# tavily-python

> Python wrapper for the Tavily API

- **URL**: https://www.freshcrate.ai/projects/tavily-python
- **Author**: Tavily AI
- **Category**: Developer Tools
- **Latest version**: `master@2026-05-28` (2026-05-28)
- **License**: Unknown
- **Source**: https://github.com/tavily-ai/tavily-python
- **Language**: Python
- **GitHub**: 1,181 stars, 148 forks
- **Registry**: pypi (`tavily-python`)
- **Tags**: `pypi`

## Description

# Tavily Python SDK

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The Tavily Python wrapper allows for easy interaction with the Tavily API, offering the full range of our search, extract, crawl, map, and research functionalities directly from your Python programs. Easily integrate smart search, content extraction, and research capabilities into your applications, harnessing Tavily's powerful features.

## Installing

```bash
pip install tavily-python
```

# Tavily Search

Search lets you search the web for a given query.

## Usage

Below are some code snippets that show you how to interact with our search API. The different steps and components of this code are explained in more detail in the API Methods section further down.

### Getting and printing the full Search API response

```python
from tavily import TavilyClient

# Step 1. Instantiating your TavilyClient
tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")

# Step 2. Executing a simple search query
response = tavily_client.search("Who is Leo Messi?")

# Step 3. That's it! You've done a Tavily Search!
print(response)
```

### Using exact match to find specific names or phrases

```python
from tavily import TavilyClient

client = TavilyClient(api_key="tvly-YOUR_API_KEY")

# Use exact_match=True to only return results containing the exact phrase(s) inside quotes
response = client.search(
    query='"John Smith" CEO Acme Corp',
    exact_match=True
)
print(response)
```

This is equivalent to directly querying our REST API.

### Generating context for a RAG Application

```python
from tavily import TavilyClient

# Step 1. Instantiating your TavilyClient
tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")

# Step 2. Executing a context search query
context = tavily_client.get_search_context(query="What happened during the Burning Man floods?")

# Step 3. That's it! You now have a context string that you can feed directly into your RAG Application
print(context)
```

This is how you can generate precise and fact-based context for your RAG application in one line of code.

### Getting a quick answer to a question

```python
from tavily import TavilyClient

# Step 1. Instantiating your TavilyClient
tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")

# Step 2. Executing a Q&A search query
answer = tavily_client.qna_search(query="Who is Leo Messi?")

# Step 3. That's it! Your question has been answered!
print(answer)
```

This is how you get accurate and concise answers to questions, in one line of code. Perfect for usage by LLMs!

# Tavily Extract

Extract web page content from one or more specified URLs.

## Usage

Below are some code snippets that demonstrate how to interact with our Extract API. Each step and component of this code is explained in greater detail in the API Methods section below.

### Extracting Raw Content from Multiple URLs using Tavily Extract API

```python
from tavily import TavilyClient

# Step 1. Instantiating your TavilyClient
tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")

# Step 2. Defining the list of URLs to extract content from
urls = [
    "https://en.wikipedia.org/wiki/Artificial_intelligence",
    "https://en.wikipedia.org/wiki/Machine_learning",
    "https://en.wikipedia.org/wiki/Data_science",
    "https://en.wikipedia.org/wiki/Quantum_computing",
    "https://en.wikipedia.org/wiki/Climate_change"
] # You can provide up to 20 URLs simultaneously

# Step 3. Executing the extract request
response = tavily_client.extract(urls=urls, include_images=True)

# Step 4. Printing the extracted raw content
for result in response["results"]:
    print(f"URL: {result['url']}")
    print(f"Raw Content: {result['raw_content']}")
    print(f"Images: {result['images']}\n")

# Note that URLs that could not be extracted will be stored in response["failed_results"]
```

# Tavily Crawl

Crawl lets you traverse a website's content starting from a base URL.

> **Note**: Crawl is currently available on an invite-only basis. For more information, please visit [crawl.tavily.com](https://crawl.tavily.com)

## Usage

Below are some code snippets that demonstrate how to interact with our Crawl API. Each step and component of this code is explained in greater detail in the API Methods section below.

### Crawling a website with instructions

```python
from tavily import TavilyClient

# Step 1. Instantiating your TavilyClient
tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")

# Step 2. Defining the starting URL
start_url = "https:/

## Recent releases

| Version | Date | Urgency | Changes |
| --- | --- | --- | --- |
| `master@2026-05-28` | 2026-05-28 | High | Latest activity on master branch |
| `0.7.23` | 2026-04-21 | Low | Imported from PyPI (0.7.23) |

## Citation

- HTML: https://www.freshcrate.ai/projects/tavily-python
- Markdown: https://www.freshcrate.ai/projects/tavily-python.md
- Dependencies JSON: https://www.freshcrate.ai/api/projects/tavily-python/deps

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