feat: add Phase F.1 memory infrastructure

Add multi-tenancy support and memory storage infrastructure:

- Add ContextVar-based request context (src/core/context.py)
  - Async-safe user/conversation tracking via contextvars
  - RequestContext manager for clean setup/teardown
  - get_user(), get_conversation_id() helpers

- Add multi-tenancy utilities (src/core/multi_tenancy.py)
  - User ID sanitization for collection/key names
  - get_memory_collection_name(), get_session_key() helpers

- Add Ollama embedding client (src/core/embeddings.py)
  - nomic-embed-text model (768 dimensions)
  - embed(), embed_batch(), health_check() methods

- Add Qdrant client wrapper (src/core/qdrant.py)
  - Per-user collection pattern: memories_{user}
  - upsert_memory(), search_memories(), delete_memory()
  - Type-based filtering support

- Add Redis memory cache (src/core/memory_cache.py)
  - Session context with 24h TTL
  - Recent entities tracking
  - Separate from benchmarks (db=2)

- Update config with memory settings
  - QDRANT_HOST, QDRANT_PORT, QDRANT_EMBEDDING_DIM
  - OLLAMA_EMBEDDING_MODEL
  - REDIS_MEMORY_DB, REDIS_MEMORY_TTL_HOURS

- Add user field to ResponseRequest (OpenAI standard)
- Set context in router, reset in finally block
- Update librarian client to use get_user() (12 methods)

All 333 unit tests pass.

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

src/core/config.py

@@ -124,6 +124,36 @@ class Config(BaseSettings):
         description="Library-Desk request timeout in seconds"
     )
 
+    # Qdrant Configuration (Memory vector storage)
+    QDRANT_HOST: str = Field(
+        default="localhost",
+        description="Qdrant server host"
+    )
+    QDRANT_PORT: int = Field(
+        default=6333,
+        description="Qdrant server port"
+    )
+    QDRANT_EMBEDDING_DIM: int = Field(
+        default=768,
+        description="Embedding dimension (768 for nomic-embed-text)"
+    )
+
+    # Ollama Embedding Configuration
+    OLLAMA_EMBEDDING_MODEL: str = Field(
+        default="nomic-embed-text",
+        description="Ollama model for embeddings"
+    )
+
+    # Redis Memory Database (separate from benchmarks)
+    REDIS_MEMORY_DB: int = Field(
+        default=2,
+        description="Redis database number for memory cache"
+    )
+    REDIS_MEMORY_TTL_HOURS: int = Field(
+        default=24,
+        description="TTL for session context in hours"
+    )
+
     # Logging
     LOG_LEVEL: str = Field(default="INFO", description="Logging level")
     ENABLE_BENCHMARKS: bool = Field(default=True, description="Enable performance benchmarking")
@@ -139,9 +169,19 @@ class Config(BaseSettings):
 
     @property
     def redis_url(self) -> str:
-        """Construct Redis connection URL."""
+        """Construct Redis connection URL for benchmarks."""
         return f"redis://{self.REDIS_HOST}:{self.REDIS_PORT}/{self.REDIS_DB}"
 
+    @property
+    def redis_memory_url(self) -> str:
+        """Construct Redis connection URL for memory cache."""
+        return f"redis://{self.REDIS_HOST}:{self.REDIS_PORT}/{self.REDIS_MEMORY_DB}"
+
+    @property
+    def qdrant_url(self) -> str:
+        """Construct Qdrant server URL."""
+        return f"http://{self.QDRANT_HOST}:{self.QDRANT_PORT}"
+
     @property
     def log_format(self) -> str:
         """