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docs: add notes to websearch tool and two extra example scripts

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Yu An 2025-03-03 10:23:22 +00:00
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60
docs/source/building_applications/tools.md
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@ -41,7 +41,7 @@ client.toolgroups.register(
The tool requires an API key which can be provided either in the configuration or through the request header `X-LlamaStack-Provider-Data`. The format of the header is `{"<provider_name>_api_key": <your api key>}`.
> **NOTE:** When using Tavily Search and Bing Search, the inference output will still display "Brave Search." This is because Llama models have been trained with Brave Search as a built-in tool. Tavily and bing is just being used in lieu of Brave search.
#### Code Interpreter
@ -206,3 +206,61 @@ response = agent.create_turn(
session_id=session_id,
)
```
## Simple Example2: Using an Agent with the websearch Tool
```python
from llama_stack_client.lib.agents.agent import Agent
from llama_stack_client.types.agent_create_params import AgentConfig
from llama_stack_client.lib.agents.event_logger import EventLogger
from llama_stack_client import LlamaStackClient
client = LlamaStackClient(
base_url=f"http://localhost:8321",
provider_data = {"tavily_search_api_key": "your_TAVILY_SEARCH_API_KEY"})
agent_config = AgentConfig(
model="meta-llama/Llama-3.2-3B-Instruct",
instructions=(
"You are a highly knowledgeable and helpful web search assistant. "
"Your primary goal is to provide accurate and reliable information to the user. "
"Whenever you encounter a query, make sure to use the websearch tools to look up the most current and precise information available. "
),
toolgroups=["builtin::websearch"],
)
agent = Agent(client, agent_config)
session_id = agent.create_session("websearch-session")
response = agent.create_turn(
messages=[{"role": "user", "content": "How US performed in the olympics?"}],
session_id=session_id,
)
for log in EventLogger().log(response):
log.print()
```
## Simple Example3: Using an Agent with the WolframAlpha Tool
```python
from llama_stack_client.lib.agents.agent import Agent
from llama_stack_client.types.agent_create_params import AgentConfig
from llama_stack_client.lib.agents.event_logger import EventLogger
from llama_stack_client import LlamaStackClient
client = LlamaStackClient(base_url=f"http://localhost:8321")
agent_config = AgentConfig(
model="meta-llama/Llama-3.2-3B-Instruct",
instructions="You are a helpful wolfram_alpha assistant, use wolfram_alpha tool as external source validation.",
toolgroups=["builtin::wolfram_alpha"],
wolfram_api_key="your_WOLFRAM_ALPHA_API_KEY",
)
agent = Agent(client, agent_config)
session_id = agent.create_session("wolframa-alpha-session")
response = agent.create_turn(
messages=[{"role": "user", "content": "Tell me 10 densest elemental metals"}],
session_id=session_id,
)
for log in EventLogger().log(response):
log.print()
```