Update more distribution docs to be simpler and partially codegen'ed

llama_stack/templates/bedrock/__init__.py

@@ -0,0 +1,7 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .bedrock import get_distribution_template  # noqa: F401

llama_stack/templates/bedrock/bedrock.py

@@ -0,0 +1,38 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from pathlib import Path
+
+from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
+
+
+def get_distribution_template() -> DistributionTemplate:
+    providers = {
+        "inference": ["remote::bedrock"],
+        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "safety": ["remote::bedrock"],
+        "agents": ["inline::meta-reference"],
+        "telemetry": ["inline::meta-reference"],
+    }
+
+    return DistributionTemplate(
+        name="bedrock",
+        distro_type="self_hosted",
+        description="Use AWS Bedrock for running LLM inference and safety",
+        docker_image=None,
+        template_path=Path(__file__).parent / "doc_template.md",
+        providers=providers,
+        default_models=[],
+        run_configs={
+            "run.yaml": RunConfigSettings(),
+        },
+        run_config_env_vars={
+            "LLAMASTACK_PORT": (
+                "5001",
+                "Port for the Llama Stack distribution server",
+            ),
+        },
+    )

llama_stack/templates/bedrock/build.yaml

@@ -1,9 +1,19 @@
+version: '2'
 name: bedrock
 distribution_spec:
-  description: Use Amazon Bedrock APIs.
+  description: Use AWS Bedrock for running LLM inference and safety
+  docker_image: null
   providers:
-    inference: remote::bedrock
-    memory: inline::faiss
-    safety: inline::llama-guard
-    agents: inline::meta-reference
-    telemetry: inline::meta-reference
+    inference:
+    - remote::bedrock
+    memory:
+    - inline::faiss
+    - remote::chromadb
+    - remote::pgvector
+    safety:
+    - remote::bedrock
+    agents:
+    - inline::meta-reference
+    telemetry:
+    - inline::meta-reference
+image_type: conda

llama_stack/templates/bedrock/doc_template.md

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+# Bedrock Distribution
+
+The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations:
+
+{{ providers_table }}
+
+
+{% if run_config_env_vars %}
+### Environment Variables
+
+The following environment variables can be configured:
+
+{% for var, (default_value, description) in run_config_env_vars.items() %}
+- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
+{% endfor %}
+{% endif %}
+
+{% if default_models %}
+### Models
+
+The following models are available by default:
+
+{% for model in default_models %}
+- `{{ model.model_id }} ({{ model.provider_model_id }})`
+{% endfor %}
+{% endif %}
+
+
+### Prerequisite: API Keys
+
+Make sure you have access to a AWS Bedrock API Key. You can get one by visiting [AWS Bedrock](https://aws.amazon.com/bedrock/).
+
+
+## Running Llama Stack with AWS Bedrock
+
+You can do this via Conda (build code) or Docker which has a pre-built image.
+
+### Via Docker
+
+This method allows you to get started quickly without having to build the distribution code.
+
+```bash
+LLAMA_STACK_PORT=5001
+docker run \
+  -it \
+  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+  llamastack/distribution-{{ name }} \
+  --port $LLAMA_STACK_PORT \
+  --env AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
+  --env AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
+  --env AWS_SESSION_TOKEN=$AWS_SESSION_TOKEN
+```
+
+### Via Conda
+
+```bash
+llama stack build --template {{ name }} --image-type conda
+llama stack run ./run.yaml \
+  --port $LLAMA_STACK_PORT \
+  --env AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
+  --env AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
+  --env AWS_SESSION_TOKEN=$AWS_SESSION_TOKEN
+```

llama_stack/templates/bedrock/run.yaml

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+version: '2'
+image_name: bedrock
+docker_image: null
+conda_env: bedrock
+apis:
+- agents
+- inference
+- memory
+- safety
+- telemetry
+providers:
+  inference:
+  - provider_id: bedrock
+    provider_type: remote::bedrock
+    config: {}
+  memory:
+  - provider_id: faiss
+    provider_type: inline::faiss
+    config:
+      kvstore:
+        type: sqlite
+        namespace: null
+        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/bedrock}/faiss_store.db
+  safety:
+  - provider_id: bedrock
+    provider_type: remote::bedrock
+    config: {}
+  agents:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      persistence_store:
+        type: sqlite
+        namespace: null
+        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/bedrock}/agents_store.db
+  telemetry:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config: {}
+metadata_store:
+  namespace: null
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/bedrock}/registry.db
+models: []
+shields: []
+memory_banks: []
+datasets: []
+scoring_fns: []
+eval_tasks: []