[feat] copy resources folder from lisa-on-cuda repository to /var/task/resources, bump to version 1.3.1

Dockerfile

@@ -63,6 +63,11 @@ RUN poetry run python -m pip install pip wheel setuptools --upgrade
 RUN poetry install --with ${DEPENDENCY_GROUP} --no-root
 
 RUN git clone https://huggingface.co/aletrn/sam-quantized/ ${LAMBDA_TASK_ROOT}/sam-quantized
+RUN git clone -n --depth=1 --filter=tree:0 https://huggingface.co/spaces/aletrn/lisa-on-cuda ${LAMBDA_TASK_ROOT}/lisa-on-cuda && \
+    cd ${LAMBDA_TASK_ROOT}/lisa-on-cuda && \
+    git sparse-checkout set --no-cone resources && \
+    git checkout
+WORKDIR ${LAMBDA_TASK_ROOT}
 
 FROM nvcr.io/nvidia/pytorch:24.01-py3 as runtime
 
@@ -138,6 +143,7 @@ RUN mkdir -p ${FASTAPI_STATIC}
 
 COPY --from=builder_global  ${LAMBDA_TASK_ROOT}/sam-quantized/machine_learning_models \
     ${LAMBDA_TASK_ROOT}/machine_learning_models
+COPY --from=builder_global ${LAMBDA_TASK_ROOT}/lisa-on-cuda/resources ${LAMBDA_TASK_ROOT}/resources
 COPY --from=node_prod_deps /appnode/node_modules* ${FASTAPI_STATIC}/node_modules
 COPY --from=node_build /appnode/dist* ${FASTAPI_STATIC}/dist
 

poetry.lock

@@ -1410,13 +1410,13 @@ files = [
 
 [[package]]
 name = "lisa-on-cuda"
-version = "1.0.2"
+version = "1.0.3"
 description = ""
 optional = false
 python-versions = ">=3.10,<3.11"
 files = [
-    {file = "lisa_on_cuda-1.0.2-py3-none-any.whl", hash = "sha256:fd0bab06cd673b52b6a68c0b9add8dfed2ab57737b94a6fe375cb71c1ec923e0"},
-    {file = "lisa_on_cuda-1.0.2.tar.gz", hash = "sha256:96b446405b27b6c001bb5e5db15489b6ba4c60b67323ab7874cc54bc9d6da56e"},
+    {file = "lisa_on_cuda-1.0.3-py3-none-any.whl", hash = "sha256:e60e4abc5905c3fc29ff739430f480edeb6b4b192d1cd3aecf752d57fdfe34bd"},
+    {file = "lisa_on_cuda-1.0.3.tar.gz", hash = "sha256:cdf7f61ffa1c66c7e5001d691c09cc98b901ec089e5ef3d96ba17a0cf27679bd"},
 ]
 
 [package.dependencies]
@@ -3329,7 +3329,7 @@ testing = ["h5py (>=3.7.0)", "huggingface_hub (>=0.12.1)", "hypothesis (>=6.70.2
 torch = ["safetensors[numpy]", "torch (>=1.10)"]
 
 [[package]]
-name = "samgis_core"
+name = "samgis-core"
 version = "1.0.7"
 description = "SamGIS CORE"
 optional = false
@@ -4383,4 +4383,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "~3.10"
-content-hash = "6420e74251249e5a97a0c7faa9f6bf02311ca0b7f7e1c466bb6283efd97da03d"
+content-hash = "99c7d41a0f92e6971da37bd09ad0857f7654fd1304524b9d182f0c2fffced075"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "samgis-lisa-on-cuda"
-version = "1.3.0"
+version = "1.3.1"
 description = "A VLM backend for machine learning instance segmentation on geospatial data that uses LISA (Reasoning Segmentation via Large Language Model)."
 authors = ["alessandro trinca tornidor <alessandro@trinca.tornidor.com>"]
 license = "MIT license"
@@ -8,7 +8,7 @@ readme = "README.md"
 
 [metadata]
 name = "samgis-lisa-on-cuda"
-version = "1.3.0"
+version = "1.3.1"
 
 [tool.poetry.dependencies]
 bson = "^0.5.10"
@@ -23,7 +23,7 @@ python = "~3.10"
 python-dotenv = "^1.0.1"
 rasterio = "^1.3.9"
 requests = "^2.31.0"
-lisa-on-cuda = "^1.0.2"
+lisa-on-cuda = "^1.0.3"
 samgis-core = "^1.0.7"
 
 [tool.poetry.group.aws_lambda]

scripts/entrypoint.sh

@@ -19,7 +19,7 @@ nvidia-smi || true
 pip list
 
 which uvicorn
-ls -l ${WORKDIR}/venv/bin/uvicorn
+ls -l ${WORKDIR}/.venv/bin/uvicorn
 
 df -h / /home ${WORKDIR} ${XDG_CACHE_HOME}