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Langchain Python Guide

Setup

Prerequisites

  • Install langchain: pip install langchain
  • Sign up for an OpenAI account and obtain an API key
  • Install OpenAI: pip install -qU langchain-openai
  • Set your OpenAI key in an environment variable (optional)

Additional packages

  • langchain_community
  • langchain_chroma
  • langchain-core

Prompting a model

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from langchain_openai import ChatOpenAI

chat_model = ChatOpenAI()

Once instantiated, the model can be queried:

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response = chat_model.invoke('Translate "Hello World" into German.')
print(response)
# Outputs:
content='Hallo Welt'

Alternatively, the output can be isolated:

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print(response.content)
# Outputs:
Hallo Welt

Langchain also provides templates to allow system prompts and metadata:

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# imports and code as above...
from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a world class translator."),
    ("user", "{input}")
])

llm_chain = prompt | chat_model
response = llm_chain.invoke({
    "input": 'Translate "Hello World" into German.'
})
print(response)
# Outputs:
content='"Hello World" in German is "Hallo Welt".'

pipe creates a chain of commands - a concept that is central to Langchain.

Langchain provides a convenient parser for isolating the model’s output:

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# imports and code as above...
from langchain_core.output_parsers import StrOutputParser

output_parser = StrOutputParser()
llm_chain = prompt | chat_model | output_parser
response = llm_chain.invoke({
    "input": 'Translate "Hello World" into German.'
})
print(response)
# Outputs:
"Hello World" in German is "Hallo Welt."