id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
408ec4da345f-7 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
408ec4da345f-8 | 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,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
408ec4da345f-9 | 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?")... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
408ec4da345f-10 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
f5b78b92b09d-0 | langchain.chains.graph_qa.arangodb.ArangoGraphQAChain¶
class langchain.chains.graph_qa.arangodb.ArangoGraphQAChain[source]¶
Bases: Chain
Chain for question-answering against a graph by generating AQL statements.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if th... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-1 | 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 qa_chain: LLMChain [Required]¶
param return_aql_query: bool = False¶
param return_aql_result: bool = False¶
param tags: Optional[List[str]] = None¶
Optional list of tags... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-2 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-3 | 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
these runtime callbacks will propagate to calls to other objects.... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-4 | with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as the
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 call... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-5 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-6 | 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
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-7 | classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['adb_schema', 'user_input', 'aql_query', 'aql_result'], template="Task: Generate a natural language `Summary` from the results of an ArangoDB Query Language query.\n\nYou are an ArangoDB Query Language (AQL) ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-8 | 'aql_examples', 'user_input'], template="Task: Generate an ArangoDB Query Language (AQL) query from a User Input.\n\nYou are an ArangoDB Query Language (AQL) expert responsible for translating a `User Input` into an ArangoDB Query Language (AQL) query.\n\nYou are given an `ArangoDB Schema`. It is a JSON Object containi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-9 | the `AQL Query Examples`. \n- Do not include any text except the generated AQL Query.\n- Do not provide explanations or apologies in your responses.\n- Do not generate an AQL Query that removes or deletes any data.\n\nUnder no circumstance should you generate an AQL Query that deletes any data whatsoever.\n\nArangoDB S... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-10 | Query` wrapped in 3 backticks (```). Do not include any text except the Corrected AQL Query.\n\nRemember to think step by step.\n\nArangoDB Schema:\n{adb_schema}\n\nAQL Query:\n{aql_query}\n\nAQL Error:\n{aql_error}\n\nCorrected AQL Query:\n"), **kwargs: Any) → ArangoGraphQAChain[source]¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-11 | Initialize from LLM.
classmethod from_orm(obj: Any) → Model¶
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
invoke(input: Dict[str, Any], config: Optional[RunnableConf... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-12 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-13 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-14 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
f5b78b92b09d-15 | property input_schema: Type[pydantic.main.BaseModel]¶
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.arangodb.ArangoGraphQAChain.html |
7f394f28d00a-0 | langchain.chains.llm_bash.base.LLMBashChain¶
class langchain.chains.llm_bash.base.LLMBashChain[source]¶
Bases: Chain
Chain that interprets a prompt and executes bash operations.
Example
from langchain.chains import LLMBashChain
from langchain.llms import OpenAI
llm_bash = LLMBashChain.from_llm(OpenAI())
Create a new mo... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-1 | 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 prompt: BasePromptTemplate = PromptTemplate(input_variables=['question'], output_parser=BashOutputParser(), template='If someone asks you to perform a task, your job is ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-2 | will be printed to the console. Defaults to langchain.verbose value.
__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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-3 | Default implementation of abatch, which calls ainvoke N times.
Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optiona... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-4 | Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Call the chain on all inputs i... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-5 | # Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in Boise is..."
async astream(input: Inp... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-6 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override this method if they can ba... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-7 | **kwargs – Keyword arguments passed to default pydantic.BaseModel.dict
method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, prompt: BasePromptTemplate = PromptTemplate(input_variables=['... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-8 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-9 | 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,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-10 | 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?")... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
7f394f28d00a-11 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_bash.base.LLMBashChain.html |
a0b74736f51f-0 | langchain.chains.retrieval_qa.base.BaseRetrievalQA¶
class langchain.chains.retrieval_qa.base.BaseRetrievalQA[source]¶
Bases: Chain
Base class for question-answering chains.
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-1 | Return the source documents or not.
param tags: Optional[List[str]] = None¶
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-2 | 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 abatch... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-3 | 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 chain. Defaults to None
include_run_info – Whether to include run ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-4 | 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.
**kwargs – If the chain expects multiple inputs, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-5 | This includes all inner runs of LLMs, Retrievers, Tools, etc.
Output is streamed as Log objects, which include a list of
jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
The jsonpatch ops can be applied in order to construct state.
async atransform(input: As... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-6 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-7 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-8 | 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,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-9 | 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?")... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
a0b74736f51f-10 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
53f8464c8883-0 | langchain.chains.prompt_selector.BasePromptSelector¶
class langchain.chains.prompt_selector.BasePromptSelector[source]¶
Bases: BaseModel, ABC
Base class for prompt selectors.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form... | https://api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.BasePromptSelector.html |
53f8464c8883-1 | Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
classmethod from_orm(obj: Any) → Model¶
abstract get_prompt(llm: BaseLanguageModel) → BasePromptTemplate[source]¶
Get default prompt for a language model.
json(*, include: Optional[Union[AbstractSetIntStr, Mappi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.BasePromptSelector.html |
53f8464c8883-2 | Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.BasePromptSelector.html |
7c66680ae3ea-0 | langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain¶
class langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain[source]¶
Bases: BaseQAWithSourcesChain
Question-answering with sources over a vector database.
Create a new model by parsing and validating input data from keyword arguments... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-1 | 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 chain with its use case.
param reduce_k_below_max_tokens: bool = False¶
Reduce the number of results to return from store based on tokens... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-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
... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-3 | 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 chain will be
returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-4 | The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-5 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-6 | 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
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-7 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-8 | 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 ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-9 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-10 | 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 ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-11 | 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}\... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-12 | Construct the chain from an LLM.
classmethod from_orm(obj: Any) → Model¶
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
invoke(input: Dict[str, Any], config: Optional[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-13 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-14 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-15 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
7c66680ae3ea-16 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.vector_db.VectorDBQAWithSourcesChain.html |
2e5ff60a4e2d-0 | langchain.chains.llm_math.base.LLMMathChain¶
class langchain.chains.llm_math.base.LLMMathChain[source]¶
Bases: Chain
Chain that interprets a prompt and executes python code to do math.
Example
from langchain.chains import LLMMathChain
from langchain.llms import OpenAI
llm_math = LLMMathChain.from_llm(OpenAI())
Create a... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-1 | 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 prompt: BasePromptTemplate = PromptTemplate(input_variables=['question'], template='Translate a math problem into a expression that can be executed using Python\'s numex... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-2 | will be printed to the console. Defaults to langchain.verbose value.
__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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-3 | Default implementation of abatch, which calls ainvoke N times.
Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optiona... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-4 | Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Call the chain on all inputs i... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-5 | # Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in Boise is..."
async astream(input: Inp... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-6 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override this method if they can ba... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-7 | **kwargs – Keyword arguments passed to default pydantic.BaseModel.dict
method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, prompt: BasePromptTemplate = PromptTemplate(input_variables=['... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-8 | namespace is [“langchain”, “llms”, “openai”]
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-9 | prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
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 ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-10 | 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.
**kwargs – If the chain expects multiple inputs, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-11 | to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
2e5ff60a4e2d-12 | 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: Type[pydantic.main.BaseModel]¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm_math.base.LLMMathChain.html |
5293a8ab6241-0 | langchain.chains.transform.TransformChain¶
class langchain.chains.transform.TransformChain[source]¶
Bases: Chain
Chain that transforms the chain output.
Example
from langchain.chains import TransformChain
transform_chain = TransformChain(input_variables=["text"],
output_variables["entities"], transform=func())
Create ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-1 | 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 output_variables: List[str] [Required]¶
The keys returned by the transform’s output dictionary.
param tags: Optional[List[str]] = None¶
Optional list of tags associated ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-2 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-3 | 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
these runtime callbacks will propagate to calls to other objects.... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-4 | with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as the
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 call... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-5 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-6 | 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
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-7 | namespace is [“langchain”, “llms”, “openai”]
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-8 | prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
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 ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-9 | 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.
**kwargs – If the chain expects multiple inputs, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-10 | to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
5293a8ab6241-11 | 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: Type[pydantic.main.BaseModel]¶
Examples using TransformChain¶
Zapier Natural Language Actions
Rebuff
Transformation | https://api.python.langchain.com/en/latest/chains/langchain.chains.transform.TransformChain.html |
7c7123bffa6c-0 | langchain.chains.qa_with_sources.loading.LoadingCallable¶
class langchain.chains.qa_with_sources.loading.LoadingCallable(*args, **kwargs)[source]¶
Interface for loading the combine documents chain.
Methods
__init__(*args, **kwargs)
__init__(*args, **kwargs)¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.loading.LoadingCallable.html |
788699c76a0e-0 | langchain.chains.graph_qa.falkordb.extract_cypher¶
langchain.chains.graph_qa.falkordb.extract_cypher(text: str) → str[source]¶
Extract Cypher code from a text.
:param text: Text to extract Cypher code from.
Returns
Cypher code extracted from the text. | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.falkordb.extract_cypher.html |
1bb5a3c9fec6-0 | langchain.chains.query_constructor.ir.Visitor¶
class langchain.chains.query_constructor.ir.Visitor[source]¶
Defines interface for IR translation using visitor pattern.
Attributes
allowed_comparators
allowed_operators
Methods
__init__()
visit_comparison(comparison)
Translate a Comparison.
visit_operation(operation)
Tran... | https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.Visitor.html |
4dec27c69f0b-0 | langchain.chains.graph_qa.hugegraph.HugeGraphQAChain¶
class langchain.chains.graph_qa.hugegraph.HugeGraphQAChain[source]¶
Bases: Chain
Chain for question-answering against a graph by generating gremlin statements.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-1 | param tags: Optional[List[str]] = None¶
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 ve... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-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, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-3 | 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 chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Sho... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-4 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-5 | jsonpatch ops that describe how the state of the run has changed in each
step, and the final state of the run.
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 im... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-6 | 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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-7 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], template="You are an assistant that helps to form nice and human understandable answers.\nThe information part contains the provided inform... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-8 | namespace is [“langchain”, “llms”, “openai”]
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
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