test: add integration tests for semantic search with in-process embeddings

Adds comprehensive integration tests for vector database semantic search that
work without external dependencies (Ollama), making them suitable for CI/CD.

Changes:
- Add SimpleEmbeddingProvider: in-process TF-IDF-like embeddings using feature hashing
- Make Ollama optional: embedding service now falls back to SimpleEmbeddingProvider
- Add 6 integration tests covering semantic search, filtering, and batch operations
- Downgrade urllib3 to 1.26.x for qdrant-client compatibility
- Update docker-compose.yml to comment out Ollama configuration (optional)

The SimpleEmbeddingProvider generates deterministic, normalized embeddings
suitable for testing semantic similarity without requiring external services.
Tests validate that similar texts have higher cosine similarity and that
semantic search correctly ranks results by relevance.

Test coverage:
- Deterministic embedding generation
- Semantic similarity between texts
- Full search flow with Qdrant (in-memory)
- Category filtering
- Empty result handling
- Batch embedding generation

All tests pass and can run in GitHub CI without Ollama infrastructure.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

nextcloud_mcp_server/embedding/service.py

@@ -5,6 +5,7 @@ import os
 
 from .base import EmbeddingProvider
 from .ollama_provider import OllamaEmbeddingProvider
+from .simple_provider import SimpleEmbeddingProvider
 
 logger = logging.getLogger(__name__)
 
@@ -21,27 +22,35 @@ class EmbeddingService:
         Auto-detect available embedding provider.
 
         Checks environment variables in order:
-        1. OLLAMA_BASE_URL - Use Ollama provider
+        1. OLLAMA_BASE_URL - Use Ollama provider (production)
+        2. OPENAI_API_KEY - Use OpenAI provider (future)
+        3. Fallback to SimpleEmbeddingProvider (testing/development)
 
         Returns:
             Configured embedding provider
-
-        Raises:
-            ValueError: If no embedding provider is configured
         """
-        # Ollama provider (for this deployment)
+        # Ollama provider (production)
         ollama_url = os.getenv("OLLAMA_BASE_URL")
         if ollama_url:
+            logger.info(f"Using Ollama embedding provider: {ollama_url}")
             return OllamaEmbeddingProvider(
                 base_url=ollama_url,
                 model=os.getenv("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text"),
                 verify_ssl=os.getenv("OLLAMA_VERIFY_SSL", "true").lower() == "true",
             )
 
-        raise ValueError(
-            "No embedding provider configured. "
-            "Set OLLAMA_BASE_URL environment variable."
+        # OpenAI provider (future implementation)
+        # openai_key = os.getenv("OPENAI_API_KEY")
+        # if openai_key:
+        #     return OpenAIEmbeddingProvider(api_key=openai_key)
+
+        # Fallback to simple provider for development/testing
+        logger.warning(
+            "No embedding provider configured (OLLAMA_BASE_URL or OPENAI_API_KEY not set). "
+            "Using SimpleEmbeddingProvider for testing/development. "
+            "For production, configure an external embedding service."
         )
+        return SimpleEmbeddingProvider(dimension=384)
 
     async def embed(self, text: str) -> list[float]:
         """