Search Engine

SerpApi (Google)

To obtain fact-based content, we can perform search queries via SerpApi with a Google backend. The following example demonstrates how to search for a query and return the results:

from symai.interfaces import Interface

search = Interface('serpapi')
res = search('Birthday of Barack Obama')

Here's a quick example for how to set it up:

{
    …
    "SEARCH_ENGINE_API_KEY": …,
    "SEARCH_ENGINE_ENGINE": "google",
    …
}

PerplexityAI

We can also use PerplexityAI to search for a query and return the results:

from symai.interfaces import Interface
search = Interface("perplexity")
res = search('What is a quantum computer?', system_message='You are Rick from Rick and Morty. You reply back as Rick would reply to Morty.')

Please note that the system_message is optional and can be used to provide context to the model. For all available kwargs that can be passed to the perplexity engine, please refer to the PerplexityAI documentation. Also, please see the available supported engines for PerplexityAI here. Here's a quick example for how to set it up:

{
    …
    "SEARCH_ENGINE_API_KEY": "pplx-…",
    "SEARCH_ENGINE_MODEL": "sonar",
    …
}

OpenAI Search

Additionally, we can use OpenAI's search capabilities to answer queries and get citations for the information:

from symai.interfaces import Interface
search = Interface("openai_search")
res = search('Who is Nicusor Dan?')

The OpenAI search engine returns a SearchResult object that includes citations for the information. You can access these citations using:

citations = res.get_citations()

The engine supports various customization options, such as specifying user location and timezone:

# Search with user location
res = search("What are popular tourist attractions nearby?",
             user_location={
                 "type": "approximate",
                 "country": "US",
                 "city": "New York",
                 "region": "New York"
             })

# Search with timezone
res = search("What local events are happening today?",
             user_location={
                 "type": "approximate",
                 "country": "JP",
                 "city": "Tokyo",
                 "region": "Tokyo",
                 "timezone": "Asia/Tokyo"
             })

# Control the amount of search context
res = search("Explain quantum computing developments", search_context_size="high")

Here's how to configure the OpenAI search engine:

{
    …
    "SEARCH_ENGINE_API_KEY": "sk-…",
    "SEARCH_ENGINE_MODEL": "gpt-4.1-mini",
    …
}