feat(backend): add LLM provider adapters for Ollama, OpenAI, Groq and Anthropic

backend/tests/test_llm.py

@@ -0,0 +1,226 @@
+"""Testes dos adaptadores de LLM.
+
+Cada adaptador converte o formato de streaming do próprio provedor em deltas de
+texto. Os testes usam transportes falsos: verificam a conversão, não a rede.
+"""
+
+from __future__ import annotations
+
+import json
+import sys
+from pathlib import Path
+
+import httpx
+import pytest
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
+
+from app.config import Settings  # noqa: E402
+from app.llm import (  # noqa: E402
+    SYSTEM_PROMPT,
+    AnthropicProvider,
+    LLMProviderError,
+    OllamaProvider,
+    OpenAIProvider,
+    StubProvider,
+    build_provider,
+)
+
+
+class FakeStreamResponse:
+    """Dublê do contexto assíncrono devolvido por `httpx.AsyncClient.stream`."""
+
+    status_code = 200
+
+    def __init__(self, chunks):
+        self._chunks = chunks
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, *exc_info):
+        return False
+
+    async def aiter_lines(self):
+        for chunk in self._chunks:
+            text = chunk.decode() if isinstance(chunk, bytes) else chunk
+            for line in text.splitlines():
+                yield line
+
+    async def aread(self):
+        return b"erro"
+
+
+class FakeStreamClient:
+    """Dublê do `httpx.AsyncClient` que devolve um stream fixo."""
+
+    def __init__(self, chunks):
+        self._chunks = chunks
+
+    def stream(self, *args, **kwargs):
+        return FakeStreamResponse(self._chunks)
+
+
+def collect(provider, messages=None, system=SYSTEM_PROMPT):
+    import asyncio
+
+    async def run():
+        chunks = []
+        async for delta in provider.stream(messages or [{"role": "user", "content": "olá"}], system):
+            chunks.append(delta)
+        return "".join(chunks)
+
+    return asyncio.run(run())
+
+
+# --------------------------------------------------------------------------- #
+# Seleção de provedor
+# --------------------------------------------------------------------------- #
+
+def test_build_provider_selects_ollama():
+    provider = build_provider(Settings(llm_provider="ollama"))
+    assert isinstance(provider, OllamaProvider)
+
+
+def test_build_provider_selects_openai():
+    provider = build_provider(Settings(llm_provider="openai", openai_api_key="sk-x"))
+    assert isinstance(provider, OpenAIProvider)
+
+
+def test_build_provider_selects_groq_as_openai_compatible():
+    provider = build_provider(Settings(llm_provider="groq", groq_api_key="gsk-x"))
+    assert isinstance(provider, OpenAIProvider)
+    assert provider.base_url.startswith("https://api.groq.com")
+
+
+def test_build_provider_selects_anthropic():
+    provider = build_provider(Settings(llm_provider="anthropic", anthropic_api_key="sk-x"))
+    assert isinstance(provider, AnthropicProvider)
+
+
+def test_build_provider_selects_stub():
+    provider = build_provider(Settings(llm_provider="stub"))
+    assert isinstance(provider, StubProvider)
+
+
+def test_build_provider_rejects_unknown_provider():
+    with pytest.raises(ValueError, match="não suportado"):
+        build_provider(Settings(llm_provider="desconhecido"))
+
+
+def test_openai_provider_requires_api_key():
+    with pytest.raises(ValueError, match="OPENAI_API_KEY"):
+        build_provider(Settings(llm_provider="openai", openai_api_key=""))
+
+
+# --------------------------------------------------------------------------- #
+# System prompt
+# --------------------------------------------------------------------------- #
+
+def test_system_prompt_contains_the_spec_directives():
+    assert "conselheiro espiritual e Pastor Online" in SYSTEM_PROMPT
+    assert "única fonte de autoridade" in SYSTEM_PROMPT
+    assert "livro, capítulo e versículo" in SYSTEM_PROMPT
+    assert "tom acolhedor" in SYSTEM_PROMPT
+    assert "Não crie doutrina própria" in SYSTEM_PROMPT
+
+
+def test_system_prompt_contains_the_crisis_scope():
+    assert "emergência" in SYSTEM_PROMPT.lower()
+    assert "diagnóstico" in SYSTEM_PROMPT.lower() or "diagnost" in SYSTEM_PROMPT.lower()
+
+
+# --------------------------------------------------------------------------- #
+# Conversão de streaming
+# --------------------------------------------------------------------------- #
+
+def test_ollama_provider_converts_ndjson_stream(monkeypatch):
+    provider = OllamaProvider(base_url="http://ollama:11434", model="qwen2.5:1.5b")
+
+    lines = [
+        {"message": {"content": "Olá "}, "done": False},
+        {"message": {"content": "mundo"}, "done": False},
+        {"message": {"content": ""}, "done": True},
+    ]
+
+    async def fake_stream(*args, **kwargs):
+        for line in lines:
+            yield f"{json.dumps(line)}\n".encode()
+
+    monkeypatch.setattr(
+        provider, "_client", FakeStreamClient([f"{json.dumps(line)}\n" for line in lines])
+    )
+
+    assert collect(provider) == "Olá mundo"
+
+
+def test_openai_provider_converts_sse_stream(monkeypatch):
+    provider = OpenAIProvider(
+        base_url="https://api.openai.com/v1", model="gpt-4o-mini", api_key="sk-test"
+    )
+
+    chunks = [
+        'data: {"choices":[{"delta":{"content":"Olá "}}]}\n\n'.encode(),
+        'data: {"choices":[{"delta":{"content":"mundo"}}]}\n\n'.encode(),
+        b"data: [DONE]\n\n",
+    ]
+
+    async def fake_stream(*args, **kwargs):
+        for chunk in chunks:
+            yield chunk
+
+    monkeypatch.setattr(provider, "_client", FakeStreamClient(chunks))
+
+    assert collect(provider) == "Olá mundo"
+
+
+def test_anthropic_provider_converts_event_stream(monkeypatch):
+    provider = AnthropicProvider(
+        base_url="https://api.anthropic.com", model="claude-sonnet-4-5", api_key="sk-test"
+    )
+
+    events = [
+        'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"type":"text_delta","text":"Olá "}}\n\n'.encode(),
+        'event: content_block_delta\ndata: {"type":"content_block_delta","delta":{"type":"text_delta","text":"mundo"}}\n\n'.encode(),
+    ]
+
+    async def fake_stream(*args, **kwargs):
+        for event in events:
+            yield event
+
+    monkeypatch.setattr(provider, "_client", FakeStreamClient(events))
+
+    assert collect(provider) == "Olá mundo"
+
+
+def test_stub_provider_returns_deterministic_text():
+    provider = StubProvider()
+    text = collect(provider, [{"role": "user", "content": "Quem criou o mundo?"}])
+    assert "Gênesis 1:1" in text
+
+
+# --------------------------------------------------------------------------- #
+# Erros
+# --------------------------------------------------------------------------- #
+
+def test_provider_error_does_not_leak_the_api_key():
+    provider = OpenAIProvider(
+        base_url="https://api.openai.com/v1", model="gpt-4o-mini", api_key="sk-super-secreta"
+    )
+
+    def raise_error(*args, **kwargs):
+        raise httpx.ConnectError("connection refused")
+
+    monkeypatched = provider._client
+    try:
+        provider._client = type(
+            "FailingClient",
+            (),
+            {"stream": staticmethod(raise_error)},
+        )()
+        with pytest.raises(LLMProviderError) as exc:
+            collect(provider)
+        assert "sk-super-secreta" not in str(exc.value)
+        assert "sk-super-secreta" not in str(exc.value.__cause__ or "")
+    finally:
+        provider._client = monkeypatched