MCP_Chai1_Modal / app.py
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# Import librairies
from pathlib import Path
from typing import Optional
from uuid import uuid4
import hashlib
import json
import gradio as gr
import gemmi
from gradio_molecule3d import Molecule3D
from modal_app import app, chai1_inference, download_inference_dependencies, here
# Definition of the tools for the MCP server
# Function to compute Chai1 inference
def compute_Chai1(
force_redownload: bool = False,
fasta_file: Optional[str] = None,
inference_config_file: Optional[str] = None,
output_dir: Optional[str] = None,
run_id: Optional[str] = None,
):
"""Compute a Chai1 simulation.
Args:
x (float | int): The number to square.
Returns:
float: The square of the input number.
"""
with app.run():
print("🧬 checking inference dependencies")
download_inference_dependencies.remote(force=force_redownload)
if fasta_file is None:
fasta_file = here / "inputs" / "chai1_default_input.fasta"
print(f"🧬 running Chai inference on {fasta_file}")
fasta_content = Path(fasta_file).read_text()
if inference_config_file is None:
inference_config_file = here / "inputs" / "chai1_quick_inference.json"
print(f"🧬 loading Chai inference config from {inference_config_file}")
inference_config = json.loads(Path(inference_config_file).read_text())
if run_id is None:
run_id = hashlib.sha256(uuid4().bytes).hexdigest()[:8] # short id
print(f"🧬 running inference with {run_id=}")
results = chai1_inference.remote(fasta_content, inference_config, run_id)
if output_dir is None:
output_dir = Path("./results")
output_dir.mkdir(parents=True, exist_ok=True)
print(f"🧬 saving results to disk locally in {output_dir}")
for ii, (scores, cif) in enumerate(results):
(Path(output_dir) / f"{run_id}-scores.model_idx_{ii}.npz").write_bytes(scores)
(Path(output_dir) / f"{run_id}-preds.model_idx_{ii}.cif").write_text(cif)
print(Path(output_dir) / f"{run_id}-preds.model_idx_{ii}.cif")
cif_name = output_dir+"/"+str(run_id)+"-preds.model_idx_"+str(ii)+".cif"
print(cif_name)
pdb_name = cif_name.split('.cif')[0] + '.pdb'
st = gemmi.read_structure(cif_name)
st.write_minimal_pdb(pdb_name)
return pdb_name
# Create the Gradio interface
reps = [{"model": 0,"style": "cartoon","color": "whiteCarbon"}]
with gr.Blocks() as demo:
inp = gr.Textbox(placeholder="Sequence file", label="Input Fasta file")
btn = gr.Button("Run")
out = Molecule3D(label="Molecule3D", reps=reps)
btn.click(fn=compute_Chai1, inputs=[inp], outputs=[out])
# Launch both the Gradio web interface and the MCP server
if __name__ == "__main__":
demo.launch(mcp_server=True)