From 117a3601ded079f81a65275d3de13bcdd94c312f Mon Sep 17 00:00:00 2001 From: Xi Yan Date: Tue, 18 Feb 2025 11:05:10 -0800 Subject: [PATCH] fix typo --- .../inline/agents/meta_reference/agent_instance.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/llama_stack/providers/inline/agents/meta_reference/agent_instance.py b/llama_stack/providers/inline/agents/meta_reference/agent_instance.py index 730b0f1f5..35e8a00ba 100644 --- a/llama_stack/providers/inline/agents/meta_reference/agent_instance.py +++ b/llama_stack/providers/inline/agents/meta_reference/agent_instance.py @@ -63,7 +63,11 @@ from llama_stack.apis.models import Models from llama_stack.apis.safety import Safety from llama_stack.apis.tools import RAGDocument, RAGQueryConfig, ToolGroups, ToolRuntime from llama_stack.apis.vector_io import VectorIO -from llama_stack.models.llama.datatypes import BuiltinTool, ToolCall, ToolParamDefinition +from llama_stack.models.llama.datatypes import ( + BuiltinTool, + ToolCall, + ToolParamDefinition, +) from llama_stack.providers.utils.kvstore import KVStore from llama_stack.providers.utils.memory.vector_store import concat_interleaved_content from llama_stack.providers.utils.telemetry import tracing @@ -829,11 +833,11 @@ class ChatAgent(ShieldRunnerMixin): # so we need to fix it if we expect the agent to create a new vector db # for each session list_models_response = await self.models_api.list_models() - embdding_models = [x for x in list_models_response.data if x.model_type == "embedding"] + embedding_models = [x for x in list_models_response.data if x.model_type == "embedding"] await self.vector_io_api.register_vector_db( vector_db_id=vector_db_id, - embedding_model=embdding_models[0].identifier, - embedding_dimension=embdding_models[0].metadata["embedding_dimension"], + embedding_model=embedding_models[0].identifier, + embedding_dimension=embedding_models[0].metadata["embedding_dimension"], ) await self.storage.add_vector_db_to_session(session_id, vector_db_id) else: