Fix FastAPI, async, database, caching, concurrency, RAG, LangChain, security, and enterprise backend issues
Two service classes import each other, causing FastAPI dependency injection failure.
Connections were not closed properly because asyncpg.connect() was being called per request.
Background tasks were kept forever in a list, preventing garbage collection.
Multiple concurrent writes corrupted data because dict writes are unsafe without locks.
JWT verification was disabled, allowing attackers to forge tokens.
Chunk size was extremely large, reducing semantic precision.
Embeddings were recomputed on every request, making retrieval slow.
User input is directly concatenated into SQL query, allowing SQL injection attacks.
Multiple threads lock files in different order, causing deadlocks.
Files are opened but never explicitly closed, causing file handle exhaustion.
Multiple workers process the same task because task locking is not implemented.
Python's GIL prevents true parallelism in multi-threaded CPU-bound tasks, causing poor performance.
Dynamic attribute access fails when attribute doesn't exist, causing AttributeError.
Closure captures large objects, preventing garbage collection and causing memory leaks.
Module A imports B, B imports C, C imports A, causing circular import error.
Attempting to pickle objects with lambda functions or file handles causes PickleError.
Async operation exceeds timeout but doesn't handle cancellation properly, causing resource leaks.
Connection pool size is too small for concurrent requests, causing connection timeouts.
Async generator is not properly closed, causing resource leaks and memory issues.
Updating nested Pydantic model fields doesn't trigger validation, causing invalid state.
Celery task fails on transient errors but doesn't retry, causing task loss.
Multiple threads modify shared global dictionary without locks, causing data corruption.
Exception objects with tracebacks are kept in memory, preventing garbage collection of referenced objects.
Looping through objects triggers individual queries for each, causing N+1 query problem.
Multiple processes check file existence and create lock file simultaneously, causing race condition.