id stringlengths 14 16 | text stringlengths 4 1.28k | source stringlengths 54 121 |
|---|---|---|
07ceff43f477-416 | output_variables (List[str]) –
transform (Callable[[Dict[str, str]], Dict[str, str]]) –
Return type
None
attribute callback_manager: Optional[BaseCallbackManager] = None
Deprecated, use callbacks instead.
attribute callbacks: Callbacks = None
Optional list of callback handlers (or callback manager). Defaults to Non... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-417 | 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.
attribute output_variables: List[str] [Required]
attribute tags: Optional[List[str]] = None
Optional list of tags associated with the chain. Defaults to None
Th... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-418 | async acall(inputs, return_only_outputs=False, callbacks=None, *, tags=None, include_run_info=False)
Run the logic of this chain and add to output if desired.
Parameters
inputs (Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if chain expects
only one param.
return_only_outputs (bool) – boolean for... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-419 | to False.
tags (Optional[List[str]]) –
Return type
Dict[str, Any]
apply(input_list, callbacks=None)
Call the chain on all inputs in the list.
Parameters
input_list (List[Dict[str, Any]]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-420 | Return dictionary representation of chain.
Parameters
kwargs (Any) –
Return type
Dict
prep_inputs(inputs)
Validate and prep inputs.
Parameters
inputs (Union[Dict[str, Any], Any]) –
Return type
Dict[str, str]
prep_outputs(inputs, outputs, return_only_outputs=False)
Validate and prep outputs.
Parameters
inputs (Dict[... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-421 | tags (Optional[List[str]]) –
kwargs (Any) –
Return type
str
save(file_path)
Save the chain.
Parameters
file_path (Union[pathlib.Path, str]) – Path to file to save the chain to.
Return type
None
Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
to_json()
Return type
Union[langchain.load.seriali... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-422 | Return the namespace of the langchain object.
eg. [“langchain”, “llms”, “openai”]
property lc_secrets: Dict[str, str]
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.
class langchain.chain... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-423 | Parameters
memory (Optional[langchain.schema.BaseMemory]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) –
verbose (bool) –
tags (Optional[List[str]]) –
combi... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-424 | attribute callbacks: Callbacks = None
Optional list of callback handlers (or callback manager). Defaults to None.
Callback handlers are called throughout the lifecycle of a call to a chain,
starting with on_chain_start, ending with on_chain_end or on_chain_error.
Each custom chain can optionally call additional callba... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-425 | for the full catalog.
attribute return_source_documents: bool = False
Return the source documents.
attribute search_kwargs: Dict[str, Any] [Optional]
Extra search args.
attribute search_type: str = 'similarity'
Search type to use over vectorstore. similarity or mmr.
attribute tags: Optional[List[str]] = None
Option... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-426 | async acall(inputs, return_only_outputs=False, callbacks=None, *, tags=None, include_run_info=False)
Run the logic of this chain and add to output if desired.
Parameters
inputs (Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if chain expects
only one param.
return_only_outputs (bool) – boolean for... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-427 | to False.
tags (Optional[List[str]]) –
Return type
Dict[str, Any]
apply(input_list, callbacks=None)
Call the chain on all inputs in the list.
Parameters
input_list (List[Dict[str, Any]]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-428 | Return dictionary representation of chain.
Parameters
kwargs (Any) –
Return type
Dict
classmethod from_chain_type(llm, chain_type='stuff', chain_type_kwargs=None, **kwargs)
Load chain from chain type.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
chain_type (str) –
chain_type_kwargs (Optional[dict]) ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-429 | prep_inputs(inputs)
Validate and prep inputs.
Parameters
inputs (Union[Dict[str, Any], Any]) –
Return type
Dict[str, str]
prep_outputs(inputs, outputs, return_only_outputs=False)
Validate and prep outputs.
Parameters
inputs (Dict[str, str]) –
outputs (Dict[str, str]) –
return_only_outputs (bool) –
Return type
Dic... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-430 | Save the chain.
Parameters
file_path (Union[pathlib.Path, str]) – Path to file to save the chain to.
Return type
None
Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
to_json()
Return type
Union[langchain.load.serializable.SerializedConstructor, langchain.load.serializable.SerializedNotImplement... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-431 | 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.
class langchain.chains.VectorDBQAWithSourcesChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, combine_do... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-432 | callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) –
verbose (bool) –
tags (Optional[List[str]]) –
combine_documents_chain (langchain.chains.combine_documents.base.B... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-433 | Deprecated, use callbacks instead.
attribute callbacks: Callbacks = None
Optional list of callback handlers (or callback manager). Defaults to None.
Callback handlers are called throughout the lifecycle of a call to a chain,
starting with on_chain_start, ending with on_chain_end or on_chain_error.
Each custom chain ca... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-434 | 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, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full ca... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-435 | You can use these to eg identify a specific instance of a chain with its use case.
attribute vectorstore: langchain.vectorstores.base.VectorStore [Required]
Vector Database to connect to.
attribute verbose: bool [Optional]
Whether or not run in verbose mode. In verbose mode, some intermediate logs
will be printed to ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-436 | chain will be returned. Defaults to False.
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – Callbacks to use for this chain run. If not provided, will
use the callbacks provided to the chain.
include_run_info (bool) – Whether to include run ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-437 | Run the chain as text in, text out or multiple variables, text out.
Parameters
args (Any) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
tags (Optional[List[str]]) –
kwargs (Any) –
Return type
str
dict(**kwargs)
Return dictionary re... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-438 | classmethod from_llm(llm, document_prompt=PromptTemplate(input_variables=['page_content', 'source'], output_parser=None, partial_variables={}, template='Content: {page_content}\nSource: {source}', template_format='f-string', validate_template=True), question_prompt=PromptTemplate(input_variables=['context', 'question']... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-439 | just say that you don\'t know. Don\'t try to make up an answer.\nALWAYS return a "SOURCES" part in your answer.\n\nQUESTION: Which state/country\'s law governs the interpretation of the contract?\n=========\nContent: This Agreement is governed by English law and the parties submit to the exclusive jurisdiction of the E... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-440 | this Agreement shall not affect the continuation in force of the remainder of the term (if any) and this 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 Beneficiar... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-441 | Lady and Second Gentleman. Members of Congress and the Cabinet. Justices of the Supreme Court. My fellow Americans. \n\nLast year COVID-19 kept us apart. This year we are finally together again. \n\nTonight, we meet as Democrats Republicans and Independents. But most importantly as Americans. \n\nWith a duty to one an... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-442 | fearlessness, their courage, their determination, inspires the world. \n\nGroups of citizens blocking 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... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-443 | York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera. \n\nThey were responding to a 9-1-1 call when a man shot and killed them with a stolen gun. \n\nOfficer Mora was 27 years old. \n\nOfficer Rivera was 22. \n\nBoth Dominican Americans who’d grown up on the ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-444 | you, as I’ve always promised. A Russian dictator, invading a foreign country, has costs around the 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 a... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-445 | for patients and families. \n\nTo get there, I call on Congress to fund ARPA-H, the Advanced Research Projects Agency for Health. \n\nIt’s based on DARPA—the Defense Department project that led to the Internet, GPS, and so much more. \n\nARPA-H will have a singular purpose—to drive breakthroughs in cancer, Alzheimer’s... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-446 | known. \n\nNow is the hour. \n\nOur moment of responsibility. \n\nOur test 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 ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-447 | Construct the chain from an LLM.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
document_prompt (langchain.prompts.base.BasePromptTemplate) –
question_prompt (langchain.prompts.base.BasePromptTemplate) –
combine_prompt (langchain.prompts.base.BasePromptTemplate) –
kwargs (Any) –
Return type
langchain... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-448 | Return type
Dict[str, str]
run(*args, callbacks=None, tags=None, **kwargs)
Run the chain as text in, text out or multiple variables, text out.
Parameters
args (Any) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
tags (Optional[List[st... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-449 | to_json_not_implemented()
Return type
langchain.load.serializable.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]
Return the namespace of the... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-450 | llm (langchain.base_language.BaseLanguageModel) – The language model to use.
Returns
Chain that can be used to extract information from a passage.
Return type
langchain.chains.base.Chain
langchain.chains.create_extraction_chain_pydantic(pydantic_schema, llm)[source]
Creates a chain that extracts information from a pas... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-451 | llm (langchain.base_language.BaseLanguageModel) – The language model to use.
Returns
Chain (LLMChain) that can be used to extract information from a passage.
Return type
langchain.chains.base.Chain
langchain.chains.create_tagging_chain_pydantic(pydantic_schema, llm)[source]
Creates a chain that extracts information fr... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-452 | kwargs (Any) –
Return type
langchain.chains.base.Chain
langchain.chains.create_citation_fuzzy_match_chain(llm)[source]
Create a citation fuzzy match chain.
Parameters
llm (langchain.base_language.BaseLanguageModel) – Language model to use for the chain.
Returns
Chain (LLMChain) that can be used to answer questions wi... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-453 | output_parser (str) – Output parser to use. Should be one of pydantic or base.
Default to base.
prompt (Optional[Union[langchain.prompts.prompt.PromptTemplate, langchain.prompts.chat.ChatPromptTemplate]]) – Optional prompt to use for the chain.
Return type
langchain.chains.llm.LLMChain
Returns:
langchain.chains.create_... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-454 | langchain.chains.llm.LLMChain
class langchain.chains.StuffDocumentsChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, input_key='input_documents', output_key='output_text', llm_chain, document_prompt=None, document_variable_name, document_separator='\n\n')[source]
Bases: langchain.ch... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-455 | output_key (str) –
llm_chain (langchain.chains.llm.LLMChain) –
document_prompt (langchain.prompts.base.BasePromptTemplate) –
document_variable_name (str) –
document_separator (str) –
Return type
None
attribute callback_manager: Optional[BaseCallbackManager] = None
Deprecated, use callbacks instead.
attribute call... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-456 | The string with which to join the formatted documents
attribute document_variable_name: str [Required]
The variable name in the llm_chain to put the documents in.
If only one variable in the llm_chain, this need not be provided.
attribute llm_chain: langchain.chains.llm.LLMChain [Required]
LLM wrapper to use after fo... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-457 | 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.
attribute verbose: bool [Optional]
Whether or not run in verbose mode. In verbose mode, some intermediate logs
wil... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-458 | returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – Callbacks to use for this chain run. If not provided, will
use the callbacks provi... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-459 | Return type
Tuple[str, dict]
apply(input_list, callbacks=None)
Call the chain on all inputs in the list.
Parameters
input_list (List[Dict[str, Any]]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
Return type
List[Dict[str, str]]
asyn... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-460 | Stuff all documents into one prompt and pass to LLM.
Parameters
docs (List[langchain.schema.Document]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
kwargs (Any) –
Return type
Tuple[str, dict]
dict(**kwargs)
Return dictionary repres... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-461 | Return type
Dict[str, str]
prompt_length(docs, **kwargs)[source]
Get the prompt length by formatting the prompt.
Parameters
docs (List[langchain.schema.Document]) –
kwargs (Any) –
Return type
Optional[int]
run(*args, callbacks=None, tags=None, **kwargs)
Run the chain as text in, text out or multiple variables, text... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-462 | Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
to_json()
Return type
Union[langchain.load.serializable.SerializedConstructor, langchain.load.serializable.SerializedNotImplemented]
to_json_not_implemented()
Return type
langchain.load.serializable.SerializedNotImplemented
property lc_attributes... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-463 | property lc_serializable: bool
Return whether or not the class is serializable.
class langchain.chains.MapRerankDocumentsChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, input_key='input_documents', output_key='output_text', llm_chain, document_variable_name, rank_key, answer_key, ... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-464 | tags (Optional[List[str]]) –
input_key (str) –
output_key (str) –
llm_chain (langchain.chains.llm.LLMChain) –
document_variable_name (str) –
rank_key (str) –
answer_key (str) –
metadata_keys (Optional[List[str]]) –
return_intermediate_steps (bool) –
Return type
None
attribute answer_key: str [Required]
Key in... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-465 | Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
attribute document_variable_name: str [Required]
The variable name in the llm_chain to put the documents in.
If only one variable in the llm_chain, this need not be provided.
attribute llm_chain: LLMChain [Required]... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-466 | Key in output of llm_chain to rank on.
attribute return_intermediate_steps: bool = False
attribute 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... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-467 | only one param.
return_only_outputs (bool) – 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 (Optional[Union[List[langchain.callbacks... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-468 | Parameters
docs (List[langchain.schema.Document]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
kwargs (Any) –
Return type
Tuple[str, dict]
apply(input_list, callbacks=None)
Call the chain on all inputs in the list.
Parameters
input... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-469 | tags (Optional[List[str]]) –
kwargs (Any) –
Return type
str
combine_docs(docs, callbacks=None, **kwargs)[source]
Combine documents in a map rerank manner.
Combine by mapping first chain over all documents, then reranking the results.
Parameters
docs (List[langchain.schema.Document]) –
callbacks (Optional[Union[List... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-470 | Validate and prep outputs.
Parameters
inputs (Dict[str, str]) –
outputs (Dict[str, str]) –
return_only_outputs (bool) –
Return type
Dict[str, str]
prompt_length(docs, **kwargs)
Return the prompt length given the documents passed in.
Returns None if the method does not depend on the prompt length.
Parameters
docs (L... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-471 | Return type
str
save(file_path)
Save the chain.
Parameters
file_path (Union[pathlib.Path, str]) – Path to file to save the chain to.
Return type
None
Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
to_json()
Return type
Union[langchain.load.serializable.SerializedConstructor, langchain.load.se... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-472 | property lc_secrets: Dict[str, str]
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.
class langchain.chains.MapReduceDocumentsChain(*, memory=None, callbacks=None, callback_manager=None, v... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-473 | callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) –
verbose (bool) –
tags (Optional[List[str]]) –
input_key (str) –
output_key (str) –
llm_chain (langchain.chains.llm.LLMChain) –
combine_document_chain (langchain.chains.combine_documents.base.BaseCombineDocumentsChain) –
collapse_document... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-474 | starting with on_chain_start, ending with on_chain_end or on_chain_error.
Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
attribute collapse_document_chain: Optional[BaseCombineDocumentsChain] = None
Chain to use to collapse intermediary results if needed.
If None... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-475 | 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, it saves any returned variables.
There are many different types of memory - please see memory docs
for the full ca... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-476 | will be printed to the console. Defaults to langchain.verbose value.
async acall(inputs, return_only_outputs=False, callbacks=None, *, tags=None, include_run_info=False)
Run the logic of this chain and add to output if desired.
Parameters
inputs (Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if c... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-477 | use the callbacks provided to the chain.
include_run_info (bool) – Whether to include run info in the response. Defaults
to False.
tags (Optional[List[str]]) –
Return type
Dict[str, Any]
async acombine_docs(docs, callbacks=None, **kwargs)[source]
Combine documents in a map reduce manner.
Combine by mapping first chai... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-478 | callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
Return type
List[Dict[str, str]]
async arun(*args, callbacks=None, tags=None, **kwargs)
Run the chain as text in, text out or multiple variables, text out.
Parameters
args (Any) –
callbacks... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-479 | Parameters
docs (List[langchain.schema.Document]) –
token_max (int) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
kwargs (Any) –
Return type
Tuple[str, dict]
dict(**kwargs)
Return dictionary representation of chain.
Parameters
kwar... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-480 | prompt_length(docs, **kwargs)
Return the prompt length given the documents passed in.
Returns None if the method does not depend on the prompt length.
Parameters
docs (List[langchain.schema.Document]) –
kwargs (Any) –
Return type
Optional[int]
run(*args, callbacks=None, tags=None, **kwargs)
Run the chain as text in... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-481 | Return type
None
Example:
.. code-block:: python
chain.save(file_path=”path/chain.yaml”)
to_json()
Return type
Union[langchain.load.serializable.SerializedConstructor, langchain.load.serializable.SerializedNotImplemented]
to_json_not_implemented()
Return type
langchain.load.serializable.SerializedNotImplemented
prope... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-482 | property lc_serializable: bool
Return whether or not the class is serializable.
class langchain.chains.RefineDocumentsChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, input_key='input_documents', output_key='output_text', initial_llm_chain, refine_llm_chain, document_variable_name,... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-483 | tags (Optional[List[str]]) –
input_key (str) –
output_key (str) –
initial_llm_chain (langchain.chains.llm.LLMChain) –
refine_llm_chain (langchain.chains.llm.LLMChain) –
document_variable_name (str) –
initial_response_name (str) –
document_prompt (langchain.prompts.base.BasePromptTemplate) –
return_intermediate_... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-484 | Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
attribute document_prompt: BasePromptTemplate [Optional]
Prompt to use to format each document.
attribute document_variable_name: str [Required]
The variable name in the initial_llm_chain to put the documents in.
If... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-485 | 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.
attribute refine_llm_chain: LLMChain [Required]
LLM chain to use when refining.
attribute return_intermediate_steps: bool = False
Return the results of the refi... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-486 | async acall(inputs, return_only_outputs=False, callbacks=None, *, tags=None, include_run_info=False)
Run the logic of this chain and add to output if desired.
Parameters
inputs (Union[Dict[str, Any], Any]) – Dictionary of inputs, or single input if chain expects
only one param.
return_only_outputs (bool) – boolean for... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-487 | to False.
tags (Optional[List[str]]) –
Return type
Dict[str, Any]
async acombine_docs(docs, callbacks=None, **kwargs)[source]
Combine by mapping first chain over all, then stuffing into final chain.
Parameters
docs (List[langchain.schema.Document]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallba... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-488 | List[Dict[str, str]]
async arun(*args, callbacks=None, tags=None, **kwargs)
Run the chain as text in, text out or multiple variables, text out.
Parameters
args (Any) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
tags (Optional[List[s... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-489 | Return dictionary representation of chain.
Parameters
kwargs (Any) –
Return type
Dict
prep_inputs(inputs)
Validate and prep inputs.
Parameters
inputs (Union[Dict[str, Any], Any]) –
Return type
Dict[str, str]
prep_outputs(inputs, outputs, return_only_outputs=False)
Validate and prep outputs.
Parameters
inputs (Dict[... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-490 | Run the chain as text in, text out or multiple variables, text out.
Parameters
args (Any) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
tags (Optional[List[str]]) –
kwargs (Any) –
Return type
str
save(file_path)
Save the chain.
Par... | https://api.python.langchain.com/en/latest/modules/chains.html |
07ceff43f477-491 | 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_secrets: Dict[str, str]
... | https://api.python.langchain.com/en/latest/modules/chains.html |
8ab9cc7dfede-0 | Agent Toolkits
Agent toolkits. | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-1 | langchain.agents.agent_toolkits.create_json_agent(llm, toolkit, callback_manager=None, prefix='You are an agent designed to interact with JSON.\nYour goal is to return a final answer by interacting with the JSON.\nYou have access to the following tools which help you learn more about the JSON you are interacting with.\... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-2 | key in one of those responses, you cannot use it.\nYou should only add one key at a time to the path. You cannot add multiple keys at once.\nIf you encounter a "KeyError", go back to the previous key, look at the available keys, and try again.\n\nIf the question does not seem to be related to the JSON, just return "I d... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-3 | the JSON or a section of the JSON, as this is not a valid answer. Keep digging until you find the answer and explicitly return it.\n', suffix='Begin!"\n\nQuestion: {input}\nThought: I should look at the keys that exist in data to see what I have access to\n{agent_scratchpad}', format_instructions='Use the following for... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-4 | Construct a json agent from an LLM and tools.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
toolkit (langchain.agents.agent_toolkits.json.toolkit.JsonToolkit) –
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) –
prefix (str) –
suffix (str) –
format_instructions (str) –
inpu... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-5 | langchain.agents.agent_toolkits.create_sql_agent(llm, toolkit, agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager=None, prefix='You are an agent designed to interact with a SQL database.\nGiven an input question, create a syntactically correct {dialect} query to run, then look at the results of the quer... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-6 | before executing it. If you get an error while executing a query, rewrite the query and try again.\n\nDO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n\nIf the question does not seem related to the database, just return "I don\'t know" as the answer.\n', suffix=None, format_instructi... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-7 | max_iterations=15, max_execution_time=None, early_stopping_method='force', verbose=False, agent_executor_kwargs=None, **kwargs)[source] | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-8 | Construct a sql agent from an LLM and tools.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
toolkit (langchain.agents.agent_toolkits.sql.toolkit.SQLDatabaseToolkit) –
agent_type (langchain.agents.agent_types.AgentType) –
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) –
prefi... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-9 | langchain.agents.agent_toolkits.create_openapi_agent(llm, toolkit, callback_manager=None, prefix="You are an agent designed to answer questions by making web requests to an API given the openapi spec.\n\nIf the question does not seem related to the API, return I don't know. Do not make up an answer.\nOnly use informati... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-10 | correct parameters to the request by checking which parameters are required. For parameters with a fixed set of values, please use the spec to look at which values are allowed.\n\nUse the exact parameter names as listed in the spec, do not make up any names or abbreviate the names of parameters.\nIf you get a not found... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-11 | Input/Observation can repeat N times)\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question', input_variables=None, max_iterations=15, max_execution_time=None, early_stopping_method='force', verbose=False, return_intermediate_steps=False, agent_executor_kwargs=None, **kwar... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-12 | Construct a json agent from an LLM and tools.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
toolkit (langchain.agents.agent_toolkits.openapi.toolkit.OpenAPIToolkit) –
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) –
prefix (str) –
suffix (str) –
format_instructions (str) –... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-13 | langchain.agents.agent_toolkits.create_pbi_agent(llm, toolkit, powerbi=None, callback_manager=None, prefix='You are an agent designed to help users interact with a PowerBI Dataset.\n\nAgent has access to a tool that can write a query based on the question and then run those against PowerBI, Microsofts business intellig... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-14 | in readable ways, like 1M instead of 1000000. Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.\n', suffix='Begin!\n\nQuestion: {input}\nThought: I can first ask which tables I have, then how each table is defined and then ask the query tool... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-15 | the final answer\nFinal Answer: the final answer to the original input question', examples=None, input_variables=None, top_k=10, verbose=False, agent_executor_kwargs=None, **kwargs)[source] | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-16 | Construct a pbi agent from an LLM and tools.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
toolkit (Optional[langchain.agents.agent_toolkits.powerbi.toolkit.PowerBIToolkit]) –
powerbi (Optional[langchain.utilities.powerbi.PowerBIDataset]) –
callback_manager (Optional[langchain.callbacks.base.BaseCallb... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-17 | langchain.agents.agent_toolkits.create_pbi_chat_agent(llm, toolkit, powerbi=None, callback_manager=None, output_parser=None, prefix='Assistant is a large language model built to help users interact with a PowerBI Dataset.\n\nAssistant has access to a tool that can write a query based on the question and then run those ... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-18 | human, also make sure to represent numbers in readable ways, like 1M instead of 1000000. Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.\n', suffix="TOOLS\n------\nAssistant can ask the user to use tools to look up information that may be ... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-19 | Construct a pbi agent from an Chat LLM and tools.
If you supply only a toolkit and no powerbi dataset, the same LLM is used for both.
Parameters
llm (langchain.chat_models.base.BaseChatModel) –
toolkit (Optional[langchain.agents.agent_toolkits.powerbi.toolkit.PowerBIToolkit]) –
powerbi (Optional[langchain.utilities.p... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-20 | verbose (bool) –
agent_executor_kwargs (Optional[Dict[str, Any]]) –
kwargs (Dict[str, Any]) –
Return type
langchain.agents.agent.AgentExecutor | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-21 | langchain.agents.agent.AgentExecutor
langchain.agents.agent_toolkits.create_python_agent(llm, tool, agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION, callback_manager=None, verbose=False, prefix='You are an agent designed to write and execute python code to answer questions.\nYou have access to a python REPL, which you... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-22 | tool (langchain.tools.python.tool.PythonREPLTool) –
agent_type (langchain.agents.agent_types.AgentType) –
callback_manager (Optional[langchain.callbacks.base.BaseCallbackManager]) –
verbose (bool) –
prefix (str) –
agent_executor_kwargs (Optional[Dict[str, Any]]) –
kwargs (Dict[str, Any]) –
Return type
langchain.... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
8ab9cc7dfede-23 | langchain.agents.agent.AgentExecutor
langchain.agents.agent_toolkits.create_vectorstore_agent(llm, toolkit, callback_manager=None, prefix='You are an agent designed to answer questions about sets of documents.\nYou have access to tools for interacting with the documents, and the inputs to the tools are questions.\nSome... | https://api.python.langchain.com/en/latest/modules/agent_toolkits.html |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.