fix: Update rag examples to use fresh faiss index every time (#998)

# What does this PR do?
In several examples we use the same faiss index , which means running it
multiple times fills up the index with duplicates which eventually
degrades the model performance on RAG as multiple copies of the same
irrelevant chunks might be picked up several times.

Fix is to ensure we create a new index each time. 

Resolves issue in this discussion -
https://github.com/meta-llama/llama-stack/discussions/995

## Test Plan
Re-ran the getting started guide multiple times to see the same output

Co-authored-by: Hardik Shah <hjshah@fb.com>

docs/getting_started.ipynb

@@ -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",

docs/source/getting_started/index.md

@@ -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",

tests/client-sdk/agents/test_agents.py

@@ -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",