id stringlengths 14 16 | text stringlengths 31 2.41k | source stringlengths 53 121 |
|---|---|---|
5d97bfd0cb46-59 | 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.base.BaseCallba... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-60 | classmethod from_llm(llm, *, qa_prompt=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 information that you must use to construct an answ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-61 | Initialize from LLM.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
qa_prompt (langchain.prompts.base.BasePromptTemplate) –
cypher_prompt (langchain.prompts.base.BasePromptTemplate) –
kwargs (Any) –
Return type
langchain.chains.graph_qa.kuzu.KuzuQAChain
prep_inputs(inputs)
Validate and prep inputs.
P... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-62 | 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]
Return a map of constructor ar... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-63 | Chain that interprets a prompt and executes bash code to perform bash operations.
Example
from langchain import LLMBashChain, OpenAI
llm_bash = LLMBashChain.from_llm(OpenAI())
Parameters
memory (Optional[langchain.schema.BaseMemory]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langc... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-64 | 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.
attribute prompt: BasePromptTemplate = PromptTemplate(input_variables=['question'],... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-65 | 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 whether to return only outputs in the
response. If True, only new keys generated by this chain will b... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-66 | Parameters
kwargs (Any) –
Return type
Dict
classmethod from_llm(llm, prompt=PromptTemplate(input_variables=['question'], output_parser=BashOutputParser(), partial_variables={}, template='If someone asks you to perform a task, your job is to come up with a series of bash commands that will perform the task. There is no... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-67 | 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[str]]) –
kwargs (Any) –
Ret... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-68 | Bases: langchain.chains.base.Chain
Chain to run queries against LLMs.
Example
from langchain import LLMChain, OpenAI, PromptTemplate
prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(
input_variables=["adjective"], template=prompt_template
)
llm = LLMChain(llm=OpenAI(), prompt=prompt)
Parameter... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-69 | 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/stable/modules/chains.html |
5d97bfd0cb46-70 | Parameters
input_list (List[Dict[str, Any]]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
Return type
Sequence[Union[str, List[str], Dict[str, str]]]
async acall(inputs, return_only_outputs=False, callbacks=None, *, tags=None, includ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-71 | 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]]
apply_and_parse(input_list, callbacks=None)[source]
Call apply and then parse the results.
Parameters
input_l... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-72 | Return type
Tuple[List[langchain.schema.PromptValue], Optional[List[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.callback... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-73 | Returns
Completion from LLM.
Return type
str
Example
completion = llm.predict(adjective="funny")
predict_and_parse(callbacks=None, **kwargs)[source]
Call predict and then parse the results.
Parameters
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackMan... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-74 | 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/stable/modules/chains.html |
5d97bfd0cb46-75 | property lc_serializable: bool
Return whether or not the class is serializable.
class langchain.chains.LLMCheckerChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, question_to_checked_assertions_chain, llm=None, create_draft_answer_prompt=PromptTemplate(input_variables=['question'], ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-76 | 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]]) –
quest... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-77 | [Deprecated]
attribute create_draft_answer_prompt: PromptTemplate = PromptTemplate(input_variables=['question'], output_parser=None, partial_variables={}, template='{question}\n\n', template_format='f-string', validate_template=True)
[Deprecated]
attribute list_assertions_prompt: PromptTemplate = PromptTemplate(input_... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-78 | 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
will be printed to the console. Defaults to langchain.verbose v... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-79 | 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/stable/modules/chains.html |
5d97bfd0cb46-80 | list_assertions_prompt (langchain.prompts.prompt.PromptTemplate) –
check_assertions_prompt (langchain.prompts.prompt.PromptTemplate) –
revised_answer_prompt (langchain.prompts.prompt.PromptTemplate) –
kwargs (Any) –
Return type
langchain.chains.llm_checker.base.LLMCheckerChain
prep_inputs(inputs)
Validate and prep... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-81 | 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]
Return a map of constructor ar... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-82 | property lc_serializable: bool
Return whether or not the class is serializable.
class langchain.chains.LLMMathChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, llm_chain, llm=None, prompt=PromptTemplate(input_variables=['question'], output_parser=None, partial_variables={}, template... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-83 | 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]]) –
llm_c... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-84 | There are many different types of memory - please see memory docs
for the full catalog.
attribute prompt: BasePromptTemplate = PromptTemplate(input_variables=['question'], output_parser=None, partial_variables={}, template='Translate a math problem into a expression that can be executed using Python\'s numexpr library.... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-85 | Whether or not run in verbose mode. In verbose mode, some intermediate logs
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
inpu... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-86 | tags (Optional[List[str]]) –
kwargs (Any) –
Return type
str
dict(**kwargs)
Return dictionary representation of chain.
Parameters
kwargs (Any) –
Return type
Dict
classmethod from_llm(llm, prompt=PromptTemplate(input_variables=['question'], output_parser=None, partial_variables={}, template='Translate a math problem ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-87 | 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/stable/modules/chains.html |
5d97bfd0cb46-88 | 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.LLMRequestsChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, llm_chain, requests_... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-89 | for full details.
attribute llm_chain: LLMChain [Required]
attribute 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, it save... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-90 | 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/stable/modules/chains.html |
5d97bfd0cb46-91 | return_only_outputs (bool) –
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.BaseCallbackManage... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-92 | Bases: langchain.chains.router.base.RouterChain
A router chain that uses an LLM chain to perform routing.
Parameters
memory (Optional[langchain.schema.BaseMemory]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
callback_manager (Option... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-93 | 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
will be printed to the console. Defaults to langchain.verbose value.
async acall(inputs, return_only_outputs=False, callbacks... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-94 | Return type
langchain.chains.router.base.Route
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]]... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-95 | 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/stable/modules/chains.html |
5d97bfd0cb46-96 | class langchain.chains.LLMSummarizationCheckerChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, sequential_chain, llm=None, create_assertions_prompt=PromptTemplate(input_variables=['summary'], output_parser=None, partial_variables={}, template='Given some text, extract a list of fact... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-97 | output_parser=None, partial_variables={}, template='Below are some assertions that have been fact checked and are labeled as true or false.\n\nIf all of the assertions are true, return "True". If any of the assertions are false, return "False".\n\nHere are some examples:\n===\n\nChecked Assertions: """\n- The sky is re... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-98 | Bases: langchain.chains.base.Chain
Chain for question-answering with self-verification.
Example
from langchain import OpenAI, LLMSummarizationCheckerChain
llm = OpenAI(temperature=0.0)
checker_chain = LLMSummarizationCheckerChain.from_llm(llm)
Parameters
memory (Optional[langchain.schema.BaseMemory]) –
callbacks (Opti... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-99 | max_checks (int) –
Return type
None
attribute are_all_true_prompt: PromptTemplate = PromptTemplate(input_variables=['checked_assertions'], output_parser=None, partial_variables={}, template='Below are some assertions that have been fact checked and are labeled as true or false.\n\nIf all of the assertions are true, re... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-100 | Each custom chain can optionally call additional callback methods, see Callback docs
for full details.
attribute check_assertions_prompt: PromptTemplate = PromptTemplate(input_variables=['assertions'], output_parser=None, partial_variables={}, template='You are an expert fact checker. You have been hired by a major new... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-101 | There are many different types of memory - please see memory docs
for the full catalog.
attribute revised_summary_prompt: PromptTemplate = PromptTemplate(input_variables=['checked_assertions', 'summary'], output_parser=None, partial_variables={}, template='Below are some assertions that have been fact checked and are l... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-102 | 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.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – Callbacks to use ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-103 | classmethod from_llm(llm, create_assertions_prompt=PromptTemplate(input_variables=['summary'], output_parser=None, partial_variables={}, template='Given some text, extract a list of facts from the text.\n\nFormat your output as a bulleted list.\n\nText:\n"""\n{summary}\n"""\n\nFacts:', template_format='f-string', valid... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-104 | true or false.\n\nIf all of the assertions are true, return "True". If any of the assertions are false, return "False".\n\nHere are some examples:\n===\n\nChecked Assertions: """\n- The sky is red: False\n- Water is made of lava: False\n- The sun is a star: True\n"""\nResult: False\n\n===\n\nChecked Assertions: """\n- ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-105 | Parameters
llm (langchain.base_language.BaseLanguageModel) –
create_assertions_prompt (langchain.prompts.prompt.PromptTemplate) –
check_assertions_prompt (langchain.prompts.prompt.PromptTemplate) –
revised_summary_prompt (langchain.prompts.prompt.PromptTemplate) –
are_all_true_prompt (langchain.prompts.prompt.Promp... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-106 | 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/stable/modules/chains.html |
5d97bfd0cb46-107 | 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 callback methods, see Callback docs
for full ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-108 | 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.base.BaseCallba... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-109 | Construct a map-reduce chain that uses the chain for map and reduce.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
prompt (langchain.prompts.base.BasePromptTemplate) –
text_splitter (langchain.text_splitter.TextSplitter) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], l... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-110 | 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: Dict
Return a list of attribu... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-111 | default_chain (langchain.chains.llm.LLMChain) –
silent_errors (bool) –
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 None.
Callback handl... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-112 | 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
will be printed to the console. Defaults to langchain.verbose value.
async acall(inputs, return_only_outputs=False, callbacks... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-113 | 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 representation of chain.
Parameters
kwargs (Any) –
Return type
Dict
c... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-114 | 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/stable/modules/chains.html |
5d97bfd0cb46-115 | verbose (bool) –
tags (Optional[List[str]]) –
router_chain (langchain.chains.router.llm_router.LLMRouterChain) –
destination_chains (Mapping[str, langchain.chains.retrieval_qa.base.BaseRetrievalQA]) –
default_chain (langchain.chains.base.Chain) –
silent_errors (bool) –
Return type
None
attribute callback_manager:... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-116 | If True, use default_chain when an invalid destination name is provided.
Defaults to 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 callbac... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-117 | 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]]
async arun(*args, callbacks=None, tags=None, **kwargs)
Run the chain as text in, text out or multiple variabl... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-118 | inputs (Dict[str, str]) –
outputs (Dict[str, str]) –
return_only_outputs (bool) –
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.BaseCallba... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-119 | property lc_serializable: bool
Return whether or not the class is serializable.
class langchain.chains.MultiRouteChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, router_chain, destination_chains, default_chain, silent_errors=False)[source]
Bases: langchain.chains.base.Chain
Use a ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-120 | 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/stable/modules/chains.html |
5d97bfd0cb46-121 | 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]
apply(input_list, callbacks=None)
Call the chain on all inputs in the list.
Parameters
input_list (List[Dict[str, Any]]) –
callbac... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-122 | 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.
Parameters
file_path (Union[pathlib.Path, str]) – Path to file to save ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-123 | Implement an LLM driven browser.
Example
from langchain import NatBotChain
natbot = NatBotChain.from_default("Buy me a new hat.")
Parameters
memory (Optional[langchain.schema.BaseMemory]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-124 | 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 objective: str [Required]
Objective that NatBot is tasked with completing.
attribute tags: Optional[List[str]] = None
Optional list of tags associated... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-125 | 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]]) –
Return type
List[Dict[str, str]]
async ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-126 | objective (str) –
kwargs (Any) –
Return type
langchain.chains.natbot.base.NatBotChain
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/stable/modules/chains.html |
5d97bfd0cb46-127 | property lc_namespace: List[str]
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 s... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-128 | 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 callback methods, see Callback docs
for full details.
attribute graph: NebulaGraph [Required]
attribute memory: Optional... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-129 | 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.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) – Callbacks to use ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-130 | classmethod from_llm(llm, *, qa_prompt=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 information that you must use to construct an answ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-131 | Do not include any explanations or apologies in your responses.\nDo not respond to any questions that might ask anything else than for you to construct a Cypher statement.\nDo not include any text except the generated Cypher statement.\n\nThe question is:\n{question}", template_format='f-string', validate_template=True... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-132 | Initialize from LLM.
Parameters
llm (langchain.base_language.BaseLanguageModel) –
qa_prompt (langchain.prompts.base.BasePromptTemplate) –
ngql_prompt (langchain.prompts.base.BasePromptTemplate) –
kwargs (Any) –
Return type
langchain.chains.graph_qa.nebulagraph.NebulaGraphQAChain
prep_inputs(inputs)
Validate and pr... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-133 | 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 langchain object.
eg. [“langchain”, “l... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-134 | client (Any) –
model_name (Optional[str]) –
error (bool) –
input_key (str) –
output_key (str) –
openai_api_key (Optional[str]) –
openai_organization (Optional[str]) –
Return type
None
attribute callback_manager: Optional[BaseCallbackManager] = None
Deprecated, use callbacks instead.
attribute callbacks: Callbac... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-135 | attribute 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.
async acall(inputs, return_only_outputs=False, callbacks=None, *, tags=None, include_run_info=False)
Run the logic of this chain and add t... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-136 | tags (Optional[List[str]]) –
kwargs (Any) –
Return type
str
dict(**kwargs)
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, r... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-137 | constructor.
property lc_namespace: List[str]
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 t... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-138 | max_text_length (Optional[int]) –
Return type
None
attribute api_operation: APIOperation [Required]
attribute api_request_chain: LLMChain [Required]
attribute api_response_chain: Optional[LLMChain] = None
attribute callback_manager: Optional[BaseCallbackManager] = None
Deprecated, use callbacks instead.
attribute ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-139 | 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/stable/modules/chains.html |
5d97bfd0cb46-140 | kwargs (Any) –
Return type
str
deserialize_json_input(serialized_args)[source]
Use the serialized typescript dictionary.
Resolve the path, query params dict, and optional requestBody dict.
Parameters
serialized_args (str) –
Return type
dict
dict(**kwargs)
Return dictionary representation of chain.
Parameters
kwargs... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-141 | 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/stable/modules/chains.html |
5d97bfd0cb46-142 | 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. | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-143 | class langchain.chains.PALChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, llm_chain, llm=None, prompt=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... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-144 | computers were installed each day, from monday to thursday. How many computers are now in the server room?\n\n# solution in Python:\n\n\ndef 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 ro... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-145 | 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 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 l... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-146 | 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 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\... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-147 | Bases: langchain.chains.base.Chain
Implements Program-Aided Language Models.
Parameters
memory (Optional[langchain.schema.BaseMemory]) –
callbacks (Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]]) –
callback_manager (Optional[langchain.callbacks.base.B... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-148 | 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/stable/modules/chains.html |
5d97bfd0cb46-149 | attribute 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 f... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-150 | 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/stable/modules/chains.html |
5d97bfd0cb46-151 | = 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/stable/modules/chains.html |
5d97bfd0cb46-152 | 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/stable/modules/chains.html |
5d97bfd0cb46-153 | [Deprecated]
attribute python_globals: Optional[Dict[str, Any]] = None
attribute python_locals: Optional[Dict[str, Any]] = None
attribute return_intermediate_steps: bool = False
attribute stop: str = '\n\n'
attribute tags: Optional[List[str]] = None
Optional list of tags associated with the chain. Defaults to None... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-154 | 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]]) –
Return type
List[Dict[str, str]]
async ... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-155 | Validate and prep outputs.
Parameters
inputs (Dict[str, str]) –
outputs (Dict[str, str]) –
return_only_outputs (bool) –
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[Li... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-156 | property lc_serializable: bool
Return whether or not the class is serializable.
class langchain.chains.QAGenerationChain(*, memory=None, callbacks=None, callback_manager=None, verbose=None, tags=None, llm_chain, text_splitter=<langchain.text_splitter.RecursiveCharacterTextSplitter object>, input_key='text', output_key... | https://api.python.langchain.com/en/stable/modules/chains.html |
5d97bfd0cb46-157 | 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/stable/modules/chains.html |
5d97bfd0cb46-158 | 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]
apply(input_list, callbacks=None)
Call the chain on all inputs in the list.
Parameters
input_list (List[Dict[str, Any]]) –
callbac... | https://api.python.langchain.com/en/stable/modules/chains.html |
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