fix(agent): v4.13.1 - actions contenu document (resume/traduire/ameliorer/meeting) sans outils, apercu + appliquer/rejeter, mock ignore contexte

tests/test_agent.py

@@ -661,4 +661,53 @@ def test_router_user_key_test_failure(client, monkeypatch):
 
     prov = client.get("/api/agent/providers").json()
     p = [x for x in prov["providers"] if x["id"] == "openai"][0]
-    assert p["functional"] is False
+    assert p["functional"] is False
+
+
+def test_generate_endpoint_returns_text(client, monkeypatch):
+    """/api/agent/generate performs headless text generation (no tools)."""
+    from app.routers import agent as agent_router
+    from app.services.llm_client import LLMResponse
+
+    class FakeLLM(agent_router.LLMClient):
+        def __init__(self, *args, **kwargs):
+            super().__init__(*args, **kwargs)
+
+        async def complete(self, messages, *, model=None, tools=None, stream=False):
+            # The tool schema must never be offered for content generation.
+            assert tools is None
+            return LLMResponse(text="Voici le document traduit en anglais.", model="gpt-4o-mini")
+
+    monkeypatch.setattr(agent_router, "LLMClient", FakeLLM)
+
+    r = client.post("/api/agent/generate", json={
+        "prompt": "Traduis ce document en anglais.",
+        "context": "Titre du document : Doc\nContenu en français.",
+        "model": "gpt-4o-mini",
+    })
+    assert r.status_code == 200
+    body = r.json()
+    assert body["ok"] is True
+    assert "traduit en anglais" in body["text"]
+
+
+def test_generate_endpoint_requires_prompt(client):
+    r = client.post("/api/agent/generate", json={"prompt": "  "})
+    assert r.status_code == 400
+
+
+def test_mock_planner_ignores_context_keywords(client):
+    """Document context words (ex: 'cherche', 'collection') must not trigger
+    tool intents — the planner only inspects the user objective."""
+    import asyncio
+    from app.services.llm_client import LLMClient
+
+    llm = LLMClient(provider="offline")
+    resp = asyncio.run(llm.complete(
+        [{"role": "system", "content": "x"},
+         {"role": "user", "content": "Résume ce document.\n\n# Contexte\n"
+                                     "Le rapport mentionne une recherche sur la collection Z."}],
+        model="gpt-4o", tools=[{"type": "function"}],
+    ))
+    assert resp.tool_calls == []
+    assert resp.text