update rag examples to use fresh faiss index every time

This commit is contained in:
Hardik Shah 2025-02-06 16:07:38 -08:00
parent c79cc92b37
commit 3e7f682906
3 changed files with 9 additions and 7 deletions

View file

@ -89,7 +89,7 @@
"# install a branch of llama stack\n",
"import os\n",
"os.environ[\"UV_SYSTEM_PYTHON\"] = \"1\"\n",
"!pip install uv \n",
"!pip install uv\n",
"!uv pip install llama-stack"
]
},
@ -691,7 +691,7 @@
" from google.colab import userdata\n",
" os.environ['TOGETHER_API_KEY'] = userdata.get('TOGETHER_API_KEY')\n",
" os.environ['TAVILY_SEARCH_API_KEY'] = userdata.get('TAVILY_SEARCH_API_KEY')\n",
"except ImportError: \n",
"except ImportError:\n",
" print(\"Not in Google Colab environment\")\n",
"\n",
"for key in ['TOGETHER_API_KEY', 'TAVILY_SEARCH_API_KEY']:\n",
@ -1656,6 +1656,7 @@
}
],
"source": [
"import uuid\n",
"from llama_stack_client.lib.agents.agent import Agent\n",
"from llama_stack_client.lib.agents.event_logger import EventLogger\n",
"from llama_stack_client.types.agent_create_params import AgentConfig\n",
@ -1673,7 +1674,7 @@
" for i, url in enumerate(urls)\n",
"]\n",
"\n",
"vector_db_id = \"test-vector-db\"\n",
"vector_db_id = f\"test-vector-db-{uuid.uuid4().hex}\"\n",
"client.vector_dbs.register(\n",
" vector_db_id=vector_db_id,\n",
" embedding_model=\"all-MiniLM-L6-v2\",\n",
@ -3098,7 +3099,7 @@
}
],
"source": [
"# NBVAL_SKIP \n",
"# NBVAL_SKIP\n",
"print(f\"Getting traces for session_id={session_id}\")\n",
"import json\n",
"\n",

View file

@ -173,6 +173,7 @@ Here is an example of a simple RAG (Retrieval Augmented Generation) chatbot agen
```python
import os
import uuid
from termcolor import cprint
from llama_stack_client.lib.agents.agent import Agent
@ -214,7 +215,7 @@ documents = [
]
# Register a vector database
vector_db_id = "test-vector-db"
vector_db_id = f"test-vector-db-{uuid.uuid4().hex}"
client.vector_dbs.register(
vector_db_id=vector_db_id,
embedding_model="all-MiniLM-L6-v2",

View file

@ -414,7 +414,7 @@ def test_rag_and_code_agent(llama_stack_client, agent_config):
)
for i, url in enumerate(urls)
]
vector_db_id = "test-vector-db"
vector_db_id = f"test-vector-db-{uuid4()}"
llama_stack_client.vector_dbs.register(
vector_db_id=vector_db_id,
embedding_model="all-MiniLM-L6-v2",