fix agent test_rag

tests/integration/agents/test_agents.py

@@ -77,6 +77,24 @@ def agent_config(llama_stack_client, text_model_id):
     return agent_config
 
 
+@pytest.fixture(scope="session")
+def agent_config_without_safety(text_model_id):
+    agent_config = dict(
+        model=text_model_id,
+        instructions="You are a helpful assistant",
+        sampling_params={
+            "strategy": {
+                "type": "top_p",
+                "temperature": 0.0001,
+                "top_p": 0.9,
+            },
+        },
+        tools=[],
+        enable_session_persistence=False,
+    )
+    return agent_config
+
+
 def test_agent_simple(llama_stack_client, agent_config):
     agent = Agent(llama_stack_client, **agent_config)
     session_id = agent.create_session(f"test-session-{uuid4()}")
@@ -491,7 +509,7 @@ def test_rag_agent(llama_stack_client, agent_config, rag_tool_name):
             assert expected_kw in response.output_message.content.lower()
 
 
-def test_rag_agent_with_attachments(llama_stack_client, agent_config):
+def test_rag_agent_with_attachments(llama_stack_client, agent_config_without_safety):
     urls = ["llama3.rst", "lora_finetune.rst"]
     documents = [
         # passign as url
@@ -514,14 +532,8 @@ def test_rag_agent_with_attachments(llama_stack_client, agent_config):
             metadata={},
         ),
     ]
-    rag_agent = Agent(llama_stack_client, **agent_config)
+    rag_agent = Agent(llama_stack_client, **agent_config_without_safety)
     session_id = rag_agent.create_session(f"test-session-{uuid4()}")
-    user_prompts = [
-        (
-            "Instead of the standard multi-head attention, what attention type does Llama3-8B use?",
-            "grouped",
-        ),
-    ]
     user_prompts = [
         (
             "I am attaching some documentation for Torchtune. Help me answer questions I will ask next.",
@@ -549,82 +561,6 @@ def test_rag_agent_with_attachments(llama_stack_client, agent_config):
     assert "lora" in response.output_message.content.lower()
 
 
-@pytest.mark.skip(reason="Code interpreter is currently disabled in the Stack")
-def test_rag_and_code_agent(llama_stack_client, agent_config):
-    if "llama-4" in agent_config["model"].lower():
-        pytest.xfail("Not working for llama4")
-
-    documents = []
-    documents.append(
-        Document(
-            document_id="nba_wiki",
-            content="The NBA was created on August 3, 1949, with the merger of the Basketball Association of America (BAA) and the National Basketball League (NBL).",
-            metadata={},
-        )
-    )
-    documents.append(
-        Document(
-            document_id="perplexity_wiki",
-            content="""Perplexity the company was founded in 2022 by Aravind Srinivas, Andy Konwinski, Denis Yarats and Johnny Ho, engineers with backgrounds in back-end systems, artificial intelligence (AI) and machine learning:
-
-    Srinivas, the CEO, worked at OpenAI as an AI researcher.
-    Konwinski was among the founding team at Databricks.
-    Yarats, the CTO, was an AI research scientist at Meta.
-    Ho, the CSO, worked as an engineer at Quora, then as a quantitative trader on Wall Street.[5]""",
-            metadata={},
-        )
-    )
-    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",
-        embedding_dimension=384,
-    )
-    llama_stack_client.tool_runtime.rag_tool.insert(
-        documents=documents,
-        vector_db_id=vector_db_id,
-        chunk_size_in_tokens=128,
-    )
-    agent_config = {
-        **agent_config,
-        "tools": [
-            dict(
-                name="builtin::rag/knowledge_search",
-                args={"vector_db_ids": [vector_db_id]},
-            ),
-            "builtin::code_interpreter",
-        ],
-    }
-    agent = Agent(llama_stack_client, **agent_config)
-    user_prompts = [
-        (
-            "when was Perplexity the company founded?",
-            [],
-            "knowledge_search",
-            "2022",
-        ),
-        (
-            "when was the nba created?",
-            [],
-            "knowledge_search",
-            "1949",
-        ),
-    ]
-
-    for prompt, docs, tool_name, expected_kw in user_prompts:
-        session_id = agent.create_session(f"test-session-{uuid4()}")
-        response = agent.create_turn(
-            messages=[{"role": "user", "content": prompt}],
-            session_id=session_id,
-            documents=docs,
-            stream=False,
-        )
-        tool_execution_step = next(step for step in response.steps if step.step_type == "tool_execution")
-        assert tool_execution_step.tool_calls[0].tool_name == tool_name, f"Failed on {prompt}"
-        if expected_kw:
-            assert expected_kw in response.output_message.content.lower()
-
-
 @pytest.mark.parametrize(
     "client_tools",
     [(get_boiling_point, False), (get_boiling_point_with_metadata, True)],