danaaubakirova HF Staff
Model card: move the agent-tool section before Limitations; add examples and the carbon-dna skill
b3f11f8 verified | """Use Carbon-X as a tool for an Inspect react() agent. | |
| Serve Carbon-X first: vllm serve HuggingFaceBio/Carbon-X --trust-remote-code | |
| Then run: python inspect_agent.py | |
| """ | |
| from inspect_ai import Task, eval, task | |
| from inspect_ai.agent import as_solver, react | |
| from inspect_ai.dataset import Sample | |
| from inspect_ai.scorer import includes | |
| from inspect_ai.solver import solver | |
| from inspect_ai.tool import ToolError, tool | |
| from inspect_ai.util import store | |
| from openai import AsyncOpenAI | |
| carbon = AsyncOpenAI(base_url="http://localhost:8000/v1", api_key="EMPTY") | |
| def ask_carbon(): | |
| async def execute(question: str, sequences: list[str], context: str = "") -> str: | |
| """Ask Carbon-X, a DNA language model, about this task's DNA sequences. Its answers are predictions. | |
| Args: | |
| question: One self-contained question. | |
| sequences: Names of the sequences to send, as given in the task. | |
| context: Known facts, such as the gene, positions or alleles. | |
| """ | |
| dna = store().get("sequences") | |
| if missing := [name for name in sequences if name not in dna]: | |
| raise ToolError(f"Unknown sequence names: {missing}. Available: {list(dna)}") | |
| parts = [context, question] if context else [question] | |
| parts += [f"{name}: <dna>{dna[name]}</dna>" for name in sequences] | |
| response = await carbon.chat.completions.create( | |
| model="HuggingFaceBio/Carbon-X", | |
| messages=[{"role": "user", "content": "\n\n".join(parts)}], | |
| max_tokens=4096, | |
| extra_body={"chat_template_kwargs": {"enable_thinking": False}}, | |
| ) | |
| return response.choices[0].message.content | |
| return execute | |
| def load_sequences(): | |
| async def solve(state, generate): | |
| store().set("sequences", state.metadata["sequences"]) # the tool reads DNA from here | |
| return state | |
| return solve | |
| def carbon_agent(): | |
| sample = Sample( | |
| input="Sequence `variant` differs from `reference` at position 20 (A>T). Is the variant benign or pathogenic?", | |
| target="pathogenic", | |
| metadata={"sequences": { | |
| "reference": "ATGGTGCATCTGACTCCTGAGGAGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGG", | |
| "variant": "ATGGTGCATCTGACTCCTGTGGAGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGG", | |
| }}, | |
| ) | |
| agent = react(prompt="Consult Carbon-X with the ask_carbon tool before you answer.", tools=[ask_carbon()]) | |
| return Task(dataset=[sample], solver=[load_sequences(), as_solver(agent)], scorer=includes()) | |
| eval(carbon_agent(), model="openai/gpt-5") # any Inspect model with tool calling as the agent | |