all distros

llama_stack/templates/tgi/run.yaml

@@ -25,12 +25,6 @@ providers:
         type: sqlite
         namespace: null
         db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/tgi}/faiss_store.db
-  - provider_id: chromadb
-    provider_type: remote::chromadb
-    config: {}
-  - provider_id: pgvector
-    provider_type: remote::pgvector
-    config: {}
   safety:
   - provider_id: llama-guard
     provider_type: inline::llama-guard

llama_stack/templates/tgi/tgi.py

@@ -7,6 +7,7 @@
 from pathlib import Path
 
 from llama_stack.distribution.datatypes import ModelInput, Provider, ShieldInput
+from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.tgi import TGIImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -22,7 +23,7 @@ def get_distribution_template() -> DistributionTemplate:
         "datasetio": ["remote::huggingface", "inline::localfs"],
         "scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
     }
-
+    name = "tgi"
     inference_provider = Provider(
         provider_id="tgi-inference",
         provider_type="remote::tgi",
@@ -30,6 +31,11 @@ def get_distribution_template() -> DistributionTemplate:
             url="${env.TGI_URL}",
         ),
     )
+    memory_provider = Provider(
+        provider_id="faiss",
+        provider_type="inline::faiss",
+        config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
+    )
 
     inference_model = ModelInput(
         model_id="${env.INFERENCE_MODEL}",
@@ -41,7 +47,7 @@ def get_distribution_template() -> DistributionTemplate:
     )
 
     return DistributionTemplate(
-        name="tgi",
+        name=name,
         distro_type="self_hosted",
         description="Use (an external) TGI server for running LLM inference",
         docker_image=None,
@@ -52,6 +58,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider],
+                    "memory": [memory_provider],
                 },
                 default_models=[inference_model],
             ),