diff --git a/pyproject.toml b/pyproject.toml
index d6497c2..4235de8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,11 +34,11 @@ dependencies = [
"tenacity>=9.1.2",
"tiktoken==0.7.0",
"tqdm>=4.66.2",
+ "transformers[torch]>=4.55.4",
"tree-sitter==0.22.3",
"tree-sitter-haskell==0.21.0",
"types-deprecated>=1.2.15.20250304",
"types-requests>=2.31.0",
- "vllm>=0.10.1.1",
]
[build-system]
diff --git a/src/main.py b/src/main.py
index 03cf67a..0357ece 100755
--- a/src/main.py
+++ b/src/main.py
@@ -18,8 +18,8 @@ def main(
def _run(pure: bool):
results: list[EvalResult] = []
split = "pure" if pure else "base"
+ result_dir = abspath(pjoin("results", model, split))
for i in range(n_repeats):
- result_dir = abspath(pjoin("results", model, split))
os.makedirs(result_dir, exist_ok=True)
result_file = pjoin(result_dir, f"run-{i}.jsonl")
r = run_one_model(
diff --git a/src/tfbench/env.py b/src/tfbench/env.py
index f84a2d2..f0fa17c 100644
--- a/src/tfbench/env.py
+++ b/src/tfbench/env.py
@@ -1,5 +1,3 @@
-from dotenv import dotenv_values
+from dotenv import load_dotenv
-ENV = dotenv_values(".env")
-
-assert ENV, "No .env file found! Please create one with the required variables."
+load_dotenv(override=True) # override existing env vars with those in .env
diff --git a/src/tfbench/experiment.py b/src/tfbench/experiment.py
index a49e8e4..7020b09 100644
--- a/src/tfbench/experiment.py
+++ b/src/tfbench/experiment.py
@@ -31,7 +31,6 @@ def run_one_model(
EvalResult: evaluation result including accuracy
"""
client = router(model, pure, effort)
- assert client is not None, f"Failed to create client for {model}."
tasks = load_tfb_from_hf("pure" if pure else "base")
gen_results: list[LMAnswer | None] = []
diff --git a/src/tfbench/lm/_hf.py b/src/tfbench/lm/_hf.py
new file mode 100644
index 0000000..711aeab
--- /dev/null
+++ b/src/tfbench/lm/_hf.py
@@ -0,0 +1,53 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+from ._types import LM, LMAnswer
+
+
+def extract_thinking_content(output: str) -> tuple[str, str | None]:
+ """Extract the thinking content and the final answer from the model output.
+ based on and tags.
+
+ Args:
+ output (str): The model output.
+ Returns:
+ tuple[str, str | None]: The thinking content and the final answer.
+ """
+ if "" in output and "" in output:
+ thinking_content = output.split("")[1].split("")[0].strip()
+ content = output.split("")[-1].strip()
+ return content, thinking_content
+
+ return output, None
+
+
+class HFChat(LM):
+
+ def __init__(self, model_name: str, pure: bool = False):
+ super().__init__(model_name=model_name, pure=pure)
+
+ # load the tokenizer and the model
+ self.tokenizer = AutoTokenizer.from_pretrained(model_name)
+ self.model = AutoModelForCausalLM.from_pretrained(
+ model_name, torch_dtype="auto", device_map="auto"
+ )
+
+ def _gen(self, prompt: str) -> LMAnswer:
+ messages = [
+ {"role": "system", "content": self.instruction},
+ {"role": "user", "content": prompt},
+ ]
+ text = self.tokenizer.apply_chat_template(
+ messages,
+ tokenize=False,
+ add_generation_prompt=True,
+ )
+
+ model_inputs = self.tokenizer([text], return_tensors="pt").to(self.model.device)
+
+ # conduct text completion
+ generated_ids = self.model.generate(**model_inputs, max_new_tokens=32768)
+ output_ids = generated_ids[0][len(model_inputs.input_ids[0]) :].tolist()
+ output = self.tokenizer.decode(output_ids, skip_special_tokens=True).strip("\n")
+
+ content, thinking_content = extract_thinking_content(output)
+ return LMAnswer(answer=content, reasoning_steps=thinking_content)
diff --git a/src/tfbench/lm/_vllm.py b/src/tfbench/lm/_vllm.py
deleted file mode 100644
index dcf8e53..0000000
--- a/src/tfbench/lm/_vllm.py
+++ /dev/null
@@ -1,70 +0,0 @@
-from vllm import LLM
-from vllm.entrypoints.chat_utils import ChatCompletionMessageParam
-
-from openai import OpenAI
-
-from ..env import ENV
-from ._types import LM, LMAnswer, NoneResponseError
-
-
-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:
- """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)
-
-
-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
- content = message.content
- if content is None:
- raise NoneResponseError(self.model_name)
-
- return LMAnswer(
- answer=content,
- reasoning_steps=(
- message.reasoning_content # type: ignore
- if hasattr(message, "reasoning_content")
- else None
- ),
- )
diff --git a/src/tfbench/lm/utils.py b/src/tfbench/lm/utils.py
index 4f62b5d..2864a23 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 ._ollama import OllamaChat, OLLAMA_TTC_MODELS
+from ._hf import HFChat
from ._google import GeminiReasoningEffort
from ._types import ReasoningEffort
@@ -47,7 +48,7 @@ def router(
model_name: str,
pure: bool,
effort: str | None = None,
-) -> LM | 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)
@@ -89,7 +90,7 @@ def router(
if model_name in OLLAMA_TTC_MODELS:
return OllamaChat(model_name=model_name, pure=pure)
- return None
+ return HFChat(model_name=model_name, pure=pure)
def extract_response(response: ResultE[LMAnswer]) -> str:
diff --git a/uv.lock b/uv.lock
index 507b261..c246bfa 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2,6 +2,24 @@ version = 1
revision = 1
requires-python = ">=3.12"
+[[package]]
+name = "accelerate"
+version = "1.10.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "huggingface-hub" },
+ { name = "numpy" },
+ { name = "packaging" },
+ { name = "psutil" },
+ { name = "pyyaml" },
+ { name = "safetensors" },
+ { name = "torch" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/b1/72/ff3961c19ee395c3d30ac630ee77bfb0e1b46b87edc504d4f83bb4a89705/accelerate-1.10.1.tar.gz", hash = "sha256:3dea89e433420e4bfac0369cae7e36dcd6a56adfcfd38cdda145c6225eab5df8", size = 392446 }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/5f/a0/d9ef19f780f319c21ee90ecfef4431cbeeca95bec7f14071785c17b6029b/accelerate-1.10.1-py3-none-any.whl", hash = "sha256:3621cff60b9a27ce798857ece05e2b9f56fcc71631cfb31ccf71f0359c311f11", size = 374909 },
+]
+
[[package]]
name = "aiohappyeyeballs"
version = "2.6.1"
@@ -116,15 +134,6 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213 },
]
-[[package]]
-name = "astor"
-version = "0.8.1"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/5a/21/75b771132fee241dfe601d39ade629548a9626d1d39f333fde31bc46febe/astor-0.8.1.tar.gz", hash = "sha256:6a6effda93f4e1ce9f618779b2dd1d9d84f1e32812c23a29b3fff6fd7f63fa5e", size = 35090 }
-wheels = [
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-]
-
[[package]]
name = "attrs"
version = "25.3.0"
@@ -134,50 +143,6 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/77/06/bb80f5f86020c4551da315d78b3ab75e8228f89f0162f2c3a819e407941a/attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3", size = 63815 },
]
-[[package]]
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-version = "1.0.5"
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