From b18690222d41ce2da92d2f2cc21520be4fc5833d Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Thu, 14 Aug 2025 22:02:07 +0000 Subject: [PATCH 01/28] add an empty .env --- .env | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 .env diff --git a/.env b/.env new file mode 100644 index 0000000..cf58a01 --- /dev/null +++ b/.env @@ -0,0 +1,3 @@ +OPENAI_API_KEY= +ANTHROPIC_API_KEY= +GEMINI_API_KEY= \ No newline at end of file From 11ef4cab000d6c6ff766b2254c86da888b75c27d Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 15 Aug 2025 00:22:49 +0000 Subject: [PATCH 02/28] refactor OpenAI util class --- pyproject.toml | 4 +- src/main.py | 39 ++++++++-------- src/tfbench/__init__.py | 5 +- src/tfbench/common.py | 28 ------------ src/tfbench/env.py | 6 +++ src/tfbench/experiment.py | 63 +------------------------- src/tfbench/lm/__init__.py | 22 +++++++++ src/tfbench/lm/_openai.py | 93 ++++++++++++++++++++++++++++++++++++++ src/tfbench/lm/_types.py | 44 ++++++++++++++++++ src/tfbench/lm/prompts.py | 27 +++++++++++ src/tfbench/lm/settings.py | 2 + src/tfbench/lm/utils.py | 26 +++++++++++ uv.lock | 32 +++++++++++-- 13 files changed, 271 insertions(+), 120 deletions(-) create mode 100644 src/tfbench/env.py create mode 100644 src/tfbench/lm/__init__.py create mode 100644 src/tfbench/lm/_openai.py create mode 100644 src/tfbench/lm/_types.py create mode 100644 src/tfbench/lm/prompts.py create mode 100644 src/tfbench/lm/settings.py create mode 100644 src/tfbench/lm/utils.py diff --git a/pyproject.toml b/pyproject.toml index b6e546d..bb2b55d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,6 +7,7 @@ requires-python = ">=3.11" dependencies = [ "anthropic>=0.49.0", "dacite>=1.8.1", + "dotenv>=0.9.9", "fire==0.5.0", "funcy==2.0", "funcy-chain==0.2.0", @@ -17,7 +18,7 @@ dependencies = [ "matplotlib>=3.8.3", "numpy>=1.26.4", "ollama>=0.2.1", - "openai==1.75.0", + "openai>=1.99.9", "pathos>=0.3.3", "pylint>=3.3.6", "pytest>=8.0.0", @@ -26,6 +27,7 @@ dependencies = [ "returns[compatible-mypy]==0.22.0", "seaborn==0.13.2", "tabulate>=0.9.0", + "tenacity>=9.1.2", "tiktoken==0.7.0", "tqdm>=4.66.2", "tree-sitter==0.22.3", diff --git a/src/main.py b/src/main.py index 9cfa7d2..f015abd 100755 --- a/src/main.py +++ b/src/main.py @@ -18,9 +18,8 @@ get_prompt, ) +from tfbench.lm._openai import OAI_MODELS, OAI_TTC_MODELS from tfbench.experiment import ( - OAI_MODELS, - OAI_TTC_MODELS, CLAUDE_MODELS, CLAUDE_TTC_MODELS, DEEPSEEK_MODELS, @@ -28,8 +27,6 @@ GEMINI_TTC_MODELS, get_ant_model, get_ant_ttc_model, - get_oai_model, - get_oai_ttc_model, get_gemini_model, get_gemini_ttc_model, ) @@ -87,16 +84,16 @@ def main( client: OpenAI | Anthropic | OllamaClient | genai.Client generate: Callable[[str], str | None] - if model in OAI_MODELS: - assert "OPENAI_API_KEY" in os.environ, "Please set OPEN_API_KEY in environment!" - client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) - generate = get_oai_model(client, model, pure) + # if model in OAI_MODELS: + # assert "OPENAI_API_KEY" in os.environ, "Please set OPEN_API_KEY in environment!" + # client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) + # generate = get_oai_model(client, model, pure) - elif model in OAI_TTC_MODELS: - assert "OPENAI_API_KEY" in os.environ, "Please set OPEN_API_KEY in environment!" - client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) - generate = get_oai_ttc_model(client, model, pure) - elif model in CLAUDE_MODELS: + # elif model in OAI_TTC_MODELS: + # assert "OPENAI_API_KEY" in os.environ, "Please set OPEN_API_KEY in environment!" + # client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) + # generate = get_oai_ttc_model(client, model, pure) + if model in CLAUDE_MODELS: assert ( "ANTHROPIC_API_KEY" in os.environ ), "Please set ANTHROPIC_API_KEY in environment!" @@ -106,14 +103,14 @@ def main( client = Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]) generate = get_ant_ttc_model(client, model, pure, thinking_budget) - elif model in DEEPSEEK_MODELS: - assert ( - "DEEPSEEK_API_KEY" in os.environ - ), "Please set DEEPSEEK_API_KEY in environment!" - client = OpenAI( - api_key=os.environ["DEEPSEEK_API_KEY"], base_url="https://api.deepseek.com" - ) - generate = get_oai_model(client, model, pure) + # elif model in DEEPSEEK_MODELS: + # assert ( + # "DEEPSEEK_API_KEY" in os.environ + # ), "Please set DEEPSEEK_API_KEY in environment!" + # client = OpenAI( + # api_key=os.environ["DEEPSEEK_API_KEY"], base_url="https://api.deepseek.com" + # ) + # generate = get_oai_model(client, model, pure) elif model in GEMINI_MODELS: assert ( diff --git a/src/tfbench/__init__.py b/src/tfbench/__init__.py index 55aa49a..0b53434 100644 --- a/src/tfbench/__init__.py +++ b/src/tfbench/__init__.py @@ -1,4 +1 @@ -import logging - -logging.getLogger("openai").setLevel(logging.ERROR) -logging.getLogger("httpx").setLevel(logging.ERROR) +from . import env diff --git a/src/tfbench/common.py b/src/tfbench/common.py index 44dc987..1df74d0 100644 --- a/src/tfbench/common.py +++ b/src/tfbench/common.py @@ -7,28 +7,6 @@ from funcy import lmap import markdown_to_json -# Default hyper-parameters -MAX_TOKENS = 1024 - -SYSTEM_PROMPT = """ -Act as a static analysis tool for type inference. -ONLY output the type signature. -Do Not Provide any additional commentaries or explanations.""" - -INSTRUCT_PROMPT = """ -Remember that in Haskell: -1. The list type `[a]` is a polymorphic type, defined as `data [] a = [] | (:) a [a]`, -so `(:)` is a constructor for list type. -2. The String type is a list of characters, defined as `type String = [Char]`.""" - -CORE_PROMPT = """ -For polymorphic types variables, you can use type variables like `a`, `b`, `c`, etc. -You should start with `a` and increment the alphabet as needed.""" - -PURE_PROMPT = """ -For polymorphic types variables, you can use type variables like `t1`, `t2`, `t3`, etc. -You should start with `t1` and increment the number as needed.""" - @dataclass class BenchmarkTask: @@ -71,12 +49,6 @@ def remove_comments(code: str) -> str: return code -def get_sys_prompt(pure: bool) -> str: - """helper function to get system prompt for pure version of TF-Bench""" - sys_prompt = SYSTEM_PROMPT + INSTRUCT_PROMPT - sys_prompt += PURE_PROMPT if pure else CORE_PROMPT - return sys_prompt - def remove_return_type(sig: str) -> str: """ diff --git a/src/tfbench/env.py b/src/tfbench/env.py new file mode 100644 index 0000000..6e741e1 --- /dev/null +++ b/src/tfbench/env.py @@ -0,0 +1,6 @@ +from dotenv import load_dotenv, dotenv_values + +ENV = dotenv_values(".env") + +assert ENV, "No .env file found! Please create one with the required variables." +print(ENV) diff --git a/src/tfbench/experiment.py b/src/tfbench/experiment.py index 775f5b0..9be0fd4 100644 --- a/src/tfbench/experiment.py +++ b/src/tfbench/experiment.py @@ -5,28 +5,12 @@ from typing import Callable import logging -from openai import OpenAI from anthropic import Anthropic, InternalServerError from google import genai from google.genai.types import GenerateContentConfig, ThinkingConfig -from tfbench.common import get_sys_prompt, MAX_TOKENS +from .lm import get_sys_prompt, MAX_TOKENS -OAI_MODELS = [ - "gpt-3.5-turbo-0125", - "gpt-4-turbo-2024-04-09", - "gpt-4o-2024-11-20", - "gpt-4o-mini-2024-07-18", -] - -OAI_TTC_MODELS = [ - "o1-mini-2024-09-12", - "o1-preview-2024-09-12", - "o1-2024-12-17", - "o3-mini-2025-01-31", - "o3-2025-04-16", - "o4-mini-2025-04-16", -] CLAUDE_MODELS = [ "claude-3-opus-20240229", @@ -60,51 +44,6 @@ ] -def get_oai_ttc_model( - client: OpenAI, - model: str = "o1-preview-2024-09-12", - pure: bool = False, -) -> Callable[[str], str | None]: - """OpenAI Reasoning Models""" - - def generate_type_signature(prompt: str) -> str | None: - completion = client.chat.completions.create( - messages=[ - {"role": "user", "content": get_sys_prompt(pure) + "\n\n" + prompt}, - ], - model=model, - ) - - content = completion.choices[0].message.content - return content if isinstance(content, str) else None - - return generate_type_signature - - -def get_oai_model( - client: OpenAI, - model: str = "gpt-3.5-turbo", - pure: bool = False, -) -> Callable[[str], str | None]: - """Regular OpenAI Models""" - - def generate_type_signature(prompt: str) -> str | None: - completion = client.chat.completions.create( - messages=[ - { - "role": "system", - "content": get_sys_prompt(pure), - }, - {"role": "user", "content": prompt}, - ], - model=model, - ) - - content = completion.choices[0].message.content - return content if isinstance(content, str) else None - - return generate_type_signature - def get_ant_ttc_model( client: Anthropic, diff --git a/src/tfbench/lm/__init__.py b/src/tfbench/lm/__init__.py new file mode 100644 index 0000000..ec3e09c --- /dev/null +++ b/src/tfbench/lm/__init__.py @@ -0,0 +1,22 @@ +import logging + +from .prompts import get_sys_prompt +from .settings import MAX_TOKENS +from ._openai import OpenAIChatCompletion, OpenAIResponses +from ._types import LMResponse, LM, ReasoningEffort +from .utils import router, is_model_supported + +logging.getLogger("openai").setLevel(logging.ERROR) +logging.getLogger("httpx").setLevel(logging.ERROR) + +__all__ = [ + "get_sys_prompt", + "MAX_TOKENS", + "LMResponse", + "LM", + "ReasoningEffort", + "OpenAIChatCompletion", + "OpenAIResponses", + "router", + "is_model_supported", +] diff --git a/src/tfbench/lm/_openai.py b/src/tfbench/lm/_openai.py new file mode 100644 index 0000000..aef40bc --- /dev/null +++ b/src/tfbench/lm/_openai.py @@ -0,0 +1,93 @@ +from openai import OpenAI, NOT_GIVEN + +from ..env import ENV +from .prompts import get_sys_prompt +from ._types import LMResponse, LM, ReasoningEffort + +OAI_MODELS = [ + "gpt-3.5-turbo-0125", + "gpt-4-turbo-2024-04-09", + "gpt-4o-2024-11-20", + "gpt-4o-mini-2024-07-18", +] + +OAI_TTC_MODELS = [ + "o1-mini-2024-09-12", + "o1-preview-2024-09-12", + "o1-2024-12-17", + "o3-mini-2025-01-31", + "o3-2025-04-16", + "o4-mini-2025-04-16", +] + +OAI_O5 = [ + "gpt-5-2025-08-07", + "gpt-5-mini-2025-08-07", + "gpt-5-nano-2025-08-07", + "gpt-5-chat-latest", +] + + +class OpenAIChatCompletion(LM): + """ + Generate using OpenAI SDK's Chat Completions API. + This is the previous standard (supported indefinitely). + This client should be only used for legacy non-reasoning models, + i.e., (gpt-3.5-turbo, gpt-4-turbo, gpt-4o). + """ + + def __init__(self, model_name: str, pure: bool = False): + super().__init__(model_name=model_name, pure=pure) + + api_key = ENV.get("OPENAI_API_KEY") + assert api_key, "Please set OPENAI_API_KEY in environment!" + self.client = OpenAI(api_key=api_key) + + def _gen(self, prompt: str) -> LMResponse: + """Generate using OpenAI SDK's Chat Completions API.""" + completion = self.client.chat.completions.create( + messages=[ + { + "role": "developer", + "content": self.instruction, + }, + {"role": "user", "content": prompt}, + ], + model=self.model_name, + ) + + return completion.choices[0].message.content + + +class OpenAIResponses(LM): + """Client for New OpenAI Responses API. + This should be used for newer *reasoning* models, + especially GPT-5. + """ + + def __init__( + self, model_name: str, pure: bool = False, effort: ReasoningEffort | None = None + ): + super().__init__(model_name=model_name, pure=pure) + + api_key = ENV.get("OPENAI_API_KEY") + assert api_key, "Please set OPENAI_API_KEY in environment!" + self.client = OpenAI(api_key=api_key) + + self.effort = effort + + def _gen(self, prompt: str) -> LMResponse: + """Generate using OpenAI SDK's Responses API.""" + response = self.client.responses.create( + model=self.model_name, + instructions=self.instruction, + input=prompt, + reasoning=( + { + "effort": self.effort.value, + } + if self.effort + else NOT_GIVEN + ), + ) + return response.output_text diff --git a/src/tfbench/lm/_types.py b/src/tfbench/lm/_types.py new file mode 100644 index 0000000..63906fa --- /dev/null +++ b/src/tfbench/lm/_types.py @@ -0,0 +1,44 @@ +from abc import ABC, abstractmethod +from enum import StrEnum + +from returns.result import safe +from tenacity import ( + retry, + stop_after_attempt, + wait_random_exponential, +) # for exponential backoff + +from .prompts import get_sys_prompt + +Answer = str +ReasoningSteps = str + +LMResponse = Answer | tuple[Answer, ReasoningSteps] | None + + +class ReasoningEffort(StrEnum): + """Enum for reasoning effort levels.""" + + LOW = "low" + MEDIUM = "medium" + HIGH = "high" + + +class LM(ABC): + def __init__(self, model_name: str, pure: bool = False): + self.model_name = model_name + self.pure = pure + self.instruction = get_sys_prompt(self.pure) + + @safe + @retry(wait=wait_random_exponential(min=1, max=10), stop=stop_after_attempt(3)) + def generate(self, prompt: str) -> LMResponse: + """Generate a response for the given prompt. + We use factory mode to for @safe and @retry, + see https://www.oodesign.com/factory-method-pattern + """ + return self._gen(prompt) + + @abstractmethod + def _gen(self, prompt) -> LMResponse: + """The actual generation method for different clients""" diff --git a/src/tfbench/lm/prompts.py b/src/tfbench/lm/prompts.py new file mode 100644 index 0000000..51e8b0b --- /dev/null +++ b/src/tfbench/lm/prompts.py @@ -0,0 +1,27 @@ +"""This file contains the generic default prompts for the LLMs used in the project.""" + +SYSTEM_PROMPT = """ +Act as a static analysis tool for type inference. +ONLY output the type signature. +Do Not Provide any additional commentaries or explanations.""" + +INSTRUCT_PROMPT = """ +Remember that in Haskell: +1. The list type `[a]` is a polymorphic type, defined as `data [] a = [] | (:) a [a]`, +so `(:)` is a constructor for list type. +2. The String type is a list of characters, defined as `type String = [Char]`.""" + +CORE_PROMPT = """ +For polymorphic types variables, you can use type variables like `a`, `b`, `c`, etc. +You should start with `a` and increment the alphabet as needed.""" + +PURE_PROMPT = """ +For polymorphic types variables, you can use type variables like `t1`, `t2`, `t3`, etc. +You should start with `t1` and increment the number as needed.""" + + +def get_sys_prompt(pure: bool) -> str: + """helper function to get system prompt for pure version of TF-Bench""" + sys_prompt = SYSTEM_PROMPT + INSTRUCT_PROMPT + sys_prompt += PURE_PROMPT if pure else CORE_PROMPT + return sys_prompt diff --git a/src/tfbench/lm/settings.py b/src/tfbench/lm/settings.py new file mode 100644 index 0000000..21fceac --- /dev/null +++ b/src/tfbench/lm/settings.py @@ -0,0 +1,2 @@ +# Default hyper-parameters +MAX_TOKENS = 1024 diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py new file mode 100644 index 0000000..a5b64d5 --- /dev/null +++ b/src/tfbench/lm/utils.py @@ -0,0 +1,26 @@ +from ._types import LMResponse, LM, ReasoningEffort + +from ._openai import ( + OpenAIChatCompletion, + OpenAIResponses, + OAI_MODELS, + OAI_TTC_MODELS, + OAI_O5, +) + + +def router(model_name: str, pure: bool, effort: ReasoningEffort | None) -> LM | None: + """Route the model name to the appropriate LM class.""" + if model_name in OAI_MODELS: + return OpenAIChatCompletion(model_name=model_name, pure=pure) + if model_name in OAI_TTC_MODELS: + return OpenAIResponses(model_name=model_name, pure=pure) + if model_name in OAI_O5: + return OpenAIResponses(model_name=model_name, pure=pure, effort=effort) + return None + + +def is_model_supported(model_name: str) -> bool: + """check if the model is supported""" + all_models = OAI_MODELS + OAI_TTC_MODELS + OAI_O5 + return model_name in all_models diff --git a/uv.lock b/uv.lock index 8215549..74c9d02 100644 --- a/uv.lock +++ b/uv.lock @@ -226,6 +226,17 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277 }, ] +[[package]] +name = "dotenv" +version = "0.9.9" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "python-dotenv" }, +] +wheels = [ + { url = "https://files.pythonhosted.org/packages/b2/b7/545d2c10c1fc15e48653c91efde329a790f2eecfbbf2bd16003b5db2bab0/dotenv-0.9.9-py2.py3-none-any.whl", hash = "sha256:29cf74a087b31dafdb5a446b6d7e11cbce8ed2741540e2339c69fbef92c94ce9", size = 1892 }, +] + [[package]] name = "fire" version = "0.5.0" @@ -702,7 +713,7 @@ wheels = [ [[package]] name = "openai" -version = "1.75.0" +version = "1.99.9" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "anyio" }, @@ -714,9 +725,9 @@ dependencies = [ { name = "tqdm" }, { name = "typing-extensions" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/99/b1/318f5d4c482f19c5fcbcde190801bfaaaec23413cda0b88a29f6897448ff/openai-1.75.0.tar.gz", hash = "sha256:fb3ea907efbdb1bcfd0c44507ad9c961afd7dce3147292b54505ecfd17be8fd1", size = 429492 } +sdist = { url = "https://files.pythonhosted.org/packages/8a/d2/ef89c6f3f36b13b06e271d3cc984ddd2f62508a0972c1cbcc8485a6644ff/openai-1.99.9.tar.gz", hash = "sha256:f2082d155b1ad22e83247c3de3958eb4255b20ccf4a1de2e6681b6957b554e92", size = 506992 } wheels = [ - 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{ name = "openai", specifier = "==1.75.0" }, + { name = "openai", specifier = ">=1.99.9" }, { name = "pathos", specifier = ">=0.3.3" }, { name = "pylint", specifier = ">=3.3.6" }, { name = "pytest", specifier = ">=8.0.0" }, @@ -1254,6 +1277,7 @@ requires-dist = [ { name = "returns", extras = ["compatible-mypy"], specifier = "==0.22.0" }, { name = "seaborn", specifier = "==0.13.2" }, { name = "tabulate", specifier = ">=0.9.0" }, + { name = "tenacity", specifier = ">=9.1.2" }, { name = "tiktoken", specifier = "==0.7.0" }, { name = "tqdm", specifier = ">=4.66.2" }, { name = "tree-sitter", specifier = "==0.22.3" }, From 0be71d287531aa2933a38911afa4cded01a94a36 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Thu, 14 Aug 2025 22:06:34 -0700 Subject: [PATCH 03/28] use new OpenAI client in main --- src/main.py | 71 +++++--------------------------- src/tfbench/env.py | 1 - src/tfbench/experiment_ollama.py | 2 +- src/tfbench/lm/__init__.py | 4 +- src/tfbench/lm/utils.py | 6 ++- 5 files changed, 17 insertions(+), 67 deletions(-) diff --git a/src/main.py b/src/main.py index f015abd..8e6954c 100755 --- a/src/main.py +++ b/src/main.py @@ -1,6 +1,8 @@ import os from typing import Callable import json +import logging + from funcy_chain import Chain from funcy import lmap from tqdm import tqdm @@ -33,6 +35,7 @@ from tfbench.experiment_ollama import OLLAMA_MODELS, get_ollama_model from tfbench.postprocessing import postprocess, RESPONSE_STRATEGIES from tfbench.evaluation import evaluate +from tfbench.lm import is_supported, router def main( @@ -58,17 +61,7 @@ def main( pure (bool): If True, uses the original variable naming in type inference. If False, uses rewritten variable naming (e.g., `v1`, `v2`, ...). Default is False. """ - assert ( - model - in OAI_MODELS - + OAI_TTC_MODELS - + OLLAMA_MODELS - + DEEPSEEK_MODELS - + CLAUDE_MODELS - + CLAUDE_TTC_MODELS - + GEMINI_MODELS - + GEMINI_TTC_MODELS - ), f"{model} is not supported." + assert is_supported(model), f"{model} is not supported." # hard-coding benchmark file path for experiment input_file = "tfb.pure.json" if pure else "tfb.json" @@ -79,61 +72,17 @@ def main( if output_file is None: os.makedirs("result", exist_ok=True) - output_file = f"result/{model}.txt" - - client: OpenAI | Anthropic | OllamaClient | genai.Client - generate: Callable[[str], str | None] - - # if model in OAI_MODELS: - # assert "OPENAI_API_KEY" in os.environ, "Please set OPEN_API_KEY in environment!" - # client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) - # generate = get_oai_model(client, model, pure) - - # elif model in OAI_TTC_MODELS: - # assert "OPENAI_API_KEY" in os.environ, "Please set OPEN_API_KEY in environment!" - # client = OpenAI(api_key=os.environ["OPENAI_API_KEY"]) - # generate = get_oai_ttc_model(client, model, pure) - if model in CLAUDE_MODELS: - assert ( - "ANTHROPIC_API_KEY" in os.environ - ), "Please set ANTHROPIC_API_KEY in environment!" - client = Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]) - generate = get_ant_model(client, model, pure) - elif model in CLAUDE_TTC_MODELS: - client = Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]) - generate = get_ant_ttc_model(client, model, pure, thinking_budget) - - # elif model in DEEPSEEK_MODELS: - # assert ( - # "DEEPSEEK_API_KEY" in os.environ - # ), "Please set DEEPSEEK_API_KEY in environment!" - # client = OpenAI( - # api_key=os.environ["DEEPSEEK_API_KEY"], base_url="https://api.deepseek.com" - # ) - # generate = get_oai_model(client, model, pure) - - elif model in GEMINI_MODELS: - assert ( - "GOOGLE_API_KEY" in os.environ - ), "Please set GOOGLE_API_KEY in environment!" - client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"]) - generate = get_gemini_model(client, model, pure) - elif model in GEMINI_TTC_MODELS: - assert ( - "GOOGLE_API_KEY" in os.environ - ), "Please set GOOGLE_API_KEY in environment!" - client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"]) - generate = get_gemini_ttc_model(client, model, pure, thinking_budget) - - else: - client = OllamaClient(host=f"http://localhost:{port}") - generate = get_ollama_model(client, model, pure) + output_file = os.path.abspath(f"result/{model}.txt") + logging.info(f"Writing generation results in {output_file}.") + + client = router(model, pure) + assert client, f"Failed to create client for {model}." with open(input_file, "r") as fp: tasks = [from_dict(data_class=BenchmarkTask, data=d) for d in json.load(fp)] prompts = lmap(get_prompt, tasks) - responses = lmap(generate, tqdm(prompts, desc=model)) + responses = lmap(client.generate, tqdm(prompts, desc=model)) gen_results = ( Chain(responses) .map(lambda x: x if x is not None else "") # convert None to empty string diff --git a/src/tfbench/env.py b/src/tfbench/env.py index 6e741e1..a7d9ac7 100644 --- a/src/tfbench/env.py +++ b/src/tfbench/env.py @@ -3,4 +3,3 @@ ENV = dotenv_values(".env") assert ENV, "No .env file found! Please create one with the required variables." -print(ENV) diff --git a/src/tfbench/experiment_ollama.py b/src/tfbench/experiment_ollama.py index 29a9201..bce002b 100644 --- a/src/tfbench/experiment_ollama.py +++ b/src/tfbench/experiment_ollama.py @@ -4,7 +4,7 @@ from typing import Union from ollama import Client as OllamaClient, ResponseError -from tfbench.common import get_sys_prompt +from tfbench.lm.prompts import get_sys_prompt OLLAMA_OSS = [ "phi3:3.8b", diff --git a/src/tfbench/lm/__init__.py b/src/tfbench/lm/__init__.py index ec3e09c..410fc24 100644 --- a/src/tfbench/lm/__init__.py +++ b/src/tfbench/lm/__init__.py @@ -4,7 +4,7 @@ from .settings import MAX_TOKENS from ._openai import OpenAIChatCompletion, OpenAIResponses from ._types import LMResponse, LM, ReasoningEffort -from .utils import router, is_model_supported +from .utils import router, is_supported logging.getLogger("openai").setLevel(logging.ERROR) logging.getLogger("httpx").setLevel(logging.ERROR) @@ -18,5 +18,5 @@ "OpenAIChatCompletion", "OpenAIResponses", "router", - "is_model_supported", + "is_supported", ] diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index a5b64d5..4231eb0 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -9,7 +9,9 @@ ) -def router(model_name: str, pure: bool, effort: ReasoningEffort | None) -> LM | None: +def router( + model_name: str, pure: bool, effort: ReasoningEffort | None = None +) -> LM | None: """Route the model name to the appropriate LM class.""" if model_name in OAI_MODELS: return OpenAIChatCompletion(model_name=model_name, pure=pure) @@ -20,7 +22,7 @@ def router(model_name: str, pure: bool, effort: ReasoningEffort | None) -> LM | return None -def is_model_supported(model_name: str) -> bool: +def is_supported(model_name: str) -> bool: """check if the model is supported""" all_models = OAI_MODELS + OAI_TTC_MODELS + OAI_O5 return model_name in all_models From 824692df545cc7b1857bd92ea86fe97dde4a702a Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Thu, 14 Aug 2025 22:15:37 -0700 Subject: [PATCH 04/28] assume .env unchanged --- README.md | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/README.md b/README.md index ffe59b4..499ac35 100644 --- a/README.md +++ b/README.md @@ -46,6 +46,14 @@ You can also download our pre-built benchmark from [Zenodo](https://doi.org/10.5 ## Benchmarking! +Please have your API key ready in `.env`. +Please note that the `.env` in the repository is tracked by git, +we recommend telling your git to ignore its changes by + +```sh +git update-index --assume-unchanged .env +``` + ### GPT Models To run single model: From faf9b7358d8fbcc619ec6ab1df0667e45ee0c5cd Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Thu, 14 Aug 2025 23:27:48 -0700 Subject: [PATCH 05/28] fix: response processing --- src/main.py | 29 +++++++---------------------- src/tfbench/lm/__init__.py | 7 ++++--- src/tfbench/lm/_openai.py | 13 +++++++------ src/tfbench/lm/_types.py | 12 +++++++----- src/tfbench/lm/utils.py | 16 +++++++++++++++- 5 files changed, 40 insertions(+), 37 deletions(-) diff --git a/src/main.py b/src/main.py index 8e6954c..a688319 100755 --- a/src/main.py +++ b/src/main.py @@ -7,12 +7,7 @@ from funcy import lmap from tqdm import tqdm from dacite import from_dict - - -from openai import OpenAI -from ollama import Client as OllamaClient -from anthropic import Anthropic -from google import genai +from returns.result import ResultE, Success, Failure import fire from tfbench.common import ( @@ -20,22 +15,9 @@ get_prompt, ) -from tfbench.lm._openai import OAI_MODELS, OAI_TTC_MODELS -from tfbench.experiment import ( - CLAUDE_MODELS, - CLAUDE_TTC_MODELS, - DEEPSEEK_MODELS, - GEMINI_MODELS, - GEMINI_TTC_MODELS, - get_ant_model, - get_ant_ttc_model, - get_gemini_model, - get_gemini_ttc_model, -) -from tfbench.experiment_ollama import OLLAMA_MODELS, get_ollama_model from tfbench.postprocessing import postprocess, RESPONSE_STRATEGIES from tfbench.evaluation import evaluate -from tfbench.lm import is_supported, router +from tfbench.lm import is_supported, router, LMAnswer, extract_response def main( @@ -82,10 +64,13 @@ def main( tasks = [from_dict(data_class=BenchmarkTask, data=d) for d in json.load(fp)] prompts = lmap(get_prompt, tasks) - responses = lmap(client.generate, tqdm(prompts, desc=model)) + responses: list[ResultE[LMAnswer]] = lmap( + client.generate, tqdm(prompts, desc=model) + ) + gen_results = ( Chain(responses) - .map(lambda x: x if x is not None else "") # convert None to empty string + .map(extract_response) .map(lambda s: postprocess(s, RESPONSE_STRATEGIES)) .map(str.strip) .value diff --git a/src/tfbench/lm/__init__.py b/src/tfbench/lm/__init__.py index 410fc24..3580521 100644 --- a/src/tfbench/lm/__init__.py +++ b/src/tfbench/lm/__init__.py @@ -3,8 +3,8 @@ from .prompts import get_sys_prompt from .settings import MAX_TOKENS from ._openai import OpenAIChatCompletion, OpenAIResponses -from ._types import LMResponse, LM, ReasoningEffort -from .utils import router, is_supported +from ._types import LM, ReasoningEffort, LMAnswer +from .utils import router, is_supported, extract_response logging.getLogger("openai").setLevel(logging.ERROR) logging.getLogger("httpx").setLevel(logging.ERROR) @@ -12,11 +12,12 @@ __all__ = [ "get_sys_prompt", "MAX_TOKENS", - "LMResponse", + "LMAnswer", "LM", "ReasoningEffort", "OpenAIChatCompletion", "OpenAIResponses", "router", "is_supported", + "extract_response", ] diff --git a/src/tfbench/lm/_openai.py b/src/tfbench/lm/_openai.py index aef40bc..36b138e 100644 --- a/src/tfbench/lm/_openai.py +++ b/src/tfbench/lm/_openai.py @@ -1,8 +1,7 @@ from openai import OpenAI, NOT_GIVEN from ..env import ENV -from .prompts import get_sys_prompt -from ._types import LMResponse, LM, ReasoningEffort +from ._types import LM, ReasoningEffort, LMAnswer OAI_MODELS = [ "gpt-3.5-turbo-0125", @@ -43,7 +42,7 @@ def __init__(self, model_name: str, pure: bool = False): assert api_key, "Please set OPENAI_API_KEY in environment!" self.client = OpenAI(api_key=api_key) - def _gen(self, prompt: str) -> LMResponse: + def _gen(self, prompt: str) -> LMAnswer: """Generate using OpenAI SDK's Chat Completions API.""" completion = self.client.chat.completions.create( messages=[ @@ -56,7 +55,9 @@ def _gen(self, prompt: str) -> LMResponse: model=self.model_name, ) - return completion.choices[0].message.content + return LMAnswer( + answer=completion.choices[0].message.content, + ) class OpenAIResponses(LM): @@ -76,7 +77,7 @@ def __init__( self.effort = effort - def _gen(self, prompt: str) -> LMResponse: + def _gen(self, prompt: str) -> LMAnswer: """Generate using OpenAI SDK's Responses API.""" response = self.client.responses.create( model=self.model_name, @@ -90,4 +91,4 @@ def _gen(self, prompt: str) -> LMResponse: else NOT_GIVEN ), ) - return response.output_text + return LMAnswer(answer=response.output_text) diff --git a/src/tfbench/lm/_types.py b/src/tfbench/lm/_types.py index 63906fa..f25d461 100644 --- a/src/tfbench/lm/_types.py +++ b/src/tfbench/lm/_types.py @@ -1,5 +1,6 @@ from abc import ABC, abstractmethod from enum import StrEnum +from dataclasses import dataclass from returns.result import safe from tenacity import ( @@ -10,10 +11,11 @@ from .prompts import get_sys_prompt -Answer = str -ReasoningSteps = str -LMResponse = Answer | tuple[Answer, ReasoningSteps] | None +@dataclass +class LMAnswer: + answer: str | None + reasoning_steps: str | None = None class ReasoningEffort(StrEnum): @@ -32,7 +34,7 @@ def __init__(self, model_name: str, pure: bool = False): @safe @retry(wait=wait_random_exponential(min=1, max=10), stop=stop_after_attempt(3)) - def generate(self, prompt: str) -> LMResponse: + def generate(self, prompt: str) -> LMAnswer: """Generate a response for the given prompt. We use factory mode to for @safe and @retry, see https://www.oodesign.com/factory-method-pattern @@ -40,5 +42,5 @@ def generate(self, prompt: str) -> LMResponse: return self._gen(prompt) @abstractmethod - def _gen(self, prompt) -> LMResponse: + def _gen(self, prompt) -> LMAnswer: """The actual generation method for different clients""" diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index 4231eb0..4c08635 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -1,5 +1,8 @@ -from ._types import LMResponse, LM, ReasoningEffort +import logging +from returns.result import ResultE, Success, Failure, Result + +from ._types import LM, ReasoningEffort, LMAnswer from ._openai import ( OpenAIChatCompletion, OpenAIResponses, @@ -26,3 +29,14 @@ def is_supported(model_name: str) -> bool: """check if the model is supported""" all_models = OAI_MODELS + OAI_TTC_MODELS + OAI_O5 return model_name in all_models + + +def extract_response(response: ResultE[LMAnswer]) -> str: + """Extract the answer from the LMAnswer or return an empty string if None.""" + match response: + case Success(r): + return r.answer or "" + case Failure(e): + logging.error(f"Error generating response: {e}") + return "" + return "" From b9286f2dd8819ac4a8e05f52ed499ec5b48aaf23 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 15 Aug 2025 15:46:25 -0700 Subject: [PATCH 06/28] use new Gemini client in main --- pyproject.toml | 1 + src/tfbench/experiment.py | 60 --------------------- src/tfbench/lm/__init__.py | 6 ++- src/tfbench/lm/_google.py | 108 +++++++++++++++++++++++++++++++++++++ src/tfbench/lm/_openai.py | 19 +++++-- src/tfbench/lm/_types.py | 9 +--- src/tfbench/lm/utils.py | 40 ++++++++++++-- uv.lock | 73 +++++++++++++++++++++++++ 8 files changed, 237 insertions(+), 79 deletions(-) create mode 100644 src/tfbench/lm/_google.py diff --git a/pyproject.toml b/pyproject.toml index bb2b55d..77173c9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,6 +7,7 @@ requires-python = ">=3.11" dependencies = [ "anthropic>=0.49.0", "dacite>=1.8.1", + "deprecated>=1.2.18", "dotenv>=0.9.9", "fire==0.5.0", "funcy==2.0", diff --git a/src/tfbench/experiment.py b/src/tfbench/experiment.py index 9be0fd4..c944ccb 100644 --- a/src/tfbench/experiment.py +++ b/src/tfbench/experiment.py @@ -6,8 +6,6 @@ import logging from anthropic import Anthropic, InternalServerError -from google import genai -from google.genai.types import GenerateContentConfig, ThinkingConfig from .lm import get_sys_prompt, MAX_TOKENS @@ -30,20 +28,6 @@ "deepseek-chat", ] -GEMINI_MODELS = [ - "gemini-2.0-flash", - "gemini-2.0-flash-lite", - "gemini-1.5-flash", - "gemini-1.5-flash-8b", - "gemini-1.5-pro", -] - -GEMINI_TTC_MODELS = [ - "gemini-2.5-flash-preview-04-17", - "gemini-2.5-pro-preview-03-25", -] - - def get_ant_ttc_model( client: Anthropic, @@ -109,47 +93,3 @@ def generate_type_signature(prompt: str) -> str | None: return generate_type_signature - -def get_gemini_model( - client: genai.Client, - model: str = "gemini-2.0-flash-lite", - pure: bool = False, -) -> Callable[[str], str | None]: - """Gemini Models""" - - def generate_type_signature(prompt: str) -> str | None: - response = client.models.generate_content( - model=model, - contents=[prompt], - config=GenerateContentConfig( - system_instruction=[get_sys_prompt(pure)], - ), - ) - return response.text if isinstance(response.text, str) else None - - return generate_type_signature - - -def get_gemini_ttc_model( - client: genai.Client, - model: str = "gemini-2.5-flash-preview-04-17", - pure: bool = False, - thinking_budget: int = 1024, -) -> Callable[[str], str | None]: - """Gemini Reasoning Models""" - - def generate_type_signature(prompt: str) -> str | None: - response = client.models.generate_content( - model=model, - contents=[prompt], - config=GenerateContentConfig( - system_instruction=[get_sys_prompt(pure)], - thinking_config=ThinkingConfig( - thinking_budget=thinking_budget, - include_thoughts=False, - ), - ), - ) - return response.text if isinstance(response.text, str) else None - - return generate_type_signature diff --git a/src/tfbench/lm/__init__.py b/src/tfbench/lm/__init__.py index 3580521..233f854 100644 --- a/src/tfbench/lm/__init__.py +++ b/src/tfbench/lm/__init__.py @@ -3,7 +3,8 @@ from .prompts import get_sys_prompt from .settings import MAX_TOKENS from ._openai import OpenAIChatCompletion, OpenAIResponses -from ._types import LM, ReasoningEffort, LMAnswer +from ._google import GeminiChat, GeminiReasoning +from ._types import LM, LMAnswer from .utils import router, is_supported, extract_response logging.getLogger("openai").setLevel(logging.ERROR) @@ -14,9 +15,10 @@ "MAX_TOKENS", "LMAnswer", "LM", - "ReasoningEffort", "OpenAIChatCompletion", "OpenAIResponses", + "GeminiChat", + "GeminiReasoning", "router", "is_supported", "extract_response", diff --git a/src/tfbench/lm/_google.py b/src/tfbench/lm/_google.py new file mode 100644 index 0000000..f388a41 --- /dev/null +++ b/src/tfbench/lm/_google.py @@ -0,0 +1,108 @@ +"""Inference helper for Google Gemini""" + +from typing import Literal +from enum import Enum + +from google import genai +from google.genai.types import GenerateContentConfig, ThinkingConfig + +from ..env import ENV +from ._types import LM, LMAnswer + +GEMINI_MODELS = [ + "gemini-2.0-flash", + "gemini-2.0-flash-lite", + # ! gemini-1.5 models are deprecated + # "gemini-1.5-flash", + # "gemini-1.5-flash-8b", + # "gemini-1.5-pro", +] + +GEMINI_TTC_MODELS = [ + "gemini-2.5-flash-preview-04-17", + "gemini-2.5-pro-preview-03-25", +] + + +class GeminiChat(LM): + """Wrapper class for `google-genai` SDK for chat models""" + + def __init__(self, model_name: str, pure: bool = False): + super().__init__(model_name=model_name, pure=pure) + + api_key = ENV.get("GEMINI_API_KEY") + assert api_key, "Please set GEMINI_API_KEY in environment!" + self.client = genai.Client(api_key=api_key) + + def _gen(self, prompt: str) -> LMAnswer: + + response = self.client.models.generate_content( + model=self.model_name, + contents=[prompt], + config=GenerateContentConfig( + system_instruction=[self.instruction], + ), + ) + return LMAnswer(answer=response.text) + + +GeminiReasoningEffort = Literal["low", "medium", "high", "dynamic", "off"] + +EFFORT_TOKEN_MAP: dict[GeminiReasoningEffort, int] = { + "low": 512, + "medium": 1024, + "high": 2048, + "dynamic": -1, + "off": 0, +} + + +class GeminiReasoning(LM): + """Wrapper class for `google-genai` SDK for reasoning models""" + + def __init__( + self, + model_name: str, + pure: bool = False, + effort: GeminiReasoningEffort = "dynamic", + ): + super().__init__(model_name=model_name, pure=pure) + + api_key = ENV.get("GEMINI_API_KEY") + assert api_key, "Please set GEMINI_API_KEY in environment!" + self.client = genai.Client(api_key=api_key) + + self.effort: GeminiReasoningEffort = effort + + def _gen(self, prompt: str) -> LMAnswer: + + response = self.client.models.generate_content( + model=self.model_name, + contents=[prompt], + config=GenerateContentConfig( + system_instruction=[self.instruction], + thinking_config=ThinkingConfig( + thinking_budget=EFFORT_TOKEN_MAP[self.effort], + include_thoughts=True, + ), + ), + ) + + if not response.candidates: + raise ValueError("No candidates returned from Gemini model.") + + candidate = response.candidates[0] + if not candidate.content or not candidate.content.parts: + raise ValueError("No content in the candidate response.") + + answer = "" + thinking = "" + for part in candidate.content.parts: + if not part.text: + continue + if part.thought: + thinking += part.text + else: + answer += part.text + + return LMAnswer(answer=answer, reasoning_steps=thinking) diff --git a/src/tfbench/lm/_openai.py b/src/tfbench/lm/_openai.py index 36b138e..1372f47 100644 --- a/src/tfbench/lm/_openai.py +++ b/src/tfbench/lm/_openai.py @@ -1,7 +1,11 @@ +from typing import get_args + from openai import OpenAI, NOT_GIVEN +from openai.types.shared_params.reasoning import Reasoning +from openai.types.shared.reasoning_effort import ReasoningEffort from ..env import ENV -from ._types import LM, ReasoningEffort, LMAnswer +from ._types import LM, LMAnswer OAI_MODELS = [ "gpt-3.5-turbo-0125", @@ -67,25 +71,32 @@ class OpenAIResponses(LM): """ def __init__( - self, model_name: str, pure: bool = False, effort: ReasoningEffort | None = None + self, + model_name: str, + pure: bool = False, + effort: ReasoningEffort = None, ): + """OpenAI Responses SDK Client + If `effort` is None (not provided), we disable reasoning mode. + """ super().__init__(model_name=model_name, pure=pure) api_key = ENV.get("OPENAI_API_KEY") assert api_key, "Please set OPENAI_API_KEY in environment!" self.client = OpenAI(api_key=api_key) - self.effort = effort + self.effort: ReasoningEffort = effort def _gen(self, prompt: str) -> LMAnswer: """Generate using OpenAI SDK's Responses API.""" + response = self.client.responses.create( model=self.model_name, instructions=self.instruction, input=prompt, reasoning=( { - "effort": self.effort.value, + "effort": self.effort, } if self.effort else NOT_GIVEN diff --git a/src/tfbench/lm/_types.py b/src/tfbench/lm/_types.py index f25d461..89636a7 100644 --- a/src/tfbench/lm/_types.py +++ b/src/tfbench/lm/_types.py @@ -1,6 +1,7 @@ from abc import ABC, abstractmethod from enum import StrEnum from dataclasses import dataclass +from typing import Literal from returns.result import safe from tenacity import ( @@ -18,14 +19,6 @@ class LMAnswer: reasoning_steps: str | None = None -class ReasoningEffort(StrEnum): - """Enum for reasoning effort levels.""" - - LOW = "low" - MEDIUM = "medium" - HIGH = "high" - - class LM(ABC): def __init__(self, model_name: str, pure: bool = False): self.model_name = model_name diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index 4c08635..49a91df 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -1,8 +1,9 @@ import logging +from typing import Literal, get_args, cast, TypeAlias from returns.result import ResultE, Success, Failure, Result -from ._types import LM, ReasoningEffort, LMAnswer +from ._types import LM, LMAnswer from ._openai import ( OpenAIChatCompletion, OpenAIResponses, @@ -10,18 +11,47 @@ OAI_TTC_MODELS, OAI_O5, ) +from ._google import GeminiChat, GeminiReasoning, GEMINI_MODELS, GEMINI_TTC_MODELS +from openai.types.shared.reasoning_effort import ReasoningEffort as OAIReasoningEffort +from ._google import GeminiReasoningEffort -def router( - model_name: str, pure: bool, effort: ReasoningEffort | None = None -) -> LM | None: + +def _assert_valid_effort(model: str, effort: str | None, effort_cls): + """Check if the given effort is valid for the model.""" + assert effort in get_args( + effort_cls + ), f"`{effort}` is not a valid reasoning effort for {model}." + + +def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: """Route the model name to the appropriate LM class.""" if model_name in OAI_MODELS: return OpenAIChatCompletion(model_name=model_name, pure=pure) + if model_name in OAI_TTC_MODELS: return OpenAIResponses(model_name=model_name, pure=pure) + if model_name in OAI_O5: - return OpenAIResponses(model_name=model_name, pure=pure, effort=effort) + _assert_valid_effort(model_name, effort, OAIReasoningEffort) + # cast is safe here after assertion + return OpenAIResponses( + model_name=model_name, + pure=pure, + effort=cast(OAIReasoningEffort, effort), + ) + + if model_name in GEMINI_MODELS: + return GeminiChat(model_name=model_name, pure=pure) + + if model_name in GEMINI_TTC_MODELS: + _assert_valid_effort(model_name, effort, GeminiReasoningEffort) + return GeminiReasoning( + model_name=model_name, + pure=pure, + effort=cast(GeminiReasoningEffort, effort), + ) + return None diff --git a/uv.lock b/uv.lock index 74c9d02..3801905 100644 --- a/uv.lock +++ b/uv.lock @@ -208,6 +208,18 @@ wheels = [ { url = 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a688319..f22e82f 100755 --- a/src/main.py +++ b/src/main.py @@ -24,7 +24,7 @@ def main( model: str, port: int = 11434, pure: bool = False, - thinking_budget: int = 1024, + effort: str | None = None, output_file: str | None = None, log_file: str = "evaluation_log.jsonl", ): @@ -57,7 +57,7 @@ def main( output_file = os.path.abspath(f"result/{model}.txt") logging.info(f"Writing generation results in {output_file}.") - client = router(model, pure) + client = router(model, pure, effort) assert client, f"Failed to create client for {model}." with open(input_file, "r") as fp: diff --git a/src/tfbench/lm/_google.py b/src/tfbench/lm/_google.py index f388a41..9a0862e 100644 --- a/src/tfbench/lm/_google.py +++ b/src/tfbench/lm/_google.py @@ -19,8 +19,12 @@ ] GEMINI_TTC_MODELS = [ - "gemini-2.5-flash-preview-04-17", - "gemini-2.5-pro-preview-03-25", + "gemini-2.5-pro", + "gemini-2.5-flash", + "gemini-2.5-flash-lite", + # ! gemini-2.5-preview models are deprecated + # "gemini-2.5-flash-preview-04-17", + # "gemini-2.5-pro-preview-03-25", ] @@ -64,15 +68,20 @@ def __init__( self, model_name: str, pure: bool = False, - effort: GeminiReasoningEffort = "dynamic", + effort: GeminiReasoningEffort | None = None, ): + """Initialize the GeminiReasoning model. + effort (GeminiReasoningEffort, optional): Defaults to None, which is `dynamic`. + """ + super().__init__(model_name=model_name, pure=pure) api_key = ENV.get("GEMINI_API_KEY") assert api_key, "Please set GEMINI_API_KEY in environment!" self.client = genai.Client(api_key=api_key) - self.effort: GeminiReasoningEffort = effort + # default to dynamic if effort is None + self.effort: GeminiReasoningEffort = effort or "dynamic" def _gen(self, prompt: str) -> LMAnswer: diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index 49a91df..1b74596 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -19,9 +19,10 @@ def _assert_valid_effort(model: str, effort: str | None, effort_cls): """Check if the given effort is valid for the model.""" - assert effort in get_args( - effort_cls - ), f"`{effort}` is not a valid reasoning effort for {model}." + if effort: + assert effort in get_args( + effort_cls + ), f"`{effort}` is not a valid reasoning effort for {model}." def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: @@ -57,7 +58,9 @@ def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: def is_supported(model_name: str) -> bool: """check if the model is supported""" - all_models = OAI_MODELS + OAI_TTC_MODELS + OAI_O5 + all_models = ( + OAI_MODELS + OAI_TTC_MODELS + OAI_O5 + GEMINI_MODELS + GEMINI_TTC_MODELS + ) return model_name in all_models From ac40a1927c62b16e0b5d4b419c2e2249511dbf49 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 15 Aug 2025 16:51:04 -0700 Subject: [PATCH 08/28] document why two gemini wrapper --- src/tfbench/experiment.py | 81 ---------------------------------- src/tfbench/lm/_anthropic.py | 85 ++++++++++++++++++++++++++++++++++++ src/tfbench/lm/_google.py | 10 ++++- src/tfbench/lm/_openai.py | 1 - 4 files changed, 94 insertions(+), 83 deletions(-) create mode 100644 src/tfbench/lm/_anthropic.py diff --git a/src/tfbench/experiment.py b/src/tfbench/experiment.py index c944ccb..91b3ce0 100644 --- a/src/tfbench/experiment.py +++ b/src/tfbench/experiment.py @@ -5,91 +5,10 @@ from typing import Callable import logging -from anthropic import Anthropic, InternalServerError from .lm import get_sys_prompt, MAX_TOKENS - -CLAUDE_MODELS = [ - "claude-3-opus-20240229", - "claude-3-sonnet-20240229", - "claude-3-haiku-20240307", - "claude-3-5-sonnet-20240620", - "claude-3-5-sonnet-20241022", - "claude-3-5-haiku-20241022", -] - -CLAUDE_TTC_MODELS = [ - "claude-3-7-sonnet-20250219", -] - DEEPSEEK_MODELS = [ "deepseek-reasoner", "deepseek-chat", ] - - -def get_ant_ttc_model( - client: Anthropic, - model: str = "claude-3-7-sonnet-20250219", - pure: bool = False, - thinking_budget: int = 1024, -) -> Callable[[str], str | None]: - "Claude Reasoning Models" - - def generate_type_signature(prompt: str) -> str | None: - try: - message = client.beta.messages.create( - model=model, - thinking={"type": "enabled", "budget_tokens": thinking_budget}, - system=get_sys_prompt(pure), - messages=[ - {"role": "user", "content": prompt}, - ], - max_tokens=thinking_budget + MAX_TOKENS, - betas=["output-128k-2025-02-19"], - ) - except InternalServerError as e: - print(e) - return None - - try: - thinking, answer = message.content - text = answer.text # type: ignore - return text if isinstance(text, str) else None - except Exception as e: - logging.error(f"Error processing message content: {e}") - return None - - return generate_type_signature - - -def get_ant_model( - client: Anthropic, - model: str = "claude-3-5-sonnet-20240620", - pure: bool = False, -) -> Callable[[str], str | None]: - """Claude regular Models""" - - def generate_type_signature(prompt: str) -> str | None: - try: - message = client.messages.create( - system=get_sys_prompt(pure), - messages=[ - {"role": "user", "content": prompt}, - ], - model=model, - max_tokens=MAX_TOKENS, - ) - except InternalServerError as e: - print(e) - return None - contents = message.content - if len(contents) > 0: - text = contents[0].text # type: ignore - return text if isinstance(text, str) else None - - return None - - return generate_type_signature - diff --git a/src/tfbench/lm/_anthropic.py b/src/tfbench/lm/_anthropic.py new file mode 100644 index 0000000..903cd46 --- /dev/null +++ b/src/tfbench/lm/_anthropic.py @@ -0,0 +1,85 @@ +from typing import Callable +from anthropic import Anthropic, InternalServerError +from ..env import ENV +from ._types import LM, LMAnswer +from .settings import MAX_TOKENS + +CLAUDE_MODELS = [ + "claude-3-opus-20240229", + "claude-3-sonnet-20240229", + "claude-3-haiku-20240307", + "claude-3-5-sonnet-20240620", + "claude-3-5-sonnet-20241022", + "claude-3-5-haiku-20241022", +] + +CLAUDE_TTC_MODELS = [ + "claude-3-7-sonnet-20250219", + "claude-opus-4-1-20250805", + "claude-opus-4-20250514", + "claude-sonnet-4-20250514", +] + + +def get_ant_ttc_model( + client: Anthropic, + model: str = "claude-3-7-sonnet-20250219", + pure: bool = False, + thinking_budget: int = 1024, +) -> Callable[[str], str | None]: + "Claude Reasoning Models" + + def generate_type_signature(prompt: str) -> str | None: + try: + message = client.beta.messages.create( + model=model, + thinking={"type": "enabled", "budget_tokens": thinking_budget}, + system=get_sys_prompt(pure), + messages=[ + {"role": "user", "content": prompt}, + ], + max_tokens=thinking_budget + MAX_TOKENS, + betas=["output-128k-2025-02-19"], + ) + except InternalServerError as e: + print(e) + return None + + try: + thinking, answer = message.content + text = answer.text # type: ignore + return text if isinstance(text, str) else None + except Exception as e: + logging.error(f"Error processing message content: {e}") + return None + + return generate_type_signature + + +class ClaudeLM(LM): + """API client for Claude models.""" + + def __init__(self, model_name: str, pure: bool = False): + """Initialize the Claude model client.""" + super().__init__(model_name=model_name, pure=pure) + + api_key = ENV.get("ANTHROPIC_API_KEY") + assert api_key, "Please set ANTHROPIC_API_KEY in environment!" + self.client = Anthropic(api_key=api_key) + + def _gen(self, prompt: str) -> LMAnswer: + """Generate using Anthropic's Chat Completions API.""" + message = self.client.messages.create( + system=self.instruction, + messages=[ + {"role": "user", "content": prompt}, + ], + model=self.model_name, + max_tokens=MAX_TOKENS, + ) + contents = message.content + if not contents: + raise ValueError("No content returned from the model.") + text = contents[0].text # type: ignore + + return LMAnswer(answer=text) diff --git a/src/tfbench/lm/_google.py b/src/tfbench/lm/_google.py index 9a0862e..bd26189 100644 --- a/src/tfbench/lm/_google.py +++ b/src/tfbench/lm/_google.py @@ -29,7 +29,14 @@ class GeminiChat(LM): - """Wrapper class for `google-genai` SDK for chat models""" + """Wrapper class for `google-genai` SDK for chat models + NOTE: this class is only used for legacy Gemini models (2.0-flash) that cannot "think". + + For reasoning models with "thinking" disabled, please use `GeminiReasoning` + with `reasoning_effort` set to "off". + We keep this implementation since there are default thinking config for each model, + and `thinking_config=None` has different behavior with `thinking_budget=0`. + """ def __init__(self, model_name: str, pure: bool = False): super().__init__(model_name=model_name, pure=pure) @@ -39,6 +46,7 @@ def __init__(self, model_name: str, pure: bool = False): self.client = genai.Client(api_key=api_key) def _gen(self, prompt: str) -> LMAnswer: + """generation function for legacy Gemini models (2.0)""" response = self.client.models.generate_content( model=self.model_name, diff --git a/src/tfbench/lm/_openai.py b/src/tfbench/lm/_openai.py index 1372f47..a5b1afc 100644 --- a/src/tfbench/lm/_openai.py +++ b/src/tfbench/lm/_openai.py @@ -1,7 +1,6 @@ from typing import get_args from openai import OpenAI, NOT_GIVEN -from openai.types.shared_params.reasoning import Reasoning from openai.types.shared.reasoning_effort import ReasoningEffort from ..env import ENV From 6241e5f667add3cc782545a985e1cbcb88e6fce3 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Mon, 18 Aug 2025 15:40:27 -0700 Subject: [PATCH 09/28] add Claude API --- src/tfbench/lm/_anthropic.py | 105 +++++++++++++++++++++-------------- src/tfbench/lm/_google.py | 26 ++++----- src/tfbench/lm/_types.py | 10 ++++ src/tfbench/lm/utils.py | 13 +++++ 4 files changed, 96 insertions(+), 58 deletions(-) diff --git a/src/tfbench/lm/_anthropic.py b/src/tfbench/lm/_anthropic.py index 903cd46..b91200e 100644 --- a/src/tfbench/lm/_anthropic.py +++ b/src/tfbench/lm/_anthropic.py @@ -1,7 +1,7 @@ from typing import Callable -from anthropic import Anthropic, InternalServerError +from anthropic import Anthropic, InternalServerError, NOT_GIVEN from ..env import ENV -from ._types import LM, LMAnswer +from ._types import LM, LMAnswer, ReasoningEffort, EFFORT_TOKEN_MAP from .settings import MAX_TOKENS CLAUDE_MODELS = [ @@ -21,43 +21,11 @@ ] -def get_ant_ttc_model( - client: Anthropic, - model: str = "claude-3-7-sonnet-20250219", - pure: bool = False, - thinking_budget: int = 1024, -) -> Callable[[str], str | None]: - "Claude Reasoning Models" - - def generate_type_signature(prompt: str) -> str | None: - try: - message = client.beta.messages.create( - model=model, - thinking={"type": "enabled", "budget_tokens": thinking_budget}, - system=get_sys_prompt(pure), - messages=[ - {"role": "user", "content": prompt}, - ], - max_tokens=thinking_budget + MAX_TOKENS, - betas=["output-128k-2025-02-19"], - ) - except InternalServerError as e: - print(e) - return None - - try: - thinking, answer = message.content - text = answer.text # type: ignore - return text if isinstance(text, str) else None - except Exception as e: - logging.error(f"Error processing message content: {e}") - return None - - return generate_type_signature - - -class ClaudeLM(LM): - """API client for Claude models.""" +class ClaudeChat(LM): + """API client for Claude models. + + SDK wrapper for legacy Claude models with no reasoning. + """ def __init__(self, model_name: str, pure: bool = False): """Initialize the Claude model client.""" @@ -77,9 +45,60 @@ def _gen(self, prompt: str) -> LMAnswer: model=self.model_name, max_tokens=MAX_TOKENS, ) - contents = message.content - if not contents: - raise ValueError("No content returned from the model.") - text = contents[0].text # type: ignore + + text = None + for c in message.content: + if c.type == "text": + text = c.text + break + + if text is None: + raise ValueError("No text content returned from the model.") return LMAnswer(answer=text) + + +class ClaudeReasoning(LM): + """API client for Claude models.""" + + def __init__( + self, model_name: str, pure: bool = False, effort: ReasoningEffort | None = None + ): + """Initialize the Claude model client.""" + super().__init__(model_name=model_name, pure=pure) + + api_key = ENV.get("ANTHROPIC_API_KEY") + assert api_key, "Please set ANTHROPIC_API_KEY in environment!" + self.client = Anthropic(api_key=api_key) + + self.effort: ReasoningEffort = effort or "medium" + + def _gen(self, prompt: str) -> LMAnswer: + """Generate using Anthropic's Chat Completions API.""" + rsn_tokens = EFFORT_TOKEN_MAP[self.effort] + message = self.client.messages.create( + system=self.instruction, + messages=[ + {"role": "user", "content": prompt}, + ], + thinking={ + "type": "enabled", + "budget_tokens": rsn_tokens, + }, + model=self.model_name, + max_tokens=MAX_TOKENS + rsn_tokens, + ) + text = None + thinking = None + for block in message.content: + if block.type == "text": + text = block.text + if block.type == "thinking": + thinking = block.thinking + if text and thinking: + break + + if text is None or thinking is None: + raise ValueError("No text content returned from the model.") + + return LMAnswer(answer=text, reasoning_steps=thinking) diff --git a/src/tfbench/lm/_google.py b/src/tfbench/lm/_google.py index bd26189..a5503af 100644 --- a/src/tfbench/lm/_google.py +++ b/src/tfbench/lm/_google.py @@ -1,13 +1,13 @@ """Inference helper for Google Gemini""" -from typing import Literal +from typing import Literal, Mapping from enum import Enum from google import genai from google.genai.types import GenerateContentConfig, ThinkingConfig from ..env import ENV -from ._types import LM, LMAnswer +from ._types import LM, LMAnswer, ReasoningEffort, EFFORT_TOKEN_MAP GEMINI_MODELS = [ "gemini-2.0-flash", @@ -27,6 +27,13 @@ # "gemini-2.5-pro-preview-03-25", ] +GeminiReasoningEffort = ReasoningEffort | Literal["dynamic"] +# Upcast to a Mapping with the *wider* key type +GEMINI_MAP: dict[str, int] = { + **EFFORT_TOKEN_MAP, + "dynamic": -1, +} + class GeminiChat(LM): """Wrapper class for `google-genai` SDK for chat models @@ -58,17 +65,6 @@ def _gen(self, prompt: str) -> LMAnswer: return LMAnswer(answer=response.text) -GeminiReasoningEffort = Literal["low", "medium", "high", "dynamic", "off"] - -EFFORT_TOKEN_MAP: dict[GeminiReasoningEffort, int] = { - "low": 512, - "medium": 1024, - "high": 2048, - "dynamic": -1, - "off": 0, -} - - class GeminiReasoning(LM): """Wrapper class for `google-genai` SDK for reasoning models""" @@ -79,7 +75,7 @@ def __init__( effort: GeminiReasoningEffort | None = None, ): """Initialize the GeminiReasoning model. - effort (GeminiReasoningEffort, optional): Defaults to None, which is `dynamic`. + effort (ReasoningEffort, optional): Defaults to None, which is `dynamic`. """ super().__init__(model_name=model_name, pure=pure) @@ -89,7 +85,7 @@ def __init__( self.client = genai.Client(api_key=api_key) # default to dynamic if effort is None - self.effort: GeminiReasoningEffort = effort or "dynamic" + self.effort = effort or "dynamic" def _gen(self, prompt: str) -> LMAnswer: diff --git a/src/tfbench/lm/_types.py b/src/tfbench/lm/_types.py index 89636a7..ce28190 100644 --- a/src/tfbench/lm/_types.py +++ b/src/tfbench/lm/_types.py @@ -37,3 +37,13 @@ def generate(self, prompt: str) -> LMAnswer: @abstractmethod def _gen(self, prompt) -> LMAnswer: """The actual generation method for different clients""" + + +ReasoningEffort = Literal["low", "medium", "high", "off"] + +EFFORT_TOKEN_MAP: dict[str, int] = { + "low": 1024, + "medium": 4096, + "high": 8192, + "off": 0, +} diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index 1b74596..8deed17 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -12,9 +12,11 @@ OAI_O5, ) from ._google import GeminiChat, GeminiReasoning, GEMINI_MODELS, GEMINI_TTC_MODELS +from ._anthropic import ClaudeChat, ClaudeReasoning, CLAUDE_MODELS, CLAUDE_TTC_MODELS from openai.types.shared.reasoning_effort import ReasoningEffort as OAIReasoningEffort from ._google import GeminiReasoningEffort +from ._types import ReasoningEffort def _assert_valid_effort(model: str, effort: str | None, effort_cls): @@ -53,6 +55,17 @@ def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: effort=cast(GeminiReasoningEffort, effort), ) + if model_name in CLAUDE_MODELS: + return ClaudeChat(model_name=model_name, pure=pure) + + if model_name in CLAUDE_TTC_MODELS: + _assert_valid_effort(model_name, effort, ReasoningEffort) + return ClaudeReasoning( + model_name=model_name, + pure=pure, + effort=cast(ReasoningEffort, effort), + ) + return None From d618e584c0f165ff2048627fd3ea43633ee9fcca Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Mon, 18 Aug 2025 15:45:29 -0700 Subject: [PATCH 10/28] add claude models to supported list --- src/tfbench/lm/utils.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index 8deed17..428a812 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -72,7 +72,13 @@ def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: def is_supported(model_name: str) -> bool: """check if the model is supported""" all_models = ( - OAI_MODELS + OAI_TTC_MODELS + OAI_O5 + GEMINI_MODELS + GEMINI_TTC_MODELS + OAI_MODELS + + OAI_TTC_MODELS + + OAI_O5 + + GEMINI_MODELS + + GEMINI_TTC_MODELS + + CLAUDE_MODELS + + CLAUDE_TTC_MODELS ) return model_name in all_models From 0fde1f7af361efc4878d515d5edd09d55a377f03 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Mon, 18 Aug 2025 15:56:12 -0700 Subject: [PATCH 11/28] handle UnionType for Literal ReasoningEffort --- src/tfbench/lm/utils.py | 27 +++++++++++++++++++++------ 1 file changed, 21 insertions(+), 6 deletions(-) diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index 428a812..f2c77e6 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -1,5 +1,6 @@ import logging -from typing import Literal, get_args, cast, TypeAlias +from typing import Literal, get_args, cast, TypeAlias, Any, Union, get_origin +from types import UnionType from returns.result import ResultE, Success, Failure, Result @@ -19,12 +20,26 @@ from ._types import ReasoningEffort -def _assert_valid_effort(model: str, effort: str | None, effort_cls): +def _literal_options(tp: Any) -> set[str]: + """Collect string values from Literal[...] inside tp (handles Unions).""" + origin = get_origin(tp) + if origin is Literal: + # Direct Literal["a", "b", ...] + return set(get_args(tp)) + if origin is Union or (UnionType is not None and origin is UnionType): + vals: set[str] = set() + for arg in get_args(tp): + vals |= _literal_options(arg) + return vals + return set() # not a Literal or Union of Literals + + +def _assert_valid_effort(model: str, effort: str | None, effort_cls: Any) -> None: """Check if the given effort is valid for the model.""" - if effort: - assert effort in get_args( - effort_cls - ), f"`{effort}` is not a valid reasoning effort for {model}." + if effort is None: + return + allowed = _literal_options(effort_cls) + assert effort in allowed, f"`{effort}` is not a valid reasoning effort for {model}." def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: From 6d0d91d1bf807a6e69ab55007c59ec103b31b446 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Wed, 20 Aug 2025 22:25:35 +0000 Subject: [PATCH 12/28] add vLLM support and use it as default option --- src/main.py | 7 +++++-- src/tfbench/lm/__init__.py | 5 +++-- src/tfbench/lm/_vllm.py | 25 +++++++++++++++++++++++++ src/tfbench/lm/utils.py | 17 ++--------------- 4 files changed, 35 insertions(+), 19 deletions(-) create mode 100644 src/tfbench/lm/_vllm.py diff --git a/src/main.py b/src/main.py index f22e82f..a3d6299 100755 --- a/src/main.py +++ b/src/main.py @@ -17,7 +17,7 @@ from tfbench.postprocessing import postprocess, RESPONSE_STRATEGIES from tfbench.evaluation import evaluate -from tfbench.lm import is_supported, router, LMAnswer, extract_response +from tfbench.lm import router, LMAnswer, extract_response def main( @@ -43,7 +43,6 @@ def main( pure (bool): If True, uses the original variable naming in type inference. If False, uses rewritten variable naming (e.g., `v1`, `v2`, ...). Default is False. """ - assert is_supported(model), f"{model} is not supported." # hard-coding benchmark file path for experiment input_file = "tfb.pure.json" if pure else "tfb.json" @@ -54,6 +53,9 @@ def main( if output_file is None: os.makedirs("result", exist_ok=True) + if "/" in model: + dir_name = model.split("/")[0] + os.makedirs(f"result/{dir_name}", exist_ok=True) output_file = os.path.abspath(f"result/{model}.txt") logging.info(f"Writing generation results in {output_file}.") @@ -76,6 +78,7 @@ def main( .value ) + # writing results with open(output_file, "w", errors="ignore") as file: file.write("\n".join(gen_results)) diff --git a/src/tfbench/lm/__init__.py b/src/tfbench/lm/__init__.py index 233f854..0e2e0f9 100644 --- a/src/tfbench/lm/__init__.py +++ b/src/tfbench/lm/__init__.py @@ -4,8 +4,9 @@ from .settings import MAX_TOKENS from ._openai import OpenAIChatCompletion, OpenAIResponses from ._google import GeminiChat, GeminiReasoning +from ._vllm import VLLMGen from ._types import LM, LMAnswer -from .utils import router, is_supported, extract_response +from .utils import router, extract_response logging.getLogger("openai").setLevel(logging.ERROR) logging.getLogger("httpx").setLevel(logging.ERROR) @@ -20,6 +21,6 @@ "GeminiChat", "GeminiReasoning", "router", - "is_supported", "extract_response", + "VLLMGen", ] diff --git a/src/tfbench/lm/_vllm.py b/src/tfbench/lm/_vllm.py new file mode 100644 index 0000000..be70357 --- /dev/null +++ b/src/tfbench/lm/_vllm.py @@ -0,0 +1,25 @@ +from vllm import LLM, SamplingParams + +from ..env import ENV +from ._types import LM, LMAnswer, ReasoningEffort, EFFORT_TOKEN_MAP + + +_CHAT_TEMPLATE = """# Instructions +{instruction} + +## Task +{task} +""" + + +class VLLMGen(LM): + + def __init__(self, model_name: str, pure: bool = False): + super().__init__(model_name=model_name, pure=pure) + self.llm = LLM(model=self.model_name) + + def _gen(self, prompt: str) -> LMAnswer: + _prompt = _CHAT_TEMPLATE.format(instruction=self.instruction, task=prompt) + result = self.llm.generate(_prompt) + output = result[0].outputs[0] # any exception would be caught by @safe + return LMAnswer(answer=output.text) diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index f2c77e6..b7d7a95 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -14,6 +14,7 @@ ) from ._google import GeminiChat, GeminiReasoning, GEMINI_MODELS, GEMINI_TTC_MODELS from ._anthropic import ClaudeChat, ClaudeReasoning, CLAUDE_MODELS, CLAUDE_TTC_MODELS +from ._vllm import VLLMGen from openai.types.shared.reasoning_effort import ReasoningEffort as OAIReasoningEffort from ._google import GeminiReasoningEffort @@ -81,21 +82,7 @@ def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: effort=cast(ReasoningEffort, effort), ) - return None - - -def is_supported(model_name: str) -> bool: - """check if the model is supported""" - all_models = ( - OAI_MODELS - + OAI_TTC_MODELS - + OAI_O5 - + GEMINI_MODELS - + GEMINI_TTC_MODELS - + CLAUDE_MODELS - + CLAUDE_TTC_MODELS - ) - return model_name in all_models + return VLLMGen(model_name=model_name, pure=pure) def extract_response(response: ResultE[LMAnswer]) -> str: From e3a0964327b7c34f4c387671649d06ab42fca69c Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Thu, 21 Aug 2025 03:56:03 +0000 Subject: [PATCH 13/28] fix: use vLLM chat interface instead of gen --- src/tfbench/lm/__init__.py | 4 ++-- src/tfbench/lm/_vllm.py | 13 +++++++++---- src/tfbench/lm/utils.py | 6 +++--- 3 files changed, 14 insertions(+), 9 deletions(-) diff --git a/src/tfbench/lm/__init__.py b/src/tfbench/lm/__init__.py index 0e2e0f9..abd1bf6 100644 --- a/src/tfbench/lm/__init__.py +++ b/src/tfbench/lm/__init__.py @@ -4,7 +4,7 @@ from .settings import MAX_TOKENS from ._openai import OpenAIChatCompletion, OpenAIResponses from ._google import GeminiChat, GeminiReasoning -from ._vllm import VLLMGen +from ._vllm import VLLMChat from ._types import LM, LMAnswer from .utils import router, extract_response @@ -22,5 +22,5 @@ "GeminiReasoning", "router", "extract_response", - "VLLMGen", + "VLLMChat", ] diff --git a/src/tfbench/lm/_vllm.py b/src/tfbench/lm/_vllm.py index be70357..ece79a1 100644 --- a/src/tfbench/lm/_vllm.py +++ b/src/tfbench/lm/_vllm.py @@ -1,4 +1,5 @@ from vllm import LLM, SamplingParams +from vllm.entrypoints.chat_utils import ChatCompletionMessageParam from ..env import ENV from ._types import LM, LMAnswer, ReasoningEffort, EFFORT_TOKEN_MAP @@ -12,14 +13,18 @@ """ -class VLLMGen(LM): +class VLLMChat(LM): def __init__(self, model_name: str, pure: bool = False): super().__init__(model_name=model_name, pure=pure) self.llm = LLM(model=self.model_name) def _gen(self, prompt: str) -> LMAnswer: - _prompt = _CHAT_TEMPLATE.format(instruction=self.instruction, task=prompt) - result = self.llm.generate(_prompt) - output = result[0].outputs[0] # any exception would be caught by @safe + """generate using vLLM's chat interface""" + conversation: list[ChatCompletionMessageParam] = [ + {"role": "system", "content": self.instruction}, + {"role": "user", "content": prompt}, + ] + outputs = self.llm.chat(conversation) + output = outputs[0].outputs[0] # any exception would be caught by @safe return LMAnswer(answer=output.text) diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index b7d7a95..c1aec2e 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -14,7 +14,7 @@ ) from ._google import GeminiChat, GeminiReasoning, GEMINI_MODELS, GEMINI_TTC_MODELS from ._anthropic import ClaudeChat, ClaudeReasoning, CLAUDE_MODELS, CLAUDE_TTC_MODELS -from ._vllm import VLLMGen +from ._vllm import VLLMChat from openai.types.shared.reasoning_effort import ReasoningEffort as OAIReasoningEffort from ._google import GeminiReasoningEffort @@ -43,7 +43,7 @@ def _assert_valid_effort(model: str, effort: str | None, effort_cls: Any) -> Non assert effort in allowed, f"`{effort}` is not a valid reasoning effort for {model}." -def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: +def router(model_name: str, pure: bool, effort: str | None = None) -> LM: """Route the model name to the appropriate LM class.""" if model_name in OAI_MODELS: return OpenAIChatCompletion(model_name=model_name, pure=pure) @@ -82,7 +82,7 @@ def router(model_name: str, pure: bool, effort: str | None = None) -> LM | None: effort=cast(ReasoningEffort, effort), ) - return VLLMGen(model_name=model_name, pure=pure) + return VLLMChat(model_name=model_name, pure=pure) def extract_response(response: ResultE[LMAnswer]) -> str: From 8eebc39dde9e096b8917ac80a4d6042f277481d7 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 22 Aug 2025 05:11:31 +0800 Subject: [PATCH 14/28] env add vllm api key --- .env | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.env b/.env index cf58a01..76a10dc 100644 --- a/.env +++ b/.env @@ -1,3 +1,4 @@ OPENAI_API_KEY= ANTHROPIC_API_KEY= -GEMINI_API_KEY= \ No newline at end of file +GEMINI_API_KEY= +VLLM_API_KEY= \ No newline at end of file From 38cd5f52a22035799183adc9370a9e77b2e74525 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 22 Aug 2025 06:11:36 +0800 Subject: [PATCH 15/28] add VLLM_HOST and VLLM_PORT --- .env | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.env b/.env index 76a10dc..9686f5e 100644 --- a/.env +++ b/.env @@ -1,4 +1,6 @@ OPENAI_API_KEY= ANTHROPIC_API_KEY= GEMINI_API_KEY= -VLLM_API_KEY= \ No newline at end of file +VLLM_API_KEY= +VLLM_HOST= +VLLM_PORT= \ No newline at end of file From 3f3c1ca7bcfed9e3bec2905e9429972ef18de543 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 22 Aug 2025 07:35:13 +0800 Subject: [PATCH 16/28] add vllm server mode --- .env | 5 +---- README.md | 35 ++++++++++++++++++++++++++++++++-- src/main.py | 8 +++----- src/tfbench/env.py | 2 ++ src/tfbench/lm/_vllm.py | 42 +++++++++++++++++++++++++++++++++++++++++ src/tfbench/lm/utils.py | 15 ++++++++++++--- 6 files changed, 93 insertions(+), 14 deletions(-) diff --git a/.env b/.env index 9686f5e..cf58a01 100644 --- a/.env +++ b/.env @@ -1,6 +1,3 @@ OPENAI_API_KEY= ANTHROPIC_API_KEY= -GEMINI_API_KEY= -VLLM_API_KEY= -VLLM_HOST= -VLLM_PORT= \ No newline at end of file +GEMINI_API_KEY= \ No newline at end of file diff --git a/README.md b/README.md index 499ac35..ee1d3a7 100644 --- a/README.md +++ b/README.md @@ -69,9 +69,40 @@ To run all GPT models: uv run run_all.py --option gpt ``` -### Open Source Models +### Open Source Models with vLLM -We use [Ollama](https://ollama.com/) to manage and run the OSS models. +#### OpenAI-Compatible Server + +First, launch the vLLM OpenAI-Compatible Server (with default values, please check vLLM's doc for setting your own): + +```sh +vllm serve openai/gpt-oss-120b --tensor-parallel-size 2 --async-scheduling +``` + +Then, run the benchmark: + +```sh +uv run main.py -i Benchmark-F.json -m vllm_openai_chat_completion +``` + +NOTE: if you set your API key, host, and port when launching the vLLM server, +please add them to the `.env` file as well. +Please modify `.env` for your vLLM api-key, host, and port. +If they are left empty, the default values ("", "localhost", "8000") will be used. +We do not recommend using the default values on machine connect to the public web, +as they are not secure. + +``` +VLLM_API_KEY= +VLLM_HOST= +VLLM_PORT= +``` + +### (deprecated) Open Source Models with Ollama + +We use [Ollama](https://ollama.com/) to manage and run the OSS models reported in the Appendix. +We switched to vLLM for better performance and SDK design. +Although the Ollama option is still available, we recommend using vLLM instead. ```sh curl -fsSL https://ollama.com/install.sh | sh # install ollama, you need sudo for this diff --git a/src/main.py b/src/main.py index a3d6299..fa2c1f2 100755 --- a/src/main.py +++ b/src/main.py @@ -22,11 +22,11 @@ def main( model: str, - port: int = 11434, pure: bool = False, effort: str | None = None, output_file: str | None = None, log_file: str = "evaluation_log.jsonl", + use_vllm_server: bool = False, ): """ Run an experiment using various AI models to generate and evaluate type signatures. @@ -37,11 +37,9 @@ def main( - OLLAMA_MODELS, CLAUDE_MODELS, or O1_MODELS. Default is "gpt-3.5-turbo". - port (int): Port number for connecting to the Ollama server (if using Ollama models). - Ignored for other models. Default is 11434. - pure (bool): If True, uses the original variable naming in type inference. If False, uses rewritten variable naming (e.g., `v1`, `v2`, ...). Default is False. + """ # hard-coding benchmark file path for experiment @@ -59,7 +57,7 @@ def main( output_file = os.path.abspath(f"result/{model}.txt") logging.info(f"Writing generation results in {output_file}.") - client = router(model, pure, effort) + client = router(model, pure, effort, use_vllm_server) assert client, f"Failed to create client for {model}." with open(input_file, "r") as fp: diff --git a/src/tfbench/env.py b/src/tfbench/env.py index a7d9ac7..c8e9a6f 100644 --- a/src/tfbench/env.py +++ b/src/tfbench/env.py @@ -1,3 +1,5 @@ +import os + from dotenv import load_dotenv, dotenv_values ENV = dotenv_values(".env") diff --git a/src/tfbench/lm/_vllm.py b/src/tfbench/lm/_vllm.py index ece79a1..12219ee 100644 --- a/src/tfbench/lm/_vllm.py +++ b/src/tfbench/lm/_vllm.py @@ -1,6 +1,8 @@ from vllm import LLM, SamplingParams from vllm.entrypoints.chat_utils import ChatCompletionMessageParam +from openai import OpenAI + from ..env import ENV from ._types import LM, LMAnswer, ReasoningEffort, EFFORT_TOKEN_MAP @@ -28,3 +30,43 @@ def _gen(self, prompt: str) -> LMAnswer: outputs = self.llm.chat(conversation) output = outputs[0].outputs[0] # any exception would be caught by @safe return LMAnswer(answer=output.text) + + +class VLLMOpenAIChatCompletion(LM): + """Serving mode of vLLM that is compatible with OpenAI-Compatible Server + https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html + """ + + def __init__(self, model_name: str, pure: bool = False): + super().__init__(model_name=model_name, pure=pure) + + api_key = ENV.get("VLLM_API_KEY", "") + host = ENV.get("VLLM_HOST", "localhost") + port = ENV.get("VLLM_PORT", "8000") + + url = f"http://{host}:{port}/v1" + self.client = OpenAI( + base_url=url, + api_key=api_key, + ) + + def _gen(self, prompt: str) -> LMAnswer: + """generate using vLLM's OpenAI compatible interface""" + completion = self.client.chat.completions.create( + messages=[ + { + "role": "developer", + "content": self.instruction, + }, + {"role": "user", "content": prompt}, + ], + model=self.model_name, + ) + + message = completion.choices[0].message + return LMAnswer( + answer=message.content, + reasoning_steps=( + message.reasoning_steps if hasattr(message, "reasoning_steps") else None + ), + ) diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index c1aec2e..77e4dd3 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -3,6 +3,7 @@ from types import UnionType from returns.result import ResultE, Success, Failure, Result +from openai.types.shared.reasoning_effort import ReasoningEffort as OAIReasoningEffort from ._types import LM, LMAnswer from ._openai import ( @@ -14,9 +15,8 @@ ) from ._google import GeminiChat, GeminiReasoning, GEMINI_MODELS, GEMINI_TTC_MODELS from ._anthropic import ClaudeChat, ClaudeReasoning, CLAUDE_MODELS, CLAUDE_TTC_MODELS -from ._vllm import VLLMChat +from ._vllm import VLLMChat, VLLMOpenAIChatCompletion -from openai.types.shared.reasoning_effort import ReasoningEffort as OAIReasoningEffort from ._google import GeminiReasoningEffort from ._types import ReasoningEffort @@ -43,7 +43,12 @@ def _assert_valid_effort(model: str, effort: str | None, effort_cls: Any) -> Non assert effort in allowed, f"`{effort}` is not a valid reasoning effort for {model}." -def router(model_name: str, pure: bool, effort: str | None = None) -> LM: +def router( + model_name: str, + pure: bool, + effort: str | None = None, + use_vllm_server: bool = False, +) -> LM: """Route the model name to the appropriate LM class.""" if model_name in OAI_MODELS: return OpenAIChatCompletion(model_name=model_name, pure=pure) @@ -82,6 +87,10 @@ def router(model_name: str, pure: bool, effort: str | None = None) -> LM: effort=cast(ReasoningEffort, effort), ) + # all allow lists are exhausted, use vLLM + if use_vllm_server: + return VLLMOpenAIChatCompletion(model_name=model_name, pure=pure) + return VLLMChat(model_name=model_name, pure=pure) From 583d85594a6458eb81411691e1bacd9654c93f55 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 22 Aug 2025 18:46:39 +0000 Subject: [PATCH 17/28] add vLLM in dependencies --- pyproject.toml | 1 + src/tfbench/lm/_vllm.py | 4 +- uv.lock | 2946 +++++++++++++++++++++++++++++++++++++-- 3 files changed, 2867 insertions(+), 84 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 77173c9..f7c321a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -34,6 +34,7 @@ dependencies = [ "tree-sitter==0.22.3", "tree-sitter-haskell==0.21.0", "types-requests>=2.31.0", + "vllm>=0.10.1.1", ] [build-system] diff --git a/src/tfbench/lm/_vllm.py b/src/tfbench/lm/_vllm.py index 12219ee..5cf6435 100644 --- a/src/tfbench/lm/_vllm.py +++ b/src/tfbench/lm/_vllm.py @@ -67,6 +67,8 @@ def _gen(self, prompt: str) -> LMAnswer: return LMAnswer( answer=message.content, reasoning_steps=( - message.reasoning_steps if hasattr(message, "reasoning_steps") else None + message.reasoning_content # type: ignore + if 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17 00:00:00 2001 From: Yifeng He Date: Fri, 22 Aug 2025 19:09:11 +0000 Subject: [PATCH 19/28] make deprecated ollama a standalone script --- scripts/experiment_ollama.py | 176 +++++++++++++++++++++++++++++++ src/tfbench/experiment_ollama.py | 99 ----------------- 2 files changed, 176 insertions(+), 99 deletions(-) create mode 100644 scripts/experiment_ollama.py delete mode 100644 src/tfbench/experiment_ollama.py diff --git a/scripts/experiment_ollama.py b/scripts/experiment_ollama.py new file mode 100644 index 0000000..433f167 --- /dev/null +++ b/scripts/experiment_ollama.py @@ -0,0 +1,176 @@ +""" +(deprecated) Experiment script for OSS models using Ollama +This script reproduce legacy results for OSS models using Ollama in our paper's Appendix. +New models should use our vLLM option instead. +""" + +from typing import Union +import os +import json + +from ollama import Client as OllamaClient, ResponseError +import fire +from dacite import from_dict +from tqdm import tqdm +from funcy_chain import Chain + +from tfbench.lm import get_sys_prompt +from tfbench.common import BenchmarkTask, get_prompt +from tfbench.postprocessing import postprocess, RESPONSE_STRATEGIES +from tfbench.evaluation import evaluate + +OLLAMA_OSS = [ + "phi3:3.8b", + "phi3:14b", + "mistral", + "mixtral:8x7b", + "mixtral:8x22b", + "llama3:8b", + "llama3:70b", + "llama3.1:8b", + "llama3.1:70b", + "llama3.1:405b", + "llama3.2:1b", + "llama3.2:3b", + "llama3.3:70b", + "gemma:2b", + "gemma:7b", + "gemma2:9b", + "gemma2:27b", + "qwen2:1.5b", + "qwen2:7b", + "qwen2:72b", + "qwen2.5:1.5b", + "qwen2.5:7b", + "qwen2.5:72b", + "deepseek-v2:16b", + "deepseek-v2:236b", + "deepseek-v2.5:236b", +] + + +OLLAMA_CODE = [ + "qwen2.5-coder:1.5b", + "qwen2.5-coder:7b", + "granite-code:3b", + "granite-code:8b", + "granite-code:20b", + "granite-code:34b", + "deepseek-coder-v2:16b", + "deepseek-coder-v2:236b", +] + +OLLAMA_MODELS = OLLAMA_OSS + OLLAMA_CODE + + +def get_ollama_model( + client: OllamaClient, + model: str = "llama3:8b", + pure: bool = False, +): + """ + Configure and return a function to generate type signatures using an Ollama model. + + Parameters: + client (OllamaClient): The Ollama client instance used for sending requests to the model. + + model (str): Name of the model to use for generating type signatures. + Must be one of the predefined models in OLLAMA_MODELS. + Default is "llama3:8b". + + pure (bool): If True, uses the original variable naming in type inference. + If False, uses rewritten variable naming (e.g., `v1`, `v2`, ...). Default is False. + + Returns: + Callable[[str], Union[str, None]]: + A function that takes a prompt string as input and returns the generated type + signature as a string, or None if the generation fails. + """ + + def generate_type_signature(prompt: str) -> Union[str, None]: + try: + response = client.chat( + messages=[ + { + "role": "system", + "content": get_sys_prompt(pure), + }, + {"role": "user", "content": prompt}, + ], + model=model, + ) + except ResponseError as e: + print(e) + return None + + message = response.message + if message.content: + return str(message.content) + + return None + + return generate_type_signature + + +def main( + model: str = "llama3:8b", + pure: bool = False, + port: int = 11434, + output_file: str | None = None, + log_file: str = "evaluation_log.jsonl", +): + """ + Run an experiment using various AI models to generate and evaluate type signatures. + + Parameters: + model (str): Name of the model to use for generating type signatures. Must be one of OLLAMA_MODELS + + port (int): Port number for connecting to the Ollama server. + Ignored for other models. Default is 11434. + + pure (bool): If True, uses the original variable naming in type inference. + If False, uses rewritten variable naming (e.g., `v1`, `v2`, ...). Default is False. + """ + assert model in OLLAMA_MODELS, f"{model} is not supported." + + # hard-coding benchmark file path for experiment + input_file = "tfb.pure.json" if pure else "tfb.json" + input_file = os.path.abspath(input_file) + assert os.path.exists( + input_file + ), f"{input_file} does not exist! Please download or build it first." + + if output_file is None: + os.makedirs("result", exist_ok=True) + output_file = f"result/{model}.txt" + + client = OllamaClient(host=f"http://localhost:{port}") + generate = get_ollama_model(client, model, pure) + + with open(input_file, "r") as fp: + tasks = [from_dict(data_class=BenchmarkTask, data=d) for d in json.load(fp)] + + prompts = map(get_prompt, tasks) + responses = map(generate, tqdm(prompts, desc=model)) + gen_results = ( + Chain(responses) + .map(lambda x: x if x is not None else "") # convert None to empty string + .map(lambda s: postprocess(s, RESPONSE_STRATEGIES)) + .map(str.strip) + .value + ) + + with open(output_file, "w", errors="ignore") as file: + file.write("\n".join(gen_results)) + + eval_acc = evaluate(tasks, gen_results) + print(eval_acc) + + os.makedirs(os.path.dirname(output_file), exist_ok=True) + with open(log_file, "a") as fp: + logging_result = {"model_name": model, **eval_acc, "pure": pure} + fp.write(f"{json.dumps(logging_result)}\n") + + +if __name__ == "__main__": + fire.Fire(main) diff --git a/src/tfbench/experiment_ollama.py b/src/tfbench/experiment_ollama.py deleted file mode 100644 index bce002b..0000000 --- a/src/tfbench/experiment_ollama.py +++ /dev/null @@ -1,99 +0,0 @@ -""" -Experiment script for OSS models using Ollama -""" - -from typing import Union -from ollama import Client as OllamaClient, ResponseError -from tfbench.lm.prompts import get_sys_prompt - -OLLAMA_OSS = [ - "phi3:3.8b", - "phi3:14b", - "mistral", - "mixtral:8x7b", - "mixtral:8x22b", - "llama3:8b", - "llama3:70b", - "llama3.1:8b", - "llama3.1:70b", - "llama3.1:405b", - "llama3.2:1b", - "llama3.2:3b", - "llama3.3:70b", - "gemma:2b", - "gemma:7b", - "gemma2:9b", - "gemma2:27b", - "qwen2:1.5b", - "qwen2:7b", - "qwen2:72b", - "qwen2.5:1.5b", - "qwen2.5:7b", - "qwen2.5:72b", - "deepseek-v2:16b", - "deepseek-v2:236b", - "deepseek-v2.5:236b", -] - - -OLLAMA_CODE = [ - "qwen2.5-coder:1.5b", - "qwen2.5-coder:7b", - "granite-code:3b", - "granite-code:8b", - "granite-code:20b", - "granite-code:34b", - "deepseek-coder-v2:16b", - "deepseek-coder-v2:236b", -] - -OLLAMA_MODELS = OLLAMA_OSS + OLLAMA_CODE - - -def get_ollama_model( - client: OllamaClient, - model: str = "llama3:8b", - pure: bool = False, -): - """ - Configure and return a function to generate type signatures using an Ollama model. - - Parameters: - client (OllamaClient): The Ollama client instance used for sending requests to the model. - - model (str): Name of the model to use for generating type signatures. - Must be one of the predefined models in OLLAMA_MODELS. - Default is "llama3:8b". - - pure (bool): If True, uses the original variable naming in type inference. - If False, uses rewritten variable naming (e.g., `v1`, `v2`, ...). Default is False. - - Returns: - Callable[[str], Union[str, None]]: - A function that takes a prompt string as input and returns the generated type - signature as a string, or None if the generation fails. - """ - - def generate_type_signature(prompt: str) -> Union[str, None]: - try: - response = client.chat( - messages=[ - { - "role": "system", - "content": get_sys_prompt(pure), - }, - {"role": "user", "content": prompt}, - ], - model=model, - ) - except ResponseError as e: - print(e) - return None - - message = response.message - if message.content: - return str(message.content) - - return None - - return generate_type_signature From 9f6c70c44a101d3147e3bc301f9a17a2f68199a1 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Fri, 22 Aug 2025 19:19:32 +0000 Subject: [PATCH 20/28] doc: revise ollama --- README.md | 20 +++++++++----------- scripts/preprocess_benchmark.py | 1 + 2 files changed, 10 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 88bd7d6..b07687e 100644 --- a/README.md +++ b/README.md @@ -21,7 +21,7 @@ uv sync # create a virtual environment, and install dependencies This script will build the benchmark (Prelude with NL) from the raw data. ```sh -uv run scripts/preprocess_benchmark.py +uv run scripts/preprocess_benchmark.py -o tfb.json ``` ### TF-Bench_pure @@ -36,7 +36,7 @@ stack exec alpharewrite-exe 1 ../tfb.json > ../tfb.pure.json cd .. ``` -For details, please take a look at the README of [alpharewrite](https://github.com/SecurityLab-UCD/alpharewrite). +For details, please check out the README of [alpharewrite](https://github.com/SecurityLab-UCD/alpharewrite). ## Download Pre-built Benchmark @@ -98,24 +98,22 @@ VLLM_HOST= VLLM_PORT= ``` -### (deprecated) Open Source Models with Ollama +### (_deprecated_) Open Source Models with Ollama We use [Ollama](https://ollama.com/) to manage and run the OSS models reported in the Appendix. We switched to vLLM for better performance and SDK design. -Although the Ollama option is still available, we recommend using vLLM instead. +Although the Ollama option is still available, +it is no longer maintained. +We recommend using vLLM instead. ```sh curl -fsSL https://ollama.com/install.sh | sh # install ollama, you need sudo for this ollama serve # start your own instance instead of a system service -uv run --project . scripts/ollama_pull.sh # install required models +uv run scripts/ollama_pull.sh # install required models ``` -```sh -uv run main.py -i Benchmark-F.json -m llama3:70b -``` - -To run all Ollama models: +Run the benchmark. ```sh -uv run run_all.py --option ollama +uv run scripts/experiment_ollama.py -m llama3:8b ``` diff --git a/scripts/preprocess_benchmark.py b/scripts/preprocess_benchmark.py index 32a1e22..818b2c7 100644 --- a/scripts/preprocess_benchmark.py +++ b/scripts/preprocess_benchmark.py @@ -10,6 +10,7 @@ def main(input_raw_benchmark_path: str = "benchmark", output_path: str = "tfb.json"): + """Process pre-extracted tasks from Markdown to JSON""" # read in all files ending with .md in the input_raw_benchmark_path tasks: list[BenchmarkTask] = [] From 6bc63d3c6ef56a63357bc90705754a94af04c50d Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Tue, 26 Aug 2025 05:05:54 +0800 Subject: [PATCH 21/28] use 3.12 --- .python-version | 2 +- pyproject.toml | 5 +- uv.lock | 576 +----------------------------------------------- 3 files changed, 11 insertions(+), 572 deletions(-) diff --git a/.python-version b/.python-version index 2c07333..e4fba21 100644 --- a/.python-version +++ b/.python-version @@ -1 +1 @@ -3.11 +3.12 diff --git a/pyproject.toml b/pyproject.toml index f7c321a..e004ec7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,7 +3,7 @@ name = "tfbench" version = "0.1.0" description = "Add your description here" readme = "README.md" -requires-python = ">=3.11" +requires-python = ">=3.12" dependencies = [ "anthropic>=0.49.0", 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--- a/README.md +++ b/README.md @@ -69,7 +69,34 @@ To run all GPT models: uv run run_all.py --option gpt ``` -### Open Source Models with vLLM +### Open Source Models with Ollama + +We use [Ollama](https://ollama.com/) to manage and run the OSS models reported in the Appendix. +We switched to vLLM for better performance and SDK design. +Although the Ollama option is still available, +it is no longer maintained. +We recommend using vLLM instead. + +```sh +curl -fsSL https://ollama.com/install.sh | sh # install ollama, you need sudo for this +ollama serve # start your own instance instead of a system service +``` + +NOTE: we required the ollama version at least 0.9.0 to enable thinking parsers. +We use 0.11.7 for our experiments. + +```sh +> ollama --version +ollama version is 0.11.7 +``` + +Run the benchmark. + +```sh +uv run scripts/experiment_ollama.py -m llama3:8b +``` + +### (WIP) Running Your Model with vLLM #### OpenAI-Compatible Server @@ -97,23 +124,3 @@ VLLM_API_KEY= VLLM_HOST= VLLM_PORT= ``` - -### (_deprecated_) Open Source Models with Ollama - -We use [Ollama](https://ollama.com/) to manage and run the OSS models reported in the Appendix. -We switched to vLLM for better performance and SDK design. -Although the Ollama option is still available, -it is no longer maintained. -We recommend using vLLM instead. - -```sh -curl -fsSL https://ollama.com/install.sh | sh # install ollama, you need sudo for this -ollama serve # start your own instance instead of a system service -uv run scripts/ollama_pull.sh # install required models -``` - -Run the benchmark. - -```sh -uv run scripts/experiment_ollama.py -m llama3:8b -``` diff --git a/src/tfbench/lm/_ollama.py b/src/tfbench/lm/_ollama.py new file mode 100644 index 0000000..948100d --- /dev/null +++ b/src/tfbench/lm/_ollama.py @@ -0,0 +1,41 @@ +from ollama import chat, ChatResponse + +from ._types import LM, LMAnswer + +OLLAMA_TTC_MODELS = [ + "qwen3:30b", + "qwen3:32b", + "qwen3:235b", + "gpt-oss:20b", + "gpt-oss:120b", + "deepseek-r1:32b", + "deepseek-r1:70b", + "magistral:24b", +] + + +class OllamaChat(LM): + """Generate using Ollama's chat API,""" + + def __init__(self, model_name: str, pure: bool = False): + super().__init__(model_name=model_name, pure=pure) + + def _gen(self, prompt: str) -> LMAnswer: + response: ChatResponse = chat( + model="gemma3", + messages=[ + { + "role": "developer", + "content": self.instruction, + }, + { + "role": "user", + "content": prompt, + }, + ], + think=True, + ) + return LMAnswer( + answer=response.message.content, # type: ignore + reasoning_steps=response.message.thinking, # type: ignore + ) diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py index 77e4dd3..1f04808 100644 --- a/src/tfbench/lm/utils.py +++ b/src/tfbench/lm/utils.py @@ -16,6 +16,7 @@ from ._google import GeminiChat, GeminiReasoning, GEMINI_MODELS, GEMINI_TTC_MODELS from ._anthropic import ClaudeChat, ClaudeReasoning, CLAUDE_MODELS, CLAUDE_TTC_MODELS from ._vllm import VLLMChat, VLLMOpenAIChatCompletion +from ._ollama import OllamaChat, OLLAMA_TTC_MODELS from ._google import GeminiReasoningEffort from ._types import ReasoningEffort @@ -87,6 +88,9 @@ def router( effort=cast(ReasoningEffort, effort), ) + if model_name in OLLAMA_TTC_MODELS: + return OllamaChat(model_name=model_name, pure=pure) + # all allow lists are exhausted, use vLLM if use_vllm_server: return VLLMOpenAIChatCompletion(model_name=model_name, pure=pure) From 702bb6ceefc5af237d0b3283fa2c6269d9606b79 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Tue, 26 Aug 2025 06:48:41 +0800 Subject: [PATCH 23/28] fix: ollama model name --- src/tfbench/lm/_ollama.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/tfbench/lm/_ollama.py b/src/tfbench/lm/_ollama.py index 948100d..21a0163 100644 --- a/src/tfbench/lm/_ollama.py +++ b/src/tfbench/lm/_ollama.py @@ -22,10 +22,10 @@ def __init__(self, model_name: str, pure: bool = False): def _gen(self, prompt: str) -> LMAnswer: response: ChatResponse = chat( - model="gemma3", + model=self.model_name, messages=[ { - "role": "developer", + "role": "system", "content": self.instruction, }, { @@ -36,6 +36,6 @@ def _gen(self, prompt: str) -> LMAnswer: think=True, ) return LMAnswer( - answer=response.message.content, # type: ignore - reasoning_steps=response.message.thinking, # type: ignore + answer=response.message.content, + reasoning_steps=response.message.thinking, ) From 6e498dfb3af8628bf79bd46e6f82b31c0dc44e24 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Tue, 26 Aug 2025 06:52:08 +0800 Subject: [PATCH 24/28] fix: ollama model name --- pyproject.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/pyproject.toml b/pyproject.toml index e004ec7..5fad804 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -63,6 +63,7 @@ disable = [ "too-many-statements", "unspecified-encoding", "missing-class-docstring", + "too-few-public-methods", # LM only have 1 public method ] fail-under = 9 max-line-length = 120 From 1bbd562b5c9a8f18f4b57d2ba6034772628bed5f Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Tue, 26 Aug 2025 07:02:01 +0800 Subject: [PATCH 25/28] fix: Gemini use its own EFFORT_TOKEN_MAP --- src/tfbench/lm/_google.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/tfbench/lm/_google.py b/src/tfbench/lm/_google.py index a5503af..4a5a624 100644 --- a/src/tfbench/lm/_google.py +++ b/src/tfbench/lm/_google.py @@ -95,7 +95,7 @@ def _gen(self, prompt: str) -> LMAnswer: config=GenerateContentConfig( system_instruction=[self.instruction], thinking_config=ThinkingConfig( - thinking_budget=EFFORT_TOKEN_MAP[self.effort], + thinking_budget=GEMINI_MAP[self.effort], include_thoughts=True, ), ), From 044c0f44c042d3b3dec8961f3fa60a50889bd998 Mon Sep 17 00:00:00 2001 From: Yifeng He Date: Mon, 25 Aug 2025 16:35:54 -0700 Subject: [PATCH 26/28] remove unused imports --- pyproject.toml | 2 +- src/main.py | 3 +- src/tfbench/__init__.py | 1 - src/tfbench/env.py | 4 +-- src/tfbench/experiment.py | 11 -------- src/tfbench/lm/_anthropic.py | 3 +- src/tfbench/lm/_google.py | 3 +- src/tfbench/lm/_ollama.py | 4 +-- src/tfbench/lm/_openai.py | 2 -- src/tfbench/lm/_types.py | 1 - src/tfbench/lm/_vllm.py | 4 +-- src/tfbench/lm/utils.py | 4 +-- uv.lock | 53 ++++++++++++++++++++++++------------ 13 files changed, 46 insertions(+), 49 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 5fad804..e3a44b7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -24,7 +24,7 @@ dependencies = [ "pytest>=8.0.0", "python-dotenv==1.0.1", "requests==2.32.3", - "returns[compatible-mypy]==0.22.0", + "returns[compatible-mypy]>=0.26.0", "seaborn==0.13.2", "tabulate>=0.9.0", "tenacity>=9.1.2", diff --git a/src/main.py b/src/main.py index fa2c1f2..14bc59b 100755 --- a/src/main.py +++ b/src/main.py @@ -1,5 +1,4 @@ import os -from typing import Callable import json import logging @@ -7,7 +6,7 @@ from funcy import lmap from tqdm import tqdm from dacite import from_dict -from returns.result import ResultE, Success, Failure +from returns.result import ResultE import fire from tfbench.common import ( diff --git a/src/tfbench/__init__.py b/src/tfbench/__init__.py index 0b53434..e69de29 100644 --- a/src/tfbench/__init__.py +++ b/src/tfbench/__init__.py @@ -1 +0,0 @@ -from . import env diff --git a/src/tfbench/env.py b/src/tfbench/env.py index c8e9a6f..f84a2d2 100644 --- a/src/tfbench/env.py +++ b/src/tfbench/env.py @@ -1,6 +1,4 @@ -import os - -from dotenv import load_dotenv, dotenv_values +from dotenv import dotenv_values ENV = dotenv_values(".env") diff --git a/src/tfbench/experiment.py b/src/tfbench/experiment.py index 91b3ce0..1988486 100644 --- a/src/tfbench/experiment.py +++ b/src/tfbench/experiment.py @@ -1,14 +1,3 @@ """ Experiment script for OpenAI models """ - -from typing import Callable -import logging - - -from .lm import get_sys_prompt, MAX_TOKENS - -DEEPSEEK_MODELS = [ - "deepseek-reasoner", - "deepseek-chat", -] diff --git a/src/tfbench/lm/_anthropic.py b/src/tfbench/lm/_anthropic.py index b91200e..6aa444d 100644 --- a/src/tfbench/lm/_anthropic.py +++ b/src/tfbench/lm/_anthropic.py @@ -1,5 +1,4 @@ -from typing import Callable -from anthropic import Anthropic, InternalServerError, NOT_GIVEN +from anthropic import Anthropic from ..env import ENV from ._types import LM, LMAnswer, ReasoningEffort, EFFORT_TOKEN_MAP from .settings import MAX_TOKENS diff --git a/src/tfbench/lm/_google.py b/src/tfbench/lm/_google.py index 4a5a624..11cad9b 100644 --- a/src/tfbench/lm/_google.py +++ b/src/tfbench/lm/_google.py @@ -1,7 +1,6 @@ """Inference helper for Google Gemini""" -from typing import Literal, Mapping -from enum import Enum +from typing import Literal from google import genai from google.genai.types import GenerateContentConfig, ThinkingConfig diff --git a/src/tfbench/lm/_ollama.py b/src/tfbench/lm/_ollama.py index 21a0163..9e848e6 100644 --- a/src/tfbench/lm/_ollama.py +++ b/src/tfbench/lm/_ollama.py @@ -36,6 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version --- .github/workflows/mypy.yml | 6 ++- .github/workflows/pylint.yml | 5 +- pyproject.toml | 9 ++-- src/tfbench/lm/_google.py | 4 +- uv.lock | 92 ++++++------------------------------ 5 files changed, 28 insertions(+), 88 deletions(-) diff --git a/.github/workflows/mypy.yml b/.github/workflows/mypy.yml index 636012e..cda6049 100644 --- a/.github/workflows/mypy.yml +++ b/.github/workflows/mypy.yml @@ -17,6 +17,8 @@ jobs: - name: Set up Python run: uv sync + - name: install mypy + run: uv pip install mypy + - name: Type Check Source Code - run: uv run mypy src - \ No newline at end of file + run: mypy src diff --git a/.github/workflows/pylint.yml b/.github/workflows/pylint.yml index 023055e..3161899 100644 --- a/.github/workflows/pylint.yml +++ b/.github/workflows/pylint.yml @@ -16,6 +16,9 @@ jobs: - name: Set up Python run: uv sync + + - name: Install Pylint + run: uv pip install pylint - name: Lint Source Code - run: uv run pylint src \ No newline at end of file + run: pylint src 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pylint src