id stringlengths 14 15 | text stringlengths 49 2.47k | source stringlengths 61 166 |
|---|---|---|
e72cd91d48b3-2 | 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 |
e72cd91d48b3-3 | 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 chain during construction, but only
these runtime tags will propagate to c... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
e72cd91d48b3-4 | 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, they can be passed in
directly as keyword arguments.
Returns
The c... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
e72cd91d48b3-5 | 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.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
e72cd91d48b3-6 | 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_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
e72cd91d48b3-7 | Validate and prepare chain outputs, and save info about this run to memory.
Parameters
inputs – Dictionary of chain inputs, including any inputs added by chain
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 fi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
e72cd91d48b3-8 | # and 'context' string:
question = "What's the temperature in Boise, Idaho?"
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 i... | https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
e72cd91d48b3-9 | 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/latest/chains/langchain.chains.router.multi_retrieval_qa.MultiRetrievalQAChain.html |
da1e6e6f3fad-0 | langchain.chains.openai_functions.extraction.create_extraction_chain_pydantic¶
langchain.chains.openai_functions.extraction.create_extraction_chain_pydantic(pydantic_schema: Any, llm: BaseLanguageModel) → Chain[source]¶
Creates a chain that extracts information from a passage using pydantic schema.
Parameters
pydantic_... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.extraction.create_extraction_chain_pydantic.html |
df9e6461a787-0 | 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 |
df9e6461a787-1 | # 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 |
df9e6461a787-2 | 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 |
df9e6461a787-3 | Chain.input_keys except for inputs that will be set by the chain’s
memory.
return_only_outputs – Whether to return only outputs in the
response. If True, only new keys generated by this chain will be
returned. If False, both input keys and new keys generated by this
chain will be returned. Defaults to False.
callbacks ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
df9e6461a787-4 | 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 – Callbacks to use for this chain run. These will be called in
addi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
df9e6461a787-5 | apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Call the chain on all inputs in the list.
async arun(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]]... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
df9e6461a787-6 | 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: Input, config: Optional[RunnableConfig] = None) → AsyncIterator[Output]¶
batch(inputs: List[Inpu... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
df9e6461a787-7 | 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 |
df9e6461a787-8 | 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_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
df9e6461a787-9 | Validate and prepare chain outputs, and save info about this run to memory.
Parameters
inputs – Dictionary of chain inputs, including any inputs added by chain
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 fi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
df9e6461a787-10 | 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.combine_documents.reduce.ReduceDocumentsChain.html |
df9e6461a787-11 | classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.Runnable[~langchain.schema.runnable.Input, ~langchain.schema.runnable.Out... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html |
ca785a794ae2-0 | langchain.chains.sql_database.query.create_sql_query_chain¶
langchain.chains.sql_database.query.create_sql_query_chain(llm: BaseLanguageModel, db: SQLDatabase, prompt: Optional[BasePromptTemplate] = None, k: int = 5) → RunnableSequence[Union[SQLInput, SQLInputWithTables], str][source]¶
Create a chain that generates SQL... | https://api.python.langchain.com/en/latest/chains/langchain.chains.sql_database.query.create_sql_query_chain.html |
559db883dcc7-0 | 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 |
559db883dcc7-1 | 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 |
559db883dcc7-2 | 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 |
559db883dcc7-3 | 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.base.Chain.html |
559db883dcc7-4 | 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.base.Chain.html |
559db883dcc7-5 | 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__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
559db883dcc7-6 | 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_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
559db883dcc7-7 | Validate and prepare chain outputs, and save info about this run to memory.
Parameters
inputs – Dictionary of chain inputs, including any inputs added by chain
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 fi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
559db883dcc7-8 | # 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..."
chain.run(question=question, context=context)
# -> "The temperature in Boise is..."
save(file_path: Union[Path, str... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
559db883dcc7-9 | Keys expected to be in the chain input.
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... | https://api.python.langchain.com/en/latest/chains/langchain.chains.base.Chain.html |
d111337adb95-0 | langchain.chains.combine_documents.reduce.CombineDocsProtocol¶
class langchain.chains.combine_documents.reduce.CombineDocsProtocol(*args, **kwargs)[source]¶
Interface for the combine_docs method.
Methods
__init__(*args, **kwargs)
__init__(*args, **kwargs)¶ | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.reduce.CombineDocsProtocol.html |
ae9cdbf48e57-0 | langchain.chains.query_constructor.ir.Operation¶
class langchain.chains.query_constructor.ir.Operation[source]¶
Bases: FilterDirective
A logical operation over other directives.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to f... | https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.Operation.html |
ae9cdbf48e57-1 | 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.query_constructor.ir.Operation.html |
ae9cdbf48e57-2 | 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.query_constructor.ir.Operation.html |
013f6e9ce514-0 | langchain.chains.natbot.crawler.ElementInViewPort¶
class langchain.chains.natbot.crawler.ElementInViewPort[source]¶
A typed dictionary containing information about elements in the viewport.
node_index: str¶
backend_node_id: int¶
node_name: Optional[str]¶
node_value: Optional[str]¶
node_meta: List[str]¶
is_clickable: bo... | https://api.python.langchain.com/en/latest/chains/langchain.chains.natbot.crawler.ElementInViewPort.html |
35fc01dbb37f-0 | langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain¶
class langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain[source]¶
Bases: BaseCombineDocumentsChain
Combining documents by mapping a chain over them, then combining results.
We first call llm_chain on each document individually, pa... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-1 | document_variable_name=document_variable_name
)
reduce_documents_chain = ReduceDocumentsChain(
combine_documents_chain=combine_documents_chain,
)
chain = MapReduceDocumentsChain(
llm_chain=llm_chain,
reduce_documents_chain=reduce_documents_chain,
)
# If we wanted to, we could also pass in collapse_documents... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-2 | If only one variable in the llm_chain, this need not be provided.
param llm_chain: LLMChain [Required]¶
Chain to apply to each document individually.
param memory: Optional[BaseMemory] = None¶
Optional memory object. Defaults to None.
Memory is a class that gets called at the start
and at the end of every chain. At the... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-3 | 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, include_... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-4 | 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, include_run_info: bool = False) → Dict[str, Any]¶
Asynchronously execute t... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-5 | Combine by mapping first chain over all documents, then reducing the results.
This reducing can be done recursively if needed (if there are many documents).
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None) → Dict[str, Any]¶
apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[L... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-6 | 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?"
context = "Weather report for Boise, Idaho on 07/03/23..."
await chain.arun(... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-7 | 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.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-8 | 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_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-9 | Validate and prepare chain outputs, and save info about this run to memory.
Parameters
inputs – Dictionary of chain inputs, including any inputs added by chain
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 fi... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-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.combine_documents.map_reduce.MapReduceDocumentsChain.html |
35fc01dbb37f-11 | classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
classmethod validate(value: Any) → Model¶
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.Runnable[~langchain.schema.runnable.Input, ~langchain.schema.runnable.Out... | https://api.python.langchain.com/en/latest/chains/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html |
3b5b5f66d7af-0 | langchain.chains.query_constructor.ir.Comparison¶
class langchain.chains.query_constructor.ir.Comparison[source]¶
Bases: FilterDirective
A comparison to a value.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid mode... | https://api.python.langchain.com/en/latest/chains/langchain.chains.query_constructor.ir.Comparison.html |
3b5b5f66d7af-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.query_constructor.ir.Comparison.html |
3b5b5f66d7af-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.query_constructor.ir.Comparison.html |
51ec320aa567-0 | 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 |
8464471e123f-0 | langchain.chains.openai_functions.utils.get_llm_kwargs¶
langchain.chains.openai_functions.utils.get_llm_kwargs(function: dict) → dict[source]¶
Returns the kwargs for the LLMChain constructor.
Parameters
function – The function to use.
Returns
The kwargs for the LLMChain constructor. | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.utils.get_llm_kwargs.html |
cf59dfb1f917-0 | langchain.chains.conversation.base.ConversationChain¶
class langchain.chains.conversation.base.ConversationChain[source]¶
Bases: LLMChain
Chain to have a conversation and load context from memory.
Example
from langchain import ConversationChain, OpenAI
conversation = ConversationChain(llm=OpenAI())
Create a new model b... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-1 | Defaults to one that takes the most likely string but does not change it
otherwise.
param prompt: langchain.schema.prompt_template.BasePromptTemplate = PromptTemplate(input_variables=['history', 'input'], output_parser=None, partial_variables={}, template='The following is a friendly conversation between a human and an... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-2 | 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.conversation.base.ConversationChain.html |
cf59dfb1f917-3 | 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, include_run_info: bool = False) → Dict[str, Any]¶
Asynchronously execute t... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-4 | apply(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None) → List[Dict[str, str]]¶
Utilize the LLM generate method for speed gains.
apply_and_parse(input_list: List[Dict[str, Any]], callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-5 | 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.conversation.base.ConversationChain.html |
cf59dfb1f917-6 | 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__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-7 | classmethod from_orm(obj: Any) → Model¶
classmethod from_string(llm: BaseLanguageModel, template: str) → LLMChain¶
Create LLMChain from LLM and template.
generate(input_list: List[Dict[str, Any]], run_manager: Optional[CallbackManagerForChainRun] = None) → LLMResult¶
Generate LLM result from inputs.
invoke(input: Dict[... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-8 | Format prompt with kwargs and pass to LLM.
Parameters
callbacks – Callbacks to pass to LLMChain
**kwargs – Keys to pass to prompt template.
Returns
Completion from LLM.
Example
completion = llm.predict(adjective="funny")
predict_and_parse(callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-9 | Prepare prompts from inputs.
run(*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 Chain.__c... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-10 | 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 save the chain to.
Example
chain.save(file_path="path/chain.yaml")
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definiti... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
cf59dfb1f917-11 | 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.
Examples using ConversationChain¶
Entity Memory with SQLite storage
Figma
Bedrock
Agent Debates with To... | https://api.python.langchain.com/en/latest/chains/langchain.chains.conversation.base.ConversationChain.html |
fc8f2af83042-0 | langchain.chains.openai_functions.base.create_openai_fn_chain¶
langchain.chains.openai_functions.base.create_openai_fn_chain(functions: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable]], llm: BaseLanguageModel, prompt: BasePromptTemplate, *, output_parser: Optional[BaseLLMOutputParser] = None, **kwargs: Any) →... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.base.create_openai_fn_chain.html |
fc8f2af83042-1 | Returns
An LLMChain that will pass in the given functions to the model when run.
Example
from langchain.chains.openai_functions import create_openai_fn_chain
from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
from pydantic import BaseModel, Field
cl... | https://api.python.langchain.com/en/latest/chains/langchain.chains.openai_functions.base.create_openai_fn_chain.html |
b88159037905-0 | langchain.chains.api.openapi.chain.OpenAPIEndpointChain¶
class langchain.chains.api.openapi.chain.OpenAPIEndpointChain[source]¶
Bases: Chain, BaseModel
Chain interacts with an OpenAPI endpoint using natural language.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError ... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-1 | param requests: Requests [Optional]¶
param return_intermediate_steps: bool = False¶
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the chain. Defaults to None.
These tags will be associated with each call to this chain,
and passed as arguments to the handlers defined in callbacks.
You can... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-2 | these runtime tags will propagate to calls to other objects.
metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async abatch... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-3 | metadata – Optional metadata associated with the chain. Defaults to None
include_run_info – Whether to include run info in the response. Defaults
to False.
Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = N... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-4 | 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.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-5 | Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include
update – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep – set to True to make a deep co... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-6 | Create an OpenAPIEndpoint from a spec at the specified url.
invoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None) → Dict[str, Any]¶
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False,... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-7 | 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.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-8 | 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?")
# -> "The temperature in Boise is..."
# Suppose we have a multi-input chain that takes a 'question' string
# and 'context' string:
... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
b88159037905-9 | classmethod validate(value: Any) → Model¶
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.Runnable[~langchain.schema.runnable.Input, ~langchain.schema.runnable.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException]] = (<class 'Exception'>,)) → RunnableWithFallbacks[Input, Out... | https://api.python.langchain.com/en/latest/chains/langchain.chains.api.openapi.chain.OpenAPIEndpointChain.html |
36e8154e2a43-0 | langchain.chat_models.anthropic.ChatAnthropic¶
class langchain.chat_models.anthropic.ChatAnthropic[source]¶
Bases: BaseChatModel, _AnthropicCommon
Anthropic’s large language chat model.
To use, you should have the anthropic python package installed, and the
environment variable ANTHROPIC_API_KEY set with your API key, ... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-1 | param model: str = 'claude-2'¶
Model name to use.
param streaming: bool = False¶
Whether to stream the results.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temperature: Optional[float] = None¶
A non-negative float that tunes the degree of randomness in generation.
param top_k: Optional[i... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-2 | This method should make use of batched calls for models that expose a batched
API.
Use this method when you want to:
take advantage of batched calls,
need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion ... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-3 | to the model provider API call.
Returns
Top model prediction as a string.
async apredict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶
Asynchronously pass messages to the model and return a message prediction.
Use this method when calling chat models and on... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-4 | 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/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-5 | need more output from the model than just the top generated value,
are building chains that are agnostic to the underlying language modeltype (e.g., pure text completion models vs chat models).
Parameters
prompts – List of PromptValues. A PromptValue is an object that can be
converted to match the format of any languag... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-6 | 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_defaults: bool = False, exclude_none: bool = False, encoder: Optional[Cal... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-7 | to the model provider API call.
Returns
Top model prediction as a string.
predict_messages(messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → BaseMessage¶
Pass a message sequence to the model and return a message prediction.
Use this method when passing in chat messages. If you want ... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
36e8154e2a43-8 | classmethod validate(value: Any) → Model¶
with_fallbacks(fallbacks: ~typing.Sequence[~langchain.schema.runnable.Runnable[~langchain.schema.runnable.Input, ~langchain.schema.runnable.Output]], *, exceptions_to_handle: ~typing.Tuple[~typing.Type[BaseException]] = (<class 'Exception'>,)) → RunnableWithFallbacks[Input, Out... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.anthropic.ChatAnthropic.html |
ea53f4c96a7f-0 | langchain.chat_models.human.HumanInputChatModel¶
class langchain.chat_models.human.HumanInputChatModel[source]¶
Bases: BaseChatModel
ChatModel which returns user input as the response.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be pars... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-1 | async agenerate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → LLMResult¶
Top Level call
async agenerate_prompt(prompt... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-2 | async ainvoke(input: Union[PromptValue, str, List[BaseMessage]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → BaseMessageChunk¶
async apredict(text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any) → str¶
Asynchronously pass a string to the model and return ... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-3 | batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]¶
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments to a Runnable, returning a new Runnable.
call_as_llm(message: str, stop: Optional[List[str]] = None, **... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-4 | classmethod from_orm(obj: Any) → Model¶
generate(messages: List[List[BaseMessage]], stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → LLMResult¶
Top Level c... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-5 | Get the number of tokens present in the text.
Useful for checking if an input will fit in a model’s context window.
Parameters
text – The string input to tokenize.
Returns
The integer number of tokens in the text.
get_num_tokens_from_messages(messages: List[BaseMessage]) → int¶
Get the number of tokens in the messages.... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-6 | 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¶
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-7 | to the model provider API call.
Returns
Top model prediction as a message.
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(in... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
ea53f4c96a7f-8 | property lc_serializable: bool¶
Return whether or not the class is serializable.
Examples using HumanInputChatModel¶
Human input Chat Model | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.human.HumanInputChatModel.html |
d03c862ff44c-0 | langchain.chat_models.google_palm.ChatGooglePalm¶
class langchain.chat_models.google_palm.ChatGooglePalm[source]¶
Bases: BaseChatModel, BaseModel
Wrapper around Google’s PaLM Chat API.
To use you must have the google.generativeai Python package installed and
either:
The GOOGLE_API_KEY` environment variable set with you... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.google_palm.ChatGooglePalm.html |
d03c862ff44c-1 | Must be positive.
param top_p: Optional[float] = None¶
Decode using nucleus sampling: consider the smallest set of tokens whose
probability sum is at least top_p. Must be in the closed interval [0.0, 1.0].
param verbose: bool [Optional]¶
Whether to print out response text.
__call__(messages: List[BaseMessage], stop: Op... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.google_palm.ChatGooglePalm.html |
d03c862ff44c-2 | Parameters
prompts – List of PromptValues. A PromptValue is an object that can be
converted to match the format of any language model (string for pure
text generation models and BaseMessages for chat models).
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these subst... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.google_palm.ChatGooglePalm.html |
d03c862ff44c-3 | Use this method when calling chat models and only the topcandidate generation is needed.
Parameters
messages – A sequence of chat messages corresponding to a single model input.
stop – Stop words to use when generating. Model output is cut off at the
first occurrence of any of these substrings.
**kwargs – Arbitrary add... | https://api.python.langchain.com/en/latest/chat_models/langchain.chat_models.google_palm.ChatGooglePalm.html |
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