id stringlengths 14 16 | text stringlengths 20 3.26k | source stringlengths 65 181 |
|---|---|---|
a120bec9ca06-1 | transformed_document = await qa_transformer.atransform_documents(documents)
Methods
__init__(properties[, openai_api_key, ...])
atransform_documents(documents, **kwargs)
Extracts properties from text documents using doctran.
transform_documents(documents, **kwargs)
Extracts properties from text documents using doctran.... | https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.doctran_text_extract.DoctranPropertyExtractor.html |
6265e13d12e8-0 | langchain_community.document_transformers.beautiful_soup_transformer.get_navigable_strings¶
langchain_community.document_transformers.beautiful_soup_transformer.get_navigable_strings(element: Any, *, remove_comments: bool = False) → Iterator[str][source]¶
Get all navigable strings from a BeautifulSoup element.
Paramete... | https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.beautiful_soup_transformer.get_navigable_strings.html |
39e8bd8a6abb-0 | langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter¶
class langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter[source]¶
Bases: BaseDocumentTransformer, BaseModel
Perform K-means clustering on document vectors.
Returns an arbitrary... | https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter.html |
39e8bd8a6abb-1 | kwargs (Any) –
Returns
A list of transformed Documents.
Return type
Sequence[Document]
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... | https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter.html |
39e8bd8a6abb-2 | self (Model) –
Returns
new model instance
Return type
Model
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, exclude_defaults: bo... | https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter.html |
39e8bd8a6abb-3 | Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
by_alias (bool) –
skip_defaults (Optional[bool]) –
exclude_unset (bool) –
exclude_defaults (bool) –
exclude_none (bool) –
encoder (Optional[Callable[[Any], Any]]) –
models... | https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter.html |
39e8bd8a6abb-4 | ref_template (unicode) –
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) –
ref_template (unicode) –
dumps_kwargs (Any) –
Return type
unicode
transform_documents(documents: Sequence[Do... | https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsClusteringFilter.html |
bf0f912852d4-0 | langchain_experimental.generative_agents.memory.GenerativeAgentMemory¶
class langchain_experimental.generative_agents.memory.GenerativeAgentMemory[source]¶
Bases: BaseMemory
Memory for the generative agent.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the inp... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.memory.GenerativeAgentMemory.html |
bf0f912852d4-1 | Add an observations or memories to the agent’s memory.
Parameters
memory_content (str) –
now (Optional[datetime]) –
Return type
List[str]
add_memory(memory_content: str, now: Optional[datetime] = None) → List[str][source]¶
Add an observation or memory to the agent’s memory.
Parameters
memory_content (str) –
now (Opt... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.memory.GenerativeAgentMemory.html |
bf0f912852d4-2 | values (Any) –
Return type
Model
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 choose which fields to include, exclude an... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.memory.GenerativeAgentMemory.html |
bf0f912852d4-3 | exclude_unset (bool) –
exclude_defaults (bool) –
exclude_none (bool) –
Return type
DictStrAny
fetch_memories(observation: str, now: Optional[datetime] = None) → List[Document][source]¶
Fetch related memories.
Parameters
observation (str) –
now (Optional[datetime]) –
Return type
List[Document]
format_memories_detai... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.memory.GenerativeAgentMemory.html |
bf0f912852d4-4 | 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().
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
exclude (Optional[Union[AbstractSetIntStr, Map... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.memory.GenerativeAgentMemory.html |
bf0f912852d4-5 | Parameters
obj (Any) –
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) –
content_type (unicode) –
encoding (unicode) –
proto (Protocol) –
allow_pi... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.memory.GenerativeAgentMemory.html |
bf0f912852d4-6 | SerializedNotImplemented
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) –
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) –
Return type
Model
property lc_attributes: Dict¶... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.memory.GenerativeAgentMemory.html |
88c73d88f8e3-0 | langchain_experimental.generative_agents.generative_agent.GenerativeAgent¶
class langchain_experimental.generative_agents.generative_agent.GenerativeAgent[source]¶
Bases: BaseModel
Agent as a character with memory and innate characteristics.
Create a new model by parsing and validating input data from keyword arguments... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.generative_agent.GenerativeAgent.html |
88c73d88f8e3-1 | Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) –
values (Any) –
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.generative_agent.GenerativeAgent.html |
88c73d88f8e3-2 | include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) –
by_alias (bool) –
skip_defaults (Optional[bool]) –
exclude_unset (bool) –
exclude_defaults (bool) –
exclude_none (bool) –
Return type
DictStrAny
classmethod from_orm(obj: Any) → Model... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.generative_agent.GenerativeAgent.html |
88c73d88f8e3-3 | now (Optional[datetime]) –
Return type
str
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, exclu... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.generative_agent.GenerativeAgent.html |
88c73d88f8e3-4 | Parameters
obj (Any) –
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) –
content_type (unicode) –
encoding (unicode) –
proto (Protocol) –
allow_pi... | https://api.python.langchain.com/en/latest/generative_agents/langchain_experimental.generative_agents.generative_agent.GenerativeAgent.html |
7ac48834f3ca-0 | langchain_experimental.llm_bash.base.LLMBashChain¶
class langchain_experimental.llm_bash.base.LLMBashChain[source]¶
Bases: Chain
Chain that interprets a prompt and executes bash operations.
Example
from langchain.chains import LLMBashChain
from langchain_community.llms import OpenAI
llm_bash = LLMBashChain.from_llm(Ope... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-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 prompt: BasePromptTemplate = PromptTemplate(input_variables=['question'], output_parser=BashOutputParser(), template='If someone asks you to perform a task, your job is ... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-2 | accessible via langchain.globals.get_verbose().
__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: Optional[str] = Non... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-3 | Return type
Dict[str, Any]
Notes
Deprecated since version langchain==0.1.0: Use invoke instead.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶
Default implementation runs ainvoke in para... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-4 | Return type
AsyncIterator[Tuple[int, Union[Output, Exception]]]
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, run_name: ... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-5 | Returns
A dict of named outputs. Should contain all outputs specified inChain.output_keys.
Return type
Dict[str, Any]
Notes
Deprecated since version langchain==0.1.0: Use ainvoke instead.
async ainvoke(input: Dict[str, Any], config: Optional[RunnableConfig] = None, **kwargs: Any) → Dict[str, Any]¶
Default implementatio... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-6 | A dictionary of all inputs, including those added by the chain’s memory.
Return type
Dict[str, str]
async aprep_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 (Dic... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-7 | addition to tags passed to the chain during construction, but only
these runtime tags will propagate to calls to other objects.
**kwargs (Any) – If the chain expects multiple inputs, they can be passed in
directly as keyword arguments.
metadata (Optional[Dict[str, Any]]) –
**kwargs –
Returns
The chain output.
Return ... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-8 | )
llm = FakeStreamingListLLM(responses=["foo-lish"])
chain: Runnable = prompt | llm | {"str": StrOutputParser()}
chain_with_assign = chain.assign(hello=itemgetter("str") | llm)
print(chain_with_assign.input_schema.schema())
# {'title': 'PromptInput', 'type': 'object', 'properties':
{'question': {'title': 'Question', 't... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-9 | kwargs (Optional[Any]) –
Return type
AsyncIterator[Output]
astream_events(input: Any, config: Optional[RunnableConfig] = None, *, version: Literal['v1', 'v2'], include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Opti... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-10 | Below is a table that illustrates some evens that might be emitted by various
chains. Metadata fields have been omitted from the table for brevity.
Chain definitions have been included after the table.
ATTENTION This reference table is for the V2 version of the schema.
event
name
chunk
input
output
on_chat_model_start
... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-11 | format_docs:
def format_docs(docs: List[Document]) -> str:
'''Format the docs.'''
return ", ".join([doc.page_content for doc in docs])
format_docs = RunnableLambda(format_docs)
some_tool:
@tool
def some_tool(x: int, y: str) -> dict:
'''Some_tool.'''
return {"x": x, "y": y}
prompt:
template = ChatPromptT... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-12 | },
]
Parameters
input (Any) – The input to the runnable.
config (Optional[RunnableConfig]) – The config to use for the runnable.
version (Literal['v1', 'v2']) – The version of the schema to use either v2 or v1.
Users should use v2.
v1 is for backwards compatibility and will be deprecated
in 0.4.0.
No default will be as... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-13 | An async stream of StreamEvents.
Return type
AsyncIterator[StreamEvent]
Notes
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, with_streamed_output_list: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: O... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-14 | exclude_tags (Optional[Sequence[str]]) – Exclude logs with these tags.
kwargs (Any) –
Return type
Union[AsyncIterator[RunLogPatch], AsyncIterator[RunLog]]
async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of a... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-15 | yielding results as they complete.
Parameters
inputs (Sequence[Input]) –
config (Optional[Union[RunnableConfig, Sequence[RunnableConfig]]]) –
return_exceptions (bool) –
kwargs (Optional[Any]) –
Return type
Iterator[Tuple[int, Union[Output, Exception]]]
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments t... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-16 | Return type
Type[BaseModel]
configurable_alternatives(which: ConfigurableField, *, default_key: str = 'default', prefix_keys: bool = False, **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
Configure alternatives for runnables that can be set at runt... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-17 | max_tokens=ConfigurableField(
id="output_token_number",
name="Max tokens in the output",
description="The maximum number of tokens in the output",
)
)
# max_tokens = 20
print(
"max_tokens_20: ",
model.invoke("tell me something about chess").content
)
# max_tokens = 200
print("max_tok... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-18 | update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
self (Model) –
Returns
new model instance
Return type
Model
dict(**kwargs: Any) → Dict¶
Dictionary ... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-19 | Parameters
llm (BaseLanguageModel) –
prompt (BasePromptTemplate) –
kwargs (Any) –
Return type
LLMBashChain
classmethod from_orm(obj: Any) → Model¶
Parameters
obj (Any) –
Return type
Model
get_graph(config: Optional[RunnableConfig] = None) → Graph¶
Return a graph representation of this runnable.
Parameters
config (O... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-20 | Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific co... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-21 | Is this class serializable?
Return type
bool
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, excl... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-22 | def _lambda(x: int) -> int:
return x + 1
runnable = RunnableLambda(_lambda)
print(runnable.map().invoke([1, 2, 3])) # [2, 3, 4]
Return type
Runnable[List[Input], List[Output]]
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pi... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-23 | json_only_chain = chain.pick("json")
json_only_chain.invoke("[1, 2, 3]")
# -> [1, 2, 3]
Pick list of keys:from typing import Any
import json
from langchain_core.runnables import RunnableLambda, RunnableMap
as_str = RunnableLambda(str)
as_json = RunnableLambda(json.loads)
def as_bytes(x: Any) -> bytes:
return bytes(... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-24 | return x * 2
runnable_1 = RunnableLambda(add_one)
runnable_2 = RunnableLambda(mul_two)
sequence = runnable_1.pipe(runnable_2)
# Or equivalently:
# sequence = runnable_1 | runnable_2
# sequence = RunnableSequence(first=runnable_1, last=runnable_2)
sequence.invoke(1)
await sequence.ainvoke(1)
# -> 4
sequence.batch([1, 2,... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-25 | return_only_outputs (bool) – 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.
Return type
Dict[str, str]
run(*args: Any, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, tags: Optional[List[str]] ... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-26 | # -> "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..."
chain.run(question=question, context=context)
# -> "The temperature in Boise ... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-27 | Iterator[Output]
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
Serialize the runnable to JSON.
Return type
Union[SerializedConstructor, SerializedNotImplemented]
to_json_not_implemented() → SerializedNotImplemented¶
Return type
SerializedNotImplemented
transform(input: Iterator[Input], config: Opt... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-28 | Example:
Parameters
on_start (Optional[AsyncListener]) –
on_end (Optional[AsyncListener]) –
on_error (Optional[AsyncListener]) –
Return type
Runnable[Input, Output]
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runnable.
Para... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-29 | exceptions will not be passed to fallbacks. If used, the base runnable
and its fallbacks must accept a dictionary as input.
Returns
A new Runnable that will try the original runnable, and then each
fallback in order, upon failures.
Return type
RunnableWithFallbacksT[Input, Output]
with_listeners(*, on_start: Optional[U... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-30 | on_end=fn_end
)
chain.invoke(2)
Parameters
on_start (Optional[Union[Callable[[Run], None], Callable[[Run, RunnableConfig], None]]]) –
on_end (Optional[Union[Callable[[Run], None], Callable[[Run, RunnableConfig], None]]]) –
on_error (Optional[Union[Callable[[Run], None], Callable[[Run, RunnableConfig], None]]]) –
Ret... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
7ac48834f3ca-31 | Return type
Runnable[Input, Output]
with_types(*, input_type: Optional[Type[Input]] = None, output_type: Optional[Type[Output]] = None) → Runnable[Input, Output]¶
Bind input and output types to a Runnable, returning a new Runnable.
Parameters
input_type (Optional[Type[Input]]) –
output_type (Optional[Type[Output]]) – ... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.base.LLMBashChain.html |
30fba74d63fa-0 | langchain_experimental.llm_bash.bash.BashProcess¶
class langchain_experimental.llm_bash.bash.BashProcess(strip_newlines: bool = False, return_err_output: bool = False, persistent: bool = False)[source]¶
Wrapper for starting subprocesses.
Uses the python built-in subprocesses.run()
Persistent processes are not available... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.bash.BashProcess.html |
30fba74d63fa-1 | Uses regex to remove the command from the output
Parameters
output (str) – a process’ output string
command (str) – the executed command
Return type
str
run(commands: Union[str, List[str]]) → str[source]¶
Run commands in either an existing persistent
subprocess or on in a new subprocess environment.
Parameters
commands... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.bash.BashProcess.html |
5b566a64b9f8-0 | langchain_experimental.llm_bash.prompt.BashOutputParser¶
class langchain_experimental.llm_bash.prompt.BashOutputParser[source]¶
Bases: BaseOutputParser
Parser for bash output.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to for... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-1 | Return type
AsyncIterator[Tuple[int, Union[Output, Exception]]]
async ainvoke(input: Union[str, BaseMessage], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → T¶
Default implementation of ainvoke, calls invoke from a thread.
The default implementation allows usage of async code even if
the runnable d... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-2 | from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import SystemMessagePromptTemplate
from langchain_core.runnables import Runnable
from operator import itemgetter
prompt = (
SystemMessagePromptTemplate.from_template("You are a nice assistant.")
+ "{question}"
)
llm = FakeStre... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-3 | kwargs (Optional[Any]) –
Return type
AsyncIterator[Output]
astream_events(input: Any, config: Optional[RunnableConfig] = None, *, version: Literal['v1', 'v2'], include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names: Opti... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-4 | Below is a table that illustrates some evens that might be emitted by various
chains. Metadata fields have been omitted from the table for brevity.
Chain definitions have been included after the table.
ATTENTION This reference table is for the V2 version of the schema.
event
name
chunk
input
output
on_chat_model_start
... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-5 | format_docs:
def format_docs(docs: List[Document]) -> str:
'''Format the docs.'''
return ", ".join([doc.page_content for doc in docs])
format_docs = RunnableLambda(format_docs)
some_tool:
@tool
def some_tool(x: int, y: str) -> dict:
'''Some_tool.'''
return {"x": x, "y": y}
prompt:
template = ChatPromptT... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-6 | },
]
Parameters
input (Any) – The input to the runnable.
config (Optional[RunnableConfig]) – The config to use for the runnable.
version (Literal['v1', 'v2']) – The version of the schema to use either v2 or v1.
Users should use v2.
v1 is for backwards compatibility and will be deprecated
in 0.4.0.
No default will be as... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-7 | An async stream of StreamEvents.
Return type
AsyncIterator[StreamEvent]
Notes
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, with_streamed_output_list: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: O... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-8 | exclude_tags (Optional[Sequence[str]]) – Exclude logs with these tags.
kwargs (Any) –
Return type
Union[AsyncIterator[RunLogPatch], AsyncIterator[RunLog]]
async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶
Default implementation of a... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-9 | yielding results as they complete.
Parameters
inputs (Sequence[Input]) –
config (Optional[Union[RunnableConfig, Sequence[RunnableConfig]]]) –
return_exceptions (bool) –
kwargs (Optional[Any]) –
Return type
Iterator[Tuple[int, Union[Output, Exception]]]
bind(**kwargs: Any) → Runnable[Input, Output]¶
Bind arguments t... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-10 | Return type
Type[BaseModel]
configurable_alternatives(which: ConfigurableField, *, default_key: str = 'default', prefix_keys: bool = False, **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶
Configure alternatives for runnables that can be set at runt... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-11 | max_tokens=ConfigurableField(
id="output_token_number",
name="Max tokens in the output",
description="The maximum number of tokens in the output",
)
)
# max_tokens = 20
print(
"max_tokens_20: ",
model.invoke("tell me something about chess").content
)
# max_tokens = 200
print("max_tok... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-12 | update (Optional[DictStrAny]) – 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 (bool) – set to True to make a deep copy of the model
self (Model) –
Returns
new model instance
Return type
Model
dict(**kwargs: Any) → Dict¶
Return dict... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-13 | Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
Return type
List[str]
get_name(suffix: Optional[str] = None, *, name: Optional[str] = None) → str¶
Get the name of the runnable.
Parameters
suffix (Optional[str]) –... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-14 | in parallel, and other keys. Please refer to the RunnableConfig
for more details.
Returns
The output of the runnable.
Return type
T
classmethod is_lc_serializable() → bool¶
Is this class serializable?
Return type
bool
json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-15 | Return a new Runnable that maps a list of inputs to a list of outputs,
by calling invoke() with each input.
Example
from langchain_core.runnables import RunnableLambda
def _lambda(x: int) -> int:
return x + 1
runnable = RunnableLambda(_lambda)
print(runnable.map().invoke([1, 2, 3])) # [2, 3, 4]
Return type
Runnable... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-16 | Parse a list of candidate model Generations into a specific format.
The return value is parsed from only the first Generation in the result, whichis assumed to be the highest-likelihood Generation.
Parameters
result (List[Generation]) – A list of Generations to be parsed. The Generations are assumed
to be different can... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-17 | as_str = RunnableLambda(str)
as_json = RunnableLambda(json.loads)
def as_bytes(x: Any) -> bytes:
return bytes(x, "utf-8")
chain = RunnableMap(
str=as_str,
json=as_json,
bytes=RunnableLambda(as_bytes)
)
chain.invoke("[1, 2, 3]")
# -> {"str": "[1, 2, 3]", "json": [1, 2, 3], "bytes": b"[1, 2, 3]"}
json_and... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-18 | sequence.invoke(1)
await sequence.ainvoke(1)
# -> 4
sequence.batch([1, 2, 3])
await sequence.abatch([1, 2, 3])
# -> [4, 6, 8]
Parameters
others (Union[Runnable[Any, Other], Callable[[Any], Other]]) –
name (Optional[str]) –
Return type
RunnableSerializable[Input, Other]
classmethod schema(by_alias: bool = True, ref_te... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-19 | 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.
Parameters
input (Iterator[Input]) –
config (Optional[RunnableConfig]) –
kwargs (Optional[Any]) –
Return type
Iterator[Output... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-20 | config (Optional[RunnableConfig]) –
kwargs (Any) –
Return type
Runnable[Input, Output]
with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'Exception'>,), exception_key: Optional[str] = None) → RunnableWithFallbacksT[Input, Output]¶
Add fallb... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-21 | Return type
RunnableWithFallbacksT[Input, Output]
with_listeners(*, on_start: Optional[Union[Callable[[Run], None], Callable[[Run, RunnableConfig], None]]] = None, on_end: Optional[Union[Callable[[Run], None], Callable[[Run, RunnableConfig], None]]] = None, on_error: Optional[Union[Callable[[Run], None], Callable[[Run,... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-22 | on_error (Optional[Union[Callable[[Run], None], Callable[[Run, RunnableConfig], None]]]) –
Return type
Runnable[Input, Output]
with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_after_attempt: int = 3) → Runnable[I... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
5b566a64b9f8-23 | output_type (Optional[Type[Output]]) –
Return type
Runnable[Input, Output]
property InputType: Any¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[T]¶
The type of output this runnable produces specified as a type annotation.
property config_specs: List[ConfigurableFie... | https://api.python.langchain.com/en/latest/llm_bash/langchain_experimental.llm_bash.prompt.BashOutputParser.html |
a6ab0fa5d05f-0 | langchain_google_community.bigquery.BigQueryLoader¶
class langchain_google_community.bigquery.BigQueryLoader(query: str, project: Optional[str] = None, page_content_columns: Optional[List[str]] = None, metadata_columns: Optional[List[str]] = None, credentials: Optional[Credentials] = None)[source]¶
Load from the Google... | https://api.python.langchain.com/en/latest/bigquery/langchain_google_community.bigquery.BigQueryLoader.html |
a6ab0fa5d05f-1 | load_and_split([text_splitter])
Load Documents and split into chunks.
__init__(query: str, project: Optional[str] = None, page_content_columns: Optional[List[str]] = None, metadata_columns: Optional[List[str]] = None, credentials: Optional[Credentials] = None)[source]¶
Initialize BigQuery document loader.
Parameters
qu... | https://api.python.langchain.com/en/latest/bigquery/langchain_google_community.bigquery.BigQueryLoader.html |
a6ab0fa5d05f-2 | Defaults to RecursiveCharacterTextSplitter.
Returns
List of Documents.
Return type
List[Document] | https://api.python.langchain.com/en/latest/bigquery/langchain_google_community.bigquery.BigQueryLoader.html |
a32c098a1990-0 | langchain_text_splitters.python.PythonCodeTextSplitter¶
class langchain_text_splitters.python.PythonCodeTextSplitter(**kwargs: Any)[source]¶
Attempts to split the text along Python syntax.
Initialize a PythonCodeTextSplitter.
Methods
__init__(**kwargs)
Initialize a PythonCodeTextSplitter.
atransform_documents(documents... | https://api.python.langchain.com/en/latest/python/langchain_text_splitters.python.PythonCodeTextSplitter.html |
a32c098a1990-1 | Create documents from a list of texts.
Parameters
texts (List[str]) –
metadatas (Optional[List[dict]]) –
Return type
List[Document]
classmethod from_huggingface_tokenizer(tokenizer: Any, **kwargs: Any) → TextSplitter¶
Text splitter that uses HuggingFace tokenizer to count length.
Parameters
tokenizer (Any) –
kwargs ... | https://api.python.langchain.com/en/latest/python/langchain_text_splitters.python.PythonCodeTextSplitter.html |
a32c098a1990-2 | Parameters
text (str) –
Return type
List[str]
transform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document]¶
Transform sequence of documents by splitting them.
Parameters
documents (Sequence[Document]) –
kwargs (Any) –
Return type
Sequence[Document] | https://api.python.langchain.com/en/latest/python/langchain_text_splitters.python.PythonCodeTextSplitter.html |
1e3aa089c9f1-0 | langchain_community.docstore.base.Docstore¶
class langchain_community.docstore.base.Docstore[source]¶
Interface to access to place that stores documents.
Methods
__init__()
delete(ids)
Deleting IDs from in memory dictionary.
search(search)
Search for document.
__init__()¶
delete(ids: List) → None[source]¶
Deleting IDs ... | https://api.python.langchain.com/en/latest/docstore/langchain_community.docstore.base.Docstore.html |
33570c0bbc64-0 | langchain_community.docstore.in_memory.InMemoryDocstore¶
class langchain_community.docstore.in_memory.InMemoryDocstore(_dict: Optional[Dict[str, Document]] = None)[source]¶
Simple in memory docstore in the form of a dict.
Initialize with dict.
Methods
__init__([_dict])
Initialize with dict.
add(texts)
Add texts to in m... | https://api.python.langchain.com/en/latest/docstore/langchain_community.docstore.in_memory.InMemoryDocstore.html |
9688755dd4b5-0 | langchain_community.docstore.arbitrary_fn.DocstoreFn¶
class langchain_community.docstore.arbitrary_fn.DocstoreFn(lookup_fn: Callable[[str], Union[Document, str]])[source]¶
Docstore via arbitrary lookup function.
This is useful when:
it’s expensive to construct an InMemoryDocstore/dict
you retrieve documents from remote... | https://api.python.langchain.com/en/latest/docstore/langchain_community.docstore.arbitrary_fn.DocstoreFn.html |
4fe34177d037-0 | langchain_community.docstore.base.AddableMixin¶
class langchain_community.docstore.base.AddableMixin[source]¶
Mixin class that supports adding texts.
Methods
__init__()
add(texts)
Add more documents.
__init__()¶
abstract add(texts: Dict[str, Document]) → None[source]¶
Add more documents.
Parameters
texts (Dict[str, Doc... | https://api.python.langchain.com/en/latest/docstore/langchain_community.docstore.base.AddableMixin.html |
c650361c3da8-0 | langchain_community.docstore.wikipedia.Wikipedia¶
class langchain_community.docstore.wikipedia.Wikipedia[source]¶
Wikipedia API.
Check that wikipedia package is installed.
Methods
__init__()
Check that wikipedia package is installed.
delete(ids)
Deleting IDs from in memory dictionary.
search(search)
Try to search for w... | https://api.python.langchain.com/en/latest/docstore/langchain_community.docstore.wikipedia.Wikipedia.html |
01e680dec4f4-0 | langchain_community.llms.huggingface_hub.HuggingFaceHub¶
class langchain_community.llms.huggingface_hub.HuggingFaceHub[source]¶
Bases: LLM
[Deprecated] HuggingFaceHub models.
! This class is deprecated, you should use HuggingFaceEndpoint instead.
To use, you should have the huggingface_hub python package installed, an... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-1 | param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model_kwargs: Optional[dict] = None¶
Keyword arguments to pass to the model.
param repo_id: Optional[str] = None¶
Model name to use.
If not provided, the default model for the chosen task will be used.
param tags: Optional[List[str... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-2 | Default implementation runs ainvoke in parallel using asyncio.gather.
The default implementation of batch works well for IO bound runnables.
Subclasses should override this method if they can batch more efficiently;
e.g., if the underlying runnable uses an API which supports a batch mode.
Parameters
inputs (List[Union[... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-3 | Return type
AsyncIterator[Tuple[int, Union[Output, Exception]]]
async agenerate(prompts: List[str], stop: Optional[List[str]] = None, callbacks: Union[List[BaseCallbackHandler], BaseCallbackManager, None, List[Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]]]] = None, *, tags: Optional[Union[List[str], L... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-4 | tags (Optional[Union[List[str], List[List[str]]]]) –
metadata (Optional[Union[Dict[str, Any], List[Dict[str, Any]]]]) –
run_name (Optional[Union[str, List[str]]]) –
run_id (Optional[Union[UUID, List[Optional[UUID]]]]) –
**kwargs –
Returns
An LLMResult, which contains a list of candidate Generations for each inputp... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-5 | functionality, such as logging or streaming, throughout generation.
**kwargs (Any) – Arbitrary additional keyword arguments. These are usually passed
to the model provider API call.
Returns
An LLMResult, which contains a list of candidate Generations for each inputprompt and additional model provider-specific output.
R... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-6 | Parameters
messages (List[BaseMessage]) –
stop (Optional[Sequence[str]]) –
kwargs (Any) –
Return type
BaseMessage
assign(**kwargs: Union[Runnable[Dict[str, Any], Any], Callable[[Dict[str, Any]], Any], Mapping[str, Union[Runnable[Dict[str, Any], Any], Callable[[Dict[str, Any]], Any]]]]) → RunnableSerializable[Any, An... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-7 | Return type
RunnableSerializable[Any, Any]
async astream(input: Union[PromptValue, str, Sequence[Union[BaseMessage, List[str], Tuple[str, str], str, Dict[str, Any]]]], config: Optional[RunnableConfig] = None, *, stop: Optional[List[str]] = None, **kwargs: Any) → AsyncIterator[str]¶
Default implementation of astream, wh... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-8 | A child runnable that gets invoked as part of the execution of a
parent runnable is assigned its own unique ID.
parent_ids: List[str] - The IDs of the parent runnables thatgenerated the event. The root runnable will have an empty list.
The order of the parent IDs is from the root to the immediate parent.
Only available... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-9 | on_tool_end
some_tool
{“x”: 1, “y”: “2”}
on_retriever_start
[retriever name]
{“query”: “hello”}
on_retriever_end
[retriever name]
{“query”: “hello”}
[Document(…), ..]
on_prompt_start
[template_name]
{“question”: “hello”}
on_prompt_end
[template_name]
{“question”: “hello”}
ChatPromptValue(messages: [SystemMessage, …])
H... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-10 | "event": "on_chain_start",
"metadata": {},
"name": "reverse",
"tags": [],
},
{
"data": {"chunk": "olleh"},
"event": "on_chain_stream",
"metadata": {},
"name": "reverse",
"tags": [],
},
{
"data": {"output": "olleh"},
"event":... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
01e680dec4f4-11 | of astream_events is built on top of astream_log.
Returns
An async stream of StreamEvents.
Return type
AsyncIterator[StreamEvent]
Notes
async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, with_streamed_output_list: bool = True, include_names: Optional[Sequence[str]] = None, incl... | https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_hub.HuggingFaceHub.html |
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