Production config: disable MSA, 1 sample, errorStrategy ignore

- Disable MSA to reduce GPU memory for large complexes
- Default to 1 diffusion sample to fit within GPU VRAM
- Add errorStrategy 'ignore' so pipeline completes even if
  individual tasks fail (standard bioinformatics pattern)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Dockerfile

@@ -15,7 +15,7 @@ WORKDIR /workspace
 # Install chai_lab and compatible transformers in a single layer
 RUN pip install --no-cache-dir \
     chai_lab==0.5.2 \
-    "transformers>=4.30.0,<5.0.0"
+    "transformers>=4.30.0,<4.45.0"
 
 # Make package dirs writable for any user (K8s may run as non-root)
 RUN chmod -R a+rw /opt/conda/lib/python3.11/site-packages/chai_lab/ && \
@@ -26,7 +26,7 @@ RUN chmod -R a+rw /opt/conda/lib/python3.11/site-packages/chai_lab/ && \
 
 # Verify installations
 RUN python -c "import torch; print(f'PyTorch: {torch.__version__}')" && \
-    python -c "import transformers; print(f'transformers: {transformers.__version__}')" && \
+    python -c "from transformers import EsmModel; print('EsmModel: OK')" && \
     python -c "import chai_lab; print('chai_lab: OK')" && \
     chai --help
 

main.nf

@@ -1,17 +1,18 @@
 #!/usr/bin/env nextflow
 nextflow.enable.dsl=2
 
-params.input_dir = 's3://omic/eureka/chai1'
+params.input_dir = 's3://omic/eureka/chai1/input'
 params.outdir = 's3://omic/eureka/chai1/output'
-params.use_msa = true
+params.use_msa = false
 params.msa_server = 'https://api.colabfold.com'
-params.num_samples = 5
+params.num_samples = 1
 
 process CHAI1 {
-    container 'harbor.cluster.omic.ai/omic/chai1:v2'
+    container 'harbor.cluster.omic.ai/omic/chai1:v3'
     publishDir params.outdir, mode: 'copy'
     stageInMode 'copy'
     maxForks 1
+    errorStrategy 'ignore'
 
     input:
         path fasta

nextflow.config

@@ -3,7 +3,7 @@ docker {
 }
 
 process {
-    container = 'harbor.cluster.omic.ai/omic/chai1:v2'
+    container = 'harbor.cluster.omic.ai/omic/chai1:v3'
     memory = '32 GB'
     cpus = 4
 }