ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter1/search-codegen/test_responses_agent.py

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+from agent import GPT5NativeAgent
+from config import Config
+from run_experiment_1_3 import (
+    acceptance,
+    independent_asean_reference,
+    validate_asean,
+    validate_clarification,
+)
+
+DASHSCOPE_URL = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
+
+
+def test_request_uses_official_responses_tool_shapes():
+    agent = GPT5NativeAgent("key")
+    request = agent._build_responses_request(
+        "task", reasoning_effort="max", verbosity="high"
+    )
+    assert request["reasoning"] == {"effort": "max"}
+    assert request["text"] == {"verbosity": "high"}
+    assert request["tools"] == [
+        {"type": "web_search", "search_context_size": "medium"},
+        {
+            "type": "code_interpreter",
+            "container": {"type": "auto", "memory_limit": "4g"},
+        },
+    ]
+
+
+def test_dashscope_request_uses_hosted_tool_shapes_and_streaming():
+    agent = GPT5NativeAgent("key", base_url=DASHSCOPE_URL, model="qwen3.7-plus")
+    assert agent.provider == "dashscope"
+    request = agent._build_responses_request(
+        "task", reasoning_effort="high", verbosity="high"
+    )
+    # DashScope runs thinking natively: no reasoning.effort or text.verbosity,
+    # and streaming is mandatory because its gateway drops idle connections.
+    assert "reasoning" not in request
+    assert "text" not in request
+    assert request["stream"] is True
+    assert request["tools"] == [
+        {"type": "web_search"},
+        {"type": "code_interpreter"},
+    ]
+
+
+def test_config_resolves_dashscope_backend():
+    key, base_url, model = Config.resolve("dashscope")
+    assert base_url == DASHSCOPE_URL
+    assert model == Config.DASHSCOPE_MODEL
+    assert isinstance(key, str)
+
+
+def test_dashscope_citations_from_web_search_sources():
+    agent = GPT5NativeAgent("key", base_url=DASHSCOPE_URL, model="qwen3.7-plus")
+    response = {
+        "output": [
+            {
+                "type": "web_search_call",
+                "status": "completed",
+                "action": {
+                    "query": "ASEAN capitals",
+                    "sources": [
+                        {"type": "url", "url": "https://asean.test/one"},
+                        {"type": "url", "url": "https://asean.test/two"},
+                    ],
+                },
+            }
+        ]
+    }
+    citations = agent._citations(response)
+    assert citations == [
+        {"type": "url_citation", "url": "https://asean.test/one"},
+        {"type": "url_citation", "url": "https://asean.test/two"},
+    ]
+
+def test_dashscope_citations_from_web_search_string_url_sources():
+    agent = GPT5NativeAgent("key", base_url=DASHSCOPE_URL, model="qwen3.7-plus")
+    response = {
+        "output": [
+            {
+                "type": "web_search_call",
+                "status": "completed",
+                "action": {
+                    "query": "ASEAN capitals",
+                    "sources": [
+                        "https://asean.test/one",
+                        "https://asean.test/two",
+                    ],
+                },
+            }
+        ]
+    }
+    citations = agent._citations(response)
+    assert citations == [
+        {"type": "url_citation", "url": "https://asean.test/one"},
+        {"type": "url_citation", "url": "https://asean.test/two"},
+    ]
+
+
+def test_independent_asean_reference_is_kuala_lumpur_singapore():
+    reference = independent_asean_reference()
+    assert reference["pair"] == ["Kuala Lumpur", "Singapore"]
+    assert reference["pair_count"] == 45
+    assert 250 < reference["distance_km"] < 400
+
+
+def test_asean_acceptance_requires_both_completed_hosted_tools():
+    result = {
+        "success": True,
+        "requested_model": "gpt-5.6-sol",
+        "model": "gpt-5.6-sol",
+        "response": "Singapore and Kuala Lumpur are 316 km apart.",
+        "output_items": [
+            {"type": "web_search_call", "status": "completed"},
+            {"type": "code_interpreter_call", "status": "completed"},
+        ],
+        "citations": [
+            {"type": "url_citation", "url": "https://one.test"},
+            {"type": "url_citation", "url": "https://two.test"},
+        ],
+    }
+    assert validate_asean(result)["passed"] is True
+    result["output_items"] = result["output_items"][:1]
+    assert validate_asean(result)["passed"] is False
+
+
+def test_asean_acceptance_rejects_model_substitution():
+    result = {
+        "success": True,
+        "requested_model": "qwen3.7-plus",
+        "model": "qwen3.7-flash",
+        "response": "Singapore and Kuala Lumpur are 316 km apart.",
+        "output_items": [
+            {"type": "web_search_call", "status": "completed"},
+            {"type": "code_interpreter_call", "status": "completed"},
+        ],
+        "citations": [
+            {"type": "url_citation", "url": "https://one.test"},
+            {"type": "url_citation", "url": "https://two.test"},
+        ],
+    }
+    assert validate_asean(result)["checks"]["model_identity_exact"] is False
+    assert validate_asean(result)["passed"] is False
+
+
+def test_clarification_requires_no_tools_then_linked_tool_run():
+    first = {
+        "success": True,
+        "response": "Which source and indicators do you prefer?",
+        "tool_calls": [],
+        "response_id": "resp_1",
+    }
+    second = {
+        "success": True,
+        "request": {"previous_response_id": "resp_1"},
+        "response": "MA7, MA20, RSI14 and MACD(12,26,9) were computed.",
+        "output_items": [
+            {"type": "web_search_call", "status": "completed"},
+            {"type": "code_interpreter_call", "status": "completed"},
+        ],
+        "citations": [{"type": "url_citation"}],
+    }
+    assert validate_clarification(first, second)["passed"] is True
+    second_without_indicators = dict(second, response="Here is the report.")
+    assert validate_clarification(first, second_without_indicators)["passed"] is False
+
+
+def test_acceptance_is_multi_provider_not_openai_gated():
+    passing_run = {
+        "backend": "dashscope",
+        "started": True,
+        "requested_model": "qwen3.7-plus",
+        "asean_validation": {"passed": True},
+        "clarification": {"validation": {"passed": True}},
+    }
+    blocked_openai = {"backend": "openai", "started": True,
+                      "requested_model": "gpt-5.6-sol",
+                      "asean_validation": {"passed": False},
+                      "clarification": {"validation": {"passed": False}}}
+    result = acceptance([blocked_openai, passing_run])
+    assert result["passed"] is True
+    assert result["acceptance_backend"] == "dashscope"
+    # OpenAI keeps priority when both pass.
+    blocked_openai["asean_validation"] = {"passed": True}
+    blocked_openai["clarification"] = {"validation": {"passed": True}}
+    result = acceptance([blocked_openai, passing_run])
+    assert result["acceptance_backend"] == "openai"
+    # OpenRouter alone can never close the experiment.
+    openrouter_run = dict(passing_run, backend="openrouter")
+    result = acceptance([openrouter_run])
+    assert result["passed"] is False
+    assert result["openrouter_is_diagnostic_not_acceptance"] is True