Defines an LLMChain for performing data extraction from a body of text.

Provide the schema for desired information to be parsed into. It is treated as though there are 0 to many instances of the data structure being described so information is returned as an array.

Originally based on:

• https://github.com/langchain-ai/langchainjs/blob/main/langchain/src/chains/openai_functions/extraction.ts#L43

Example

# JSONSchema definition of data we want to capture or extract.
schema_parameters = %{
  type: "object",
  properties: %{
    person_name: %{type: "string"},
    person_age: %{type: "number"},
    person_hair_color: %{type: "string"},
    dog_name: %{type: "string"},
    dog_breed: %{type: "string"}
  },
  required: []
}

# Model setup
{:ok, chat} = ChatOpenAI.new(%{temperature: 0})

# run the chain on the text information
data_prompt =
  "Alex is 5 feet tall. Claudia is 4 feet taller than Alex and jumps higher than him.
  Claudia is a brunette and Alex is blonde. Alex's dog Frosty is a labrador and likes to play hide and seek."

{:ok, result} = LangChain.Chains.DataExtractionChain.run(chat, schema_parameters, data_prompt)

# Example result
[
  %{
    "dog_breed" => "labrador",
    "dog_name" => "Frosty",
    "person_age" => nil,
    "person_hair_color" => "blonde",
    "person_name" => "Alex"
  },
  %{
    "dog_breed" => nil,
    "dog_name" => nil,
    "person_age" => nil,
    "person_hair_color" => "brunette",
    "person_name" => "Claudia"
  }
]

The schema_parameters in the previous example can also be expressed using a list of LangChain.FunctionParam structs. An equivalent version looks like this:

alias LangChain.FunctionParam

schema_parameters = [
  FunctionParam.new!(%{name: "person_name", type: :string}),
  FunctionParam.new!(%{name: "person_age", type: :number}),
  FunctionParam.new!(%{name: "person_hair_color", type: :string}),
  FunctionParam.new!(%{name: "dog_name", type: :string}),
  FunctionParam.new!(%{name: "dog_breed", type: :string})
]
|> FunctionParam.to_parameters_schema()