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exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(*, i...
lang/api.python.langchain.com/en/latest/smith/langchain.smith.evaluation.config.SingleKeyEvalConfig.html
250271cdfbb1-2
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto...
lang/api.python.langchain.com/en/latest/smith/langchain.smith.evaluation.config.SingleKeyEvalConfig.html
8c63148cc78e-0
langchain.smith.evaluation.string_run_evaluator.StringExampleMapper¶ class langchain.smith.evaluation.string_run_evaluator.StringExampleMapper[source]¶ Bases: Serializable Map an example, or row in the dataset, to the inputs of an evaluation. Create a new model by parsing and validating input data from keyword argument...
lang/api.python.langchain.com/en/latest/smith/langchain.smith.evaluation.string_run_evaluator.StringExampleMapper.html
8c63148cc78e-1
deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
lang/api.python.langchain.com/en/latest/smith/langchain.smith.evaluation.string_run_evaluator.StringExampleMapper.html
8c63148cc78e-2
The unique identifier is a list of strings that describes the path to the object. map(example: Example) → Dict[str, str][source]¶ Maps the Example, or dataset row to a dictionary. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pi...
lang/api.python.langchain.com/en/latest/smith/langchain.smith.evaluation.string_run_evaluator.StringExampleMapper.html
f1e568bf69f9-0
langchain.prompts.base.get_template_variables¶ langchain.prompts.base.get_template_variables(template: str, template_format: str) → List[str][source]¶ Get the variables from the template. Parameters template – The template string. template_format – The template format. Should be one of “f-string” or “jinja2”. Returns T...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.get_template_variables.html
15a4d7c690db-0
langchain.prompts.chat.BaseChatPromptTemplate¶ class langchain.prompts.chat.BaseChatPromptTemplate[source]¶ Bases: BasePromptTemplate, ABC Base class for chat prompt templates. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parsed to fo...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-1
Subclasses should override this method if they can run asynchronously. async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of astream, which calls ainvoke. Subclasses should override this method if they support streaming output. a...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-2
Default implementation runs invoke in parallel using a thread pool executor. 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. bind(**kwargs: Any) → R...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-3
Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-4
Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “openai”] get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶ Get a pydantic model that can be used to validate output to the runnable. Runnables th...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-5
classmethod is_lc_serializable() → bool¶ Return whether this class is serializable. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = Fals...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-6
Save the prompt. Parameters file_path – Path to directory to save prompt to. Example: .. code-block:: python prompt.save(file_path=”path/prompt.yaml”) classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: ...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-7
Add fallbacks to a runnable, returning a new Runnable. Parameters fallbacks – A sequence of runnables to try if the original runnable fails. exceptions_to_handle – A tuple of exception types to handle. Returns A new Runnable that will try the original runnable, and then each fallback in order, upon failures. with_liste...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
15a4d7c690db-8
Bind input and output types to a Runnable, returning a new Runnable. property InputType: Type[langchain.schema.runnable.utils.Input]¶ The type of input this runnable accepts specified as a type annotation. property OutputType: Any¶ The type of output this runnable produces specified as a type annotation. property confi...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseChatPromptTemplate.html
88b7e5376a32-0
langchain.prompts.loading.load_prompt¶ langchain.prompts.loading.load_prompt(path: Union[str, Path]) → BasePromptTemplate[source]¶ Unified method for loading a prompt from LangChainHub or local fs. Examples using load_prompt¶ Amazon Comprehend Moderation Chain Serialization
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.loading.load_prompt.html
d6367679850f-0
langchain.prompts.example_selector.base.BaseExampleSelector¶ class langchain.prompts.example_selector.base.BaseExampleSelector[source]¶ Interface for selecting examples to include in prompts. Methods __init__() add_example(example) Add new example to store for a key. select_examples(input_variables) Select which exampl...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.base.BaseExampleSelector.html
2b6bd3282da2-0
langchain.prompts.example_selector.ngram_overlap.ngram_overlap_score¶ langchain.prompts.example_selector.ngram_overlap.ngram_overlap_score(source: List[str], example: List[str]) → float[source]¶ Compute ngram overlap score of source and example as sentence_bleu score. Use sentence_bleu with method1 smoothing function a...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.ngram_overlap.ngram_overlap_score.html
1748b302ba94-0
langchain.prompts.base.validate_jinja2¶ langchain.prompts.base.validate_jinja2(template: str, input_variables: List[str]) → None[source]¶ Validate that the input variables are valid for the template. Issues a warning if missing or extra variables are found. Parameters template – The template string. input_variables – T...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.validate_jinja2.html
25b90a939f5c-0
langchain.prompts.pipeline.PipelinePromptTemplate¶ class langchain.prompts.pipeline.PipelinePromptTemplate[source]¶ Bases: BasePromptTemplate A prompt template for composing multiple prompt templates together. This can be useful when you want to reuse parts of prompts. A PipelinePrompt consists of two main parts: final...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-1
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. async ainvoke(input: Input, co...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-2
The jsonpatch ops can be applied in order to construct state. async atransform(input: AsyncIterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of atransform, which buffers input and calls astream. Subclasses should override this method if th...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-3
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶ Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if Config.extra = ‘allow’ was set since it adds all passed values...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-4
methods will have a dynamic input schema that depends on which configuration the runnable is invoked with. This method allows to get an input schema for a specific configuration. Parameters config – A config to use when generating the schema. Returns A pydantic model that can be used to validate input. classmethod get_...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-5
classmethod is_lc_serializable() → bool¶ Return whether this class is serializable. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = Fals...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-6
Save the prompt. Parameters file_path – Path to directory to save prompt to. Example: .. code-block:: python prompt.save(file_path=”path/prompt.yaml”) classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_json(*, by_alias: bool = True, ref_template: ...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-7
Add fallbacks to a runnable, returning a new Runnable. Parameters fallbacks – A sequence of runnables to try if the original runnable fails. exceptions_to_handle – A tuple of exception types to handle. Returns A new Runnable that will try the original runnable, and then each fallback in order, upon failures. with_liste...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
25b90a939f5c-8
Bind input and output types to a Runnable, returning a new Runnable. property InputType: Type[langchain.schema.runnable.utils.Input]¶ The type of input this runnable accepts specified as a type annotation. property OutputType: Any¶ The type of output this runnable produces specified as a type annotation. property confi...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.pipeline.PipelinePromptTemplate.html
d313b1c83a41-0
langchain.prompts.base.jinja2_formatter¶ langchain.prompts.base.jinja2_formatter(template: str, **kwargs: Any) → str[source]¶ Format a template using jinja2. Security warning: As of LangChain 0.0.329, this method uses Jinja2’sSandboxedEnvironment by default. However, this sand-boxing should be treated as a best-effort ...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.jinja2_formatter.html
fac8f870698f-0
langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates¶ class langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates[source]¶ Bases: StringPromptTemplate Prompt template that contains few shot examples. Create a new model by parsing and validating input data from keyword arguments. Raises Va...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-1
param template_format: str = 'f-string'¶ The format of the prompt template. Options are: ‘f-string’, ‘jinja2’. param validate_template: bool = False¶ Whether or not to try validating the template. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exception...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-2
Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-3
e.g., if the underlying runnable uses an API which supports a batch mode. bind(**kwargs: Any) → Runnable[Input, Output]¶ Bind arguments to a Runnable, returning a new Runnable. config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶ The type of config this runnable accepts specified as a pydantic m...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-4
exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(**kw...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-5
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 configuration. Parameters config – A config to use when generating the schem...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-6
The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input. classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encod...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-7
to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶ Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-8
The Run object contains information about the run, including its id, type, input, output, error, start_time, end_time, and any tags or metadata added to the run. with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_af...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fac8f870698f-9
A map of constructor argument names to secret ids. For example,{“openai_api_key”: “OPENAI_API_KEY”} property output_schema: Type[pydantic.main.BaseModel]¶ The type of output this runnable produces specified as a pydantic model.
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot_with_templates.FewShotPromptWithTemplates.html
fe4e284ec39b-0
langchain.prompts.chat.BaseMessagePromptTemplate¶ class langchain.prompts.chat.BaseMessagePromptTemplate[source]¶ Bases: Serializable, ABC Base class for message prompt templates. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parsed to...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseMessagePromptTemplate.html
fe4e284ec39b-1
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. abstract format_messages(**kwargs: Any) → List[BaseMessage][source]¶ Format messages from kwargs. Should return a list of BaseMessages. Parameters **kwargs – Keyword arguments to use for formatting. Returns List...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseMessagePromptTemplate.html
fe4e284ec39b-2
classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmet...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseMessagePromptTemplate.html
b724c5932392-0
langchain.prompts.chat.BaseStringMessagePromptTemplate¶ class langchain.prompts.chat.BaseStringMessagePromptTemplate[source]¶ Bases: BaseMessagePromptTemplate, ABC Base class for message prompt templates that use a string prompt template. Create a new model by parsing and validating input data from keyword arguments. R...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseStringMessagePromptTemplate.html
b724c5932392-1
deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseStringMessagePromptTemplate.html
b724c5932392-2
A new instance of this class. classmethod get_lc_namespace() → List[str]¶ Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “openai”] classmethod is_lc_serializable() → bool¶ Return whether or not the class is serializable. ...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseStringMessagePromptTemplate.html
b724c5932392-3
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to upda...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.BaseStringMessagePromptTemplate.html
7fcb9c30e975-0
langchain.prompts.loading.load_prompt_from_config¶ langchain.prompts.loading.load_prompt_from_config(config: dict) → BasePromptTemplate[source]¶ Load prompt from Config Dict.
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.loading.load_prompt_from_config.html
418924db01b9-0
langchain.prompts.chat.HumanMessagePromptTemplate¶ class langchain.prompts.chat.HumanMessagePromptTemplate[source]¶ Bases: BaseStringMessagePromptTemplate Human message prompt template. This is a message sent from the user. Create a new model by parsing and validating input data from keyword arguments. Raises Validatio...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.HumanMessagePromptTemplate.html
418924db01b9-1
deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.HumanMessagePromptTemplate.html
418924db01b9-2
Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “openai”] classmethod is_lc_serializable() → bool¶ Return whether or not the class is serializable. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = No...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.HumanMessagePromptTemplate.html
418924db01b9-3
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to upda...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.HumanMessagePromptTemplate.html
62ca70213344-0
langchain.prompts.base.StringPromptTemplate¶ class langchain.prompts.base.StringPromptTemplate[source]¶ Bases: BasePromptTemplate, ABC String prompt that exposes the format method, returning a prompt. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input dat...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-1
Subclasses should override this method if they can run asynchronously. async astream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → AsyncIterator[Output]¶ Default implementation of astream, which calls ainvoke. Subclasses should override this method if they support streaming output. a...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-2
Default implementation runs invoke in parallel using a thread pool executor. 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. bind(**kwargs: Any) → R...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-3
Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-4
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...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-5
A unique identifier for this class for serialization purposes. The unique identifier is a list of strings that describes the path to the object. map() → Runnable[List[Input], List[Output]]¶ Return a new Runnable that maps a list of inputs to a list of outputs, by calling invoke() with each input. classmethod parse_file...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-6
to_json_not_implemented() → SerializedNotImplemented¶ transform(input: Iterator[Input], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶ Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-7
The Run object contains information about the run, including its id, type, input, output, error, start_time, end_time, and any tags or metadata added to the run. with_retry(*, retry_if_exception_type: ~typing.Tuple[~typing.Type[BaseException], ...] = (<class 'Exception'>,), wait_exponential_jitter: bool = True, stop_af...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
62ca70213344-8
A map of constructor argument names to secret ids. For example,{“openai_api_key”: “OPENAI_API_KEY”} property output_schema: Type[pydantic.main.BaseModel]¶ The type of output this runnable produces specified as a pydantic model. Examples using StringPromptTemplate¶ Plug-and-Plai Wikibase Agent SalesGPT - Your Context-Aw...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.StringPromptTemplate.html
1d3005096236-0
langchain.prompts.example_selector.ngram_overlap.NGramOverlapExampleSelector¶ class langchain.prompts.example_selector.ngram_overlap.NGramOverlapExampleSelector[source]¶ Bases: BaseExampleSelector, BaseModel Select and order examples based on ngram overlap score (sentence_bleu score). https://www.nltk.org/_modules/nltk...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.ngram_overlap.NGramOverlapExampleSelector.html
1d3005096236-1
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶ Duplicate a model, optionally...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.ngram_overlap.NGramOverlapExampleSelector.html
1d3005096236-2
classmethod from_orm(obj: Any) → 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_n...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.ngram_overlap.NGramOverlapExampleSelector.html
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classmethod update_forward_refs(**localns: Any) → None¶ Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶ Examples using NGramOverlapExampleSelector¶ Select by n-gram overlap
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.ngram_overlap.NGramOverlapExampleSelector.html
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langchain.prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector¶ class langchain.prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector[source]¶ Bases: BaseExampleSelector, BaseModel Example selector that selects examples based on SemanticSimilarity. Create a new model b...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector.html
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exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(*, i...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector.html
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classmethod from_orm(obj: Any) → 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_n...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector.html
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classmethod validate(value: Any) → Model¶ Examples using SemanticSimilarityExampleSelector¶ Select by maximal marginal relevance (MMR) Few-shot examples for chat models
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.SemanticSimilarityExampleSelector.html
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langchain.prompts.few_shot.FewShotPromptTemplate¶ class langchain.prompts.few_shot.FewShotPromptTemplate[source]¶ Bases: _FewShotPromptTemplateMixin, StringPromptTemplate Prompt template that contains few shot examples. Create a new model by parsing and validating input data from keyword arguments. Raises ValidationErr...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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The format of the prompt template. Options are: ‘f-string’, ‘jinja2’. param validate_template: bool = False¶ Whether or not to try validating the template. async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any])...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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Stream all output from a runnable, as reported to the callback system. This includes all inner runs of LLMs, Retrievers, Tools, etc. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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Returns A pydantic model that can be used to validate config. configurable_alternatives(which: ConfigurableField, default_key: str = 'default', **kwargs: Union[Runnable[Input, Output], Callable[[], Runnable[Input, Output]]]) → RunnableSerializable[Input, Output]¶ configurable_fields(**kwargs: Union[ConfigurableField, C...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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Returns A formatted string. Example: prompt.format(variable1="foo") format_prompt(**kwargs: Any) → PromptValue¶ Create Chat Messages. classmethod from_orm(obj: Any) → Model¶ get_input_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶ Get a pydantic model that can be used to validate input to the runnab...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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config – A config to use when invoking the runnable. The config supports standard keys like ‘tags’, ‘metadata’ for tracing purposes, ‘max_concurrency’ for controlling how much work to do in parallel, and other keys. Please refer to the RunnableConfig for more details. Returns The output of the runnable. classmethod is_...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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classmethod parse_obj(obj: Any) → Model¶ classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶ partial(**kwargs: Union[str, Callable[[], str]]) → BasePromptTemplate¶ Return a partial of the prompt template. s...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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classmethod validate(value: Any) → Model¶ with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶ Bind config to a Runnable, returning a new Runnable. with_fallbacks(fallbacks: Sequence[Runnable[Input, Output]], *, exceptions_to_handle: Tuple[Type[BaseException], ...] = (<class 'E...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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Create a new Runnable that retries the original runnable on exceptions. Parameters retry_if_exception_type – A tuple of exception types to retry on wait_exponential_jitter – Whether to add jitter to the wait time between retries stop_after_attempt – The maximum number of attempts to make before giving up Returns A new ...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.few_shot.FewShotPromptTemplate.html
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langchain.prompts.prompt.PromptTemplate¶ class langchain.prompts.prompt.PromptTemplate[source]¶ Bases: StringPromptTemplate A prompt template for a language model. A prompt template consists of a string template. It accepts a set of parameters from the user that can be used to generate a prompt for a language model. Th...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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param output_parser: Optional[BaseOutputParser] = None¶ How to parse the output of calling an LLM on this formatted prompt. param partial_variables: Mapping[str, Union[str, Callable[[], str]]] [Optional]¶ param template: str [Required]¶ The prompt template. param template_format: Union[Literal['f-string'], Literal['jin...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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Subclasses should override this method if they support streaming output. async astream_log(input: Any, config: Optional[RunnableConfig] = None, *, diff: bool = True, include_names: Optional[Sequence[str]] = None, include_types: Optional[Sequence[str]] = None, include_tags: Optional[Sequence[str]] = None, exclude_names:...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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e.g., if the underlying runnable uses an API which supports a batch mode. bind(**kwargs: Any) → Runnable[Input, Output]¶ Bind arguments to a Runnable, returning a new Runnable. config_schema(*, include: Optional[Sequence[str]] = None) → Type[BaseModel]¶ The type of config this runnable accepts specified as a pydantic m...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creating the new model: you should trust this data deep – set to True to make a deep copy of the model Returns new model instance dict(**kw...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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Parameters template_file – The path to the file containing the prompt template. input_variables – A list of variable names the final prompt template will expect. Returns The prompt loaded from the file. classmethod from_orm(obj: Any) → Model¶ classmethod from_template(template: str, *, template_format: str = 'f-string'...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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Get a pydantic model that can be used to validate input to the runnable. Runnables that leverage the configurable_fields and configurable_alternatives methods will have a dynamic input schema that depends on which configuration the runnable is invoked with. This method allows to get an input schema for a specific confi...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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Returns The output of the runnable. classmethod is_lc_serializable() → bool¶ Return whether this class is serializable. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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save(file_path: Union[Path, str]) → None¶ Save the prompt. Parameters file_path – Path to directory to save prompt to. Example: .. code-block:: python prompt.save(file_path=”path/prompt.yaml”) classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶ classmethod schema_jso...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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Add fallbacks to a runnable, returning a new Runnable. Parameters fallbacks – A sequence of runnables to try if the original runnable fails. exceptions_to_handle – A tuple of exception types to handle. Returns A new Runnable that will try the original runnable, and then each fallback in order, upon failures. with_liste...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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Bind input and output types to a Runnable, returning a new Runnable. property InputType: Type[langchain.schema.runnable.utils.Input]¶ The type of input this runnable accepts specified as a type annotation. property OutputType: Any¶ The type of output this runnable produces specified as a type annotation. property confi...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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Criteria Evaluation Set env var OPENAI_API_KEY or load from a .env file Set env var OPENAI_API_KEY or load from a .env file: Question Answering Retrieve from vector stores directly Improve document indexing with HyDE Structure answers with OpenAI functions Neo4j DB QA chain Multi-agent authoritarian speaker selection A...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.prompt.PromptTemplate.html
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langchain.prompts.example_selector.semantic_similarity.sorted_values¶ langchain.prompts.example_selector.semantic_similarity.sorted_values(values: Dict[str, str]) → List[Any][source]¶ Return a list of values in dict sorted by key.
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.sorted_values.html
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langchain.prompts.chat.SystemMessagePromptTemplate¶ class langchain.prompts.chat.SystemMessagePromptTemplate[source]¶ Bases: BaseStringMessagePromptTemplate System message prompt template. This is a message that is not sent to the user. Create a new model by parsing and validating input data from keyword arguments. Rai...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.SystemMessagePromptTemplate.html
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deep – set to True to make a deep copy of the model Returns new model instance dict(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, exclude_unset: bool = False, ex...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.SystemMessagePromptTemplate.html
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Get the namespace of the langchain object. For example, if the class is langchain.llms.openai.OpenAI, then the namespace is [“langchain”, “llms”, “openai”] classmethod is_lc_serializable() → bool¶ Return whether or not the class is serializable. json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = No...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.SystemMessagePromptTemplate.html
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classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶ to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ to_json_not_implemented() → SerializedNotImplemented¶ classmethod update_forward_refs(**localns: Any) → None¶ Try to upda...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.SystemMessagePromptTemplate.html
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langchain.prompts.example_selector.semantic_similarity.MaxMarginalRelevanceExampleSelector¶ class langchain.prompts.example_selector.semantic_similarity.MaxMarginalRelevanceExampleSelector[source]¶ Bases: SemanticSimilarityExampleSelector ExampleSelector that selects examples based on Max Marginal Relevance. This was s...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.MaxMarginalRelevanceExampleSelector.html
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Duplicate a model, optionally choose which fields to include, exclude and change. Parameters include – fields to include in new model exclude – fields to exclude from new model, as with values this takes precedence over include update – values to change/add in the new model. Note: the data is not validated before creat...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.MaxMarginalRelevanceExampleSelector.html
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Returns The ExampleSelector instantiated, backed by a vector store. classmethod from_orm(obj: Any) → Model¶ json(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, by_alias: bool = False, skip_defaults: Optional[bool] = None, ex...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.MaxMarginalRelevanceExampleSelector.html
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Try to update ForwardRefs on fields based on this Model, globalns and localns. classmethod validate(value: Any) → Model¶ Examples using MaxMarginalRelevanceExampleSelector¶ Select by maximal marginal relevance (MMR)
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.example_selector.semantic_similarity.MaxMarginalRelevanceExampleSelector.html
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langchain.prompts.base.check_valid_template¶ langchain.prompts.base.check_valid_template(template: str, template_format: str, input_variables: List[str]) → None[source]¶ Check that template string is valid. Parameters template – The template string. template_format – The template format. Should be one of “f-string” or ...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.base.check_valid_template.html
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langchain.prompts.chat.ChatPromptTemplate¶ class langchain.prompts.chat.ChatPromptTemplate[source]¶ Bases: BaseChatPromptTemplate A prompt template for chat models. Use to create flexible templated prompts for chat models. Examples from langchain.prompts import ChatPromptTemplate template = ChatPromptTemplate.from_mess...
lang/api.python.langchain.com/en/latest/prompts/langchain.prompts.chat.ChatPromptTemplate.html