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ValyuContext | 🦜️🔗 LangChain

Valyu allows AI applications and agents to search the internet and proprietary data sources for relevant LLM ready information.

This notebook goes over how to use Valyu context tool in LangChain.

First, get an Valyu API key and add it as an environment variable. Get $10 free credit by signing up here.

The integration lives in the langchain-valyu package.

%pip install -qU langchain-valyu

In order to use the package, you will also need to set the VALYU_API_KEY environment variable to your Valyu API key.

import getpass
import os

if not os.environ.get("VALYU_API_KEY"):
    os.environ["VALYU_API_KEY"] = getpass.getpass("Valyu API key:\n")

Here we show how to instantiate an instance of the Valyu search tool. This tool allows you to complete search queries using Valyu's Context API endpoint.

from langchain_valyu import ValyuSearchTool

tool = ValyuSearchTool()

The Valyu search tool accepts the following arguments during invocation:

• query (required): A natural language search query
• search_type (optional): Type of search, e.g., "all"
• max_num_results (optional): Maximum number of results to return
• similarity_threshold (optional): Similarity threshold for results
• query_rewrite (optional): Whether to rewrite the query
• max_price (optional): Maximum price for the search

For reliability and performance reasons, certain parameters may be required or restricted. See the Valyu API documentation for details.

search_results = tool._run(
    query="What are agentic search-enhanced large reasoning models?",
    search_type="all",
    max_num_results=5,
    similarity_threshold=0.4,
    query_rewrite=False,
    max_price=20.0,
)

print("Search Results:", search_results)

We can use our tools directly with an agent executor by binding the tool to the agent. This gives the agent the ability to dynamically set the available arguments to the Valyu search tool.

if not os.environ.get("OPENAI_API_KEY"):
    os.environ["OPENAI_API_KEY"] = getpass.getpass("OPENAI_API_KEY:\n")

from langchain_valyu import ValyuSearchTool
from langgraph.prebuilt import create_react_agent

valyu_search_tool = ValyuSearchTool()

agent = create_react_agent(llm, [valyu_search_tool])

user_input = "What are the key factors driving recent stock market volatility, and how do macroeconomic indicators influence equity prices across different sectors?"

for step in agent.stream(
    {"messages": user_input},
    stream_mode="values",
):
    step["messages"][-1].pretty_print()

For detailed documentation of all Valyu Context API features and configurations head to the API reference: https://docs.valyu.network/overview

• Tool conceptual guide
• Tool how-to guides

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