree of randomness in generation.
field tokens: Optional[bool] = False#
return tokens of completion.
field top_k: int = 0#
Number of most likely tokens to consider at each step.... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-7 | Predict text from text.
async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β Model#
Creates a new model setting __dict__ a... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-8 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-9 | Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.Anthropic[source]... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-10 | Check Cache and run the LLM on the given prompt and input.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the LLM on the given pro... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-11 | Parameters
include β fields to include in new model
exclude β fields to exclude from new model, as with values this takes precedence over include
update β 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 β set to True to make a deep co... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-12 | Get the token present in the text.
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: ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-13 | Example
prompt = "Write a poem about a stream."
prompt = f"\n\nHuman: {prompt}\n\nAssistant:"
generator = anthropic.stream(prompt)
for token in generator:
yield token
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-14 | Take in a list of prompt values and return an LLMResult.
async apredict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
async apredict_messages(messages: List[langchain.schema.BaseMessage], *, stop: Optional[Sequence[str]] = None) β langchain.schema.BaseMessage#
Predict message from m... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-15 | Run the LLM on the given prompt and input.
generate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a list of p... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-16 | Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
classmethod update_forward_refs(**localns: Any) β None#
Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.AzureOpenAI[sourc... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-17 | Adjust the probability of specific tokens being generated.
field max_retries: int = 6#
Maximum number of retries to make when generating.
field max_tokens: int = 256#
The maximum number of tokens to generate in the completion.
-1 returns as many tokens as possible given the prompt and
the models maximal context size.
f... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-18 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-19 | deep β set to True to make a deep copy of the model
Returns
new model instance
create_llm_result(choices: Any, prompts: List[str], token_usage: Dict[str, int]) β langchain.schema.LLMResult#
Create the LLMResult from the choices and prompts.
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: L... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-20 | Get the token IDs using the tiktoken package.
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, exc... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-21 | Prepare the params for streaming.
save(file_path: Union[pathlib.Path, str]) β None#
Save the LLM.
Parameters
file_path β Path to file to save the LLM to.
Example:
.. code-block:: python
llm.save(file_path=βpath/llm.yamlβ)
stream(prompt: str, stop: Optional[List[str]] = None) β Generator#
Call OpenAI with streaming flag... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-22 | field verbose: bool [Optional]#
Whether to print out response text.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β str#
Check Cache and run the LLM on the given prompt and inpu... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-23 | Behaves as if Config.extra = βallowβ 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) β Model#
Duplicate a model, optionally... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-24 | get_token_ids(text: str) β List[int]#
Get the token present in the text.
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_... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-25 | and BEAM_CLIENT_SECRET set with your client secret. Information on how
to get these is available here: https://docs.beam.cloud/account/api-keys.
The wrapper can then be called as follows, where the name, cpu, memory, gpu,
python version, and python packages can be updated accordingly. Once deployed,
the instance can be... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-26 | Run the LLM on the given prompt and input.
async agenerate_prompt(prompts: List[langchain.schema.PromptValue], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Take in a li... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-27 | the new model: you should trust this data
deep β set to True to make a deep copy of the model
Returns
new model instance
dict(**kwargs: Any) β Dict#
Return a dictionary of the LLM.
generate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler]... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-28 | 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().
predict(text: str, *, stop: Optional[Sequence[str]] = None) β str#
Predict text from text.
predict_messages(messages: List[... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-29 | field model: str [Required]#
The path to a model file or directory or the name of a Hugging Face Hub
model repo.
field model_file: Optional[str] = None#
The name of the model file in repo or directory.
field model_type: Optional[str] = None#
The model type.
field verbose: bool [Optional]#
Whether to print out response ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-30 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = βallowβ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-31 | Get the number of tokens in the message.
get_token_ids(text: str) β List[int]#
Get the token present in the text.
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = No... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-32 | environment variable CEREBRIUMAI_API_KEY set with your API key.
Any parameters that are valid to be passed to the call can be passed
in, even if not explicitly saved on this class.
Example
Validators
build_extra Β» all fields
raise_deprecation Β» all fields
set_verbose Β» verbose
validate_environment Β» all fields
field en... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-33 | Predict message from messages.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) β 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 = βallowβ was set ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-34 | Take in a list of prompt values and return an LLMResult.
get_num_tokens(text: str) β int#
Get the number of tokens present in the text.
get_num_tokens_from_messages(messages: List[langchain.schema.BaseMessage]) β int#
Get the number of tokens in the message.
get_token_ids(text: str) β List[int]#
Get the token present i... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-35 | Try to update ForwardRefs on fields based on this Model, globalns and localns.
pydantic model langchain.llms.Cohere[source]#
Wrapper around Cohere large language models.
To use, you should have the cohere python package installed, and the
environment variable COHERE_API_KEY set with your API key, or pass
it as a named ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-36 | Check Cache and run the LLM on the given prompt and input.
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None) β langchain.schema.LLMResult#
Run the LLM on the given pro... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-37 | Parameters
include β fields to include in new model
exclude β fields to exclude from new model, as with values this takes precedence over include
update β 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 β set to True to make a deep co... | https://python.langchain.com/en/latest/reference/modules/llms.html |
98a4fcd9b56e-38 | Get the token present in the text.
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: ... | https://python.langchain.com/en/latest/reference/modules/llms.html |
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