[Chore] Async implementation for perform_function_optimization

codeflash/lsp/beta.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-import contextlib
+import asyncio
 import os
 from dataclasses import dataclass
 from pathlib import Path
@@ -11,19 +11,15 @@
 
 from codeflash.api.cfapi import get_codeflash_api_key, get_user_id
 from codeflash.cli_cmds.cli import process_pyproject_config
-from codeflash.cli_cmds.console import code_print
-from codeflash.code_utils.git_worktree_utils import (
-    create_diff_patch_from_worktree,
-    get_patches_metadata,
-    overwrite_patch_metadata,
-)
+from codeflash.code_utils.git_worktree_utils import get_patches_metadata, overwrite_patch_metadata
 from codeflash.code_utils.shell_utils import save_api_key_to_rc
 from codeflash.discovery.functions_to_optimize import (
     filter_functions,
     get_functions_inside_a_commit,
     get_functions_within_git_diff,
 )
 from codeflash.either import is_successful
+from codeflash.lsp.features.perform_optimization import sync_perform_optimization
 from codeflash.lsp.server import CodeflashLanguageServer
 
 if TYPE_CHECKING:
@@ -67,7 +63,6 @@ class OptimizableFunctionsInCommitParams:
     commit_hash: str
 
 
-# server = CodeflashLanguageServer("codeflash-language-server", "v1.0", protocol_cls=CodeflashLanguageServerProtocol)
 server = CodeflashLanguageServer("codeflash-language-server", "v1.0")
 
 
@@ -325,154 +320,15 @@ def on_patch_applied(_server: CodeflashLanguageServer, params: OnPatchAppliedPar
 
 
 @server.feature("performFunctionOptimization")
-@server.thread()
-def perform_function_optimization(  # noqa: PLR0911
+async def perform_function_optimization(
     server: CodeflashLanguageServer, params: FunctionOptimizationParams
 ) -> dict[str, str]:
+    loop = asyncio.get_running_loop()
     try:
-        server.show_message_log(f"Starting optimization for function: {params.functionName}", "Info")
-        current_function = server.optimizer.current_function_being_optimized
-
-        if not current_function:
-            server.show_message_log(f"No current function being optimized for {params.functionName}", "Error")
-            return {
-                "functionName": params.functionName,
-                "status": "error",
-                "message": "No function currently being optimized",
-            }
-
-        module_prep_result = server.optimizer.prepare_module_for_optimization(current_function.file_path)
-        if not module_prep_result:
-            return {
-                "functionName": params.functionName,
-                "status": "error",
-                "message": "Failed to prepare module for optimization",
-            }
-
-        validated_original_code, original_module_ast = module_prep_result
-
-        function_optimizer = server.optimizer.create_function_optimizer(
-            current_function,
-            function_to_optimize_source_code=validated_original_code[current_function.file_path].source_code,
-            original_module_ast=original_module_ast,
-            original_module_path=current_function.file_path,
-            function_to_tests={},
-        )
-
-        server.optimizer.current_function_optimizer = function_optimizer
-        if not function_optimizer:
-            return {"functionName": params.functionName, "status": "error", "message": "No function optimizer found"}
-
-        initialization_result = function_optimizer.can_be_optimized()
-        if not is_successful(initialization_result):
-            return {"functionName": params.functionName, "status": "error", "message": initialization_result.failure()}
-
-        should_run_experiment, code_context, original_helper_code = initialization_result.unwrap()
-
-        code_print(
-            code_context.read_writable_code.flat,
-            file_name=current_function.file_path,
-            function_name=current_function.function_name,
-        )
-
-        optimizable_funcs = {current_function.file_path: [current_function]}
-
-        devnull_writer = open(os.devnull, "w")  # noqa
-        with contextlib.redirect_stdout(devnull_writer):
-            function_to_tests, _num_discovered_tests = server.optimizer.discover_tests(optimizable_funcs)
-            function_optimizer.function_to_tests = function_to_tests
-
-        test_setup_result = function_optimizer.generate_and_instrument_tests(
-            code_context, should_run_experiment=should_run_experiment
-        )
-        if not is_successful(test_setup_result):
-            return {"functionName": params.functionName, "status": "error", "message": test_setup_result.failure()}
-        (
-            generated_tests,
-            function_to_concolic_tests,
-            concolic_test_str,
-            optimizations_set,
-            generated_test_paths,
-            generated_perf_test_paths,
-            instrumented_unittests_created_for_function,
-            original_conftest_content,
-        ) = test_setup_result.unwrap()
-
-        baseline_setup_result = function_optimizer.setup_and_establish_baseline(
-            code_context=code_context,
-            original_helper_code=original_helper_code,
-            function_to_concolic_tests=function_to_concolic_tests,
-            generated_test_paths=generated_test_paths,
-            generated_perf_test_paths=generated_perf_test_paths,
-            instrumented_unittests_created_for_function=instrumented_unittests_created_for_function,
-            original_conftest_content=original_conftest_content,
-        )
-
-        if not is_successful(baseline_setup_result):
-            return {"functionName": params.functionName, "status": "error", "message": baseline_setup_result.failure()}
-
-        (
-            function_to_optimize_qualified_name,
-            function_to_all_tests,
-            original_code_baseline,
-            test_functions_to_remove,
-            file_path_to_helper_classes,
-        ) = baseline_setup_result.unwrap()
-
-        best_optimization = function_optimizer.find_and_process_best_optimization(
-            optimizations_set=optimizations_set,
-            code_context=code_context,
-            original_code_baseline=original_code_baseline,
-            original_helper_code=original_helper_code,
-            file_path_to_helper_classes=file_path_to_helper_classes,
-            function_to_optimize_qualified_name=function_to_optimize_qualified_name,
-            function_to_all_tests=function_to_all_tests,
-            generated_tests=generated_tests,
-            test_functions_to_remove=test_functions_to_remove,
-            concolic_test_str=concolic_test_str,
-        )
-
-        if not best_optimization:
-            server.show_message_log(
-                f"No best optimizations found for function {function_to_optimize_qualified_name}", "Warning"
-            )
-            return {
-                "functionName": params.functionName,
-                "status": "error",
-                "message": f"No best optimizations found for function {function_to_optimize_qualified_name}",
-            }
-
-        # generate a patch for the optimization
-        relative_file_paths = [code_string.file_path for code_string in code_context.read_writable_code.code_strings]
-
-        speedup = original_code_baseline.runtime / best_optimization.runtime
-
-        # get the original file path in the actual project (not in the worktree)
-        original_args, _ = server.optimizer.original_args_and_test_cfg
-        relative_file_path = current_function.file_path.relative_to(server.optimizer.current_worktree)
-        original_file_path = Path(original_args.project_root / relative_file_path).resolve()
-
-        metadata = create_diff_patch_from_worktree(
-            server.optimizer.current_worktree,
-            relative_file_paths,
-            metadata_input={
-                "fto_name": function_to_optimize_qualified_name,
-                "explanation": best_optimization.explanation_v2,
-                "file_path": str(original_file_path),
-                "speedup": speedup,
-            },
-        )
-
-        server.show_message_log(f"Optimization completed for {params.functionName} with {speedup:.2f}x speedup", "Info")
-
-        return {
-            "functionName": params.functionName,
-            "status": "success",
-            "message": "Optimization completed successfully",
-            "extra": f"Speedup: {speedup:.2f}x faster",
-            "patch_file": metadata["patch_path"],
-            "patch_id": metadata["id"],
-            "explanation": best_optimization.explanation_v2,
-        }
+        result = await loop.run_in_executor(None, sync_perform_optimization, server, params)
+    except asyncio.CancelledError:
+        return {"status": "canceled", "message": "Task was canceled"}
+    else:
+        return result
     finally:
         server.cleanup_the_optimizer()

codeflash/lsp/features/perform_optimization.py

@@ -0,0 +1,152 @@
+import contextlib
+import os
+from pathlib import Path
+
+from codeflash.cli_cmds.console import code_print
+from codeflash.code_utils.git_worktree_utils import create_diff_patch_from_worktree
+from codeflash.either import is_successful
+from codeflash.lsp.server import CodeflashLanguageServer
+
+
+# ruff: noqa: PLR0911, ANN001
+def sync_perform_optimization(server: CodeflashLanguageServer, params) -> dict[str, str]:
+    server.show_message_log(f"Starting optimization for function: {params.functionName}", "Info")
+    current_function = server.optimizer.current_function_being_optimized
+
+    if not current_function:
+        server.show_message_log(f"No current function being optimized for {params.functionName}", "Error")
+        return {
+            "functionName": params.functionName,
+            "status": "error",
+            "message": "No function currently being optimized",
+        }
+
+    module_prep_result = server.optimizer.prepare_module_for_optimization(current_function.file_path)
+    if not module_prep_result:
+        return {
+            "functionName": params.functionName,
+            "status": "error",
+            "message": "Failed to prepare module for optimization",
+        }
+
+    validated_original_code, original_module_ast = module_prep_result
+
+    function_optimizer = server.optimizer.create_function_optimizer(
+        current_function,
+        function_to_optimize_source_code=validated_original_code[current_function.file_path].source_code,
+        original_module_ast=original_module_ast,
+        original_module_path=current_function.file_path,
+        function_to_tests={},
+    )
+
+    server.optimizer.current_function_optimizer = function_optimizer
+    if not function_optimizer:
+        return {"functionName": params.functionName, "status": "error", "message": "No function optimizer found"}
+
+    initialization_result = function_optimizer.can_be_optimized()
+    if not is_successful(initialization_result):
+        return {"functionName": params.functionName, "status": "error", "message": initialization_result.failure()}
+
+    should_run_experiment, code_context, original_helper_code = initialization_result.unwrap()
+
+    code_print(
+        code_context.read_writable_code.flat,
+        file_name=current_function.file_path,
+        function_name=current_function.function_name,
+    )
+
+    optimizable_funcs = {current_function.file_path: [current_function]}
+
+    devnull_writer = open(os.devnull, "w")  # noqa
+    with contextlib.redirect_stdout(devnull_writer):
+        function_to_tests, _num_discovered_tests = server.optimizer.discover_tests(optimizable_funcs)
+        function_optimizer.function_to_tests = function_to_tests
+
+    test_setup_result = function_optimizer.generate_and_instrument_tests(
+        code_context, should_run_experiment=should_run_experiment
+    )
+    if not is_successful(test_setup_result):
+        return {"functionName": params.functionName, "status": "error", "message": test_setup_result.failure()}
+    (
+        generated_tests,
+        function_to_concolic_tests,
+        concolic_test_str,
+        optimizations_set,
+        generated_test_paths,
+        generated_perf_test_paths,
+        instrumented_unittests_created_for_function,
+        original_conftest_content,
+    ) = test_setup_result.unwrap()
+
+    baseline_setup_result = function_optimizer.setup_and_establish_baseline(
+        code_context=code_context,
+        original_helper_code=original_helper_code,
+        function_to_concolic_tests=function_to_concolic_tests,
+        generated_test_paths=generated_test_paths,
+        generated_perf_test_paths=generated_perf_test_paths,
+        instrumented_unittests_created_for_function=instrumented_unittests_created_for_function,
+        original_conftest_content=original_conftest_content,
+    )
+
+    if not is_successful(baseline_setup_result):
+        return {"functionName": params.functionName, "status": "error", "message": baseline_setup_result.failure()}
+
+    (
+        function_to_optimize_qualified_name,
+        function_to_all_tests,
+        original_code_baseline,
+        test_functions_to_remove,
+        file_path_to_helper_classes,
+    ) = baseline_setup_result.unwrap()
+
+    best_optimization = function_optimizer.find_and_process_best_optimization(
+        optimizations_set=optimizations_set,
+        code_context=code_context,
+        original_code_baseline=original_code_baseline,
+        original_helper_code=original_helper_code,
+        file_path_to_helper_classes=file_path_to_helper_classes,
+        function_to_optimize_qualified_name=function_to_optimize_qualified_name,
+        function_to_all_tests=function_to_all_tests,
+        generated_tests=generated_tests,
+        test_functions_to_remove=test_functions_to_remove,
+        concolic_test_str=concolic_test_str,
+    )
+
+    if not best_optimization:
+        server.show_message_log(
+            f"No best optimizations found for function {function_to_optimize_qualified_name}", "Warning"
+        )
+        return {
+            "functionName": params.functionName,
+            "status": "error",
+            "message": f"No best optimizations found for function {function_to_optimize_qualified_name}",
+        }
+    # generate a patch for the optimization
+    relative_file_paths = [code_string.file_path for code_string in code_context.read_writable_code.code_strings]
+    speedup = original_code_baseline.runtime / best_optimization.runtime
+    # get the original file path in the actual project (not in the worktree)
+    original_args, _ = server.optimizer.original_args_and_test_cfg
+    relative_file_path = current_function.file_path.relative_to(server.optimizer.current_worktree)
+    original_file_path = Path(original_args.project_root / relative_file_path).resolve()
+
+    metadata = create_diff_patch_from_worktree(
+        server.optimizer.current_worktree,
+        relative_file_paths,
+        metadata_input={
+            "fto_name": function_to_optimize_qualified_name,
+            "explanation": best_optimization.explanation_v2,
+            "file_path": str(original_file_path),
+            "speedup": speedup,
+        },
+    )
+
+    server.show_message_log(f"Optimization completed for {params.functionName} with {speedup:.2f}x speedup", "Info")
+    return {
+        "functionName": params.functionName,
+        "status": "success",
+        "message": "Optimization completed successfully",
+        "extra": f"Speedup: {speedup:.2f}x faster",
+        "patch_file": metadata["patch_path"],
+        "patch_id": metadata["id"],
+        "explanation": best_optimization.explanation_v2,
+    }