gartoid/Prompt-optimizer
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feat: async/parallel execution with configurable concurrency

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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>
This commit is contained in:
FullStackDev
2026-03-29 13:15:34 +00:00
parent e2d111ce5b
commit c92ca4a2b8
16 changed files with 297 additions and 159 deletions
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30
tests/unit/test_adapter_config.py
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@@ -57,23 +57,25 @@ def synth_lm() -> dspy.LM:
class TestDSPyLLMAdapterOwnLM:
"""Bug #2 fix: DSPyLLMAdapter must use the LM it receives, not the global one."""
def test_uses_provided_lm_not_global(self) -> None:
@pytest.mark.asyncio
async def test_uses_provided_lm_not_global(self) -> None:
local_lm = dspy.utils.DummyLM([{"output": "local response"}])
global_lm = dspy.utils.DummyLM([{"output": "global response"}])
dspy.configure(lm=global_lm)
adapter = DSPyLLMAdapter(lm=local_lm)
result = adapter.execute(Prompt(text="test"), "input")
result = await adapter.execute(Prompt(text="test"), "input")
assert result == "local response"
def test_does_not_affect_global_lm(self) -> None:
@pytest.mark.asyncio
async def test_does_not_affect_global_lm(self) -> None:
local_lm = dspy.utils.DummyLM([{"output": "local response"}])
global_lm = dspy.utils.DummyLM([{"output": "global response"}])
dspy.configure(lm=global_lm)
adapter = DSPyLLMAdapter(lm=local_lm)
adapter.execute(Prompt(text="test"), "input")
await adapter.execute(Prompt(text="test"), "input")
# Global LM should still be the same
assert dspy.settings.lm is global_lm
@@ -82,9 +84,10 @@ class TestDSPyLLMAdapterOwnLM:
class TestDSPyJudgeAdapterOwnLM:
"""DSPyJudgeAdapter must use its own LM instance."""
def test_uses_provided_lm(self, judge_lm: dspy.LM) -> None:
@pytest.mark.asyncio
async def test_uses_provided_lm(self, judge_lm: dspy.LM) -> None:
adapter = DSPyJudgeAdapter(lm=judge_lm)
results = adapter.judge_batch(
results = await adapter.judge_batch(
task_description="Test task",
pairs=[("input 1", "output 1")],
)
@@ -93,7 +96,8 @@ class TestDSPyJudgeAdapterOwnLM:
assert score == 0.8
assert feedback == "Good response."
def test_does_not_use_global_lm(self) -> None:
@pytest.mark.asyncio
async def test_does_not_use_global_lm(self) -> None:
judge_lm = dspy.utils.DummyLM(
[{"reasoning": "ok", "score": "0.9", "feedback": "Judge-specific response"}]
)
@@ -101,14 +105,15 @@ class TestDSPyJudgeAdapterOwnLM:
dspy.configure(lm=global_lm)
adapter = DSPyJudgeAdapter(lm=judge_lm)
results = adapter.judge_batch("task", [("in", "out")])
results = await adapter.judge_batch("task", [("in", "out")])
assert results[0][0] == 0.9
class TestDSPyProposerAdapterOwnLM:
"""DSPyProposerAdapter must use its own LM instance."""
def test_uses_provided_lm(self, proposer_lm: dspy.LM) -> None:
@pytest.mark.asyncio
async def test_uses_provided_lm(self, proposer_lm: dspy.LM) -> None:
adapter = DSPyProposerAdapter(lm=proposer_lm)
trajectories = [
Trajectory(
@@ -119,14 +124,15 @@ class TestDSPyProposerAdapterOwnLM:
prompt_used="old prompt",
)
]
result = adapter.propose(
result = await adapter.propose(
current_prompt=Prompt(text="old prompt"),
trajectories=trajectories,
task_description="Test task",
)
assert "Improved prompt" in result.text
def test_does_not_use_global_lm(self) -> None:
@pytest.mark.asyncio
async def test_does_not_use_global_lm(self) -> None:
proposer_lm = dspy.utils.DummyLM(
[{"reasoning": "ok", "new_instruction": "proposer-specific"}]
)
@@ -136,7 +142,7 @@ class TestDSPyProposerAdapterOwnLM:
dspy.configure(lm=global_lm)
adapter = DSPyProposerAdapter(lm=proposer_lm)
result = adapter.propose(
result = await adapter.propose(
current_prompt=Prompt(text="test"),
trajectories=[],
task_description="task",