File size: 4,445 Bytes
e918a5c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 | #!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# OpenAI tool-calling agent for pathway_analysis_env (in-process orchestrator).
#
# Usage:
# export OPENAI_API_KEY=...
# PYTHONPATH=src:envs uv run python examples/pathway_agent_loop.py \
# --case toy_case_001.json
from __future__ import annotations
import argparse
import asyncio
import json
import os
import sys
from pathway_analysis_env.agent_openai_tools import (
OPENAI_TOOLS,
observation_to_tool_result_content,
tool_call_to_pathway_action,
)
from pathway_analysis_env.models import PathwayAction
from pathway_analysis_env.server.pathway_environment import PathwayEnvironment
SYSTEM_PROMPT = """You are a computational biologist agent operating a pathway analysis environment.
Required workflow (eval mode):
1. understand_experiment_design and/or inspect_dataset — learn groups and sample layout.
2. run_differential_expression — set reference (baseline) vs alternate (treatment) conditions.
3. run_pathway_enrichment — ORA on DE genes (do not pass a custom gene_list).
4. Optionally compare_pathways between two top pathway names.
5. submit_answer — one pathway hypothesis string supported by ORA.
Rules:
- Never guess without running DE and ORA first.
- Use condition names exactly as returned in available_conditions.
- For submit_answer, name a specific pathway (e.g. from top_pathways), not a long essay.
"""
async def run_episode(
case_file: str,
model: str,
max_turns: int,
*,
strict: bool,
) -> dict:
try:
from openai import AsyncOpenAI
except ImportError as exc:
raise SystemExit("Install openai: uv add openai") from exc
if not os.environ.get("OPENAI_API_KEY"):
print("Warning: OPENAI_API_KEY not set", file=sys.stderr)
client = AsyncOpenAI()
env = PathwayEnvironment(case_file=case_file)
obs = env.reset(orchestrator_mode=True, strict=strict)
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
{
"role": "user",
"content": (
f"Episode started for case {case_file}. "
f"Conditions: {obs.available_conditions}. "
f"{obs.message}"
),
},
]
for turn in range(max_turns):
response = await client.chat.completions.create(
model=model,
messages=messages,
tools=OPENAI_TOOLS,
tool_choice="auto",
)
msg = response.choices[0].message
if not msg.tool_calls:
messages.append({"role": "assistant", "content": msg.content or ""})
if env.state.is_done:
break
continue
messages.append(msg.model_dump())
for tc in msg.tool_calls:
action = tool_call_to_pathway_action(
name=tc.function.name,
arguments_json=tc.function.arguments,
)
step_obs = env.step(action)
messages.append(
{
"role": "tool",
"tool_call_id": tc.id,
"content": observation_to_tool_result_content(step_obs),
}
)
if step_obs.done:
return {
"turns": turn + 1,
"done": True,
"episode_outcome": env.episode_outcome,
"last_message": step_obs.message,
"steps": env.state.step_count,
}
return {
"turns": max_turns,
"done": env.state.is_done,
"episode_outcome": env.episode_outcome,
"steps": env.state.step_count,
}
def main() -> None:
parser = argparse.ArgumentParser(description="LLM agent on pathway_analysis_env")
parser.add_argument("--case", default="toy_case_001.json")
parser.add_argument("--model", default="gpt-4o-mini")
parser.add_argument("--max-turns", type=int, default=24)
parser.add_argument("--strict", action="store_true")
args = parser.parse_args()
result = asyncio.run(
run_episode(args.case, args.model, args.max_turns, strict=args.strict)
)
print(json.dumps(result, indent=2))
outcome = result.get("episode_outcome") or {}
if outcome.get("correct"):
sys.exit(0)
sys.exit(1 if result.get("done") else 2)
if __name__ == "__main__":
main()
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