Refacto du code coté Python, java et coté angular afin de mieux séparer les responsabilité et d'avoir moins de répétitivité dans le code.

Mise en place de tests unitaires coté Python et Angular
Mise en place de la couverture de test directement dans le workflow : le programme ne build pas si jamais un test échoue
Passage en v0.16.2 en conséquence

brain/tests/test_onemin_adapter.py

@@ -0,0 +1,110 @@
+"""Tests de l'adapter 1min.ai (API propriétaire : prompt unique aplati, SSE
+`event: content`/`data:{content}`)."""
+from __future__ import annotations
+
+import httpx
+import pytest
+import respx
+
+from app.core.config import Settings
+from app.domain.models import ChatMessage
+from app.domain.ports import LLMProviderError
+from app.infrastructure.onemin_adapter import OneMinAiLLMProvider
+
+_URL = "https://api.1min.ai/api/chat-with-ai?isStreaming=true"
+
+
+def _svc() -> OneMinAiLLMProvider:
+    s = Settings(_env_file=None, onemin_api_key="k", onemin_model="gpt-4o-mini",
+                 llm_timeout_seconds=30)
+    return OneMinAiLLMProvider(s)
+
+
+def _sse(*blocks: str) -> str:
+    return "".join(blocks)
+
+
+# --- streaming -----------------------------------------------------------------
+
+@respx.mock
+async def test_generate_collects_content_chunks():
+    body = _sse(
+        "event: content\ndata: {\"content\": \"Bon\"}\n\n",
+        "event: content\ndata: {\"content\": \"jour\"}\n\n",
+        "event: done\ndata: {}\n\n",
+    )
+    respx.post(_URL).mock(return_value=httpx.Response(200, text=body))
+    assert await _svc().generate("salut") == "Bonjour"
+
+
+@respx.mock
+async def test_generate_sends_api_key_header_and_prompt_payload():
+    route = respx.post(_URL).mock(return_value=httpx.Response(
+        200, text="event: done\ndata: {}\n\n"))
+    await _svc().generate("ma question")
+    req = route.calls.last.request
+    assert req.headers["API-KEY"] == "k"
+    import json
+    body = json.loads(req.content)
+    assert body["model"] == "gpt-4o-mini"
+    assert body["promptObject"]["prompt"] == "ma question"
+
+
+@respx.mock
+async def test_error_event_raises_provider_error():
+    body = "event: error\ndata: {\"message\": \"quota dépassé\"}\n\n"
+    respx.post(_URL).mock(return_value=httpx.Response(200, text=body))
+    with pytest.raises(LLMProviderError) as exc:
+        await _svc().generate("p")
+    assert "quota dépassé" in str(exc.value)
+
+
+@respx.mock
+async def test_http_error_is_translated():
+    respx.post(_URL).mock(return_value=httpx.Response(502, text="bad gateway"))
+    with pytest.raises(LLMProviderError) as exc:
+        await _svc().generate("p")
+    assert "1min.ai" in str(exc.value)
+
+
+@respx.mock
+async def test_stream_chat_flattens_and_streams():
+    route = respx.post(_URL).mock(return_value=httpx.Response(
+        200, text="event: content\ndata: {\"content\": \"R\"}\n\nevent: done\ndata: {}\n\n"))
+    tokens = [t async for t in _svc().stream_chat(
+        [ChatMessage(role="user", content="Q")], system_prompt="SYS")]
+    assert tokens == ["R"]
+    import json
+    prompt = json.loads(route.calls.last.request.content)["promptObject"]["prompt"]
+    assert "[SYSTEM]" in prompt and "SYS" in prompt
+    assert "[USER]" in prompt and "Q" in prompt
+
+
+# --- helpers purs --------------------------------------------------------------
+
+def test_flatten_messages_structure():
+    out = OneMinAiLLMProvider._flatten_messages(
+        [ChatMessage(role="user", content="Q1"), ChatMessage(role="assistant", content="R1")],
+        "instructions système",
+    )
+    assert "[SYSTEM]\ninstructions système" in out
+    assert "[USER]\nQ1" in out
+    assert "[ASSISTANT]\nR1" in out
+    assert out.rstrip().endswith("[ASSISTANT]")
+
+
+def test_extract_content_chunk_json_and_fallback():
+    assert OneMinAiLLMProvider._extract_content_chunk('{"content": "x"}') == "x"
+    assert OneMinAiLLMProvider._extract_content_chunk('{"token": "y"}') == "y"
+    # Non-JSON : filet de sécurité, on renvoie le brut.
+    assert OneMinAiLLMProvider._extract_content_chunk("texte brut") == "texte brut"
+
+
+def test_extract_result_reads_nested_result_object():
+    payload = {"aiRecord": {"aiRecordDetail": {"resultObject": ["partie 1", "partie 2"]}}}
+    assert OneMinAiLLMProvider._extract_result(payload) == "partie 1partie 2"
+
+
+def test_extract_result_raises_on_unexpected_schema():
+    with pytest.raises(LLMProviderError):
+        OneMinAiLLMProvider._extract_result({"unexpected": True})