feat(ai): services partages A2 + SSE streaming B4 + confirmations UI B5 (#79)

tests/test_bookslm.py

@@ -823,3 +823,65 @@ class TestBooksLMAgentEndpoint:
         assert resp.status_code == 200
         assert "event: confirmation" in resp.text
         assert "_agent_write" in resp.text
+
+    def test_agent_confirmation_resume(self, bookslm_client, monkeypatch):
+        import re
+
+        import backend.bookslm_routes as routes
+        from backend.ai_chat import LLMResponse, ToolCall
+        from backend.tools import registry
+        from backend.tools.api import ToolRisk
+        from backend.tools.registry import ToolSpec
+        from backend.tools.schemas import ListVaultsInput
+
+        executed = {}
+
+        def handler(ctx, params):
+            executed["ran"] = True
+            return {"ok": True}
+
+        spec = ToolSpec(
+            name="_agent_write_resume",
+            description="write for tests",
+            input_model=ListVaultsInput,
+            handler=handler,
+            risk=ToolRisk.WRITE,
+        )
+        monkeypatch.setitem(registry._REGISTRY, "_agent_write_resume", spec)
+
+        responses = [LLMResponse(tool_calls=[ToolCall(id="c1", name="_agent_write_resume", arguments={})])]
+
+        async def fake_chat_completion(messages, **kwargs):
+            return responses.pop(0)
+
+        monkeypatch.setattr(routes, "chat_completion", fake_chat_completion)
+        monkeypatch.setattr(routes, "_resolve_provider_name", lambda requested: "deepseek")
+
+        token, _ = _login_bookslm(bookslm_client)
+        payload = {"vault": "TestVault", "directory": "", "message": "crée un fichier", "mode": "directory"}
+        resp = bookslm_client.post(
+            "/api/ai/bookslm/agent",
+            json=payload,
+            headers={"Authorization": f"Bearer {token}"},
+        )
+        assert "event: confirmation" in resp.text
+        assert "_agent_write_resume" in resp.text
+        assert executed.get("ran") is not True
+
+        match = re.search(r"event: confirmation\ndata: (.*)", resp.text)
+        assert match, resp.text
+        confirmation = json.loads(match.group(1))
+        assert confirmation["pending"]["error"]["tool"] == "_agent_write_resume"
+
+        # Resume: apply the pending call, then the model answers.
+        responses.append(LLMResponse(content="C'est fait."))
+        resume_payload = dict(payload, confirm=confirmation["pending"], confirm_messages=confirmation["messages"])
+        resp2 = bookslm_client.post(
+            "/api/ai/bookslm/agent",
+            json=resume_payload,
+            headers={"Authorization": f"Bearer {token}"},
+        )
+        assert resp2.status_code == 200
+        assert executed.get("ran") is True
+        assert "C'est fait." in resp2.text
+        assert "event: message" in resp2.text