System and kickoff prompts for the research agent.
These are plain strings with no LLM dependency, so they can be unit-tested directly.
Compose the full system prompt from the base template and task-specific sections.
Source code in src/agentic_ml/research/prompts.py
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53 | def build_system_prompt(task: Task, schema_text: str, config: ResearchConfig) -> str:
"""Compose the full system prompt from the base template and task-specific sections."""
sections = [
_BASE_INSTRUCTIONS.format(primary_metric=config.primary_metric),
f"## Task\n{task.role_description()}",
f"## Guidance\n{task.guidance()}",
f"## Model contract\n{task.model_contract_doc()}",
f"## Dataset schema\n{schema_text}",
(
"## Objective\n"
f"Primary metric: {config.primary_metric} "
f"({'maximize' if config.maximize else 'minimize'}). "
f"Also tracked: {', '.join(config.metrics)}."
),
]
return "\n\n".join(sections)
|
Build the first user message that starts the loop.
Source code in src/agentic_ml/research/prompts.py
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73 | def build_kickoff_prompt(config: ResearchConfig) -> str:
"""Build the first user message that starts the loop."""
lines = [
f"Run up to {config.iterations} experiment iterations to optimize {config.primary_metric}.",
(
"This is a fresh iteration budget starting now, independent of any previous run: "
"if an earlier tool result in this conversation said the budget was spent and to "
"call finish_research, that no longer applies — you now have "
f"{config.iterations} new iterations available."
),
]
if config.ideas:
lines.append(f"The user specifically wants you to explore these ideas:\n{config.ideas}")
lines.append(
"Start by proposing your first trial. If you have already tried something, "
"continue from where you left off."
)
return "\n\n".join(lines)
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