id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
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4dec27c69f0b-9 | prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prepare chain inputs, including adding inputs from memory.
Parameters
inputs – Dictionary of raw inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-10 | these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
**kwargs – If the chain expects multiple inputs, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-11 | to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream... | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
4dec27c69f0b-12 | property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶
Examples using HugeGraphQAChain¶
HugeGraph QA Chain | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.hugegraph.HugeGraphQAChain.html |
2ca8616ba88e-0 | langchain.chains.openai_functions.tagging.create_tagging_chain¶
langchain.chains.openai_functions.tagging.create_tagging_chain(schema: dict, llm: BaseLanguageModel, prompt: Optional[ChatPromptTemplate] = None, **kwargs: Any) → Chain[source]¶
Creates a chain that extracts information from a passagebased on a schema.
Par... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.tagging.create_tagging_chain.html |
9bb24c095ede-0 | langchain.chains.sql_database.query.SQLInput¶
class langchain.chains.sql_database.query.SQLInput[source]¶
Input for a SQL Chain.
question: str¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.query.SQLInput.html |
b4101ec27146-0 | langchain.chains.openai_functions.qa_with_structure.create_qa_with_sources_chain¶
langchain.chains.openai_functions.qa_with_structure.create_qa_with_sources_chain(llm: BaseLanguageModel, verbose: bool = False, **kwargs: Any) → LLMChain[source]¶
Create a question answering chain that returns an answer with sources.
Para... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.qa_with_structure.create_qa_with_sources_chain.html |
0b877469c8e3-0 | langchain.chains.graph_qa.cypher.extract_cypher¶
langchain.chains.graph_qa.cypher.extract_cypher(text: str) → str[source]¶
Extract Cypher code from a text.
Parameters
text – Text to extract Cypher code from.
Returns
Cypher code extracted from the text. | https://api.python.langchain.com/en/latest/chains/langchain.chains.graph_qa.cypher.extract_cypher.html |
fb8a1836ab70-0 | langchain.chains.loading.load_chain_from_config¶
langchain.chains.loading.load_chain_from_config(config: dict, **kwargs: Any) → Chain[source]¶
Load chain from Config Dict. | https://api.python.langchain.com/en/latest/chains/langchain.chains.loading.load_chain_from_config.html |
f960f163dabb-0 | langchain.chains.combine_documents.reduce.ReduceDocumentsChain¶
class langchain.chains.combine_documents.reduce.ReduceDocumentsChain[source]¶
Bases: BaseCombineDocumentsChain
Combine documents by recursively reducing them.
This involves
combine_documents_chain
collapse_documents_chain
combine_documents_chain is ALWAYS ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-1 | # which is specifically aimed at collapsing documents BEFORE
# the final call.
prompt = PromptTemplate.from_template(
"Collapse this content: {context}"
)
llm_chain = LLMChain(llm=llm, prompt=prompt)
collapse_documents_chain = StuffDocumentsChain(
llm_chain=llm_chain,
document_prompt=document_prompt,
do... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-2 | 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 metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the chain. Defaults to None.
This metadata will be associated with each call to... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-3 | only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by thi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-4 | Asynchronously execute the chain.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, on... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-5 | element returned is a dictionary of other keys to return.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(in... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-6 | Example
# Suppose we have a single-input chain that takes a 'question' string:
await chain.arun("What's the temperature in Boise, Idaho?")
# -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-7 | Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if they can start producing output while
input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-8 | Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-9 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-10 | Parameters
inputs – Dictionary of raw inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
Returns
A dictionary of all inputs, including those added by the chain’s memory.
prep_outputs(inputs: Dict[str,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-11 | method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as the
sole positional argument.
callbacks – Callbacks to use for this cha... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-12 | classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override t... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
f960f163dabb-13 | property InputType: Type[langchain.schema.runnable.utils.Input]¶
property OutputType: Type[langchain.schema.runnable.utils.Output]¶
property input_schema: Type[pydantic.main.BaseModel]¶
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accep... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
9cd0c62d174d-0 | langchain.chains.openai_functions.qa_with_structure.AnswerWithSources¶
class langchain.chains.openai_functions.qa_with_structure.AnswerWithSources[source]¶
Bases: BaseModel
An answer to the question, with sources.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.qa_with_structure.AnswerWithSources.html |
9cd0c62d174d-1 | deep – set to True to make a deep copy of the model
Returns
new model instance
dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.qa_with_structure.AnswerWithSources.html |
9cd0c62d174d-2 | classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.qa_with_structure.AnswerWithSources.html |
54a93dc27a6d-0 | langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain¶
class langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain[source]¶
Bases: BaseConversationalRetrievalChain
Chain for having a conversation based on retrieved documents.
This chain takes in chat history (a list of messag... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-1 | )
prompt = PromptTemplate.from_template(template)
llm = OpenAI()
question_generator_chain = LLMChain(llm=llm, prompt=prompt)
chain = ConversationalRetrievalChain(
combine_docs_chain=combine_docs_chain,
retriever=retriever,
question_generator=question_generator_chain,
)
Create a new model by parsing and vali... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-2 | There are many different types of memory - please see memory docs
for the full catalog.
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the chain. Defaults to None.
This metadata will be associated with each call to this chain,
and passed as arguments to the handlers defined in callba... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-3 | 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.
__call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallba... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-4 | Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation of abatch, which calls ai... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-5 | include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-6 | directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'question' string:
await chain.arun("What's the temperature in Boise, Idaho?")
# -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' s... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-7 | The jsonpatch ops can be applied in order to construct state.
async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of atransform, which buffers input and calls astream.
Subclasses should override this method if th... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-8 | the new model: you should trust this data
deep – set to True to make a deep copy of the model
Returns
new model instance
dict(**kwargs: Any) → Dict¶
Dictionary representation of chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
**kwargs – Keyword arguments passed to defaul... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-9 | and new question into a standalone question.
chain_type – The chain type to use to create the combine_docs_chain, will
be sent to load_qa_chain.
verbose – Verbosity flag for logging to stdout.
condense_question_llm – The language model to use for condensing the chat
history and new question into a standalone question. ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-10 | Generate a JSON representation of the model, include and exclude arguments as per dict().
encoder is an optional function to supply as default to json.dumps(), other arguments as per json.dumps().
classmethod lc_id() → List[str]¶
A unique identifier for this class for serialization purposes.
The unique identifier is a ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-11 | memory.
outputs – Dictionary of initial chain outputs.
return_only_outputs – Whether to only return the chain outputs. If False,
inputs are also added to the final outputs.
Returns
A dict of the final chain outputs.
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags:... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-12 | context = "Weather report for Boise, Idaho on 07/03/23..."
chain.run(question=question, context=context)
# -> "The temperature in Boise is..."
save(file_path: Union[Path, str]) → None¶
Save the chain.
Expects Chain._chain_type property to be implemented and for memory to benull.
Parameters
file_path – Path to file to s... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-13 | Bind config to a Runnable, returning a new Runnable.
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.base.Runnable[~langchain.schema.runnable.utils.Input, ~langchain.schema.runnable.utils.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,)) →... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
54a93dc27a6d-14 | Use LangChain, GPT and Activeloop’s Deep Lake to work with code base
Structure answers with OpenAI functions
QA using Activeloop’s DeepLake | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ConversationalRetrievalChain.html |
ce24cabfeed9-0 | langchain.chains.base.Chain¶
class langchain.chains.base.Chain[source]¶
Bases: Serializable, Runnable[Dict[str, Any], Dict[str, Any]], ABC
Abstract base class for creating structured sequences of calls to components.
Chains should be used to encode a sequence of calls to components like
models, document retrievers, oth... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-1 | 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.
param memory: Optional[langchain.schema.memory.BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-2 | Execute the chain.
Parameters
inputs – Dictionary of inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys gen... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-3 | Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-4 | Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]][source]¶
Call the chain on all ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-5 | # Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in Boise is..."
async astream(input: Inp... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-6 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override this method if they can ba... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-7 | **kwargs – Keyword arguments passed to default pydantic.BaseModel.dict
method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_orm(obj: Any) → Model¶
classmethod get_lc_namespace() → List[str]¶
Get the namespace of th... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-8 | Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
classmethod parse_obj(obj: Any) → Model¶
cl... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-9 | Convenience method for executing chain.
The main difference between this method and Chain.__call__ is that this
method expects inputs to be passed directly in as positional arguments or
keyword arguments, whereas Chain.__call__ expects a single input dictionary
with all the inputs
Parameters
*args – If the chain expect... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-10 | Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
stream(input: Input, config: Optiona... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
ce24cabfeed9-11 | with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[Input, Output]¶
property InputType: Type[langchain.schema.runnable.utils.Input]¶
property OutputType: Type[langchain.schema.runna... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
4bc86348acc8-0 | langchain.chains.example_generator.generate_example¶
langchain.chains.example_generator.generate_example(examples: List[dict], llm: BaseLanguageModel, prompt_template: PromptTemplate) → str[source]¶
Return another example given a list of examples for a prompt. | https://api.python.langchain.com/en/latest/chains/langchain.chains.example_generator.generate_example.html |
a002249d070d-0 | langchain.chains.llm.LLMChain¶
class langchain.chains.llm.LLMChain[source]¶
Bases: Chain
Chain to run queries against LLMs.
Example
from langchain.chains import LLMChain
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-1 | Optional metadata associated with the chain. Defaults to None.
This metadata will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param output_parser: BaseLLMOutputParser [Optiona... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-2 | Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-3 | Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-4 | Generate LLM result from inputs.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-5 | Prepare prompts from inputs.
async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method and Ch... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-6 | # -> "The temperature in Boise is..."
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, conf... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-7 | Subclasses should override this method if they can batch more efficiently.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ fr... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-8 | # -> {"_type": "foo", "verbose": False, ...}
classmethod from_orm(obj: Any) → Model¶
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain[source]¶
Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-9 | The unique identifier is a list of strings that describes the path
to the object.
map() → Runnable[List[Input], List[Output]]¶
Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encod... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-10 | Returns
A dictionary of all inputs, including those added by the chain’s memory.
prep_outputs(inputs: Dict[str, str], outputs: Dict[str, str], return_only_outputs: bool = False) → Dict[str, str]¶
Validate and prepare chain outputs, and save info about this run to memory.
Parameters
inputs – Dictionary of chain inputs, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-11 | addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'que... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-12 | to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
a002249d070d-13 | A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: Type[pydantic.main.BaseModel]¶
Examples using LLMChain¶
Zapier Natural Language Actions
Dall-E Image Generator
Streamlit Chat Message History
Argilla
Comet
Aim
Weights & Biases
SageMaker Tracking
... | https://api.python.langchain.com/en/latest/chains/langchain.chains.llm.LLMChain.html |
744d0094ce2c-0 | langchain.chains.conversational_retrieval.base.ChatVectorDBChain¶
class langchain.chains.conversational_retrieval.base.ChatVectorDBChain[source]¶
Bases: BaseConversationalRetrievalChain
Chain for chatting with a vector database.
Create a new model by parsing and validating input data from keyword arguments.
Raises Vali... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-1 | and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a chain with its use case.
param output_key: str = 'answer'¶
The output key to return the final answer of this chain in.
param question_generator: LLMChain [Required]¶
The chain used to generate a new q... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-2 | will be printed to the console. Defaults to langchain.verbose value.
__call__(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, run_name... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-3 | Default implementation of abatch, which calls ainvoke N times.
Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optiona... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-4 | Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Call the chain on all inputs i... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-5 | # Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
question = "What's the temperature in Boise, Idaho?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(question=question, context=context)
# -> "The temperature in Boise is..."
async astream(input: Inp... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-6 | input is still being generated.
batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation of batch, which calls invoke N times.
Subclasses should override this method if they can ba... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-7 | **kwargs – Keyword arguments passed to default pydantic.BaseModel.dict
method.
Returns
A dictionary representation of the chain.
Example
chain.dict(exclude_unset=True)
# -> {"_type": "foo", "verbose": False, ...}
classmethod from_llm(llm: BaseLanguageModel, vectorstore: VectorStore, condense_question_prompt: BasePrompt... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-8 | classmethod is_lc_serializable() → bool¶
Is this class serializable?
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, exclude_defa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-9 | Parameters
inputs – Dictionary of raw inputs, or single input if chain expects
only one param. Should contain all inputs specified in
Chain.input_keys except for inputs that will be set by the chain’s
memory.
Returns
A dictionary of all inputs, including those added by the chain’s memory.
prep_outputs(inputs: Dict[str,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-10 | these runtime tags will propagate to calls to other objects.
**kwargs – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
Returns
The chain output.
Example
# Suppose we have a single-input chain that takes a 'question' string:
chain.run("What's the temperature in Boise, Idaho?")... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
744d0094ce2c-11 | Default implementation of transform, which buffers input and then calls stream.
Subclasses should override this method if they can start producing output while
input is still being generated.
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and lo... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversational_retrieval.base.ChatVectorDBChain.html |
7d48425bec4a-0 | langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain¶
class langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain[source]¶
Bases: MultiRouteChain
A multi-route chain that uses an LLM router chain to choose amongst retrieval
qa chains.
Create a new model by parsing and validating input data from k... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-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 router_chain: LLMRouterChain [Required]¶
Chain for deciding a destination chain and the input to it.
param silent_errors: bool = False¶
If True, use default_chain when a... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-2 | callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the c... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-3 | returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-4 | with all the inputs
Parameters
*args – If the chain expects a single input, it can be passed in as the
sole positional argument.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to call... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-5 | Subclasses should override this method if they support streaming output.
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Optional[Sequence[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-6 | Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclu... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-7 | classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
classmethod is_l... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-8 | classmethod parse_obj(obj: Any) → Model¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶
Validate and prepare chain inputs, including ad... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-9 | sole positional argument.
callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
additi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-10 | Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
to_json_not_implemented() → SerializedNotImplemented¶
transform(input: Iterator[Input], config: Optional[RunnableConfig] = No... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
7d48425bec4a-11 | property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
property output_schema: T... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
cf49014054ac-0 | langchain.chains.api.openapi.response_chain.APIResponderChain¶
class langchain.chains.api.openapi.response_chain.APIResponderChain[source]¶
Bases: LLMChain
Get the response parser.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed t... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
cf49014054ac-1 | Defaults to one that takes the most likely string but does not change it
otherwise.
param prompt: BasePromptTemplate [Required]¶
Prompt object to use.
param return_final_only: bool = True¶
Whether to return only the final parsed result. Defaults to True.
If false, will return a bunch of extra information about the gene... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
cf49014054ac-2 | callbacks – Callbacks to use for this chain run. These will be called in
addition to callbacks passed to the chain during construction, but only
these runtime callbacks will propagate to calls to other objects.
tags – List of string tags to pass to all callbacks. These will be passed in
addition to tags passed to the c... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
cf49014054ac-3 | Subclasses should override this method if they can batch more efficiently.
async acall(inputs: Union[Dict[str, Any], Any], return_only_outputs: bool = False, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
cf49014054ac-4 | Generate LLM result from inputs.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementation of ainvoke, which calls invoke in a thread pool.
Subclasses should override this method if they can run asynchronously.
apply(input_list: List[Dict[str, ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
cf49014054ac-5 | Prepare prompts from inputs.
async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → Any¶
Convenience method for executing chain.
The main difference between this method and Ch... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
cf49014054ac-6 | # -> "The temperature in Boise is..."
async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of astream, which calls ainvoke.
Subclasses should override this method if they support streaming output.
async astream_log(input: Any, conf... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
cf49014054ac-7 | Subclasses should override this method if they can batch more efficiently.
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ fr... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.response_chain.APIResponderChain.html |
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