id stringlengths 14 15 | text stringlengths 35 2.51k | source stringlengths 61 154 |
|---|---|---|
b0744d6ee3b7-4 | Save the chain.
Parameters
file_path – Path to file to save the chain to.
Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
validator set_verbose » verbose¶
If verbose is None, set it.
This allows users to pass in None as verbose to access the global setting.
to_json() → Union[SerializedConstruc... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
85ca7adfb0f6-0 | langchain.chains.graph_qa.base.GraphQAChain¶
class langchain.chains.graph_qa.base.GraphQAChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[str]... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.base.GraphQAChain.html |
85ca7adfb0f6-1 | for the full catalog.
param qa_chain: LLMChain [Required]¶
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 ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.base.GraphQAChain.html |
85ca7adfb0f6-2 | Run the logic of this chain and add to output if desired.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param.
return_only_outputs – boolean for whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input key... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.base.GraphQAChain.html |
85ca7adfb0f6-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of chain.
classmethod from_llm(llm: BaseLanguageModel, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], output_parser=None, partial_variables={}, template="Use the following knowledge triplets to answer the question at t... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.base.GraphQAChain.html |
85ca7adfb0f6-4 | Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, **kwargs: Any) → str¶
Run the chain as text in, text out or m... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.base.GraphQAChain.html |
639d2f26babf-0 | langchain.chains.combine_documents.map_reduce.CombineDocsProtocol¶
class langchain.chains.combine_documents.map_reduce.CombineDocsProtocol(*args, **kwargs)[source]¶
Bases: Protocol
Interface for the combine_docs method.
Methods
__init__(*args, **kwargs)
__call__(docs: List[Document], **kwargs: Any) → str[source]¶
Inter... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.CombineDocsProtocol.html |
43f36e65a644-0 | langchain.chains.openai_functions.utils.get_llm_kwargs¶
langchain.chains.openai_functions.utils.get_llm_kwargs(function: dict) → dict[source]¶
Returns the kwargs for the LLMChain constructor.
Parameters
function – The function to use.
Returns
The kwargs for the LLMChain constructor. | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.utils.get_llm_kwargs.html |
5a88a6286c0e-0 | langchain.chains.summarize.__init__.LoadingCallable¶
class langchain.chains.summarize.__init__.LoadingCallable(*args, **kwargs)[source]¶
Bases: Protocol
Interface for loading the combine documents chain.
Methods
__init__(*args, **kwargs)
__call__(llm: BaseLanguageModel, **kwargs: Any) → BaseCombineDocumentsChain[source... | https://api.python.langchain.com/en/latest/chains/langchain.chains.summarize.__init__.LoadingCallable.html |
60784b7959c0-0 | langchain.chains.openai_functions.qa_with_structure.AnswerWithSources¶
class langchain.chains.openai_functions.qa_with_structure.AnswerWithSources(*, answer: str, sources: List[str])[source]¶
Bases: BaseModel
An answer to the question being asked, with sources.
Create a new model by parsing and validating input data fr... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.qa_with_structure.AnswerWithSources.html |
4142e99ebd0f-0 | langchain.chains.openai_functions.openapi.openapi_spec_to_openai_fn¶
langchain.chains.openai_functions.openapi.openapi_spec_to_openai_fn(spec: OpenAPISpec) → Tuple[List[Dict[str, Any]], Callable][source]¶
Convert a valid OpenAPI spec to the JSON Schema format expected for OpenAIfunctions.
Parameters
spec – OpenAPI spec... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.openapi.openapi_spec_to_openai_fn.html |
f26b3c203cc6-0 | langchain.chains.query_constructor.base.load_query_constructor_chain¶
langchain.chains.query_constructor.base.load_query_constructor_chain(llm: BaseLanguageModel, document_contents: str, attribute_info: List[AttributeInfo], examples: Optional[List] = None, allowed_comparators: Optional[Sequence[Comparator]] = None, all... | https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.base.load_query_constructor_chain.html |
c7d457087ea7-0 | langchain.chains.prompt_selector.is_chat_model¶
langchain.chains.prompt_selector.is_chat_model(llm: BaseLanguageModel) → bool[source]¶
Check if the language model is a chat model.
Parameters
llm – Language model to check.
Returns
True if the language model is a BaseChatModel model, False otherwise. | https://api.python.langchain.com/en/latest/chains/langchain.chains.prompt_selector.is_chat_model.html |
ffeb72b46431-0 | langchain.chains.natbot.crawler.ElementInViewPort¶
class langchain.chains.natbot.crawler.ElementInViewPort[source]¶
Bases: TypedDict
A typed dictionary containing information about elements in the viewport.
Methods
__init__(*args, **kwargs)
clear()
copy()
fromkeys([value])
Create a new dictionary with keys from iterabl... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.crawler.ElementInViewPort.html |
ffeb72b46431-1 | Return the value for key if key is in the dictionary, else default.
items() → a set-like object providing a view on D's items¶
keys() → a set-like object providing a view on D's keys¶
pop(k[, d]) → v, remove specified key and return the corresponding value.¶
If the key is not found, return the default if given; otherwi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.crawler.ElementInViewPort.html |
a9bb84cfdfdd-0 | langchain.chains.openai_functions.openapi.SimpleRequestChain¶
class langchain.chains.openai_functions.openapi.SimpleRequestChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: boo... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.openapi.SimpleRequestChain.html |
a9bb84cfdfdd-1 | 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 run in verbose mode. In verbose mode, some intermediate logs
will be... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.openapi.SimpleRequestChain.html |
a9bb84cfdfdd-2 | only one param.
return_only_outputs – boolean for 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 – Callbacks to use for this chain run. If not p... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.openapi.SimpleRequestChain.html |
a9bb84cfdfdd-3 | Save the chain.
Parameters
file_path – Path to file to save the chain to.
Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
validator set_verbose » verbose¶
If verbose is None, set it.
This allows users to pass in None as verbose to access the global setting.
to_json() → Union[SerializedConstruc... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.openapi.SimpleRequestChain.html |
ec41bba49000-0 | langchain.chains.retrieval_qa.base.VectorDBQA¶
class langchain.chains.retrieval_qa.base.VectorDBQA(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.VectorDBQA.html |
ec41bba49000-1 | and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param return_source_documents: bool = False¶
Return the source documents.
param sea... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.VectorDBQA.html |
ec41bba49000-2 | chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.VectorDBQA.html |
ec41bba49000-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of chain.
classmethod from_chain_type(llm: BaseLanguageModel, chain_type: str = 'stuff', chain_type_kwargs: Optional[dict] = None, **kwargs: Any) → BaseRetrievalQA¶
Load chain from chain type.
classmethod from_llm(llm: BaseLanguageModel, prompt: Optional[Prom... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.VectorDBQA.html |
ec41bba49000-4 | Validate search type.
property lc_attributes: Dict¶
Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str]¶
Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_sec... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.VectorDBQA.html |
58c292427124-0 | langchain.chains.graph_qa.kuzu.KuzuQAChain¶
class langchain.chains.graph_qa.kuzu.KuzuQAChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[str]] ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.html |
58c292427124-1 | There are many different types of memory - please see memory docs
for the full catalog.
param qa_chain: LLMChain [Required]¶
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 th... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.html |
58c292427124-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.html |
58c292427124-3 | classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], output_parser=None, partial_variables={}, template="You are an assistant that helps to form nice and human understandable answers.\nThe information part contains the provided informati... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.html |
58c292427124-4 | Cypher statement.\n\nThe question is:\n{question}', template_format='f-string', validate_template=True), **kwargs: Any) → KuzuQAChain[source]¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.html |
58c292427124-5 | Initialize from LLM.
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecation war... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.html |
58c292427124-6 | property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.kuzu.KuzuQAChain.html |
c3e3cd27560d-0 | langchain.chains.router.base.RouterChain¶
class langchain.chains.router.base.RouterChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[str]] = No... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c3e3cd27560d-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 verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to langchain.verbose value... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c3e3cd27560d-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. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to inc... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
c3e3cd27560d-3 | run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, **kwargs: Any) → str¶
Run the chain as text in, text out or multiple variables, text out.
save(file_path: Union[Path, str]) → None¶
Save the chain.
Parameters
file_path – Path to file to ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.base.RouterChain.html |
0525f921d123-0 | langchain.chains.openai_functions.extraction.create_extraction_chain¶
langchain.chains.openai_functions.extraction.create_extraction_chain(schema: dict, llm: BaseLanguageModel) → Chain[source]¶
Creates a chain that extracts information from a passage.
Parameters
schema – The schema of the entities to extract.
llm – The... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.extraction.create_extraction_chain.html |
e1eb5402832e-0 | langchain.chains.sql_database.base.SQLDatabaseSequentialChain¶
class langchain.chains.sql_database.base.SQLDatabaseSequentialChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: b... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseSequentialChain.html |
e1eb5402832e-1 | and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param return_intermediate_steps: bool = False¶
param sql_chain: SQLDatabaseChain [R... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseSequentialChain.html |
e1eb5402832e-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseSequentialChain.html |
e1eb5402832e-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of chain.
classmethod from_llm(llm: BaseLanguageModel, database: SQLDatabase, query_prompt: BasePromptTemplate = PromptTemplate(input_variables=['input', 'table_info', 'dialect', 'top_k'], output_parser=None, partial_variables={}, template='Given an input que... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseSequentialChain.html |
e1eb5402832e-4 | Load the necessary chains.
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecati... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseSequentialChain.html |
e1eb5402832e-5 | property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseSequentialChain.html |
577913c0f8d9-0 | langchain.chains.router.multi_prompt.MultiPromptChain¶
class langchain.chains.router.multi_prompt.MultiPromptChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html |
577913c0f8d9-1 | them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param router_chain: RouterChain [Required]¶
Chain for deciding a destination chain and the input to it.
param silent_errors: bool = False¶
If True, use default_ch... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html |
577913c0f8d9-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html |
577913c0f8d9-3 | Convenience constructor for instantiating from destination prompts.
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_de... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html |
577913c0f8d9-4 | property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html |
4df97523a127-0 | langchain.chains.combine_documents.base.AnalyzeDocumentChain¶
class langchain.chains.combine_documents.base.AnalyzeDocumentChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: boo... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
4df97523a127-1 | 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 text_splitter: langchain.text_splitter.Text... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
4df97523a127-2 | Run the logic of this chain and add to output if desired.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param.
return_only_outputs – boolean for whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input key... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
4df97523a127-3 | Run the chain as text in, text out or multiple variables, text out.
save(file_path: Union[Path, str]) → None¶
Save the chain.
Parameters
file_path – Path to file to save the chain to.
Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
validator set_verbose » verbose¶
If verbose is None, set it.
T... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.AnalyzeDocumentChain.html |
50a775b91307-0 | langchain.chains.openai_functions.qa_with_structure.create_qa_with_structure_chain¶
langchain.chains.openai_functions.qa_with_structure.create_qa_with_structure_chain(llm: BaseLanguageModel, schema: Union[dict, Type[BaseModel]], output_parser: str = 'base', prompt: Optional[Union[PromptTemplate, ChatPromptTemplate]] = ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.qa_with_structure.create_qa_with_structure_chain.html |
007d6f7f2a44-0 | langchain.chains.sql_database.base.SQLDatabaseChain¶
class langchain.chains.sql_database.base.SQLDatabaseChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Op... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseChain.html |
007d6f7f2a44-1 | [Deprecated] LLM wrapper to use.
param llm_chain: LLMChain [Required]¶
param memory: Optional[BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called at the start
and at the end of every chain. At the start, memory loads variables and passes
them along in the chain. At the end, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseChain.html |
007d6f7f2a44-2 | 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, include_run_info: bool = False) → Dict[str, Any]¶
R... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseChain.html |
007d6f7f2a44-3 | use the callbacks provided to the chain.
include_run_info – Whether to include run info in the response. Defaults
to False.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Call the chain on all inputs in the list.
async a... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseChain.html |
007d6f7f2a44-4 | Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
validator set_verbose » verbose¶
If verbose is None, set it.
This allows users to pass in None as verbose to access the global setting.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotI... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.base.SQLDatabaseChain.html |
58120c638b7c-0 | langchain.chains.combine_documents.stuff.StuffDocumentsChain¶
class langchain.chains.combine_documents.stuff.StuffDocumentsChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: boo... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html |
58120c638b7c-1 | param llm_chain: langchain.chains.llm.LLMChain [Required]¶
LLM wrapper to use after formatting documents.
param memory: Optional[BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called at the start
and at the end of every chain. At the start, memory loads variables and passes
th... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html |
58120c638b7c-2 | callbacks – Callbacks to use for this chain run. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbac... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html |
58120c638b7c-3 | Run the chain as text in, text out or multiple variables, text out.
combine_docs(docs: List[Document], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, **kwargs: Any) → Tuple[str, dict][source]¶
Stuff all documents into one prompt and pass to LLM.
dict(**kwargs: Any) → Dict¶
Return dic... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html |
58120c638b7c-4 | to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
property lc_attributes: Dict¶
Return a list of attribute names that should be included in the
serialized kwargs. These attributes must be accepted by the
constructor.
property lc_namespace: List[str... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html |
063afa91943b-0 | langchain.chains.pal.base.PALChain¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-1 | class langchain.chains.pal.base.PALChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[str]] = None, llm_chain: LLMChain, llm: Optional[BaseLangu... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-2 | golf_balls_left = golf_balls_initial - golf_balls_lost_tuesday - golf_balls_lost_wednesday\n result = golf_balls_left\n return result\n\n\n\n\n\nQ: There were nine computers in the server room. Five more computers were installed each day, from monday to thursday. How many computers are now in the server room?\n\n... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-3 | solution in Python:\n\n\ndef solution():\n """Jason had 20 lollipops. He gave Denny some lollipops. Now Jason has 12 lollipops. How many lollipops did Jason give to Denny?"""\n jason_lollipops_initial = 20\n jason_lollipops_after = 12\n denny_lollipops = jason_lollipops_initial - jason_lollipops_after\n ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-4 | = total_cars\n return result\n\n\n\n\n\nQ: There are 15 trees in the grove. Grove workers will plant trees in the grove today. After they are done, there will be 21 trees. How many trees did the grove workers plant today?\n\n# solution in Python:\n\n\ndef solution():\n """There are 15 trees in the grove. Grove wo... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-5 | Bases: Chain
Implements Program-Aided Language Models.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param callback_manager: Optional[BaseCallbackManager] = None¶
Deprecated, use callbacks instead.
param c... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-6 | param prompt: BasePromptTemplate = PromptTemplate(input_variables=['question'], output_parser=None, partial_variables={}, template='Q: Olivia has $23. She bought five bagels for $3 each. How much money does she have left?\n\n# solution in Python:\n\n\ndef solution():\n """Olivia has $23. She bought five bagels for $... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-7 | solution():\n """There were nine computers in the server room. Five more computers were installed each day, from monday to thursday. How many computers are now in the server room?"""\n computers_initial = 9\n computers_per_day = 5\n num_days = 4 # 4 days between monday and thursday\n computers_added = c... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-8 | = 12\n denny_lollipops = jason_lollipops_initial - jason_lollipops_after\n result = denny_lollipops\n return result\n\n\n\n\n\nQ: Leah had 32 chocolates and her sister had 42. If they ate 35, how many pieces do they have left in total?\n\n# solution in Python:\n\n\ndef solution():\n """Leah had 32 chocolate... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-9 | 15 trees in the grove. Grove workers will plant trees in the grove today. After they are done, there will be 21 trees. How many trees did the grove workers plant today?"""\n trees_initial = 15\n trees_after = 21\n trees_added = trees_after - trees_initial\n result = trees_added\n return result\n\n\n\n\n\... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-10 | [Deprecated]
param python_globals: Optional[Dict[str, Any]] = None¶
param python_locals: Optional[Dict[str, Any]] = None¶
param return_intermediate_steps: bool = False¶
param stop: str = '\n\n'¶
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None
These tags will be ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-11 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-12 | Load PAL from colored object prompt.
classmethod from_math_prompt(llm: BaseLanguageModel, **kwargs: Any) → PALChain[source]¶
Load PAL from math prompt.
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_ou... | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
063afa91943b-13 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config[source]¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.pal.base.PALChain.html |
1be1d52ff26c-0 | langchain.chains.router.llm_router.LLMRouterChain¶
class langchain.chains.router.llm_router.LLMRouterChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Option... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.LLMRouterChain.html |
1be1d52ff26c-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 verbose: bool [Optional]¶
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to the console. Defaults to langchain.verbose value... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.LLMRouterChain.html |
1be1d52ff26c-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. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to inc... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.LLMRouterChain.html |
1be1d52ff26c-3 | run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, **kwargs: Any) → str¶
Run the chain as text in, text out or multiple variables, text out.
save(file_path: Union[Path, str]) → None¶
Save the chain.
Parameters
file_path – Path to file to ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.llm_router.LLMRouterChain.html |
cf62b66ff678-0 | langchain.chains.query_constructor.parser.QueryTransformer¶
langchain.chains.query_constructor.parser.QueryTransformer¶
alias of None | https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.parser.QueryTransformer.html |
f50b0eacdfbb-0 | langchain.chains.api.base.APIChain¶
class langchain.chains.api.base.APIChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Optional[List[str]] = None, api_requ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
f50b0eacdfbb-1 | There are many different types of memory - please see memory docs
for the full catalog.
param requests_wrapper: TextRequestsWrapper [Required]¶
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
f50b0eacdfbb-2 | include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, include_run_info: bool = False) → ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
f50b0eacdfbb-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of chain.
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'], output_parser=None, partial_variables={}, template... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
f50b0eacdfbb-4 | Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
f50b0eacdfbb-5 | Return a map of constructor argument names to secret ids.
eg. {“openai_api_key”: “OPENAI_API_KEY”}
property lc_serializable: bool¶
Return whether or not the class is serializable.
model Config¶
Bases: object
Configuration for this pydantic object.
arbitrary_types_allowed = True¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.base.APIChain.html |
3ef5bc5cb4a7-0 | langchain.chains.graph_qa.cypher.GraphCypherQAChain¶
class langchain.chains.graph_qa.cypher.GraphCypherQAChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Op... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
3ef5bc5cb4a7-1 | them along in the chain. At the end, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full catalog.
param qa_chain: LLMChain [Required]¶
param return_direct: bool = False¶
Whether or not to return the result of querying the graph directly.
param return_intermedi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
3ef5bc5cb4a7-2 | callbacks – Callbacks to use for this chain run. If not provided, will
use the callbacks provided to the chain.
include_run_info – Whether to include run info in the response. Defaults
to False.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbac... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
3ef5bc5cb4a7-3 | dict(**kwargs: Any) → Dict¶
Return dictionary representation of chain.
classmethod from_llm(llm: BaseLanguageModel, *, qa_prompt: BasePromptTemplate = PromptTemplate(input_variables=['context', 'question'], output_parser=None, partial_variables={}, template="You are an assistant that helps to form nice and human unders... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
3ef5bc5cb4a7-4 | Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.GraphCypherQAChain.html |
8c7378a2f6f7-0 | langchain.chains.retrieval_qa.base.BaseRetrievalQA¶
class langchain.chains.retrieval_qa.base.BaseRetrievalQA(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, verbose: bool = None, tags: Opti... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
8c7378a2f6f7-1 | Return the source documents.
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
8c7378a2f6f7-2 | Run the logic of this chain and add to output if desired.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param.
return_only_outputs – boolean for whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input key... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
8c7378a2f6f7-3 | Validate and prep inputs.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prep outputs.
validator raise_deprecation » all fields¶
Raise deprecation warning if callback_manager is used.
run(*args: Any, callbacks: Optional[Union[List[BaseCa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
8c7378a2f6f7-4 | Configuration for this pydantic object.
allow_population_by_field_name = True¶
arbitrary_types_allowed = True¶
extra = 'forbid'¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.retrieval_qa.base.BaseRetrievalQA.html |
687655b038be-0 | langchain.chains.query_constructor.ir.Operation¶
class langchain.chains.query_constructor.ir.Operation(*, operator: Operator, arguments: List[FilterDirective])[source]¶
Bases: FilterDirective
A logical operation over other directives.
Create a new model by parsing and validating input data from keyword arguments.
Raise... | https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.Operation.html |
d50c0785e2f2-0 | langchain.chains.qa_with_sources.loading.load_qa_with_sources_chain¶
langchain.chains.qa_with_sources.loading.load_qa_with_sources_chain(llm: BaseLanguageModel, chain_type: str = 'stuff', verbose: Optional[bool] = None, **kwargs: Any) → BaseCombineDocumentsChain[source]¶
Load question answering with sources chain.
Para... | https://api.python.langchain.com/en/latest/chains/langchain.chains.qa_with_sources.loading.load_qa_with_sources_chain.html |
9dfec98ab6bd-0 | langchain.chains.combine_documents.base.BaseCombineDocumentsChain¶
class langchain.chains.combine_documents.base.BaseCombineDocumentsChain(*, memory: Optional[BaseMemory] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, callback_manager: Optional[BaseCallbackManager] = None, ve... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.base.BaseCombineDocumentsChain.html |
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