Overview
Community tools provide integrations with external services for enhanced agent capabilities. These tools require API keys and configuration through DeerFlow’s tool configuration system.
Community tools may require additional setup and API keys. Check the configuration requirements for each tool before use.
web_search (Tavily)
Search the web using the Tavily search API.
Configuration
tools:
web_search:
provider: tavily
api_key: your-tavily-api-key
max_results: 5
Parameters
Example
# Search for recent information
result = web_search(
query="latest developments in AI language models 2024"
)
Return Type
Returns a JSON string with normalized search results:
[
{
"title": "Article Title",
"url": "https://example.com/article",
"snippet": "Article description or excerpt..."
}
]
web_fetch
Fetch the contents of a web page at a given URL. Multiple providers are available.
Providers
Tavily
Uses Tavily’s content extraction API.
Configuration:
tools:
web_search:
provider: tavily
api_key: your-tavily-api-key
web_fetch(url="https://example.com/article")
# Article Title
[Article content, truncated to 4096 characters]
Firecrawl
Uses Firecrawl for advanced web scraping with JavaScript rendering.
Configuration:
tools:
web_search:
provider: firecrawl
api_key: your-firecrawl-api-key
web_fetch(url="https://example.com/dynamic-page")
Jina AI
Uses Jina AI’s reader API with readability extraction.
Configuration:
tools:
web_fetch:
timeout: 10
web_fetch(url="https://example.com/article")
Parameters
The URL to fetch the contents of.
Important Notes
- Only fetch EXACT URLs provided by the user or returned from search results
- Cannot access content requiring authentication (private Google Docs, login walls)
- Do NOT add
www. to URLs that don’t have them
- URLs must include the schema:
https://example.com is valid, example.com is invalid
Examples
# Good: Exact URL from search results
web_fetch(url="https://blog.example.com/article")
# Good: User-provided URL
web_fetch(url="https://docs.python.org/3/library/os.html")
# Bad: Missing schema
web_fetch(url="example.com") # ERROR: Invalid URL
# Bad: Adding www unnecessarily
web_fetch(url="https://www.example.com") # If original was https://example.com
Error Handling
All providers return error messages as strings:
Error: [error description]
web_search (Firecrawl)
Search the web using Firecrawl’s search API.
Configuration
tools:
web_search:
provider: firecrawl
api_key: your-firecrawl-api-key
max_results: 5
Parameters
Example
result = web_search(
query="machine learning best practices"
)
Return Type
Returns a JSON string with normalized search results:
[
{
"title": "Article Title",
"url": "https://example.com/article",
"snippet": "Article description..."
}
]
image_search
Search for images online using DuckDuckGo. Use this tool BEFORE image generation to find reference images.
Configuration
tools:
image_search:
max_results: 5
Parameters
Search keywords describing the images you want to find. Be specific for better results.
Maximum number of images to return. Default is 5.
Image size filter. Options: "Small", "Medium", "Large", "Wallpaper". Use "Large" for reference images.
Image type filter. Options: "photo", "clipart", "gif", "transparent", "line". Use "photo" for realistic references.
Layout filter. Options: "Square", "Tall", "Wide". Choose based on your generation needs.
When to Use
- Before generating character/portrait images: Search for similar poses, expressions, styles
- Before generating specific objects/products: Search for accurate visual references
- Before generating scenes/locations: Search for architectural or environmental references
- Before generating fashion/clothing: Search for style and detail references
Examples
# Good: Specific query for portrait reference
image_search(
query="Japanese woman street photography 1990s",
type_image="photo",
size="Large"
)
# Good: Product reference
image_search(
query="modern minimalist desk lamp metal",
type_image="photo",
layout="Square"
)
# Bad: Too vague
image_search(query="woman") # Not specific enough
Return Type
Returns a JSON string with search results:
{
"query": "Japanese woman street photography 1990s",
"total_results": 5,
"results": [
{
"title": "Image title",
"image_url": "https://example.com/image.jpg",
"thumbnail_url": "https://example.com/thumb.jpg"
}
],
"usage_hint": "Use the 'image_url' values as reference images in image generation. Download them first if needed."
}
Using Results
The returned image URLs can be used as reference images in image generation tools:
# 1. Search for reference images
results = image_search(
query="vintage camera Leica M3",
type_image="photo",
size="Large"
)
# 2. Parse results (in practice, this would be done by the agent)
import json
data = json.loads(results)
reference_url = data["results"][0]["image_url"]
# 3. Use in image generation (pseudocode)
generate_image(
prompt="A vintage Leica M3 camera on a wooden desk",
reference_images=[reference_url]
)
Configuration Examples
Using Tavily for Search
tools:
web_search:
provider: tavily
api_key: tvly-xxxxxxxxxxxxx
max_results: 10
Using Firecrawl for Search
tools:
web_search:
provider: firecrawl
api_key: fc-xxxxxxxxxxxxx
max_results: 5
Using Jina AI for Fetching
tools:
web_fetch:
timeout: 15
Image Search
tools:
image_search:
max_results: 10
Best Practices
Web Search
- Use specific, targeted queries
- Search before fetching to find relevant URLs
- Respect
max_results configuration
# Good: Specific query
web_search(query="Python asyncio best practices 2024")
# Bad: Too broad
web_search(query="programming")
Web Fetch
- Only fetch URLs from search results or user input
- Never modify URLs (especially don’t add/remove
www.)
- Always include URL schema (
https://)
- Handle authentication limitations gracefully
# Good: Exact URL
web_fetch(url="https://docs.python.org/3/library/asyncio.html")
# Bad: Modified URL
web_fetch(url="https://www.docs.python.org/3/library/asyncio.html")
Image Search
- Be specific in search queries
- Use appropriate filters for your use case
- Always search before generating images
- Use
"photo" type for realistic references
- Use
"Large" size for best quality references
# Good: Specific query with filters
image_search(
query="Victorian era portrait photography woman formal dress",
type_image="photo",
size="Large",
layout="Tall"
)
# Bad: Vague query
image_search(query="photo")
Error Handling
All community tools handle errors gracefully:
Search Errors
result = web_search(query="test")
# If error occurs:
# "Error: [error description]"
Fetch Errors
result = web_fetch(url="https://invalid-url.com")
# Returns:
# "Error: [error description]"
Image Search Errors
result = image_search(query="test")
# If no results:
# {"error": "No images found", "query": "test"}
Dependencies
Tavily
pip install tavily-python
Firecrawl
Jina AI
Requires custom client implementation (included in DeerFlow).
Image Search