LCORE-2436: Update rag-content to generate lightspeed-stack config together with Llama Stack config

README.md

@@ -428,22 +428,48 @@ podman run --rm \
 ```
 
 Once the command is done, you can find the vector database (embedded with the registry metadata) at
-`./vector_db/custom_docs/0.1` with the name `faiss_store.db` as well as a
-barebones llama-stack configuration file named `llama-stack.yaml` for
-reference, since it's not necessary for the final deployment.
+`./vector_db/custom_docs/0.1` with the name `faiss_store.db`, a
+`lightspeed-stack.yaml` configuration file for use with Lightspeed Core Stack,
+and a `llama-stack.yaml` for reference.
 
-The vector-io will be named `custom-docs-0_1`:
+The generated `lightspeed-stack.yaml` will look like:
 
 ```yaml
-providers:
- vector_io:
-   - provider_id: custom-docs-0_1
-     provider_type: inline::faiss
-     config:
-       kvstore:
-         type: sqlite
-         namespace: null
-         db_path: /home/<user>/rag-content/vector_db/custom_docs/0.1/faiss_store.db
+name: Lightspeed Core Stack (LCS)
+service:
+  host: 0.0.0.0
+  port: 8080
+  base_url: http://localhost:8080
+  auth_enabled: false
+  workers: 1
+  color_log: true
+  access_log: true
+llama_stack:
+  use_as_library_client: false
+  url: http://localhost:8321
+user_data_collection:
+  feedback_enabled: true
+  feedback_storage: "/tmp/data/feedback"
+  transcripts_enabled: true
+  transcripts_storage: "/tmp/data/transcripts"
+conversation_cache:
+  type: "sqlite"
+  sqlite:
+    db_path: "/tmp/data/conversation-cache.db"
+authentication:
+  module: "noop"
+
+byok_rag:
+  - rag_id: custom-docs-0_1
+    rag_type: inline::faiss
+    embedding_model: sentence-transformers/all-mpnet-base-v2
+    embedding_dimension: 768
+    vector_db_id: <generated-vector-store-id>
+    db_path: /home/<user>/rag-content/vector_db/custom_docs/0.1/faiss_store.db
+
+rag:
+  inline:
+    - custom-docs-0_1
 ```
 
 Once we have a database we can use script `query_rag.py` to check some results:

src/lightspeed_rag_content/config_templates.py

@@ -0,0 +1,196 @@
+# Copyright 2025 Red Hat, Inc.
+# All Rights Reserved.
+#
+#    Licensed under the Apache License, Version 2.0 (the "License"); you may
+#    not use this file except in compliance with the License. You may obtain
+#    a copy of the License at
+#
+#         http://www.apache.org/licenses/LICENSE-2.0
+#
+#    Unless required by applicable law or agreed to in writing, software
+#    distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
+#    WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+#    License for the specific language governing permissions and limitations
+#    under the License.
+
+"""Configuration templates for llama-stack and Lightspeed Core Stack output."""
+
+# llama-stack configuration templates
+
+LLAMA_STACK_TEMPLATE = """version: 2
+image_name: starter
+
+apis:
+- agents
+- files
+- inference
+- safety
+- tool_runtime
+- vector_io
+
+server:
+  port: 8321
+
+providers:
+  inference:
+  - config: {{}}
+    provider_id: sentence-transformers
+    provider_type: inline::sentence-transformers
+  files:
+  - config:
+      metadata_store:
+        table_name: files_metadata
+        backend: sql_default
+      storage_dir: /tmp/files
+    provider_id: meta-reference-files
+    provider_type: inline::localfs
+  agents:
+  - config:
+      persistence:
+        agent_state:
+          namespace: agents_state
+          backend: kv_default
+        responses:
+          table_name: agents_responses
+          backend: sql_default
+    provider_id: meta-reference
+    provider_type: inline::meta-reference
+  tool_runtime:
+  - config: {{}}
+    provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+  vector_io:
+  - config:
+      {vector_io_cfg}
+    provider_id: {index_id}
+    provider_type: {provider_type_prefix}::{provider_type}
+storage:
+  backends:
+    kv_rag:
+      type: kv_sqlite
+      db_path: {kv_db_path}
+    kv_default:
+      type: kv_sqlite
+      db_path: /tmp/kv_store.db
+    sql_default:
+      type: sql_sqlite
+      db_path: /tmp/sql_store.db
+  stores:
+    metadata:
+      namespace: registry
+      backend: kv_default
+    inference:
+      table_name: inference_store
+      backend: sql_default
+    conversations:
+      table_name: openai_conversations
+      backend: sql_default
+registered_resources:
+  models:
+  - metadata:
+      embedding_dimension: {dimension}
+    model_id: {model_name}
+    provider_id: sentence-transformers
+    provider_model_id: {model_name_or_dir}
+    model_type: embedding
+  vector_stores: []
+  shields: []
+  datasets: []
+  scoring_fns: []
+  benchmarks: []
+  tool_groups:
+  - toolgroup_id: builtin::rag
+    provider_id: rag-runtime
+"""
+
+LLAMA_STACK_VECTOR_STORES_TEMPLATE = """vector_stores:
+  - embedding_dimension: {dimension}
+    embedding_model: sentence-transformers/{model_name_or_dir}
+    provider_id: {vector_io_provider_id}
+    vector_store_id: {vector_store_id}"""
+
+LLAMA_STACK_VECTOR_IO_CONFIG_SQLITE = """persistence:
+        namespace: vector_io::{provider_type}
+        backend: kv_rag"""
+
+LLAMA_STACK_VECTOR_IO_CONFIG_PGVECTOR = """persistence:
+        namespace: vector_io::{provider_type}
+        backend: kv_default
+      host: ${{env.POSTGRES_HOST}}
+      port: ${{env.POSTGRES_PORT}}
+      db: ${{env.POSTGRES_DATABASE}}
+      user: ${{env.POSTGRES_USER}}
+      password: ${{env.POSTGRES_PASSWORD}}"""
+
+LLAMA_STACK_CFG_FILENAME = "llama-stack.yaml"
+
+# Lightspeed Core Stack configuration templates
+
+LCS_CFG_FILENAME = "lightspeed-stack.yaml"
+
+LCS_BASE_TEMPLATE = """\
+name: Lightspeed Core Stack (LCS)
+service:
+  host: 0.0.0.0
+  port: 8080
+  base_url: http://localhost:8080
+  auth_enabled: false
+  workers: 1
+  color_log: true
+  access_log: true
+llama_stack:
+  use_as_library_client: false
+  url: http://localhost:8321
+  # api_key: custom-key  # Uncomment if your llama-stack requires authentication
+  # To run llama-stack in-process (no external container needed), set:
+  # use_as_library_client: true
+  # library_client_config_path: /path/to/llama-stack.yaml
+user_data_collection:
+  feedback_enabled: true
+  feedback_storage: "/tmp/data/feedback"
+  transcripts_enabled: true
+  transcripts_storage: "/tmp/data/transcripts"
+conversation_cache:
+  type: "sqlite"
+  sqlite:
+    db_path: "/tmp/data/conversation-cache.db"
+authentication:
+  module: "noop"
+
+"""
+
+LCS_FAISS_BYOK_TEMPLATE = """\
+byok_rag:
+  - rag_id: {index_id}
+    rag_type: inline::faiss
+    embedding_model: {model_name}
+    embedding_dimension: {dimension}
+    vector_db_id: {vector_store_id}
+    db_path: {db_path}
+
+rag:
+  inline:
+    - {index_id}
+  # tool:
+  #   - {index_id}
+"""
+
+LCS_PGVECTOR_BYOK_TEMPLATE = """\
+byok_rag:
+  - rag_id: {index_id}
+    rag_type: remote::pgvector
+    embedding_model: {model_name}
+    embedding_dimension: {dimension}
+    vector_db_id: {vector_store_id}
+    host: ${{env.POSTGRES_HOST}}
+    port: ${{env.POSTGRES_PORT}}
+    db: ${{env.POSTGRES_DATABASE}}
+    user: ${{env.POSTGRES_USER}}
+    password: ${{env.POSTGRES_PASSWORD}}
+
+rag:
+  inline:
+    - {index_id}
+  # tool:
+  #   - {index_id}
+"""