langchain/docs/extras/expression_language/how_to/functions.ipynb

Run arbitrary functions

You can use arbitrary functions in the pipeline

Note that all inputs to these functions need to be a SINGLE argument. If you have a function that accepts multiple arguments, you should write a wrapper that accepts a single input and unpacks it into multiple argument.

In [77]:

from langchain.schema.runnable import RunnableLambda

def length_function(text):
    return len(text)

def _multiple_length_function(text1, text2):
    return len(text1) * len(text2)

def multiple_length_function(_dict):
    return _multiple_length_function(_dict["text1"], _dict["text2"])

prompt = ChatPromptTemplate.from_template("what is {a} + {b}")

chain1 = prompt | model

chain = {
    "a": itemgetter("foo") | RunnableLambda(length_function),
    "b": {"text1": itemgetter("foo"), "text2": itemgetter("bar")} | RunnableLambda(multiple_length_function)
} | prompt | model

In [78]:

chain.invoke({"foo": "bar", "bar": "gah"})

Out [78]:

AIMessage(content='3 + 9 equals 12.', additional_kwargs={}, example=False)

Accepting a Runnable Config

Runnable lambdas can optionally accept a RunnableConfig, which they can use to pass callbacks, tags, and other configuration information to nested runs.

In [139]:

from langchain.schema.runnable import RunnableConfig

In [149]:

import json

def parse_or_fix(text: str, config: RunnableConfig):
    fixing_chain = (
        ChatPromptTemplate.from_template(
            "Fix the following text:\n\n```text\n{input}\n```\nError: {error}"
            " Don't narrate, just respond with the fixed data."
        )
        | ChatOpenAI()
        | StrOutputParser()
    )
    for _ in range(3):
        try:
            return json.loads(text)
        except Exception as e:
            text = fixing_chain.invoke({"input": text, "error": e}, config)
    return "Failed to parse"

In [152]:

from langchain.callbacks import get_openai_callback

with get_openai_callback() as cb:
    RunnableLambda(parse_or_fix).invoke("{foo: bar}", {"tags": ["my-tag"], "callbacks": [cb]})
    print(cb)

Tokens Used: 65
	Prompt Tokens: 56
	Completion Tokens: 9
Successful Requests: 1
Total Cost (USD): $0.00010200000000000001