refactor: api key as input password

Dockerfile

@@ -30,9 +30,7 @@ COPY molecule.py /app/molecule.py
 
 EXPOSE 7860
 ENV GRADIO_SERVER_NAME="0.0.0.0"
-ARG FOLDING_API_KEY
 ARG FOLDING_PROJECT_CODE
-ENV FOLDING_API_KEY=$FOLDING_API_KEY
 ENV FOLDING_PROJECT_CODE=$FOLDING_PROJECT_CODE
 
 # Create directory for HTML output

Makefile

@@ -5,7 +5,7 @@ PORT = 7860
 OUTPUT_DIR = ./output
 
 # Docker build arguments
-DOCKER_BUILD_ARGS = --build-arg FOLDING_API_KEY=${FOLDING_API_KEY} --build-arg FOLDING_PROJECT_CODE=${FOLDING_PROJECT_CODE}
+DOCKER_BUILD_ARGS = --build-arg FOLDING_PROJECT_CODE=${FOLDING_PROJECT_CODE}
 
 # Docker run arguments
 DOCKER_RUN_ARGS = -p $(PORT):$(PORT) -v $(OUTPUT_DIR):/app/output/html

app.py

@@ -2,10 +2,8 @@ import hashlib
 import gradio as gr
 from pathlib import Path
 from Bio.PDB import MMCIFParser, PDBIO
-from folding_studio.commands.predict import af2 as af2_predict
-from folding_studio.commands.predict import boltz as boltz_predict
-from folding_studio.config import FOLDING_PROJECT_CODE
 import logging
+import os
 
 from molecule import molecule
 
@@ -38,15 +36,23 @@ def convert_cif_to_pdb(cif_path, pdb_path):
     
 
 
-def predict(sequence: str) -> str:
+def predict(sequence: str, api_key: str) -> str:
     """Predict protein structure from amino acid sequence using Boltz model.
     
     Args:
         sequence (str): Amino acid sequence to predict structure for
+        api_key (str): Folding API key
         
     Returns:
         str: HTML iframe containing 3D molecular visualization
     """
+    # Set API key in environment
+    os.environ["FOLDING_API_KEY"] = api_key
+    logger.info("API key has been set in environment")
+    # Import FS now so that the API key is read properly
+    from folding_studio.commands.predict import boltz as boltz_predict
+    from folding_studio.config import FOLDING_PROJECT_CODE
+    
     # Create FASTA file with sequence
     seq_file = Path("sequence.fasta")
     _write_fasta_file(seq_file, sequence)
@@ -136,6 +142,7 @@ with demo:
     with gr.Row():
         with gr.Column():
             sequence = gr.Textbox(label="Sequence", value="")
+            api_key = gr.Textbox(label="Folding API Key", type="password")
     gr.Markdown("# Output")
     with gr.Row():
         predict_btn = gr.Button("Predict")
@@ -144,7 +151,7 @@ with demo:
     
     predict_btn.click(
         fn=predict,
-        inputs=[sequence],
+        inputs=[sequence, api_key],
         outputs=[mol_output]
     )