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Bind runtime args

Sometimes we want to invoke a Runnable within a Runnable sequence with constant arguments that are not part of the output of the preceding Runnable in the sequence, and which are not part of the user input. We can use Runnable.bind() to easily pass these arguments in.

Suppose we have a simple prompt + model sequence:

%pip install --upgrade --quiet  langchain langchain-openai
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough
from langchain_openai import ChatOpenAI
prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"Write out the following equation using algebraic symbols then solve it. Use the format\n\nEQUATION:...\nSOLUTION:...\n\n",
),
("human", "{equation_statement}"),
]
)
model = ChatOpenAI(temperature=0)
runnable = (
{"equation_statement": RunnablePassthrough()} | prompt | model | StrOutputParser()
)

print(runnable.invoke("x raised to the third plus seven equals 12"))
EQUATION: x^3 + 7 = 12

SOLUTION:
Subtracting 7 from both sides of the equation, we get:
x^3 = 12 - 7
x^3 = 5

Taking the cube root of both sides, we get:
x = ∛5

Therefore, the solution to the equation x^3 + 7 = 12 is x = ∛5.

and want to call the model with certain stop words:

runnable = (
{"equation_statement": RunnablePassthrough()}
| prompt
| model.bind(stop="SOLUTION")
| StrOutputParser()
)
print(runnable.invoke("x raised to the third plus seven equals 12"))
EQUATION: x^3 + 7 = 12

Attaching OpenAI functions

One particularly useful application of binding is to attach OpenAI functions to a compatible OpenAI model:

function = {
"name": "solver",
"description": "Formulates and solves an equation",
"parameters": {
"type": "object",
"properties": {
"equation": {
"type": "string",
"description": "The algebraic expression of the equation",
},
"solution": {
"type": "string",
"description": "The solution to the equation",
},
},
"required": ["equation", "solution"],
},
}
# Need gpt-4 to solve this one correctly
prompt = ChatPromptTemplate.from_messages(
[
(
"system",
"Write out the following equation using algebraic symbols then solve it.",
),
("human", "{equation_statement}"),
]
)
model = ChatOpenAI(model="gpt-4", temperature=0).bind(
function_call={"name": "solver"}, functions=[function]
)
runnable = {"equation_statement": RunnablePassthrough()} | prompt | model
runnable.invoke("x raised to the third plus seven equals 12")
AIMessage(content='', additional_kwargs={'function_call': {'name': 'solver', 'arguments': '{\n"equation": "x^3 + 7 = 12",\n"solution": "x = ∛5"\n}'}}, example=False)

Attaching OpenAI tools

tools = [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
},
"required": ["location"],
},
},
}
]
model = ChatOpenAI(model="gpt-3.5-turbo-1106").bind(tools=tools)
model.invoke("What's the weather in SF, NYC and LA?")
AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_zHN0ZHwrxM7nZDdqTp6dkPko', 'function': {'arguments': '{"location": "San Francisco, CA", "unit": "celsius"}', 'name': 'get_current_weather'}, 'type': 'function'}, {'id': 'call_aqdMm9HBSlFW9c9rqxTa7eQv', 'function': {'arguments': '{"location": "New York, NY", "unit": "celsius"}', 'name': 'get_current_weather'}, 'type': 'function'}, {'id': 'call_cx8E567zcLzYV2WSWVgO63f1', 'function': {'arguments': '{"location": "Los Angeles, CA", "unit": "celsius"}', 'name': 'get_current_weather'}, 'type': 'function'}]})