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d1ce356 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 | #!/usr/bin/env python3
from __future__ import annotations
import json
import os
import tempfile
from pathlib import Path
from biomni.agent import A1
PROJECT_ROOT = Path(__file__).resolve().parent
MCP_ROOT = PROJECT_ROOT / "biomni_web" / "backend" / "data" / "mcp_generated"
CONFIG_PATH = PROJECT_ROOT / "strata_mcp_smoke_config_shim.yaml"
# Start with a small set of MCP servers that have already shown successful tool discovery.
SELECTED_SERVERS = [
"bioconductor-cardspa",
"bioconductor-catscradle",
"jq",
]
def find_server_script(server_name: str) -> Path:
server_dir = MCP_ROOT / f"mcp_{server_name}" / "app"
shim_candidates = sorted(server_dir.glob("*_shim_server.py"))
if shim_candidates:
return shim_candidates[0].resolve()
raw_candidates = sorted(
candidate
for candidate in server_dir.glob("*_server.py")
if not candidate.name.endswith("_shim_server.py")
)
if raw_candidates:
return raw_candidates[0].resolve()
raise FileNotFoundError(f"No MCP server script found for {server_name}: {server_dir}")
def write_smoke_config(selected_servers: list[str]) -> Path:
lines = [
"# Auto-generated smoke-test MCP config",
"",
"mcp_servers:",
]
python_cmd = os.getenv("BIOMNI_MCP_PYTHON", os.sys.executable)
for server_name in selected_servers:
server_script = find_server_script(server_name)
lines.extend(
[
f" {server_name}:",
" enabled: true",
f' command: ["{python_cmd}", "{server_script}"]',
f' description: "Smoke-test MCP server for {server_name}"',
]
)
CONFIG_PATH.write_text("\n".join(lines) + "\n", encoding="utf-8")
return CONFIG_PATH
def build_agent() -> A1:
# The smoke tests below directly call MCP tool wrappers, so a real LLM key is
# only needed if you later switch this script back to agent.go(...).
api_key = os.getenv("DEEPSEEK_API_KEY") or os.getenv("OPENAI_API_KEY") or "EMPTY"
base_url = os.getenv("DEEPSEEK_BASE_URL", "https://api.deepseek.com/v1")
model = os.getenv("DEEPSEEK_MODEL_NAME", "deepseek-chat")
return A1(
path="./data",
llm=model,
source="Custom",
base_url=base_url,
api_key=api_key,
expected_data_lake_files=[],
)
def run_smoke_tests(agent: A1) -> list[dict]:
temp_dir = Path(tempfile.gettempdir()) / "biomni_mcp_smoke"
temp_dir.mkdir(parents=True, exist_ok=True)
missing_input = temp_dir / "missing_input.rds"
test_cases = [
{
"tool_name": "cardspa",
"task": "Run cardspa on a placeholder spatial object to verify MCP invocation.",
"kwargs": {
"sce_object": str(missing_input),
"output_path": str(temp_dir / "cardspa_output.rds"),
"phenotype_col": "cell_type",
},
},
{
"tool_name": "catscradle_build_neighborhoods",
"task": "Build neighborhoods from a placeholder RDS file to verify CatsCradle MCP invocation.",
"kwargs": {
"input_rds": str(missing_input),
"output_rds": str(temp_dir / "catscradle_neighborhoods.rds"),
},
},
{
"tool_name": "catscradle_gene_centric_analysis",
"task": "Run gene-centric analysis on a placeholder RDS file to verify CatsCradle MCP invocation.",
"kwargs": {
"input_rds": str(missing_input),
"output_rds": str(temp_dir / "catscradle_gene_centric.rds"),
},
},
{
"tool_name": "jq_process_json",
"task": "Run jq on a small real JSON file to verify end-to-end MCP tool execution.",
"kwargs": {
"jq_filter": "[.[] | .score] | add / length",
"input_files": [str(_write_demo_json(temp_dir))],
},
},
]
results: list[dict] = []
for case in test_cases:
tool_name = case["tool_name"]
wrapper = agent.get_custom_tool(tool_name)
if wrapper is None:
results.append(
{
"tool_name": tool_name,
"task": case["task"],
"status": "not_registered",
"detail": "Tool wrapper not found after MCP registration.",
}
)
continue
try:
tool_result = wrapper(**case["kwargs"])
results.append(
{
"tool_name": tool_name,
"task": case["task"],
"status": "called",
"detail": tool_result,
}
)
except Exception as exc: # pragma: no cover - smoke test reporting
results.append(
{
"tool_name": tool_name,
"task": case["task"],
"status": "call_failed",
"detail": str(exc),
}
)
return results
def _write_demo_json(output_dir: Path) -> Path:
demo_file = output_dir / "demo_scores.json"
payload = [
{"name": "sample_a", "score": 10},
{"name": "sample_b", "score": 25},
{"name": "sample_c", "score": 40},
]
demo_file.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
return demo_file
def run_biomni_real_task(agent: A1) -> str:
temp_dir = Path(tempfile.gettempdir()) / "biomni_mcp_smoke"
temp_dir.mkdir(parents=True, exist_ok=True)
demo_file = _write_demo_json(temp_dir)
query = (
"Use MCP tool jq_process_json to process the JSON file "
f"'{demo_file}'. "
"Compute three things: "
"(1) average score, "
"(2) max score item name, "
"(3) number of records. "
"Please call the MCP tool directly and then report final numeric results."
)
_, final_answer = agent.go(query)
return final_answer
def main() -> None:
config_path = write_smoke_config(SELECTED_SERVERS)
print(f"Smoke-test config written to: {config_path}")
agent = build_agent()
agent.add_mcp(config_path=str(config_path))
registered_tools = sorted(agent.list_custom_tools())
print("\n===== REGISTERED MCP TOOLS =====")
for tool_name in registered_tools:
print(tool_name)
print("\n===== SMOKE TEST RESULTS =====")
for result in run_smoke_tests(agent):
print(json.dumps(result, ensure_ascii=False, indent=2))
print("\n===== BIOMNI REAL TASK (MCP-DRIVEN) =====")
try:
final_answer = run_biomni_real_task(agent)
print(final_answer)
except Exception as exc: # pragma: no cover - runtime integration reporting
print(f"Biomni real-task run failed: {exc}")
if __name__ == "__main__":
main()
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