diff --git a/GEMINI.md b/GEMINI.md new file mode 100644 index 0000000..1c02bbd --- /dev/null +++ b/GEMINI.md @@ -0,0 +1,64 @@ +# Gemini Report: SciCode + +This document provides an overview of the SciCode project, focusing on the supported models and how to run them. + +## Supported Models + +The SciCode project uses [OpenRouter](https://openrouter.ai/) to support a wide variety of Large Language Models. The core logic for model integration is located in `src/scicode/gen/models.py`. + +Any model available through the OpenRouter API can be used by providing its model identifier (e.g., `openai/gpt-4o`, `anthropic/claude-3-opus`). For a list of available models, please refer to the [OpenRouter documentation](https://openrouter.ai/docs#models). + +A `dummy` model is also available for testing purposes. + +## Running the Models + +The recommended way to evaluate a new model is by using `inspect_ai`, as suggested in the `README.md`. + +### Using `inspect_ai` (Recommended) + +1. **Clone the repository:** + ```bash + git clone git@github.com:scicode-bench/SciCode.git + cd SciCode + ``` + +2. **Install the package:** + ```bash + pip install -e . + ``` + +3. **Download test data:** + Download the numeric test results from the link provided in the `README.md` and save them as `./eval/data/test_data.h5`. + +4. **Configure API Keys:** + Set your OpenRouter API key as an environment variable. See the "Configuration" section below for more details. + +5. **Run the evaluation:** + You can run the evaluation using the `inspect` command. The model name should be a valid OpenRouter model identifier. + + ```bash + inspect eval eval/inspect_ai/scicode.py --model openai/gpt-4o --temperature 0 + ``` + +### Deprecated Method + +A deprecated two-step process is also available: + +1. **Generate code:** + ```bash + python eval/scripts/gencode.py --model + ``` +2. **Test the generated code:** + ```bash + python eval/scripts/test_generated_code.py + ``` + +## Configuration + +To use the models, you need to set your OpenRouter API key as an environment variable. + +```bash +export OPENROUTER_KEY="your-openrouter-api-key" +``` + +You can add this line to your shell's startup file (e.g., `~/.bashrc` or `~/.zshrc`) to make it permanent. \ No newline at end of file diff --git a/README.md b/README.md index 4e8327d..dcf7de8 100644 --- a/README.md +++ b/README.md @@ -68,10 +68,12 @@ Scicode has been integrated with `inspect_ai` for easier and faster model evalua ```bash cd eval/inspect_ai -export OPENAI_API_KEY=your-openai-api-key +export OPENROUTER_KEY=your-openrouter-api-key inspect eval scicode.py --model openai/gpt-4o --temperature 0 ``` +The model name should be a valid [OpenRouter](https://openrouter.ai/docs#models) model identifier (e.g., `openai/gpt-4o`, `anthropic/claude-3-opus`, `google/gemini-pro`). + 💡 For more detailed information of using `inspect_ai`, see [`eval/inspect_ai` readme](eval/inspect_ai/) ## Instructions to evaluate a new model in two steps (deprecated) diff --git a/eval/inspect_ai/scicode.py b/eval/inspect_ai/scicode.py index 8537b6a..5308aed 100644 --- a/eval/inspect_ai/scicode.py +++ b/eval/inspect_ai/scicode.py @@ -343,8 +343,8 @@ async def solve(state: TaskState, generate: Generate) -> TaskState: result = await generate(state=state_copy) response_from_llm = result.output.completion # ===Model Generation=== - except: - print(f"Failed to generate response for problem {prob_id} step {idx+1}.") + except Exception as e: + print(f"Failed to generate response for problem {prob_id} step {idx+1}. Error: {e}") response_from_llm = generate_dummy_response(prompt) prompt_assistant.register_previous_response( prob_data=state.metadata, diff --git a/eval/scripts/gencode.py b/eval/scripts/gencode.py index 4f2d1c5..cb2164d 100644 --- a/eval/scripts/gencode.py +++ b/eval/scripts/gencode.py @@ -6,7 +6,7 @@ get_function_from_code, read_from_hf_dataset, ) -from scicode.gen.models import extract_python_script, get_model_function +from scicode.gen.models import extract_python_script, get_model_response DEFAULT_PROMPT_TEMPLATE = Path("eval", "data", "background_comment_template.txt").read_text() BACKGOUND_PROMPT_TEMPLATE = Path("eval", "data", "multistep_template.txt").read_text() @@ -14,12 +14,11 @@ class Gencode: def __init__(self, model: str, output_dir: Path, - prompt_dir: Path, with_background: bool, temperature: float): + prompt_dir: Path, with_background: bool): self.model = model self.output_dir = output_dir self.prompt_dir = prompt_dir self.with_background = with_background - self.temperature = temperature self.previous_llm_code = [] def _get_background_dir(self): @@ -90,13 +89,8 @@ def generate_response_with_steps( if save: self.save_prompt_with_steps(prob_data, prompt, num_steps) - model_kwargs = {} - if "claude" in model: - model_kwargs["max_tokens"] = 4096 - model_kwargs["temperature"] = self.temperature # write the response to a file if it doesn't exist - model_fct = get_model_function(model, **model_kwargs) - response_from_llm = model_fct(prompt) + response_from_llm = get_model_response(prompt, model=model) self.previous_llm_code[num_steps - 1] = extract_python_script(response_from_llm) self.save_response_with_steps(prob_data, response_from_llm, previous_code, num_steps) @@ -174,25 +168,19 @@ def get_cli() -> argparse.ArgumentParser: action="store_true", help="Include problem background if enabled", ) - parser.add_argument( - "--temperature", - type=float, - default=0, - help="Generation temperature", - ) return parser -def main(model: str, - split: str, - output_dir: Path, - prompt_dir: Path, - with_background: bool, - temperature: float +def main( + model: str = "gpt-4o", + split: str = "test", + output_dir: Path = Path("eval_results", "generated_code"), + prompt_dir: Path = Path("eval_results", "prompt"), + with_background: bool = False, ) -> None: gcode = Gencode( model=model, output_dir=output_dir, - prompt_dir=prompt_dir, with_background=with_background, temperature=temperature + prompt_dir=prompt_dir, with_background=with_background ) prompt_template = BACKGOUND_PROMPT_TEMPLATE if with_background else DEFAULT_PROMPT_TEMPLATE data = read_from_hf_dataset(split) @@ -209,4 +197,4 @@ def main(model: str, if __name__ == "__main__": args = get_cli().parse_args() - main(**vars(args)) + main(**vars(args)) \ No newline at end of file diff --git a/src/scicode/gen/models.py b/src/scicode/gen/models.py index 00f6181..703a208 100644 --- a/src/scicode/gen/models.py +++ b/src/scicode/gen/models.py @@ -1,149 +1,61 @@ -from functools import partial from openai import OpenAI -import anthropic -import google.generativeai as genai -import config import re import os -import litellm -from litellm.utils import validate_environment as litellm_validate_environment -from scicode import keys_cfg_path from scicode.utils.log import get_logger logger = get_logger("models") -def get_config(): - if not keys_cfg_path.exists(): - raise FileNotFoundError(f"Config file not found: {keys_cfg_path}") - return config.Config(str(keys_cfg_path)) +def get_model_response(prompt: str, *, model: str) -> str: + """Call the OpenRouter api to generate a response, or use a dummy for testing.""" + if model == "dummy": + return generate_dummy_response(prompt) -def generate_litellm_response(prompt: str, *, model: str, **kwargs) -> str: - """Call the litellm api to generate a response""" - # litellm expects all keys as env variables - config = get_config() - for key, value in config.as_dict().items(): - if key in os.environ and os.environ[key] != value: - logger.warning(f"Overwriting {key} from config with environment variable") - else: - os.environ[key] = value - # Let's validate that we have everythong for this model - env_validation = litellm_validate_environment(model) - if not env_validation.get("keys_in_environment") or env_validation.get("missing_keys", []): - msg = f"Environment validation for litellm failed for model {model}: {env_validation}" - raise ValueError(msg) - response = litellm.completion( - model=model, - messages = [ - {"role": "user", "content": prompt}, - ], - **kwargs, - ) - return response.choices[0].message.content + key = os.getenv("OPENROUTER_KEY") + if not key: + raise ValueError( + "OPENROUTER_API_KEY environment variable not found. Please set it." + ) -def generate_openai_response(prompt: str, *, model="gpt-4-turbo-2024-04-09", - temperature: float = 0) -> str: - """call the openai api to generate a response""" - key: str = get_config()["OPENAI_KEY"] # type: ignore - client = OpenAI(api_key=key) - completion = client.chat.completions.create( - model=model, - temperature=temperature, - messages=[ - {"role": "system", "content": "You are a helpful assistant."}, - {"role": "user", "content": prompt}, - ], + client = OpenAI( + base_url="https://openrouter.ai/api/v1", + api_key=key, ) - return completion.choices[0].message.content - - -def generate_anthropic_response(prompt, *, model="claude-3-opus-20240229", - max_tokens: int = 4096, temperature: float = 0) -> str: - """call the anthropic api to generate a response""" - key: str = get_config()["ANTHROPIC_KEY"] # type: ignore - client = anthropic.Anthropic(api_key=key) - message = client.messages.create( - model=model, - temperature=temperature, - max_tokens=max_tokens, - messages=[ - {"role": "user", "content": prompt}, - ], - ) - return message.content[0].text - - -def generate_google_response(prompt: str, *, model: str = "gemini-pro", - temperature: float = 0) -> str: - """call the api to generate a response""" - key: str = get_config()["GOOGLE_KEY"] # type: ignore - genai.configure(api_key=key) - model = genai.GenerativeModel(model_name=model) - response = model.generate_content(prompt, - generation_config=genai.GenerationConfig(temperature=temperature), - # safety_settings=[ - # { - # "category": "HARM_CATEGORY_HARASSMENT", - # "threshold": "BLOCK_NONE", - # }, - # { - # "category": "HARM_CATEGORY_HATE_SPEECH", - # "threshold": "BLOCK_NONE", - # }, - # { - # "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", - # "threshold": "BLOCK_NONE", - # }, - # { - # "category": "HARM_CATEGORY_DANGEROUS_CONTENT", - # "threshold": "BLOCK_NONE" - # } - # ] - ) try: - return response.text - except ValueError: - print(f'prompt:\n{prompt}') - # If the response doesn't contain text, check if the prompt was blocked. - print(f'prompt feedback:\n{response.prompt_feedback}') - # Also check the finish reason to see if the response was blocked. - print(f'finish reason:\n{response.candidates[0].finish_reason.name}') - # If the finish reason was SAFETY, the safety ratings have more details. - print(f'safety rating:\n{response.candidates[0].safety_ratings}') - raise ValueError("Generate response failed.") - - -def get_model_function(model: str, **kwargs): - """Return the appropriate function to generate a response based on the model""" - if model.startswith("litellm/"): - model = model.removeprefix("litellm/") - fct = generate_litellm_response - elif "gpt" in model: - fct = generate_openai_response - elif "claude" in model: - fct = generate_anthropic_response - elif "gemini" in model: - fct = generate_google_response - elif model == "dummy": - fct = generate_dummy_response - else: - raise ValueError(f"Model {model} not supported") - return partial(fct, model=model, **kwargs) + completion = client.chat.completions.create( + model=model, + temperature=0, + max_tokens=4096, + messages=[ + {"role": "system", "content": "You are a helpful assistant."}, + {"role": "user", "content": prompt}, + ], + ) + except Exception as e: + logger.error(f"Error calling OpenRouter API: {e}") + raise + + return completion.choices[0].message.content -def generate_dummy_response(prompt: str, **kwargs) -> str: +def generate_dummy_response(prompt: str) -> str: """Used for testing as a substitute for actual models""" return "Blah blah\n```python\nprint('Hello, World!')\n```\n" def extract_python_script(response: str): # We will extract the python script from the response - if '```' in response: - python_script = response.split("```python")[1].split("```")[0] if '```python' in response else response.split('```')[1].split('```')[0] + if "```" in response: + python_script = ( + response.split("```python")[1].split("```")[0] + if "```python" in 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