chenmingxuan
2ddec53954
Localize the web console and persist custom model and capability settings. Use OpenAI Responses exclusively and move runtime limits into environment configuration. Bootstrap uv and the virtual environment on Windows, support optional China mirrors, and package source distributions without environments, build output, or credentials. Update regression tests and repository quality checks for the new behavior.
107 lines
3.4 KiB
Python
107 lines
3.4 KiB
Python
# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Token-usage normalization across the LangChain, generate_content and Interactions shapes."""
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from types import SimpleNamespace
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from artemis.llm.usage import normalize_usage, usage_from_message
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from langchain_core.messages import AIMessage
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def test_langchain_usage_metadata_shape():
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usage = normalize_usage(
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{
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"input_tokens": 1200,
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"output_tokens": 80,
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"total_tokens": 1280,
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"input_token_details": {"cache_read": 900},
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"output_token_details": {"reasoning": 30},
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}
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)
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assert usage == {
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"prompt_tokens": 1200,
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"completion_tokens": 80,
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"total_tokens": 1280,
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"cached_tokens": 900,
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"thought_tokens": 30,
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"tool_use_tokens": 0,
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}
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def test_generate_content_usage_metadata_object_shape():
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raw = SimpleNamespace(
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prompt_token_count=500,
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candidates_token_count=25,
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total_token_count=560,
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cached_content_token_count=400,
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thoughts_token_count=35,
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tool_use_prompt_token_count=None,
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)
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assert normalize_usage(raw) == {
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"prompt_tokens": 500,
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"completion_tokens": 25,
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"total_tokens": 560,
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"cached_tokens": 400,
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"thought_tokens": 35,
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"tool_use_tokens": 0,
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}
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def test_interactions_usage_shape_counts_tool_use_and_thoughts():
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raw = SimpleNamespace(
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total_input_tokens=191,
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total_output_tokens=655,
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total_tokens=10571,
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total_cached_tokens=0,
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total_thought_tokens=12,
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total_tool_use_tokens=9725,
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)
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assert normalize_usage(raw) == {
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"prompt_tokens": 191,
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"completion_tokens": 655,
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"total_tokens": 10571,
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"cached_tokens": 0,
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"thought_tokens": 12,
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"tool_use_tokens": 9725,
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}
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def test_total_is_derived_when_missing_and_empty_payloads_return_none():
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assert normalize_usage({"prompt_tokens": 3, "completion_tokens": 4})["total_tokens"] == 7
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assert normalize_usage(None) is None
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assert normalize_usage({}) is None
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assert normalize_usage({"prompt_tokens": "not-a-number"}) is None
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assert normalize_usage(SimpleNamespace()) is None
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def test_usage_from_message_prefers_langchain_then_response_metadata():
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msg = AIMessage(content="ok")
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msg.usage_metadata = {"input_tokens": 10, "output_tokens": 2, "total_tokens": 12}
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assert usage_from_message(msg)["prompt_tokens"] == 10
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fallback = AIMessage(content="ok")
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fallback.response_metadata = {"token_usage": {"prompt_tokens": 7, "completion_tokens": 1}}
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assert usage_from_message(fallback) == {
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"prompt_tokens": 7,
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"completion_tokens": 1,
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"total_tokens": 8,
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"cached_tokens": 0,
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"thought_tokens": 0,
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"tool_use_tokens": 0,
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}
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assert usage_from_message(AIMessage(content="none")) is None
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assert usage_from_message(object()) is None
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