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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, …]) Here are decl...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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"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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
6bd30ceb83cf-13
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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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exclude_types (Optional[Sequence[str]]) – Exclude logs with these types. 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, **kw...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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Run invoke in parallel on a list of inputs, 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)...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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Returns A pydantic model that can be used to validate config. 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]...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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model = ChatOpenAI(max_tokens=20).configurable_fields( 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 somethin...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include 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...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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Parameters obj (Any) – Return type Model get_graph(config: Optional[RunnableConfig] = None) → Graph¶ Return a graph representation of this runnable. Parameters config (Optional[RunnableConfig]) – Return type Graph get_input_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶ Get a pydantic model that c...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
6bd30ceb83cf-20
This method allows to get an output schema for a specific configuration. Parameters config (Optional[RunnableConfig]) – A config to use when generating the schema. Returns A pydantic model that can be used to validate output. Return type Type[BaseModel] get_prompts(config: Optional[RunnableConfig] = None) → List[BasePr...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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encoding (unicode) – proto (Protocol) – allow_pickle (bool) – Return type Model classmethod parse_obj(obj: Any) → Model¶ 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 = Fals...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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_bytes_chain = chain.pick(["json", "bytes"]) json_and_bytes_chain.invoke("[1, 2, 3]") # -> {"json": [1, 2, 3], "bytes": b"[1, 2, 3]"} Parameters keys (Union[str, List[...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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# -> [4, 6, 8] Parameters others (Union[Runnable[Any, Other], Callable[[Any], Other]]) – name (Optional[str]) – Return type RunnableSerializable[Input, Other] prep_inputs(inputs: Union[Dict[str, Any], Any]) → Dict[str, str]¶ Prepare chain inputs, including adding inputs from memory. Parameters inputs (Union[Dict[str,...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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 (Any) – If the chain expects a single input, it can be passed in as the sole positional argument. callbacks (Optional[Union[List[Base...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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Expects Chain._chain_type property to be implemented and for memory to benull. Parameters file_path (Union[Path, str]) – Path to file to save the chain to. Return type None Example chain.save(file_path="path/chain.yaml") save_progress() → None¶ This function should be called to save the state of the learned policy mode...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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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/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBest.html
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langchain_experimental.rl_chain.base.embed_string_type¶ langchain_experimental.rl_chain.base.embed_string_type(item: Union[str, _Embed], model: Any, namespace: Optional[str] = None) → Dict[str, Union[str, List[str]]][source]¶ Embed a string or an _Embed object. Parameters item (Union[str, _Embed]) – model (Any) – nam...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.embed_string_type.html
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langchain_experimental.rl_chain.metrics.MetricsTrackerAverage¶ class langchain_experimental.rl_chain.metrics.MetricsTrackerAverage(step: int)[source]¶ Metrics Tracker Average. Attributes score Methods __init__(step) on_decision() on_feedback(score) to_pandas() Parameters step (int) – __init__(step: int)[source]¶ Param...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.metrics.MetricsTrackerAverage.html
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langchain_experimental.rl_chain.base.SelectionScorer¶ class langchain_experimental.rl_chain.base.SelectionScorer[source]¶ Bases: Generic[TEvent], ABC, BaseModel Abstract class to grade the chosen selection or the response of the llm. Create a new model by parsing and validating input data from keyword arguments. Raises...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.SelectionScorer.html
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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/rl_chain/langchain_experimental.rl_chain.base.SelectionScorer.html
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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/rl_chain/langchain_experimental.rl_chain.base.SelectionScorer.html
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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 abstract score_response(inputs: Dict[str, ...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.SelectionScorer.html
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langchain_experimental.rl_chain.metrics.MetricsTrackerRollingWindow¶ class langchain_experimental.rl_chain.metrics.MetricsTrackerRollingWindow(window_size: int, step: int)[source]¶ Metrics Tracker Rolling Window. Attributes score Methods __init__(window_size, step) on_decision() on_feedback(value) to_pandas() Parameter...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.metrics.MetricsTrackerRollingWindow.html
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langchain_experimental.rl_chain.base.Event¶ class langchain_experimental.rl_chain.base.Event(inputs: Dict[str, Any], selected: Optional[TSelected] = None)[source]¶ Abstract class to represent an event. Attributes inputs selected Methods __init__(inputs[, selected]) Parameters inputs (Dict[str, Any]) – selected (Option...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.Event.html
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langchain_experimental.rl_chain.pick_best_chain.PickBestSelected¶ class langchain_experimental.rl_chain.pick_best_chain.PickBestSelected(index: Optional[int] = None, probability: Optional[float] = None, score: Optional[float] = None)[source]¶ Selected class for PickBest chain. Attributes index probability score Methods...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBestSelected.html
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langchain_experimental.rl_chain.base.ToSelectFrom¶ langchain_experimental.rl_chain.base.ToSelectFrom(anything: Any) → _ToSelectFrom[source]¶ Wrap a value to indicate that it should be selected from. Parameters anything (Any) – Return type _ToSelectFrom
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.ToSelectFrom.html
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langchain_experimental.rl_chain.base.Embed¶ langchain_experimental.rl_chain.base.Embed(anything: Any, keep: bool = False) → Any[source]¶ Wrap a value to indicate that it should be embedded. Parameters anything (Any) – keep (bool) – Return type Any
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.Embed.html
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langchain_experimental.rl_chain.vw_logger.VwLogger¶ class langchain_experimental.rl_chain.vw_logger.VwLogger(path: Optional[Union[str, PathLike]])[source]¶ Vowpal Wabbit custom logger. Methods __init__(path) log(vw_ex) logging_enabled() Parameters path (Optional[Union[str, PathLike]]) – __init__(path: Optional[Union[s...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.vw_logger.VwLogger.html
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langchain_experimental.rl_chain.pick_best_chain.PickBestEvent¶ class langchain_experimental.rl_chain.pick_best_chain.PickBestEvent(inputs: Dict[str, Any], to_select_from: Dict[str, Any], based_on: Dict[str, Any], selected: Optional[PickBestSelected] = None)[source]¶ Event class for PickBest chain. Attributes Methods __...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBestEvent.html
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langchain_experimental.rl_chain.base.EmbedAndKeep¶ langchain_experimental.rl_chain.base.EmbedAndKeep(anything: Any) → Any[source]¶ Wrap a value to indicate that it should be embedded and kept. Parameters anything (Any) – Return type Any
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.EmbedAndKeep.html
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langchain_experimental.rl_chain.base.prepare_inputs_for_autoembed¶ langchain_experimental.rl_chain.base.prepare_inputs_for_autoembed(inputs: Dict[str, Any]) → Dict[str, Any][source]¶ Prepare the inputs for auto embedding. Go over all the inputs and if something is either wrapped in _ToSelectFrom or _BasedOn, and if the...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.prepare_inputs_for_autoembed.html
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langchain_experimental.rl_chain.base.parse_lines¶ langchain_experimental.rl_chain.base.parse_lines(parser: vw.TextFormatParser, input_str: str) → List['vw.Example'][source]¶ Parse the input string into a list of examples. Parameters parser (vw.TextFormatParser) – input_str (str) – Return type List[‘vw.Example’]
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.parse_lines.html
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langchain_experimental.rl_chain.base.get_based_on_and_to_select_from¶ langchain_experimental.rl_chain.base.get_based_on_and_to_select_from(inputs: Dict[str, Any]) → Tuple[Dict, Dict][source]¶ Get the BasedOn and ToSelectFrom from the inputs. Parameters inputs (Dict[str, Any]) – Return type Tuple[Dict, Dict]
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.get_based_on_and_to_select_from.html
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langchain_experimental.rl_chain.base.embed_dict_type¶ langchain_experimental.rl_chain.base.embed_dict_type(item: Dict, model: Any) → Dict[str, Any][source]¶ Embed a dictionary item. Parameters item (Dict) – model (Any) – Return type Dict[str, Any]
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.embed_dict_type.html
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langchain_experimental.rl_chain.base.Selected¶ class langchain_experimental.rl_chain.base.Selected[source]¶ Abstract class to represent the selected item. Methods __init__() __init__()¶
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.Selected.html
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langchain_experimental.rl_chain.base.is_stringtype_instance¶ langchain_experimental.rl_chain.base.is_stringtype_instance(item: Any) → bool[source]¶ Check if an item is a string. Parameters item (Any) – Return type bool
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.base.is_stringtype_instance.html
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langchain_experimental.rl_chain.pick_best_chain.PickBestRandomPolicy¶ class langchain_experimental.rl_chain.pick_best_chain.PickBestRandomPolicy(feature_embedder: Embedder, **kwargs: Any)[source]¶ Random policy for PickBest chain. Methods __init__(feature_embedder, **kwargs) learn(event) log(event) predict(event) save(...
https://api.python.langchain.com/en/latest/rl_chain/langchain_experimental.rl_chain.pick_best_chain.PickBestRandomPolicy.html
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langchain_prompty.langchain.create_chat_prompt¶ langchain_prompty.langchain.create_chat_prompt(path: str, input_name_agent_scratchpad: str = 'agent_scratchpad') → Runnable[Dict[str, Any], ChatPromptTemplate][source]¶ Parameters path (str) – input_name_agent_scratchpad (str) – Return type Runnable[Dict[str, Any], Chat...
https://api.python.langchain.com/en/latest/langchain/langchain_prompty.langchain.create_chat_prompt.html
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langchain_core.structured_query.Visitor¶ class langchain_core.structured_query.Visitor[source]¶ Defines interface for IR translation using visitor pattern. Attributes allowed_comparators allowed_operators Methods __init__() visit_comparison(comparison) Translate a Comparison. visit_operation(operation) Translate an Ope...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Visitor.html
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langchain_core.structured_query.FilterDirective¶ class langchain_core.structured_query.FilterDirective[source]¶ Bases: Expr, ABC Filtering expression. 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 model. accept(v...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.FilterDirective.html
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deep (bool) – set to True to make a deep copy of the model 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...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.FilterDirective.html
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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/structured_query/langchain_core.structured_query.FilterDirective.html
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Parameters by_alias (bool) – 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 classmethod ...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.FilterDirective.html
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langchain_core.structured_query.Operator¶ class langchain_core.structured_query.Operator(value)[source]¶ Enumerator of the operations. AND = 'and'¶ OR = 'or'¶ NOT = 'not'¶ Examples using Operator¶ How to construct filters for query analysis
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Operator.html
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langchain_core.structured_query.Comparator¶ class langchain_core.structured_query.Comparator(value)[source]¶ Enumerator of the comparison operators. EQ = 'eq'¶ NE = 'ne'¶ GT = 'gt'¶ GTE = 'gte'¶ LT = 'lt'¶ LTE = 'lte'¶ CONTAIN = 'contain'¶ LIKE = 'like'¶ IN = 'in'¶ NIN = 'nin'¶ Examples using Comparator¶ How to constru...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Comparator.html
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langchain_core.structured_query.Comparison¶ class langchain_core.structured_query.Comparison[source]¶ Bases: FilterDirective 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 model. param attri...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Comparison.html
00b7611d31b5-1
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(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: ...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Comparison.html
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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/structured_query/langchain_core.structured_query.Comparison.html
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Parameters by_alias (bool) – 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 classmethod ...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Comparison.html
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langchain_core.structured_query.Expr¶ class langchain_core.structured_query.Expr[source]¶ Bases: BaseModel Base class for all expressions. 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 model. accept(visitor: Visi...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Expr.html
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deep (bool) – set to True to make a deep copy of the model 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...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Expr.html
0b5ca7ecf056-2
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/structured_query/langchain_core.structured_query.Expr.html
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Parameters by_alias (bool) – 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 classmethod ...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Expr.html
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langchain_core.structured_query.Operation¶ class langchain_core.structured_query.Operation[source]¶ Bases: FilterDirective Llogical 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 form a valid m...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Operation.html
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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(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: ...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Operation.html
759458d3563e-2
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/structured_query/langchain_core.structured_query.Operation.html
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Parameters by_alias (bool) – 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 classmethod ...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.Operation.html
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langchain_core.structured_query.StructuredQuery¶ class langchain_core.structured_query.StructuredQuery[source]¶ Bases: Expr Structured query. 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 model. param filter: Opt...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.StructuredQuery.html
0c148bf1eda6-1
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(*, include: Optional[Union[Abstrac...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.StructuredQuery.html
0c148bf1eda6-2
Parameters obj (Any) – Return type Model 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...
https://api.python.langchain.com/en/latest/structured_query/langchain_core.structured_query.StructuredQuery.html
0c148bf1eda6-3
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/structured_query/langchain_core.structured_query.StructuredQuery.html
a1ca80ae05e2-0
langchain_ai21.semantic_text_splitter.AI21SemanticTextSplitter¶ class langchain_ai21.semantic_text_splitter.AI21SemanticTextSplitter(chunk_size: int = 0, chunk_overlap: int = 0, client: Optional[Any] = None, api_key: Optional[SecretStr] = None, api_host: Optional[str] = None, timeout_sec: Optional[float] = None, num_re...
https://api.python.langchain.com/en/latest/semantic_text_splitter/langchain_ai21.semantic_text_splitter.AI21SemanticTextSplitter.html
a1ca80ae05e2-1
num_retries (Optional[int]) – kwargs (Any) – __init__(chunk_size: int = 0, chunk_overlap: int = 0, client: Optional[Any] = None, api_key: Optional[SecretStr] = None, api_host: Optional[str] = None, timeout_sec: Optional[float] = None, num_retries: Optional[int] = None, **kwargs: Any) → None[source]¶ Create a new Text...
https://api.python.langchain.com/en/latest/semantic_text_splitter/langchain_ai21.semantic_text_splitter.AI21SemanticTextSplitter.html
a1ca80ae05e2-2
kwargs (Any) – Return type TextSplitter classmethod from_tiktoken_encoder(encoding_name: str = 'gpt2', model_name: Optional[str] = None, allowed_special: Union[Literal['all'], AbstractSet[str]] = {}, disallowed_special: Union[Literal['all'], Collection[str]] = 'all', **kwargs: Any) → TS¶ Text splitter that uses tiktok...
https://api.python.langchain.com/en/latest/semantic_text_splitter/langchain_ai21.semantic_text_splitter.AI21SemanticTextSplitter.html
a5c59f944478-0
langchain_community.document_transformers.google_translate.GoogleTranslateTransformer¶ class langchain_community.document_transformers.google_translate.GoogleTranslateTransformer(project_id: str, *, location: str = 'global', model_id: Optional[str] = None, glossary_id: Optional[str] = None, api_endpoint: Optional[str] ...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.google_translate.GoogleTranslateTransformer.html
a5c59f944478-1
Asynchronously transform a list of documents. Parameters documents (Sequence[Document]) – A sequence of Documents to be transformed. kwargs (Any) – Returns A list of transformed Documents. Return type Sequence[Document] transform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document][source]¶ Tra...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.google_translate.GoogleTranslateTransformer.html
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langchain_community.document_transformers.openai_functions.create_metadata_tagger¶ langchain_community.document_transformers.openai_functions.create_metadata_tagger(metadata_schema: Union[Dict[str, Any], Type[BaseModel]], llm: BaseLanguageModel, prompt: Optional[ChatPromptTemplate] = None, *, tagging_chain_kwargs: Opti...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.openai_functions.create_metadata_tagger.html
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"required": ["movie_title", "critic", "tone"] } # Must be an OpenAI model that supports functions llm = ChatOpenAI(temperature=0, model="gpt-3.5-turbo-0613") document_transformer = create_metadata_tagger(schema, llm) original_documents = [ Document(page_content="Review of The Bee Movie By Roger Ebert This is the gr...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.openai_functions.create_metadata_tagger.html
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langchain_community.document_transformers.doctran_text_translate.DoctranTextTranslator¶ class langchain_community.document_transformers.doctran_text_translate.DoctranTextTranslator(openai_api_key: Optional[str] = None, language: str = 'english', openai_api_model: Optional[str] = None)[source]¶ Translate text documents ...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.doctran_text_translate.DoctranTextTranslator.html
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kwargs (Any) – Returns A list of transformed Documents. Return type Sequence[Document] transform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document][source]¶ Translates text documents using doctran. Parameters documents (Sequence[Document]) – kwargs (Any) – Return type Sequence[Document] Exa...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.doctran_text_translate.DoctranTextTranslator.html
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langchain_community.document_transformers.doctran_text_qa.DoctranQATransformer¶ class langchain_community.document_transformers.doctran_text_qa.DoctranQATransformer(openai_api_key: Optional[str] = None, openai_api_model: Optional[str] = None)[source]¶ Extract QA from text documents using doctran. Parameters openai_api_...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.doctran_text_qa.DoctranQATransformer.html
b6abeb8a170b-1
Returns A list of transformed Documents. Return type Sequence[Document] transform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document][source]¶ Extracts QA from text documents using doctran. Parameters documents (Sequence[Document]) – kwargs (Any) – Return type Sequence[Document] Examples usin...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.doctran_text_qa.DoctranQATransformer.html
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langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter¶ class langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter[source]¶ Bases: BaseDocumentTransformer, BaseModel Filter that drops redundant documents by comparing their embeddings. C...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter.html
f4c38ad90a5c-1
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/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter.html
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exclude_unset (bool) – exclude_defaults (bool) – exclude_none (bool) – Return type DictStrAny classmethod from_orm(obj: Any) → Model¶ Parameters obj (Any) – Return type Model json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] =...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter.html
f4c38ad90a5c-3
content_type (unicode) – encoding (unicode) – proto (Protocol) – allow_pickle (bool) – Return type Model classmethod parse_obj(obj: Any) → Model¶ Parameters obj (Any) – Return type Model classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None,...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter.html
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Parameters value (Any) – Return type Model Examples using EmbeddingsRedundantFilter¶ How to do retrieval with contextual compression LOTR (Merger Retriever)
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.EmbeddingsRedundantFilter.html
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langchain_community.document_transformers.beautiful_soup_transformer.BeautifulSoupTransformer¶ class langchain_community.document_transformers.beautiful_soup_transformer.BeautifulSoupTransformer[source]¶ Transform HTML content by extracting specific tags and removing unwanted ones. Example from langchain_community.docu...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.beautiful_soup_transformer.BeautifulSoupTransformer.html
68737773d507-1
Extract specific tags from a given HTML content. Parameters html_content (str) – The original HTML content string. tags (Union[List[str], Tuple[str, ...]]) – A list of tags to be extracted from the HTML. remove_comments (bool) – Returns A string combining the content of the extracted tags. Return type str static remov...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.beautiful_soup_transformer.BeautifulSoupTransformer.html
68737773d507-2
Returns A cleaned HTML string with unwanted tags removed. Return type str transform_documents(documents: Sequence[Document], unwanted_tags: Union[List[str], Tuple[str, ...]] = ('script', 'style'), tags_to_extract: Union[List[str], Tuple[str, ...]] = ('p', 'li', 'div', 'a'), remove_lines: bool = True, *, unwanted_classn...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.beautiful_soup_transformer.BeautifulSoupTransformer.html
59f8fbf848e5-0
langchain_community.document_transformers.nuclia_text_transform.NucliaTextTransformer¶ class langchain_community.document_transformers.nuclia_text_transform.NucliaTextTransformer(nua: NucliaUnderstandingAPI)[source]¶ Nuclia Text Transformer. The Nuclia Understanding API splits into paragraphs and sentences, identifies ...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.nuclia_text_transform.NucliaTextTransformer.html
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langchain_community.document_transformers.openai_functions.OpenAIMetadataTagger¶ class langchain_community.document_transformers.openai_functions.OpenAIMetadataTagger[source]¶ Bases: BaseDocumentTransformer, BaseModel Extract metadata tags from document contents using OpenAI functions. Example:from langchain_community....
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.openai_functions.OpenAIMetadataTagger.html
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Raises ValidationError if the input data cannot be parsed to form a valid model. param tagging_chain: Any = None¶ The chain used to extract metadata from each document. async atransform_documents(documents: Sequence[Document], **kwargs: Any) → Sequence[Document][source]¶ Asynchronously transform a list of documents. Pa...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.openai_functions.OpenAIMetadataTagger.html
3306b7daa32c-2
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(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: ...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.openai_functions.OpenAIMetadataTagger.html
3306b7daa32c-3
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/document_transformers/langchain_community.document_transformers.openai_functions.OpenAIMetadataTagger.html
3306b7daa32c-4
Parameters by_alias (bool) – 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_do...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.openai_functions.OpenAIMetadataTagger.html
0fa5a3afd03d-0
langchain_community.document_transformers.html2text.Html2TextTransformer¶ class langchain_community.document_transformers.html2text.Html2TextTransformer(ignore_links: bool = True, ignore_images: bool = True)[source]¶ Replace occurrences of a particular search pattern with a replacement string Parameters ignore_links (b...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.html2text.Html2TextTransformer.html
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langchain_community.document_transformers.markdownify.MarkdownifyTransformer¶ class langchain_community.document_transformers.markdownify.MarkdownifyTransformer(strip: Optional[Union[str, List[str]]] = None, convert: Optional[Union[str, List[str]]] = None, autolinks: bool = True, heading_style: str = 'ATX', **kwargs: A...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.markdownify.MarkdownifyTransformer.html
02a98ba6655e-1
transform_documents(documents, **kwargs) Transform a list of documents. __init__(strip: Optional[Union[str, List[str]]] = None, convert: Optional[Union[str, List[str]]] = None, autolinks: bool = True, heading_style: str = 'ATX', **kwargs: Any) → None[source]¶ Parameters strip (Optional[Union[str, List[str]]]) – conver...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.markdownify.MarkdownifyTransformer.html
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langchain_community.document_transformers.embeddings_redundant_filter.get_stateful_documents¶ langchain_community.document_transformers.embeddings_redundant_filter.get_stateful_documents(documents: Sequence[Document]) → Sequence[_DocumentWithState][source]¶ Convert a list of documents to a list of documents with state....
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.embeddings_redundant_filter.get_stateful_documents.html
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langchain_community.document_transformers.long_context_reorder.LongContextReorder¶ class langchain_community.document_transformers.long_context_reorder.LongContextReorder[source]¶ Bases: BaseDocumentTransformer, BaseModel Reorder long context. Lost in the middle: Performance degrades when models must access relevant in...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.long_context_reorder.LongContextReorder.html
88fc59ca292a-1
Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes preced...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.long_context_reorder.LongContextReorder.html
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Parameters obj (Any) – Return type Model 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...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.long_context_reorder.LongContextReorder.html
88fc59ca292a-3
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/document_transformers/langchain_community.document_transformers.long_context_reorder.LongContextReorder.html
a120bec9ca06-0
langchain_community.document_transformers.doctran_text_extract.DoctranPropertyExtractor¶ class langchain_community.document_transformers.doctran_text_extract.DoctranPropertyExtractor(properties: List[dict], openai_api_key: Optional[str] = None, openai_api_model: Optional[str] = None)[source]¶ Extract properties from te...
https://api.python.langchain.com/en/latest/document_transformers/langchain_community.document_transformers.doctran_text_extract.DoctranPropertyExtractor.html