Release 0.9.4

CONTRIBUTING.md

@@ -20,13 +20,14 @@ We use `asdf` to manage Python binaries and `poetry` to manage Python dependenci
 
 For development in a macOS environment, we use `brew` to manage system packages.
 
-```
+```bash
 # Install asdf (or use another method https://asdf-vm.com/)
 brew install asdf
 
 # Install `asdf` managed python and poetry
 asdf plugin add python
 asdf plugin add poetry
+asdf install
 
 # Install poetry dependencies
 poetry install
@@ -37,7 +38,7 @@ poetry run pre-commit install
 
 Then to run the entire test suite
 
-```
+```bash
 poetry run pytest truss/tests
 ```
 

README.md

@@ -9,7 +9,7 @@
 
 * **Write once, run anywhere:** Package and test model code, weights, and dependencies with a model server that behaves the same in development and production.
 * **Fast developer loop:** Implement your model with fast feedback from a live reload server, and skip Docker and Kubernetes configuration with a batteries-included model serving environment.
-* **Support for all Python frameworks**: From `transformers` and `diffusors` to `PyTorch` and `Tensorflow` to `XGBoost` and `sklearn`, Truss supports models created with any framework, even entirely custom models.
+* **Support for all Python frameworks**: From `transformers` and `diffusers` to `PyTorch` and `TensorFlow` to `TensorRT` and `Triton`, Truss supports models created and served with any framework.
 
 See Trusses for popular models including:
 

bin/generate_base_images.py

@@ -87,8 +87,6 @@ def _build(
 
         if job_type == "server":
             reqs_copy_from = templates_path / "server" / "requirements.txt"
-        elif job_type == "training":
-            reqs_copy_from = templates_path / "training" / "requirements.txt"
         else:
             raise ValueError(f"Unknown job type {job_type}")
 
@@ -128,7 +126,7 @@ def _build_all(
     dry_run: bool = False,
 ):
     if job_types is None:
-        job_types = ["server", "training"]
+        job_types = ["server"]
 
     if python_versions is None:
         python_versions = SUPPORTED_PYTHON_VERSIONS
@@ -173,7 +171,7 @@ def _build_all(
         "--job-type",
         nargs="?",
         default="all",
-        choices=["server", "training", "all"],
+        choices=["server", "all"],
         help="Create images for server",
     )
     parser.add_argument(
@@ -204,7 +202,7 @@ def _build_all(
         python_versions = {args.python_version}
 
     if args.job_type == "all":
-        job_types = ["server", "training"]
+        job_types = ["server"]
     else:
         job_types = [args.job_type]
 

docs/_snippets/config-params.mdx

@@ -299,31 +299,6 @@ Not required.
 ### `build`
 
 The `build` section is used to define options for custom servers.
-The two main model servers we support are `TGI` an `vLLM`. These are
-highly optimized servers that are built to support specific LLMs.
-
-See the following examples for how to use each of these:
-* [TGI](/examples/07-high-performance-tgi)
-* [vLLM](/examples/08-high-performance-vllm)
-
-Example configuration for TGI, running Falcon-7B:
-
-```yaml config.yaml
-build:
-  arguments:
-    endpoint: generate_stream
-    model_id: tiiuae/falcon-7b
-  model_server: TGI
-```
-
-#### `build.model_server`
-
-Either `VLLM` for vLLM, or `TGI` for TGI.
-
-#### `build.arguments`
-
-The arguments for the model server. This includes information such as which model you intend to load, and
-which endpoin from the server you'd like to use.
 
 ### `model_cache`
 

docs/contribute/base-images.mdx

@@ -5,7 +5,7 @@ description: "Add a custom base image to Truss"
 
 Base images are used to create Docker images for containers. Truss uses customized base images to:
 
-* Reduce Docker image build times for model serving and training
+* Reduce Docker image build times for model serving
 * Reduce container startup time
 * Re-use common parts of containers