ToolFunction
Types for defining tools, functions, and their execution configurations.
Overview
Tool types define how LLMs can call external functions, including schemas, parameters, HTTP configurations, and retry logic.
Tool function definition with schema and optional HTTP request configuration.
from adaline_api.models.tool_function import ToolFunction
Fields
definition
ToolFunctionDefinition
required
request
FunctionRequestHttp | None
Optional HTTP request configuration for executing the function via REST API. See FunctionRequestHttp. Example
from adaline_api.models.tool_function import ToolFunction
from adaline_api.models.tool_function_definition import ToolFunctionDefinition
from adaline_api.models.function_schema import FunctionSchema
tool = ToolFunction(
type="function",
definition=ToolFunctionDefinition(
var_schema=FunctionSchema(
name="get_weather",
description="Get current weather",
parameters={
"type": "object",
"properties": {
"city": {"type": "string"}
},
"required": ["city"]
}
)
)
)
See the dedicated ToolFunctionDefinition page for full documentation.
Wrapper for a function schema within a tool definition.
from adaline_api.models.tool_function_definition import ToolFunctionDefinition
Fields
The function schema. Aliased as schema in JSON — use var_schema in Python to avoid collision with the Python reserved word.
Example
from adaline_api.models.tool_function_definition import ToolFunctionDefinition
from adaline_api.models.function_schema import FunctionSchema
definition = ToolFunctionDefinition(
var_schema=FunctionSchema(
name="search_database",
description="Search internal database",
parameters={
"type": "object",
"properties": {
"query": {"type": "string", "description": "Search query"},
"limit": {"type": "number", "default": 10}
},
"required": ["query"]
}
)
)
FunctionSchema
See the dedicated FunctionSchema page for full documentation.
Function/tool schema definition for LLM function calling.
from adaline_api.models.function_schema import FunctionSchema
Fields
Function name. Must match ^[a-zA-Z0-9_]{1,64}$ (alphanumeric and underscores, max 64 chars).
Description of what the function does. Max 4096 characters.
JSON Schema object describing the function parameters.
Whether to enforce strict schema validation. When True, the LLM must conform exactly to the parameter schema.
Example
from adaline_api.models.function_schema import FunctionSchema
weather_function = FunctionSchema(
name="get_weather",
description="Get current weather for a city",
parameters={
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "City name"
},
"units": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"default": "celsius",
"description": "Temperature units"
}
},
"required": ["city"]
},
strict=True
)
{
"name": "get_weather",
"description": "Get weather for a city",
"parameters": {
"type": "object",
"properties": {
"city": { "type": "string" }
},
"required": ["city"]
}
}
FunctionRequestHttp
HTTP request configuration for executing functions via REST API.
from adaline_api.models.function_request_http import FunctionRequestHttp
Fields
HTTP method. One of: "get", "post".
The request URL. Supports {{variable}} template syntax.
Optional query parameters.
retry
FunctionRequestRetry | None
Example
from adaline_api.models.function_request_http import FunctionRequestHttp
from adaline_api.models.function_request_retry import FunctionRequestRetry
http_request = FunctionRequestHttp(
type="http",
method="post",
url="https://api.weather.com/v1/current",
headers={
"Authorization": "Bearer {{API_KEY}}",
"Content-Type": "application/json"
},
query={"units": "metric"},
body={"location": "{{city}}"},
retry=FunctionRequestRetry(
max_attempts=3,
initial_delay=1000,
exponential_factor=2
)
)
FunctionRequestRetry
Retry configuration with exponential backoff.
from adaline_api.models.function_request_retry import FunctionRequestRetry
Fields
Maximum number of retry attempts. Minimum: 1.
Initial delay in milliseconds. Minimum: 1.
Multiplier for each subsequent retry. Minimum: 1.
Example
from adaline_api.models.function_request_retry import FunctionRequestRetry
retry = FunctionRequestRetry(
max_attempts=3,
initial_delay=1000, # Start with 1 second
exponential_factor=2 # Double each retry: 1s, 2s, 4s
)
Complete Example
from adaline.main import Adaline
from adaline_api.models.tool_function import ToolFunction
from adaline_api.models.tool_function_definition import ToolFunctionDefinition
from adaline_api.models.function_schema import FunctionSchema
from adaline_api.models.function_request_http import FunctionRequestHttp
from adaline_api.models.function_request_retry import FunctionRequestRetry
# Define retry configuration
retry = FunctionRequestRetry(
max_attempts=3,
initial_delay=1000,
exponential_factor=2
)
# Define HTTP request
request = FunctionRequestHttp(
type="http",
method="post",
url="https://api.weather.com/current",
headers={
"Authorization": "Bearer sk_abc123",
"Content-Type": "application/json"
},
body={"city": "{{city}}", "units": "{{units}}"},
retry=retry
)
# Define function schema
schema = FunctionSchema(
name="get_weather",
description="Get current weather for a city",
parameters={
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "City name"
},
"units": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"default": "celsius"
}
},
"required": ["city"]
}
)
# Complete tool definition
tool = ToolFunction(
type="function",
definition=ToolFunctionDefinition(var_schema=schema),
request=request
)
adaline = Adaline()
deployment = await adaline.get_latest_deployment(
prompt_id="prompt_with_tools",
deployment_environment_id="environment_abc123"
)
print(f"Tools available: {len(deployment.prompt.tools)}")
for t in deployment.prompt.tools:
fn = t.definition.var_schema
print(f" - {fn.name}: {fn.description}")
