Perplexity with LangChain

pip install langchain-openai langgraph

export PERPLEXITY_API_KEY="your_api_key_here"

import os

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    base_url="https://api.perplexity.ai/v1",
    api_key=os.environ["PERPLEXITY_API_KEY"],
    model="openai/gpt-5.6-sol",
    use_responses_api=True,
    model_kwargs={"tools": [{"type": "web_search"}]},
    extra_body={"preset": "medium"},
)

response = llm.invoke("What did Perplexity announce most recently?")
print(response.text())

import os

from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

llm = ChatOpenAI(
    base_url="https://api.perplexity.ai/v1",
    api_key=os.environ["PERPLEXITY_API_KEY"],
    model="openai/gpt-5.6-sol",
    use_responses_api=True,
    model_kwargs={"tools": [{"type": "web_search"}]},
    extra_body={"preset": "medium"},
)

agent = create_react_agent(llm, tools=[])
result = agent.invoke(
    {"messages": [{"role": "user", "content": "Summarize today's top AI news."}]}
)
print(result["messages"][-1].text())

import os

from perplexity import Perplexity

client = Perplexity()

response = client.responses.create(
    model="perplexity/sonar",
    input="What did Perplexity announce most recently?",
    tools=[{"type": "web_search"}],
)

for item in response.output:
    if item.type == "search_results":
        for source in item.results:
            print(source.title, "-", source.url)