fix: update agents test (#1796)

# What does this PR do?
- we no longer query vector db when uploading documents as attachments

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
```
pytest --stack-config="http://localhost:8321" -v tests/integration/agents/test_agents.py --text-model meta-llama/Llama-3.3-70B-Instruct
```

```
pytest --stack-config=fireworks -v tests/integration/agents/test_agents.py --text-model meta-llama/Llama-3.3-70B-Instruct --record-responses
```
<img width="1160" alt="image"
src="https://github.com/user-attachments/assets/90700f79-c002-4474-bb41-7bc0a39dc91c"
/>


[//]: # (## Documentation)

tests/integration/agents/test_agents.py

@@ -8,15 +8,13 @@ from typing import Any, Dict
 from uuid import uuid4
 
 import pytest
-from llama_stack_client import Agent, AgentEventLogger, Document
-from llama_stack_client.types.shared_params.agent_config import AgentConfig, ToolConfig
 
 from llama_stack.apis.agents.agents import (
     AgentConfig as Server__AgentConfig,
-)
-from llama_stack.apis.agents.agents import (
     ToolChoice,
 )
+from llama_stack_client import Agent, AgentEventLogger, Document
+from llama_stack_client.types.shared_params.agent_config import AgentConfig, ToolConfig
 
 
 def get_boiling_point(liquid_name: str, celcius: bool = True) -> int:
@@ -173,6 +171,7 @@ def test_tool_config(llama_stack_client_with_mocked_inference, agent_config):
 def test_builtin_tool_web_search(llama_stack_client_with_mocked_inference, agent_config):
     agent_config = {
         **agent_config,
+        "instructions": "You are a helpful assistant that can use web search to answer questions.",
         "tools": [
             "builtin::websearch",
         ],
@@ -184,20 +183,20 @@ def test_builtin_tool_web_search(llama_stack_client_with_mocked_inference, agent
         messages=[
             {
                 "role": "user",
-                "content": "Search the web and tell me who the founder of Meta is.",
+                "content": "Search the web and tell me what is the local time in Tokyo currently.",
             }
         ],
         session_id=session_id,
+        stream=False,
     )
 
-    logs = [str(log) for log in AgentEventLogger().log(response) if log is not None]
-    logs_str = "".join(logs)
-
-    assert "tool_execution>" in logs_str
-    assert "Tool:brave_search Response:" in logs_str
-    assert "mark zuckerberg" in logs_str.lower()
-    if len(agent_config["output_shields"]) > 0:
-        assert "No Violation" in logs_str
+    found_tool_execution = False
+    for step in response.steps:
+        if step.step_type == "tool_execution":
+            assert step.tool_calls[0].tool_name == "brave_search"
+            found_tool_execution = True
+            break
+    assert found_tool_execution
 
 
 def test_builtin_tool_code_execution(llama_stack_client_with_mocked_inference, agent_config):
@@ -427,19 +426,7 @@ def test_rag_agent(llama_stack_client_with_mocked_inference, agent_config, rag_t
             assert expected_kw in response.output_message.content.lower()
 
 
-@pytest.mark.parametrize(
-    "tool",
-    [
-        dict(
-            name="builtin::rag/knowledge_search",
-            args={
-                "vector_db_ids": [],
-            },
-        ),
-        "builtin::rag/knowledge_search",
-    ],
-)
-def test_rag_agent_with_attachments(llama_stack_client_with_mocked_inference, agent_config, tool):
+def test_rag_agent_with_attachments(llama_stack_client_with_mocked_inference, agent_config):
     urls = ["chat.rst", "llama3.rst", "memory_optimizations.rst", "lora_finetune.rst"]
     documents = [
         Document(
@@ -452,7 +439,6 @@ def test_rag_agent_with_attachments(llama_stack_client_with_mocked_inference, ag
     ]
     agent_config = {
         **agent_config,
-        "tools": [tool],
     }
     rag_agent = Agent(llama_stack_client_with_mocked_inference, **agent_config)
     session_id = rag_agent.create_session(f"test-session-{uuid4()}")
@@ -486,10 +472,6 @@ def test_rag_agent_with_attachments(llama_stack_client_with_mocked_inference, ag
             stream=False,
         )
 
-    # rag is called
-    tool_execution_step = [step for step in response.steps if step.step_type == "tool_execution"]
-    assert len(tool_execution_step) >= 1
-    assert tool_execution_step[0].tool_calls[0].tool_name == "knowledge_search"
     assert "lora" in response.output_message.content.lower()