feat: async/parallel execution with configurable concurrency

Parallelize LLM calls across minibatches to reduce wall-clock time.
All domain ports (LLMPort, JudgePort, ProposerPort) are now async.
Adapter implementations wrap synchronous DSPy calls with asyncio.to_thread.
Judge calls run in parallel within a batch using asyncio.gather + semaphore.
Evaluator parallelizes minibatch execution with configurable concurrency.
Evolution loop and use case are fully async. Proposer stays sequential.
Added --max-concurrency CLI flag and max_concurrency YAML config field.
Added async_retry_with_backoff for async error handling.
All 139 unit tests pass.

Co-Authored-By: Paperclip <noreply@paperclip.ing>

tests/conftest.py

@@ -1,7 +1,7 @@
 """Shared test fixtures."""
 from __future__ import annotations
 
-from unittest.mock import MagicMock
+from unittest.mock import AsyncMock, MagicMock
 
 import pytest
 
@@ -66,17 +66,17 @@ def mock_eval_result() -> EvalResult:
 
 
 @pytest.fixture
-def mock_llm_port() -> MagicMock:
+def mock_llm_port() -> AsyncMock:
     """Mock LLMPort that returns canned responses."""
-    port = MagicMock()
+    port = AsyncMock()
     port.execute.return_value = "This is a mock response."
     return port
 
 
 @pytest.fixture
-def mock_judge_port() -> MagicMock:
+def mock_judge_port() -> AsyncMock:
     """Mock JudgePort that returns moderate scores."""
-    port = MagicMock()
+    port = AsyncMock()
     port.judge_batch.return_value = [
         (0.5, "Moderate quality, needs improvement."),
     ] * 5
@@ -84,9 +84,9 @@ def mock_judge_port() -> MagicMock:
 
 
 @pytest.fixture
-def mock_proposer_port() -> MagicMock:
+def mock_proposer_port() -> AsyncMock:
     """Mock ProposerPort that returns a slightly modified prompt."""
-    port = MagicMock()
+    port = AsyncMock()
     port.propose.return_value = Prompt(
         text="You are a very helpful assistant. Answer the question precisely."
     )