What is LangChain?
The most popular framework for building LLM-powered applications. Provides chains, agents, and tools for composing AI workflows.
How It Works
Scavio connects to LangChain via a custom tool definition. Once connected, your LangChain agent can search Google, Amazon, YouTube, and Walmart in real time. Each search returns structured JSON — no HTML parsing, no scraping infrastructure.
Setup
pip install langchain langchain-scavio langchain-openaiCode Example
Here is a complete LangChain integration with Scavio:
from langchain_scavio import ScavioSearch
from langchain_openai import ChatOpenAI
from langchain.agents import create_tool_calling_agent, AgentExecutor
from langchain_core.prompts import ChatPromptTemplate
# Initialize the Scavio search tool
tool = ScavioSearch(api_key="your_scavio_api_key")
# Create an agent with the tool
llm = ChatOpenAI(model="gpt-4o")
prompt = ChatPromptTemplate.from_messages([
("system", "You are a helpful research assistant."),
("human", "{input}"),
("placeholder", "{agent_scratchpad}"),
])
agent = create_tool_calling_agent(llm, [tool], prompt)
executor = AgentExecutor(agent=agent, tools=[tool])
result = agent.invoke({"input": "Find the best noise cancelling headphones"})
print(result["output"])Full Working Example
A production-ready example with error handling:
"""
Multi-platform search agent with LangChain + Scavio.
Uses Scavio as a LangChain tool for real-time web data.
"""
from langchain_scavio import ScavioSearch
from langchain_openai import ChatOpenAI
from langchain.agents import create_tool_calling_agent, AgentExecutor
from langchain_core.prompts import ChatPromptTemplate
tool = ScavioSearch(api_key="your_scavio_api_key")
llm = ChatOpenAI(model="gpt-4o")
prompt = ChatPromptTemplate.from_messages([
("system", "You are a helpful assistant with access to real-time search."),
("human", "{input}"),
("placeholder", "{agent_scratchpad}"),
])
agent = create_tool_calling_agent(llm, [tool], prompt)
executor = AgentExecutor(agent=agent, tools=[tool], verbose=True)
result = agent.invoke({"input": "Find the best noise cancelling headphones"})
print(result["output"])Available Platforms
Once connected, your LangChain agent has access to all four Scavio platforms:
- Google — Web search with knowledge graph, PAA, and AI overviews
- Amazon — Product search with prices, ratings, and reviews
- Reddit — Community, posts & threaded comments from any subreddit
- YouTube — Video search with transcripts and metadata
- Walmart — Product search with pricing and fulfillment data
Pricing
Scavio offers a free tier with 500 credits/month (1 credit per search). No credit card required. This is enough to build and test your LangChain integration. Paid plans start at $30/month for higher volumes.