v2.2.0 (#395)
Co-authored-by: Quentin Torroba <quentin.torroba@mistral.ai> Co-authored-by: Clément Siriex <clement.sirieix@mistral.ai> Co-authored-by: Kim-Adeline Miguel <kimadeline.miguel@mistral.ai> Co-authored-by: Michel Thomazo <michel.thomazo@mistral.ai> Co-authored-by: Clément Drouin <clement.drouin@mistral.ai>
This commit is contained in:
Mathias Gesbert
GitHub
parent
51fecc67d9
commit
ec7f3b25ea
107 changed files with 8002 additions and 535 deletions
591
tests/backend/test_vertex_anthropic_adapter.py
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591
tests/backend/test_vertex_anthropic_adapter.py
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from __future__ import annotations
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import json
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from unittest.mock import patch
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import pytest
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from vibe.core.config import ProviderConfig
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from vibe.core.llm.backend.vertex import (
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VertexAnthropicAdapter,
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build_vertex_base_url,
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build_vertex_endpoint,
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)
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from vibe.core.types import AvailableFunction, AvailableTool, LLMMessage, Role
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@pytest.fixture
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def adapter():
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return VertexAnthropicAdapter()
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@pytest.fixture
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def provider():
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return ProviderConfig(
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name="vertex",
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api_base="",
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project_id="test-project",
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region="us-central1",
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api_style="vertex-anthropic",
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)
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class TestBuildVertexEndpoint:
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def test_non_streaming(self):
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endpoint = build_vertex_endpoint(
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"us-central1", "my-project", "claude-3-5-sonnet"
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)
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assert endpoint == (
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"/v1/projects/my-project/locations/us-central1/"
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"publishers/anthropic/models/claude-3-5-sonnet:rawPredict"
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)
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def test_streaming(self):
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endpoint = build_vertex_endpoint(
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"us-central1", "my-project", "claude-3-5-sonnet", streaming=True
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)
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assert endpoint == (
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"/v1/projects/my-project/locations/us-central1/"
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"publishers/anthropic/models/claude-3-5-sonnet:streamRawPredict"
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)
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def test_base_url(self):
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base = build_vertex_base_url("us-central1")
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assert base == "https://us-central1-aiplatform.googleapis.com"
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def test_global_endpoint(self):
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endpoint = build_vertex_endpoint("global", "my-project", "claude-3-5-sonnet")
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assert endpoint == (
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"/v1/projects/my-project/locations/global/"
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"publishers/anthropic/models/claude-3-5-sonnet:rawPredict"
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)
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def test_global_base_url(self):
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base = build_vertex_base_url("global")
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assert base == "https://aiplatform.googleapis.com"
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class TestPrepareRequest:
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@patch(
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"vibe.core.llm.backend.vertex.get_vertex_access_token",
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return_value="fake-token",
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)
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def test_basic_request(self, mock_token, adapter, provider):
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messages = [LLMMessage(role=Role.user, content="Hello")]
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req = adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=messages,
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temperature=0.5,
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tools=None,
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max_tokens=1024,
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tool_choice=None,
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enable_streaming=False,
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provider=provider,
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)
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payload = json.loads(req.body)
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assert payload["anthropic_version"] == "vertex-2023-10-16"
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assert "model" not in payload
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assert payload["max_tokens"] == 1024
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assert payload["temperature"] == 0.5
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assert req.headers["Authorization"] == "Bearer fake-token"
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assert req.headers["anthropic-beta"] == adapter.BETA_FEATURES
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assert "rawPredict" in req.endpoint
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assert "streamRawPredict" not in req.endpoint
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assert req.base_url == "https://us-central1-aiplatform.googleapis.com"
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@patch(
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"vibe.core.llm.backend.vertex.get_vertex_access_token",
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return_value="fake-token",
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)
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def test_streaming_request(self, mock_token, adapter, provider):
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messages = [LLMMessage(role=Role.user, content="Hello")]
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req = adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=messages,
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temperature=0.5,
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tools=None,
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max_tokens=1024,
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tool_choice=None,
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enable_streaming=True,
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provider=provider,
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)
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payload = json.loads(req.body)
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assert payload.get("stream") is True
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assert "streamRawPredict" in req.endpoint
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@patch(
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"vibe.core.llm.backend.vertex.get_vertex_access_token",
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return_value="fake-token",
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)
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def test_no_beta_features_for_vertex(self, mock_token, adapter, provider):
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"""Vertex AI doesn't support the same beta features as direct Anthropic API."""
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messages = [LLMMessage(role=Role.user, content="Hello")]
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req = adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=messages,
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temperature=0.5,
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tools=None,
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max_tokens=1024,
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tool_choice=None,
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enable_streaming=False,
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provider=provider,
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)
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# Vertex AI doesn't support prompt-caching or other beta features
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assert req.headers.get("anthropic-beta", "") == ""
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@patch(
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"vibe.core.llm.backend.vertex.get_vertex_access_token",
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return_value="fake-token",
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)
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def test_with_extended_thinking(self, mock_token, adapter, provider):
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messages = [LLMMessage(role=Role.user, content="Hello")]
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req = adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=messages,
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temperature=0.5,
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tools=None,
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max_tokens=1024,
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tool_choice=None,
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enable_streaming=False,
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provider=provider,
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thinking="medium",
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)
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payload = json.loads(req.body)
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assert payload["thinking"] == {"type": "enabled", "budget_tokens": 10000}
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assert payload["max_tokens"] == 1024
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assert payload["temperature"] == 1
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@patch(
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"vibe.core.llm.backend.vertex.get_vertex_access_token",
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return_value="fake-token",
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)
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def test_with_tools(self, mock_token, adapter, provider):
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messages = [LLMMessage(role=Role.user, content="Hello")]
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tools = [
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AvailableTool(
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function=AvailableFunction(
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name="test_tool",
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description="A test tool",
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parameters={"type": "object", "properties": {}},
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)
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)
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]
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req = adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=messages,
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temperature=0.5,
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tools=tools,
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max_tokens=1024,
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tool_choice=None,
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enable_streaming=False,
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provider=provider,
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)
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payload = json.loads(req.body)
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assert len(payload["tools"]) == 1
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assert payload["tools"][0]["name"] == "test_tool"
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def test_missing_project_id(self, adapter):
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provider = ProviderConfig(
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name="vertex",
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api_base="",
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region="us-central1",
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api_style="vertex-anthropic",
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)
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with pytest.raises(ValueError, match="project_id"):
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adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=[LLMMessage(role=Role.user, content="Hello")],
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temperature=0.5,
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tools=None,
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max_tokens=1024,
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tool_choice=None,
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enable_streaming=False,
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provider=provider,
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)
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def test_missing_region(self, adapter):
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provider = ProviderConfig(
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name="vertex",
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api_base="",
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project_id="test-project",
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api_style="vertex-anthropic",
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)
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with pytest.raises(ValueError, match="region"):
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adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=[LLMMessage(role=Role.user, content="Hello")],
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temperature=0.5,
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tools=None,
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max_tokens=1024,
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tool_choice=None,
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enable_streaming=False,
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provider=provider,
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)
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@patch(
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"vibe.core.llm.backend.vertex.get_vertex_access_token",
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return_value="fake-token",
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)
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def test_default_max_tokens(self, mock_token, adapter, provider):
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messages = [LLMMessage(role=Role.user, content="Hello")]
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req = adapter.prepare_request(
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model_name="claude-3-5-sonnet",
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messages=messages,
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temperature=0.5,
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tools=None,
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max_tokens=None,
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tool_choice=None,
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enable_streaming=False,
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provider=provider,
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)
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payload = json.loads(req.body)
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assert payload["max_tokens"] == adapter.DEFAULT_MAX_TOKENS
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class TestParseFullResponse:
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def test_simple_text_response(self, adapter, provider):
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data = {
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"content": [{"type": "text", "text": "Hello there!"}],
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"usage": {"input_tokens": 10, "output_tokens": 5},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.content == "Hello there!"
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assert chunk.usage.prompt_tokens == 10
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assert chunk.usage.completion_tokens == 5
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def test_response_with_tool_calls(self, adapter, provider):
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data = {
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"content": [
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{"type": "text", "text": "Let me help."},
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{
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"type": "tool_use",
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"id": "tool_123",
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"name": "search",
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"input": {"query": "test"},
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},
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],
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"usage": {"input_tokens": 20, "output_tokens": 15},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.content == "Let me help."
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assert len(chunk.message.tool_calls) == 1
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assert chunk.message.tool_calls[0].id == "tool_123"
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assert chunk.message.tool_calls[0].function.name == "search"
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assert json.loads(chunk.message.tool_calls[0].function.arguments) == {
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"query": "test"
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}
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def test_response_with_thinking(self, adapter, provider):
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data = {
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"content": [
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{
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"type": "thinking",
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"thinking": "Let me think...",
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"signature": "sig123",
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},
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{"type": "text", "text": "Here's my answer."},
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],
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"usage": {"input_tokens": 30, "output_tokens": 20},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.content == "Here's my answer."
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assert chunk.message.reasoning_content == "Let me think..."
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assert chunk.message.reasoning_signature == "sig123"
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def test_response_with_cache_tokens(self, adapter, provider):
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data = {
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"content": [{"type": "text", "text": "Hello"}],
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"usage": {
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"input_tokens": 10,
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"cache_creation_input_tokens": 5,
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"cache_read_input_tokens": 3,
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"output_tokens": 7,
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},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.usage.prompt_tokens == 18
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assert chunk.usage.completion_tokens == 7
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def test_response_with_redacted_thinking(self, adapter, provider):
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data = {
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"content": [
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{"type": "redacted_thinking", "data": "redacted_data_here"},
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{"type": "text", "text": "Answer."},
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],
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"usage": {"input_tokens": 10, "output_tokens": 5},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.content == "Answer."
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assert chunk.message.reasoning_content is None
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def test_response_empty_usage(self, adapter, provider):
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data = {"content": [{"type": "text", "text": "Hello"}], "usage": {}}
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chunk = adapter.parse_response(data, provider)
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assert chunk.usage.prompt_tokens == 0
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assert chunk.usage.completion_tokens == 0
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class TestStreamingEvents:
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def test_message_start(self, adapter, provider):
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data = {
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"type": "message_start",
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"message": {
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"usage": {
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"input_tokens": 100,
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"cache_creation_input_tokens": 20,
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"cache_read_input_tokens": 10,
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}
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},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.usage is not None
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assert chunk.usage.prompt_tokens == 130
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assert chunk.usage.completion_tokens == 0
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def test_message_start_without_usage(self, adapter, provider):
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data = {"type": "message_start", "message": {}}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.role == Role.assistant
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def test_content_block_start_tool_use(self, adapter, provider):
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data = {
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"type": "content_block_start",
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"index": 0,
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"content_block": {"type": "tool_use", "id": "tool_abc", "name": "search"},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.tool_calls is not None
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assert len(chunk.message.tool_calls) == 1
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assert chunk.message.tool_calls[0].id == "tool_abc"
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assert chunk.message.tool_calls[0].function.name == "search"
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assert chunk.message.tool_calls[0].index == 0
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def test_content_block_start_thinking(self, adapter, provider):
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data = {
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"type": "content_block_start",
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"index": 0,
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"content_block": {"type": "thinking", "thinking": ""},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.reasoning_content is not None
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def test_content_block_start_redacted_thinking(self, adapter, provider):
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data = {
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"type": "content_block_start",
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"index": 0,
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"content_block": {"type": "redacted_thinking", "data": "abc"},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.content is None
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assert chunk.message.reasoning_content is None
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def test_content_block_delta_text(self, adapter, provider):
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data = {
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"type": "content_block_delta",
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"index": 0,
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"delta": {"type": "text_delta", "text": "Hello"},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.content == "Hello"
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def test_content_block_delta_thinking(self, adapter, provider):
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data = {
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"type": "content_block_delta",
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"index": 0,
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"delta": {"type": "thinking_delta", "thinking": "I think..."},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.reasoning_content == "I think..."
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def test_content_block_delta_input_json(self, adapter, provider):
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data = {
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"type": "content_block_delta",
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"index": 1,
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"delta": {"type": "input_json_delta", "partial_json": '{"key":'},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.tool_calls is not None
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assert chunk.message.tool_calls[0].function.arguments == '{"key":'
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def test_content_block_stop(self, adapter, provider):
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data = {"type": "content_block_stop", "index": 0}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.content is None
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assert chunk.message.reasoning_content is None
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def test_message_delta_with_usage(self, adapter, provider):
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data = {"type": "message_delta", "usage": {"output_tokens": 42}}
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chunk = adapter.parse_response(data, provider)
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assert chunk.usage is not None
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assert chunk.usage.completion_tokens == 42
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assert chunk.usage.prompt_tokens == 0
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def test_message_delta_without_usage(self, adapter, provider):
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data = {"type": "message_delta", "usage": {}}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.role == Role.assistant
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def test_unknown_event_returns_empty_chunk(self, adapter, provider):
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data = {"type": "ping"}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.role == Role.assistant
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assert chunk.message.content is None
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def test_signature_delta(self, adapter, provider):
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data = {
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"type": "content_block_delta",
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"index": 0,
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"delta": {"type": "signature_delta", "signature": "sig_abc"},
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}
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chunk = adapter.parse_response(data, provider)
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assert chunk.message.reasoning_signature == "sig_abc"
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def test_message_start_resets_state(self, adapter, provider):
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adapter._current_index = 5
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data = {"type": "message_start", "message": {"usage": {"input_tokens": 10}}}
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adapter.parse_response(data, provider)
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assert adapter._current_index == 0
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def test_full_streaming_sequence(self, adapter, provider):
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chunks = []
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# message_start
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chunks.append(
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adapter.parse_response(
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{"type": "message_start", "message": {"usage": {"input_tokens": 50}}},
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provider,
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)
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)
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assert chunks[-1].usage.prompt_tokens == 50
|
||||
|
||||
# thinking block
|
||||
adapter.parse_response(
|
||||
{
|
||||
"type": "content_block_start",
|
||||
"index": 0,
|
||||
"content_block": {"type": "thinking", "thinking": ""},
|
||||
},
|
||||
provider,
|
||||
)
|
||||
chunks.append(
|
||||
adapter.parse_response(
|
||||
{
|
||||
"type": "content_block_delta",
|
||||
"index": 0,
|
||||
"delta": {"type": "thinking_delta", "thinking": "Analyzing..."},
|
||||
},
|
||||
provider,
|
||||
)
|
||||
)
|
||||
assert chunks[-1].message.reasoning_content == "Analyzing..."
|
||||
adapter.parse_response({"type": "content_block_stop", "index": 0}, provider)
|
||||
|
||||
# text block
|
||||
chunks.append(
|
||||
adapter.parse_response(
|
||||
{
|
||||
"type": "content_block_delta",
|
||||
"index": 1,
|
||||
"delta": {"type": "text_delta", "text": "Here's the result."},
|
||||
},
|
||||
provider,
|
||||
)
|
||||
)
|
||||
assert chunks[-1].message.content == "Here's the result."
|
||||
|
||||
# tool use
|
||||
chunks.append(
|
||||
adapter.parse_response(
|
||||
{
|
||||
"type": "content_block_start",
|
||||
"index": 2,
|
||||
"content_block": {
|
||||
"type": "tool_use",
|
||||
"id": "tool_1",
|
||||
"name": "search",
|
||||
},
|
||||
},
|
||||
provider,
|
||||
)
|
||||
)
|
||||
assert chunks[-1].message.tool_calls[0].function.name == "search"
|
||||
|
||||
# message_delta with final usage
|
||||
chunks.append(
|
||||
adapter.parse_response(
|
||||
{"type": "message_delta", "usage": {"output_tokens": 100}}, provider
|
||||
)
|
||||
)
|
||||
assert chunks[-1].usage.completion_tokens == 100
|
||||
|
||||
|
||||
class TestHelperMethods:
|
||||
def test_has_thinking_content_true(self, adapter):
|
||||
messages = [
|
||||
{"role": "user", "content": "Hello"},
|
||||
{
|
||||
"role": "assistant",
|
||||
"content": [
|
||||
{"type": "thinking", "thinking": "Let me think..."},
|
||||
{"type": "text", "text": "Answer"},
|
||||
],
|
||||
},
|
||||
]
|
||||
assert adapter._has_thinking_content(messages) is True
|
||||
|
||||
def test_has_thinking_content_false(self, adapter):
|
||||
messages = [
|
||||
{"role": "user", "content": "Hello"},
|
||||
{"role": "assistant", "content": "Just text"},
|
||||
]
|
||||
assert adapter._has_thinking_content(messages) is False
|
||||
|
||||
def test_has_thinking_content_empty(self, adapter):
|
||||
assert adapter._has_thinking_content([]) is False
|
||||
|
||||
def test_has_thinking_content_non_list_content(self, adapter):
|
||||
messages = [
|
||||
{"role": "assistant", "content": [{"type": "text", "text": "no thinking"}]}
|
||||
]
|
||||
assert adapter._has_thinking_content(messages) is False
|
||||
|
||||
def test_add_cache_control_to_last_user_message(self, adapter):
|
||||
messages = [{"role": "user", "content": [{"type": "text", "text": "Hello"}]}]
|
||||
adapter._add_cache_control_to_last_user_message(messages)
|
||||
assert messages[0]["content"][0]["cache_control"] == {"type": "ephemeral"}
|
||||
|
||||
def test_add_cache_control_skips_non_user(self, adapter):
|
||||
messages = [
|
||||
{"role": "assistant", "content": [{"type": "text", "text": "Hello"}]}
|
||||
]
|
||||
adapter._add_cache_control_to_last_user_message(messages)
|
||||
assert "cache_control" not in messages[0]["content"][0]
|
||||
|
||||
def test_add_cache_control_skips_string_content(self, adapter):
|
||||
messages = [{"role": "user", "content": "Hello"}]
|
||||
adapter._add_cache_control_to_last_user_message(messages)
|
||||
assert messages[0]["content"] == "Hello"
|
||||
|
||||
def test_add_cache_control_tool_result(self, adapter):
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{"type": "tool_result", "tool_use_id": "123", "content": "result"}
|
||||
],
|
||||
}
|
||||
]
|
||||
adapter._add_cache_control_to_last_user_message(messages)
|
||||
assert messages[0]["content"][0]["cache_control"] == {"type": "ephemeral"}
|
||||
|
||||
def test_add_cache_control_empty_messages(self, adapter):
|
||||
messages: list[dict] = []
|
||||
adapter._add_cache_control_to_last_user_message(messages)
|
||||
assert messages == []
|
||||
Loading…
Add table
Add a link
Reference in a new issue