Closed
Description
In 02-explore-agentic-frameworks, the Use Modular Components section provides a code snippet which insists that Parser is a function within langchain. However, there is no Parser function within the langchain package.
I'd recommend using one of the other real functions available (ex: PydanticOutputParser). However, this would also require modifying the code snippet - it becomes quite lengthy but can be run if someone is using Azure OpenAI.
import os
from langchain.output_parsers import PydanticOutputParser
from langchain.prompts import PromptTemplate
from langchain_openai import AzureChatOpenAI
from pydantic import BaseModel, Field
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Define a Pydantic model for structured data
class FlightBooking(BaseModel):
origin: str = Field(description="Departure city")
destination: str = Field(description="Arrival city")
date: str = Field(description="Flight date")
# Initialize parser
parser = PydanticOutputParser(pydantic_object=FlightBooking)
# Define the prompt template
prompt = PromptTemplate(
template="Extract structured flight details from the following text:\n{text}\n{format_instructions}",
input_variables=["text"],
partial_variables={"format_instructions": parser.get_format_instructions()},
)
# Initialize Azure OpenAI LLM
llm = AzureChatOpenAI(
azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
openai_api_version=os.getenv("AZURE_OPENAI_API_VERSION"),
deployment_name=os.getenv("AZURE_OPENAI_DEPLOYMENT_NAME"),
openai_api_key=os.getenv("AZURE_OPENAI_API_KEY"),
temperature=0
)
# Chain together the prompt, model, and parser
chain = prompt | llm | parser
# Example input
user_input = "Book a flight from New York to London on July 15th"
# Invoke the chain
parsed_data = chain.invoke({"text": user_input})
print(parsed_data)
# Output: origin='New York' destination='London' date='July 15th'