Functions

prompt

Decorator for creating a prompt.

Parameters

• func (Optional[Callable[~P, ~T]]) - The function to decorate. Default: None


• name (Optional[str]) - The name of the prompt. Default: None


• sources (Optional[List[FeatureView]]) - The sources of the prompt. Default: None


• rtfv_kwargs (Any) -

Returns

Callable[~P, ~T]

Example

# The simplest form without a feature dependency
from tecton_gen_ai.fco import prompt

@prompt()
def simple_prompt() -> str:
    return "Hello, world!"

# With parameters but not a feature
from tecton_gen_ai.utils.tecton import make_request_source

params = make_request_source(zip=str)

@prompt(sources=[params])
def prompt_with_params(params) -> str:
    return "Hello, you zip code " + params["zip"]

# With a feature dependency
from tecton_gen_ai.testing import make_local_batch_feature_view

my_bfv = make_local_batch_feature_view(
    "my_bfv",
    {"user_id":"u1", "name":"Bob"},
    ["user_id"],
    description="User information",
)

@prompt(sources=[params, my_bfv])
def sys_prompt(params, my_bfv) -> str:
    return "Hello, " + my_bfv["name"] + " with zip code " + params["zip"]

# Serve the prompt
from tecton_gen_ai.fco import AgentService

service = AgentService(
    "my_service",
    prompts=[sys_prompt],
)

# Test locally
from tecton_gen_ai.fco import AgentClient

client = AgentClient.from_local(service)

with client.set_context({"zip": "10065", "user_id": "u1"}):
    res = client.invoke_prompt("sys_prompt")

tool

Decorator for creating a tool. The tool can be used by different LLMs and frameworks such as Langchain and LlamaIndex.

Parameters

• func (Optional[Callable[~P, ~T]]) - The function to decorate. Default: None


• name (Optional[str]) - The name of the tool. Default: None


• sources (Optional[List[FeatureView]]) - The sources of the tool. Default: None


• descripton (Optional[str]) - The description of the tool. Default: None


• subtype (str) - The subtype of the tool. Default: tool


• rtfv_kwargs (Any) -

Returns

Callable[~P, ~T]

Example

# The simplest form without a feature dependency
from tecton_gen_ai.fco import tool

@tool()
def get_months_in_a_year() -> int:
    '''The total number months of a year'''
    return 12

# With parameters but not a feature
@tool()
def add(a: int, b: int) -> int:
    '''Add two numbers

    Args:
        a (int): The first number
        b (int): The second number

    Returns:
        int: The sum of the two numbers
    '''
    return a + b

# With a feature dependency
from tecton_gen_ai.testing import make_local_batch_feature_view

my_bfv = make_local_batch_feature_view(
    "my_bfv",
    {"user_id":"u1", "name":"Bob"},
    ["user_id"],
    description="User information",
)

@tool(sources=[my_bfv])
def get_name(prefix:str, user_id:str, my_bfv) -> str:
    '''Get the name of a user with a prefix

    Args:

        prefix (str): The prefix of the name
        user_id (str): The user ID

    Returns:

        str: The name of the user with the prefix
    '''
    return prefix + " " + my_bfv["name"]

# Serve the tool
from tecton_gen_ai.fco import AgentService

service = AgentService(
    "my_service",
    tools=[get_name],
)

# Test locally
from tecton_gen_ai.fco import AgentClient

client = AgentClient.from_local(service)
with client.set_context({"user_id": "u1", "prefix": "Hello"}):
    res = client.invoke_tool("get_name")