Prompt template that contains few shot examples.
Examples to format into the prompt.
Either this or example_selector should be provided.
ExampleSelector to choose the examples to format into the prompt.
Either this or examples should be provided.
PromptTemplate used to format an individual example.
A PromptTemplate to put after the examples.
String separator used to join the prefix, the examples, and suffix.
A PromptTemplate to put before the examples.
The format of the prompt template.
Options are: 'f-string', 'jinja2', 'mustache'.
Whether or not to try validating the template.
Get the namespace of the LangChain object.
Check that one and only one of examples/example_selector are provided.
Check that prefix, suffix, and input variables are consistent.
Format the prompt with the inputs.
Async format the prompt with the inputs.
Save the prompt to a file.
Template input variables.
A list of the names of the variables for placeholder or MessagePlaceholder that
A dictionary of the types of the variables the prompt template expects.
How to parse the output of calling an LLM on this formatted prompt.
A dictionary of the partial variables the prompt template carries.
Optional metadata associated with the retriever.
Optional list of tags associated with the retriever.
Validate variable names do not include restricted names.
Return True as this class is serializable.
Invoke the retriever to get relevant documents.
Asynchronously invoke the retriever to get relevant documents.
Format prompt.
Async format prompt.
Get a new ChatPromptTemplate with some input variables already filled in.
Return dictionary representation of output parser.
Get a JSON schema that represents the input to the Runnable.
Get a JSON schema that represents the output of the Runnable.
The type of config this Runnable accepts specified as a Pydantic model.
Get a JSON schema that represents the config of the Runnable.
Return a list of prompts used by this Runnable.
Pipe Runnable objects.
Pick keys from the output dict of this Runnable.
Merge the Dict input with the output produced by the mapping argument.
Invoke the retriever to get relevant documents.
Asynchronously invoke the retriever to get relevant documents.
Run invoke in parallel on a list of inputs.
Run ainvoke in parallel on a list of inputs.
Stream all output from a Runnable, as reported to the callback system.
Generate a stream of events.
Bind arguments to a Runnable, returning a new Runnable.
Bind lifecycle listeners to a Runnable, returning a new Runnable.
Bind async lifecycle listeners to a Runnable.
Bind input and output types to a Runnable, returning a new Runnable.
Create a new Runnable that retries the original Runnable on exceptions.
Map a function to multiple iterables.
Add fallbacks to a Runnable, returning a new Runnable.
Create a BaseTool from a Runnable.
