LiteRT-LM / python /litert_lm /examples /tool_main.py
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# Copyright 2026 The ODML Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Example of using tools with LiteRT-LM."""
from collections.abc import Sequence
from absl import app
from absl import flags
import litert_lm
_MODEL_PATH = flags.DEFINE_string(
"model_path", None, "Path to the model file.", required=True
)
def product(numbers: Sequence[float]) -> float:
"""Get the product of a list of numbers.
Args:
numbers: The numbers, could be floating point.
"""
print(f"Calling tool product with arg: {numbers}")
res = 1.0
for n in numbers:
res *= n
return res
def main(argv: Sequence[str]) -> None:
if len(argv) > 1:
raise app.UsageError("Too many command-line arguments.")
litert_lm.set_min_log_severity(litert_lm.LogSeverity.ERROR)
engine = litert_lm.Engine(
_MODEL_PATH.value,
litert_lm.Backend.CPU,
)
tools = [product]
with (
engine as engine,
engine.create_conversation(tools=tools) as conversation,
):
print("LiteRT-LM Tool Example")
user_input = "What is the product of 1.1, 2.2, 3.3 and 4.4?"
# Send message (async streaming)
# We use yellow for model output as in the Kotlin example
for chunk in conversation.send_message_async(user_input):
content_list = chunk.get("content", [])
for item in content_list:
if item.get("type") == "text":
print("\033[33m", end="")
print(item.get("text", ""), end="", flush=True)
print("\033[0m", end="")
print("")
if __name__ == "__main__":
app.run(main)