id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
49d14c486324-12 | save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to save the chain to.
Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
49d14c486324-13 | Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A sequence of runnables to try if the original runnable fails.
exceptions_to_handle – A tuple of exception types to handle.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
with_liste... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
49d14c486324-14 | Bind input and output types to a Runnable, returning a new Runnable.
property InputType: Type[langchain.schema.runnable.utils.Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
The type of output this runnable produces speci... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
1cacc2bd76c1-0 | langchain.chains.retrieval_qa.base.RetrievalQA¶
class langchain.chains.retrieval_qa.base.RetrievalQA[source]¶
Bases: BaseRetrievalQA
Chain for question-answering against an index.
Example
from langchain.llms import OpenAI
from langchain.chains import RetrievalQA
from langchain.vectorstores import FAISS
from langchain.s... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-1 | for the full catalog.
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the chain. Defaults to None.
This metadata will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a cha... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-2 | response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-3 | Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys generated by this chai... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-4 | Call the chain on all inputs in the list.
async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-5 | # -> "The temperature in Boise is..."
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, conf... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-6 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-7 | Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creat... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-8 | This method allows to get an input schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate input.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langcha... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-9 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
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_defa... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-10 | Parameters
inputs – Dictionary of raw inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
Returns
A dictionary of all inputs, including those added by the chain’s memory.
prep_outputs(inputs: Dict[str,... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-11 | these runtime tags will propagate to calls to other objects.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'question' string:
chain.run("What's the temperature in Boise, Idaho?")... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-12 | Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing output while
input is still being generated.
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and lo... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-13 | added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
Create a new Runnable that retries the original runnable on exceptions.
Parameters
retry_if_exc... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
1cacc2bd76c1-14 | property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model.
Examples using RetrievalQA¶
Cohere Reranker
Ollama
Confident
Document Comparison
ScaNN
Activeloop Deep Lake
StarRocks
your local model path
Loading documents from a YouTube url
Docugami
Questi... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.RetrievalQA.html |
4712a26c9569-0 | langchain.chains.prompt_selector.is_llm¶
langchain.chains.prompt_selector.is_llm(llm: BaseLanguageModel) → bool[source]¶
Check if the language model is a LLM.
Parameters
llm – Language model to check.
Returns
True if the language model is a BaseLLM model, False otherwise. | lang/api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.is_llm.html |
db3902f76c0a-0 | langchain.chains.graph_qa.cypher_utils.Schema¶
class langchain.chains.graph_qa.cypher_utils.Schema(left_node, relation, right_node)¶
Create new instance of Schema(left_node, relation, right_node)
Attributes
left_node
Alias for field number 0
relation
Alias for field number 1
right_node
Alias for field number 2
Methods
... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher_utils.Schema.html |
2a219f70acc9-0 | langchain.chains.qa_with_sources.base.QAWithSourcesChain¶
class langchain.chains.qa_with_sources.base.QAWithSourcesChain[source]¶
Bases: BaseQAWithSourcesChain
Question answering with sources over documents.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the in... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-1 | Optional list of tags associated with the chain. Defaults to None.
These tags will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param verbose: bool [Optional]¶
Whether or not r... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-2 | metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-3 | these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-4 | callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the c... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-5 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-6 | e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶
The type of config this runnable accepts specified as a pydantic m... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-7 | 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(**kw... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-8 | classmethod from_llm(llm: BaseLanguageModel, document_prompt: BasePromptTemplate = PromptTemplate(input_variables=['page_content', 'source'], template='Content: {page_content}\nSource: {source}'), question_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], template='Use the following p... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-9 | Agreement.\n\n11.8 No Agency. Except as expressly stated otherwise, nothing in this Agreement shall create an agency, partnership or joint venture of any kind between the parties.\n\n11.9 No Third-Party Beneficiaries.\nSource: 30-pl\nContent: (b) if Google believes, in good faith, that the Distributor has violated or ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-10 | tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland.\nSource: 0-pl\nContent: And we won’t stop. \n\nWe have lost so much to COVID-19. Time with one another. And worst of all, so much loss of life. \n\nLet’s use this moment to reset. Let’s stop looking at COVID-1... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-11 | world. \n\nAnd I’m taking robust action to make sure the pain of our sanctions is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers. \n\nTonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-12 | of resolve and conscience, of history itself. \n\nIt is in this moment that our character is formed. Our purpose is found. Our future is forged. \n\nWell I know this nation.\nSource: 34-pl\n=========\nFINAL ANSWER: The president did not mention Michael Jackson.\nSOURCES:\n\nQUESTION: {question}\n=========\n{summaries}\... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-13 | Construct the chain from an LLM.
classmethod from_orm(obj: Any) → Model¶
get_input_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate input to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-14 | The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
classmethod is_lc_serializable() → bool¶
Is this class serializable?... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-15 | 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¶
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prepare chain inputs, including ad... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-16 | sole positional argument.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
additi... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-17 | Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = No... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-18 | on_start: Called before the runnable starts running, with the Run object.
on_end: Called after the runnable finishes running, with the Run object.
on_error: Called if the runnable throws an error, with the Run object.
The Run object contains information about the run, including its id,
type, input, output, error, start... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
2a219f70acc9-19 | property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: T... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.base.QAWithSourcesChain.html |
33771474f6eb-0 | langchain.chains.api.base.APIChain¶
class langchain.chains.api.base.APIChain[source]¶
Bases: Chain
Chain that makes API calls and summarizes the responses to answer a question.
Security Note: This API chain uses the requests toolkitto make GET, POST, PATCH, PUT, and DELETE requests to an API.
Exercise care in who is al... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-1 | The default value is an empty tuple, which means that no domains are
allowed by default. By design this will raise an error on instantiation.
Use a None if you want to allow all domains by default – this is not
recommended for security reasons, as it would allow malicious users to
make requests to arbitrary URLS includ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-2 | accessible via langchain.globals.get_verbose().
__call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name: Optional[str] = Non... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-3 | Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
async acall(inputs: Union[Dict... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-4 | Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, calls invoke from a thread.
The default implementation allows usage of async code e... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-5 | directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'question' string:
await chain.arun("What's the temperature in Boise, Idaho?")
# -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' s... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-6 | The jsonpatch ops can be applied in order to construct state.
async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if th... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-7 | classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-8 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm_and_api_docs(llm: BaseLanguageModel, api_docs: str, headers: Optional[dict] = None, api_url_prompt: BasePromptTemplate = PromptTemplate(input_variables=['api_docs', 'question'], template='You are given the below API Documentation:\n{api_docs}\nUsing this... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-9 | Get a pydantic model that can be used to validate input to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic input schema that depends on which
configuration the runnable is invoked with.
This method allows to get an input schema for a specific confi... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-10 | for more details.
Returns
The output of the runnable.
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[b... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-11 | Validate and prepare chain inputs, including adding inputs from memory.
Parameters
inputs – Dictionary of raw inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
Returns
A dictionary of all inputs, inc... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-12 | addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'que... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-13 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-14 | The Run object contains information about the run, including its id,
type, input, output, error, start_time, end_time, and any tags or metadata
added to the run.
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_af... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
33771474f6eb-15 | A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶
The type of output this runnable produces specified as a pydantic model.
Examples using APIChain¶
Set env var OPENAI_API_KEY or load from a .env file: | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
f2ec6844bed4-0 | langchain.chains.openai_functions.tagging.create_tagging_chain¶
langchain.chains.openai_functions.tagging.create_tagging_chain(schema: dict, llm: BaseLanguageModel, prompt: Optional[ChatPromptTemplate] = None, **kwargs: Any) → Chain[source]¶
Creates a chain that extracts information from a passagebased on a schema.
Par... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.tagging.create_tagging_chain.html |
1b2c409dcba2-0 | langchain.chains.graph_qa.neptune_cypher.use_simple_prompt¶
langchain.chains.graph_qa.neptune_cypher.use_simple_prompt(llm: BaseLanguageModel) → bool[source]¶
Decides whether to use the simple prompt | lang/api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.neptune_cypher.use_simple_prompt.html |
ebc5e140de6b-0 | langchain.chains.api.openapi.response_chain.APIResponderOutputParser¶
class langchain.chains.api.openapi.response_chain.APIResponderOutputParser[source]¶
Bases: BaseOutputParser
Parse the response and error tags.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-1 | to be different candidate outputs for a single model input.
Returns
Structured output.
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support str... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-2 | Default implementation runs invoke in parallel using a thread pool executor.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
bind(**kwargs: Any) → R... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-3 | Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creat... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-4 | methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate output.
invoke(input:... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-5 | The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
parse(llm_output: str) → str[source]¶
Parse the response and error tags.
classmethod ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-6 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-7 | fallback in order, upon failures.
with_listeners(*, on_start: Optional[Listener] = None, on_end: Optional[Listener] = None, on_error: Optional[Listener] = None) → Runnable[Input, Output]¶
Bind lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Called before the runnable starts running, with the Run ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
ebc5e140de6b-8 | The type of output this runnable produces specified as a type annotation.
property config_specs: List[langchain.schema.runnable.utils.ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[pydantic.main.BaseModel]¶
The type of input this runnable accepts specified as a pydantic ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderOutputParser.html |
5d133586bda1-0 | langchain.chains.query_constructor.base.construct_examples¶
langchain.chains.query_constructor.base.construct_examples(input_output_pairs: Sequence[Tuple[str, dict]]) → List[dict][source]¶
Construct examples from input-output pairs.
Parameters
input_output_pairs – Sequence of input-output pairs.
Returns
List of example... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.base.construct_examples.html |
4e4c49c0d077-0 | langchain.chains.query_constructor.ir.FilterDirective¶
class langchain.chains.query_constructor.ir.FilterDirective[source]¶
Bases: Expr, ABC
A filtering expression.
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 m... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.FilterDirective.html |
4e4c49c0d077-1 | 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/chains/langchain.chains.query_constructor.ir.FilterDirective.html |
4e4c49c0d077-2 | 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/chains/langchain.chains.query_constructor.ir.FilterDirective.html |
46835656825e-0 | langchain.chains.openai_functions.citation_fuzzy_match.create_citation_fuzzy_match_chain¶
langchain.chains.openai_functions.citation_fuzzy_match.create_citation_fuzzy_match_chain(llm: BaseLanguageModel) → LLMChain[source]¶
Create a citation fuzzy match chain.
Parameters
llm – Language model to use for the chain.
Return... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.citation_fuzzy_match.create_citation_fuzzy_match_chain.html |
f97c36ff59b4-0 | langchain.chains.llm.LLMChain¶
class langchain.chains.llm.LLMChain[source]¶
Bases: Chain
Chain to run queries against LLMs.
Example
from langchain.chains import LLMChain
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-1 | for the full catalog.
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the chain. Defaults to None.
This metadata will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a cha... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-2 | Execute the chain.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys gen... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-3 | Call apply and then parse the results.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-4 | these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async agener... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-5 | Completion from LLM.
Example
completion = llm.predict(adjective="funny")
async apredict_and_parse(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Union[str, List[str], Dict[str, str]][source]¶
Call apredict and then parse the results.
async aprep_prompts(input_list: L... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-6 | Example
# Suppose we have a single-input chain that takes a 'question' string:
await chain.arun("What's the temperature in Boise, Idaho?")
# -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-7 | The jsonpatch ops can be applied in order to construct state.
async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if th... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-8 | classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-9 | Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult[source]¶
Generate LLM result from inputs.
get_input_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-10 | Parameters
input – The input to the runnable.
config – A config to use when invoking the runnable.
The config supports standard keys like ‘tags’, ‘metadata’ for tracing
purposes, ‘max_concurrency’ for controlling how much work to do
in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Retur... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-11 | 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¶
predict(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → str[s... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-12 | inputs are also added to the final outputs.
Returns
A dict of the final chain outputs.
prep_prompts(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → Tuple[List[PromptValue], Optional[List[str]]][source]¶
Prepare prompts from inputs.
run(*args: Any, callbacks: Optional[Union[... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-13 | # and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
chain.run(question=question, context=context)
# -> "The temperature in Boise is..."
save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be i... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-14 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'Exception'>,)) → RunnableWithFallbacksT[Input, Output]¶
Add fallbacks to a runnable, returning a new Runnable.
Parameters
fallbacks – A se... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-15 | between retries
stop_after_attempt – The maximum number of attempts to make before giving up
Returns
A new Runnable that retries the original runnable on exceptions.
with_types(*, input_type: Optional[Type[Input]] = None, output_type: Optional[Type[Output]] = None) → Runnable[Input, Output]¶
Bind input and output types... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
f97c36ff59b4-16 | Predibase
Eden AI
Azure ML
Removing logical fallacies from model output
Amazon Comprehend Moderation Chain
Custom Trajectory Evaluator
Custom Pairwise Evaluator
Set env var OPENAI_API_KEY or load from a .env file:
Set env var OPENAI_API_KEY or load from a .env file
Retrieve from vector stores directly
Improve document ... | lang/api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
2b5407e0f812-0 | langchain.vectorstores.rocksetdb.Rockset¶
class langchain.vectorstores.rocksetdb.Rockset(client: Any, embeddings: Embeddings, collection_name: str, text_key: str, embedding_key: str, workspace: str = 'commons')[source]¶
Rockset vector store.
To use, you should have the rockset python package installed. Note that to use... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-1 | Attributes
embeddings
Access the query embedding object if available.
Methods
__init__(client, embeddings, ...[, workspace])
Initialize with Rockset client. :param client: Rockset client object :param collection: Rockset collection to insert docs / query :param embeddings: Langchain Embeddings object to use to generate... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-2 | Return docs most similar to query using specified search type.
asimilarity_search(query[, k])
Return docs most similar to query.
asimilarity_search_by_vector(embedding[, k])
Return docs most similar to embedding vector.
asimilarity_search_with_relevance_scores(query)
Return docs and relevance scores in the range [0, 1]... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-3 | similarity_search_with_score(*args, **kwargs)
Run similarity search with distance.
__init__(client: Any, embeddings: Embeddings, collection_name: str, text_key: str, embedding_key: str, workspace: str = 'commons')[source]¶
Initialize with Rockset client.
:param client: Rockset client object
:param collection: Rockset c... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-4 | Run more texts through the embeddings and add to the vectorstore
Args:
texts: Iterable of strings to add to the vectorstore.
metadatas: Optional list of metadatas associated with the texts.
ids: Optional list of ids to associate with the texts.
batch_size: Send documents in batches to rockset.
Returns
List of ids from ... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-5 | as_retriever(**kwargs: Any) → VectorStoreRetriever¶
Return VectorStoreRetriever initialized from this VectorStore.
Parameters
search_type (Optional[str]) – Defines the type of search that
the Retriever should perform.
Can be “similarity” (default), “mmr”, or
“similarity_score_threshold”.
search_kwargs (Optional[Dict]) ... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-6 | docsearch.as_retriever(search_kwargs={'k': 1})
# Use a filter to only retrieve documents from a specific paper
docsearch.as_retriever(
search_kwargs={'filter': {'paper_title':'GPT-4 Technical Report'}}
)
async asearch(query: str, search_type: str, **kwargs: Any) → List[Document]¶
Return docs most similar to query u... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-7 | **kwargs – Other keyword arguments that subclasses might use.
Returns
True if deletion is successful,
False otherwise, None if not implemented.
Return type
Optional[bool]
delete_texts(ids: List[str]) → None[source]¶
Delete a list of docs from the Rockset collection
classmethod from_documents(documents: List[Document], ... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-8 | Defaults to 0.5.
Returns
List of Documents selected by maximal marginal relevance.
max_marginal_relevance_search_by_vector(embedding: List[float], k: int = 4, fetch_k: int = 20, lambda_mult: float = 0.5, **kwargs: Any) → List[Document]¶
Return docs selected using the maximal marginal relevance.
Maximal marginal relevan... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
2b5407e0f812-9 | Accepts a query_embedding (vector), and returns documents with
similar embeddings.
similarity_search_by_vector_with_relevance_scores(embedding: List[float], k: int = 4, distance_func: DistanceFunction = DistanceFunction.COSINE_SIM, where_str: Optional[str] = None, **kwargs: Any) → List[Tuple[Document, float]][source]¶
... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.rocksetdb.Rockset.html |
1410f7059d9e-0 | langchain.vectorstores.azure_cosmos_db.CosmosDBSimilarityType¶
class langchain.vectorstores.azure_cosmos_db.CosmosDBSimilarityType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)[source]¶
Cosmos DB Similarity Type as enumerator.
COS = 'COS'¶
CosineSimilarity
IP = 'IP'¶
inner - produ... | lang/api.python.langchain.com/en/latest/vectorstores/langchain.vectorstores.azure_cosmos_db.CosmosDBSimilarityType.html |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.