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Getting Started with TatryRetriever

Getting Started with TatryRetriever

This guide will help you get up and running quickly with our platform.

Overview

ContentRetriever is a document retrieval system that makes it easy to integrate both free and copyrighted content into your LLM applications. You don't need to worry about embeddings, vectors, or complex setup - just send your queries and get relevant documents back.

Quick Start Steps

  1. Install the SDK
  2. Set up authentication
  3. Configure your setup

5-Minute Example

Here's a complete example to get you started:

curl -X POST https://api.tatry.dev/v1/retrieve \
  -H "Authorization: Bearer your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "What are the key features of Python?",
    "max_results": 3
  }'
from tatry import TatryRetriever
from langchain.chains import RetrievalQA
from langchain.llms import OpenAI
 
# Initialize TatryRetriever
retriever = TatryRetriever(
    api_key="your-api-key"
)
 
# Create a QA chain
qa_chain = RetrievalQA.from_chain_type(
    llm=OpenAI(),
    retriever=retriever
)
 
# Ask questions
response = qa_chain.run("What are the key features of Python?")
print(response)

What's Next?

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