kaxil commented on code in PR #69003: URL: https://github.com/apache/airflow/pull/69003#discussion_r3481874113
########## providers/anthropic/tests/system/anthropic/example_anthropic_agent.py: ########## @@ -0,0 +1,65 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. +from __future__ import annotations + +from airflow.sdk import dag, task + +ANTHROPIC_CONN_ID = "anthropic_default" + + +@dag(schedule=None, catchup=False) +def anthropic_managed_agent(): + @task + def setup_agent_and_environment() -> dict[str, str]: + # One-time setup helper — in production run this once and store the IDs, do not + # create a fresh agent every DAG run. Here we create them and pass the IDs via XCom. + from airflow.providers.anthropic.hooks.anthropic import AnthropicHook + + hook = AnthropicHook(conn_id=ANTHROPIC_CONN_ID) + agent = hook.create_agent( + name="airflow-research-agent", + system="You are a concise research assistant.", + tools=[{"type": "agent_toolset_20260401"}], + ) + environment = hook.create_environment(name="airflow-agent-env") + return {"agent_id": agent.id, "environment_id": environment.id} + + setup = setup_agent_and_environment() + + # [START howto_operator_anthropic_agent_session] + from airflow.providers.anthropic.operators.agent import AnthropicAgentSessionOperator + + run_agent = AnthropicAgentSessionOperator( + task_id="run_agent", + conn_id=ANTHROPIC_CONN_ID, + agent_id=setup["agent_id"], + environment_id=setup["environment_id"], + message="Summarize the latest stable Apache Airflow release in two sentences.", + deferrable=True, + ) + # [END howto_operator_anthropic_agent_session] + + run_agent + + +anthropic_managed_agent() + + +from tests_common.test_utils.system_tests import get_test_run # noqa: E402 + +# Needed to run the example DAG with pytest (see: contributing-docs/testing/system_tests.rst) Review Comment: Applied in [`260a157`](https://github.com/apache/airflow/pull/69003/commits/260a157f944e129f2857c147362e202856041f04). ########## providers/anthropic/tests/system/anthropic/example_anthropic_batch.py: ########## @@ -0,0 +1,81 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. +from __future__ import annotations + +from typing import Any + +from airflow.sdk import dag, task + +ANTHROPIC_CONN_ID = "anthropic_default" +MODEL = "claude-opus-4-8" + +POKEMON = ["pikachu", "charmander", "bulbasaur"] + + +@dag(schedule=None, catchup=False) +def anthropic_batch_messages(): + @task + def build_requests(names: list[str]) -> list[dict[str, Any]]: + return [ + { + "custom_id": name, + "params": { + "model": MODEL, + "max_tokens": 256, + "messages": [{"role": "user", "content": f"Describe {name} in one sentence."}], + }, + } + for name in names + ] + + @task + def collect_results(batch_id: str) -> dict[str, str]: + # Results stream from the API unordered; key them by custom_id. For large + # batches, persist to object storage instead of returning via XCom. + from airflow.providers.anthropic.hooks.anthropic import AnthropicHook + + hook = AnthropicHook(conn_id=ANTHROPIC_CONN_ID) + summaries: dict[str, str] = {} + for entry in hook.stream_batch_results(batch_id): + if entry.result.type == "succeeded": + text = next((b.text for b in entry.result.message.content if b.type == "text"), "") + summaries[entry.custom_id] = text + return summaries + + requests = build_requests(POKEMON) + + # [START howto_operator_anthropic_batch] + from airflow.providers.anthropic.operators.anthropic import AnthropicBatchOperator + + run_batch = AnthropicBatchOperator( + task_id="run_batch", + conn_id=ANTHROPIC_CONN_ID, + requests=requests, + deferrable=True, + ) + # [END howto_operator_anthropic_batch] + + collect_results(batch_id=run_batch.output) + + +anthropic_batch_messages() + + +from tests_common.test_utils.system_tests import get_test_run # noqa: E402 + +# Needed to run the example DAG with pytest (see: contributing-docs/testing/system_tests.rst) Review Comment: Applied in [`260a157`](https://github.com/apache/airflow/pull/69003/commits/260a157f944e129f2857c147362e202856041f04). -- This is an automated message from the Apache Git Service. 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