atropos/environments/community/protein_design/models/alphafold2_multimer.py
Shannon Sands 54967ecae9 linting
2025-05-27 12:15:15 +10:00

427 lines
18 KiB
Python

import asyncio
import json
import logging
from typing import Any, Dict, List, Optional, Tuple
import aiohttp
logger = logging.getLogger(__name__)
DEFAULT_URL = "https://health.api.nvidia.com/v1/biology/deepmind/alphafold2-multimer"
DEFAULT_STATUS_URL = "https://health.api.nvidia.com/v1/status"
def _split_pdb_content(concatenated_pdb_str: str) -> List[str]:
"""
Splits a string containing concatenated PDB file contents.
Assumes models are separated by "ENDMDL" or just "END" for the last/single model.
"""
pdbs = []
current_pdb_lines = []
if not concatenated_pdb_str:
return []
for line in concatenated_pdb_str.splitlines(keepends=True):
current_pdb_lines.append(line)
if line.startswith("ENDMDL") or line.startswith("END "):
pdbs.append("".join(current_pdb_lines).strip())
current_pdb_lines = []
if current_pdb_lines:
remaining_pdb = "".join(current_pdb_lines).strip()
if remaining_pdb:
pdbs.append(remaining_pdb)
return [pdb for pdb in pdbs if pdb]
def calculate_plddt_from_pdb_string(
pdb_string: str,
) -> Tuple[float, List[float], Dict[str, List[float]]]:
total_plddt = 0.0
ca_atom_count = 0
plddt_scores_per_ca: List[float] = []
plddt_scores_per_chain: Dict[str, List[float]] = {}
for line in pdb_string.splitlines():
if line.startswith("ATOM"):
atom_name = line[12:16].strip()
if atom_name == "CA":
try:
plddt_value = float(line[60:66].strip())
total_plddt += plddt_value
plddt_scores_per_ca.append(plddt_value)
ca_atom_count += 1
chain_id = line[21:22].strip()
if chain_id not in plddt_scores_per_chain:
plddt_scores_per_chain[chain_id] = []
plddt_scores_per_chain[chain_id].append(plddt_value)
except ValueError:
pass
except IndexError:
pass
if ca_atom_count == 0:
return 0.0, [], {}
average_plddt = total_plddt / ca_atom_count
return average_plddt, plddt_scores_per_ca, plddt_scores_per_chain
async def _process_pdb_and_scores_from_api(
pdb_contents: List[str],
job_id: str,
api_response_json: Optional[Dict[str, Any]] = None,
) -> Optional[Dict[str, Any]]:
"""
Processes a list of PDB strings received from the API.
- Calculates pLDDT scores for each PDB string.
- Does NOT save files to disk.
- Returns a dictionary containing a list of structures, each with its PDB content and scores.
"""
results: Dict[str, Any] = {"structures": []}
if (
not pdb_contents
or not isinstance(pdb_contents, list)
or not all(isinstance(s, str) for s in pdb_contents)
):
logger.warning(f"No valid PDB content strings provided for job {job_id}.")
return {
"success": False,
"error": "No valid PDB content strings from API.",
"structures": [],
}
logger.info(f"Processing {len(pdb_contents)} PDB structure(s) for job {job_id}.")
for i, pdb_str in enumerate(pdb_contents):
if not pdb_str.strip():
logger.debug(f"Skipping empty PDB string at index {i} for job {job_id}.")
continue
structure_data: Dict[str, Any] = {"model_index": i, "pdb_content": pdb_str}
avg_plddt, plddts_per_ca_residue, plddts_by_chain = (
calculate_plddt_from_pdb_string(pdb_str)
)
structure_data["average_plddt"] = avg_plddt
structure_data["plddt_scores_per_ca_residue"] = plddts_per_ca_residue
structure_data["plddt_scores_per_chain"] = plddts_by_chain
avg_plddt_per_chain = {}
for chain_id, chain_plddts in plddts_by_chain.items():
if chain_plddts:
avg_plddt_per_chain[chain_id] = sum(chain_plddts) / len(chain_plddts)
else:
avg_plddt_per_chain[chain_id] = 0.0
structure_data["average_plddt_per_chain"] = avg_plddt_per_chain
results["structures"].append(structure_data)
if results["structures"]:
logger.info(
f"Successfully processed and calculated pLDDTs for "
f"{len(results['structures'])} structures for job {job_id}."
)
else:
logger.warning(f"No structures were processed for job {job_id}.")
return {
"success": True,
"message": "No PDB structures found in API response to process.",
"structures": [],
}
return results
async def call_alphafold2_multimer(
sequences: List[str],
api_key: str,
algorithm: str = "jackhmmer",
e_value: float = 0.0001,
iterations: int = 1,
databases: List[str] = ["uniref90", "small_bfd", "mgnify"],
relax_prediction: bool = True,
selected_models: Optional[List[int]] = None,
url: str = DEFAULT_URL,
status_url: str = DEFAULT_STATUS_URL,
polling_interval: int = 30,
timeout: int = 3600,
) -> Optional[Dict[str, Any]]:
"""
Call the NVIDIA NIM AlphaFold2-Multimer API.
The API returns JSON with a list of PDB strings.
This function processes them to calculate pLDDT scores and returns a dictionary
containing a list of structures, each with its PDB content and computed scores.
File saving is handled by the caller (ToolExecutor).
"""
headers = {
"content-type": "application/json",
"Authorization": f"Bearer {api_key}",
"NVCF-POLL-SECONDS": "300",
}
data: Dict[str, Any] = {
"sequences": sequences,
"algorithm": algorithm,
"e_value": e_value,
"iterations": iterations,
"databases": databases,
"relax_prediction": relax_prediction,
}
if selected_models is not None:
data["selected_models"] = selected_models
logger.info(f"Using selected_models: {selected_models}")
try:
initial_post_timeout = min(timeout, 600)
async with aiohttp.ClientSession() as session:
async with session.post(
url, json=data, headers=headers, timeout=initial_post_timeout
) as response:
if response.status == 200:
logger.info("AlphaFold2-Multimer job completed synchronously.")
content_type = response.headers.get("Content-Type", "").lower()
if "application/json" in content_type:
api_response_json_payload = await response.json()
if not isinstance(api_response_json_payload, list):
if (
isinstance(api_response_json_payload, dict)
and "error" in api_response_json_payload
):
logger.error(
f"Sync API call returned error: "
f"{api_response_json_payload['error']}"
)
return {
"success": False,
"error": api_response_json_payload["error"],
"detail": api_response_json_payload.get(
"detail", ""
),
}
return {
"success": False,
"error": "Sync JSON response not a list of PDBs as expected.",
}
req_id_sync = response.headers.get("nvcf-reqid", "sync_job")
return await _process_pdb_and_scores_from_api(
pdb_contents=api_response_json_payload,
job_id=req_id_sync,
api_response_json=None,
)
else:
err_text = await response.text()
logger.error(
f"Sync response unexpected content type: {content_type}. "
f"Response: {err_text[:500]}"
)
return {
"success": False,
"error": f"Sync response unexpected content type: {content_type}",
"detail": err_text,
}
elif response.status == 202:
req_id = response.headers.get("nvcf-reqid")
if req_id:
logger.info(
f"AlphaFold2-Multimer job submitted, request ID: {req_id}"
)
return await _poll_job_status(
req_id=req_id,
headers=headers,
status_url=status_url,
polling_interval=polling_interval,
overall_timeout=timeout,
)
else:
logger.error("No request ID in 202 response headers")
return {
"success": False,
"error": "No request ID in 202 response headers",
}
else:
logger.error(
f"Error calling AlphaFold2-Multimer API (POST): {response.status}"
)
text = await response.text()
logger.error(f"Response: {text}")
return {
"success": False,
"error": f"Error calling API: {response.status}",
"detail": text,
}
except asyncio.TimeoutError:
logger.error("Timeout during AlphaFold2-Multimer API (initial POST).")
return {"success": False, "error": "Timeout during initial API request"}
except Exception as e:
logger.error(
f"Exception during AlphaFold2-Multimer API call (initial POST): {e}",
exc_info=True,
)
return {"success": False, "error": f"Exception during API call: {str(e)}"}
async def _poll_job_status(
req_id: str,
headers: Dict[str, str],
status_url: str,
polling_interval: int = 30,
overall_timeout: int = 3600,
) -> Optional[Dict[str, Any]]:
start_time = asyncio.get_event_loop().time()
per_status_request_timeout = 600
logger.info(
f"Polling job {req_id}. Individual status check timeout: "
f"{per_status_request_timeout}s, Polling interval: {polling_interval}s, "
f"Overall timeout: {overall_timeout}s"
)
while True:
current_loop_time = asyncio.get_event_loop().time()
elapsed_time = current_loop_time - start_time
if elapsed_time >= overall_timeout:
logger.error(
f"Overall polling timeout of {overall_timeout}s exceeded for "
f"job {req_id}."
)
return {"success": False, "error": "Overall polling timeout exceeded."}
remaining_time_for_overall_timeout = overall_timeout - elapsed_time
current_status_check_timeout = min(
per_status_request_timeout, remaining_time_for_overall_timeout
)
if current_status_check_timeout <= 0:
logger.error(
f"Not enough time left for another status check for job {req_id} "
f"within overall_timeout."
)
return {
"success": False,
"error": "Not enough time for status check within overall timeout.",
}
try:
async with aiohttp.ClientSession() as session:
logger.debug(
f"Checking status for {req_id} with timeout "
f"{current_status_check_timeout}s."
)
async with session.get(
f"{status_url}/{req_id}",
headers=headers,
timeout=current_status_check_timeout,
) as response:
if response.status == 200:
logger.info(
f"AlphaFold2-Multimer job {req_id} completed (status 200)."
)
if response.content_type == "application/json":
try:
api_response_json_payload = await response.json()
if not isinstance(api_response_json_payload, list):
if (
isinstance(api_response_json_payload, dict)
and "error" in api_response_json_payload
):
logger.error(
f"Job {req_id}: API returned error: "
f"{api_response_json_payload['error']}"
)
return {
"success": False,
"error": api_response_json_payload["error"],
"detail": api_response_json_payload.get(
"detail", ""
),
}
logger.error(
f"Job {req_id}: Expected API response to be a list of PDB strings, "
f"got {type(api_response_json_payload)}."
)
return {
"success": False,
"error": "API response was not a list of PDB strings.",
}
return await _process_pdb_and_scores_from_api(
pdb_contents=api_response_json_payload,
job_id=req_id,
api_response_json=None,
)
except json.JSONDecodeError:
logger.error(
f"Job {req_id}: Failed to decode JSON response from API.",
exc_info=True,
)
raw_text = await response.text()
return {
"success": False,
"error": "Failed to decode JSON response.",
"detail": raw_text[:500],
}
else:
raw_text = await response.text()
logger.error(
f"Job {req_id}: Unexpected content type {response.content_type}. "
f"Expected application/json. Response: {raw_text[:500]}"
)
return {
"success": False,
"error": f"Unexpected content type: {response.content_type}",
"detail": raw_text,
}
elif response.status == 202:
try:
job_status_json = await response.json()
percent_complete = job_status_json.get(
"percentComplete", "N/A"
)
status_message = job_status_json.get("status", "running")
logger.debug(
f"Job {req_id} status: {status_message} ({percent_complete}% complete). "
f"Polling again in {polling_interval}s."
)
except (aiohttp.ContentTypeError, json.JSONDecodeError):
logger.debug(
f"Job {req_id} still running (202 status, non-JSON/malformed JSON body). "
f"Polling again in {polling_interval}s."
)
await asyncio.sleep(polling_interval)
else:
text = await response.text()
logger.error(
f"Error checking AlphaFold2-Multimer job status {req_id}: "
f"HTTP {response.status} - {text}"
)
return {
"success": False,
"error": f"Status check failed with HTTP {response.status}",
"detail": text,
}
except asyncio.TimeoutError:
logger.warning(
f"Client-side timeout ({current_status_check_timeout}s) during status check for "
f"job {req_id}. Retrying poll after {polling_interval}s sleep."
)
await asyncio.sleep(polling_interval)
except aiohttp.ClientError as e:
logger.error(
f"Client error polling job status for {req_id}: {e}. "
f"Retrying poll after {polling_interval}s.",
exc_info=True,
)
await asyncio.sleep(polling_interval)
except Exception as e:
logger.error(
f"Unexpected error polling job status {req_id}: {e}", exc_info=True
)
return {"success": False, "error": f"Unexpected polling error: {str(e)}"}