fix(test): update client-sdk tests to handle tool format parametrization better (#1287)

# What does this PR do?

Tool format depends on the model. @ehhuang introduced a
`get_default_tool_prompt_format` function for this purpose. We should
use that instead of hacky model ID matching we had before.

Secondly, non llama models don't have this concept so testing with those
models should work as is.

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

## Test Plan

```bash
for distro in fireworks ollama; do
  LLAMA_STACK_CONFIG=$distro \
    pytest -s -v tests/client-sdk/inference/test_text_inference.py \
       --inference-model=meta-llama/Llama-3.2-3B-Instruct \
       --vision-inference-model=""
done

LLAMA_STACK_CONFIG=dev \
   pytest -s -v tests/client-sdk/inference/test_text_inference.py \
       --inference-model=openai/gpt-4o \
       --vision-inference-model=""

```

[//]: # (## Documentation)

tests/client-sdk/inference/test_text_inference.py

@@ -7,14 +7,9 @@
 import pytest
 from pydantic import BaseModel
 
+from llama_stack.models.llama.sku_list import resolve_model
 from llama_stack.providers.tests.test_cases.test_case import TestCase
-
-PROVIDER_TOOL_PROMPT_FORMAT = {
-    "remote::ollama": "json",
-    "remote::together": "json",
-    "remote::fireworks": "json",
-    "remote::vllm": "json",
-}
+from llama_stack.providers.utils.inference.prompt_adapter import get_default_tool_prompt_format
 
 PROVIDER_LOGPROBS_TOP_K = {"remote::together", "remote::fireworks", "remote::vllm"}
 
@@ -24,18 +19,32 @@ def skip_if_model_doesnt_support_completion(client_with_models, model_id):
     provider_id = models[model_id].provider_id
     providers = {p.provider_id: p for p in client_with_models.providers.list()}
     provider = providers[provider_id]
-    print(f"Provider: {provider.provider_type} for model {model_id}")
     if provider.provider_type in ("remote::openai", "remote::anthropic", "remote::gemini"):
         pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support completion")
 
 
-@pytest.fixture(scope="session")
-def provider_tool_format(inference_provider_type):
-    return (
-        PROVIDER_TOOL_PROMPT_FORMAT[inference_provider_type]
-        if inference_provider_type in PROVIDER_TOOL_PROMPT_FORMAT
-        else None
-    )
+def get_llama_model(client_with_models, model_id):
+    models = {}
+    for m in client_with_models.models.list():
+        models[m.identifier] = m
+        models[m.provider_resource_id] = m
+
+    assert model_id in models, f"Model {model_id} not found"
+
+    model = models[model_id]
+    ids = (model.identifier, model.provider_resource_id)
+    for mid in ids:
+        if resolve_model(mid):
+            return mid
+
+    return model.metadata.get("llama_model", None)
+
+
+def get_tool_prompt_format(client_with_models, model_id):
+    llama_model = get_llama_model(client_with_models, model_id)
+    if not llama_model:
+        return None
+    return get_default_tool_prompt_format(llama_model)
 
 
 @pytest.mark.parametrize(
@@ -237,12 +246,8 @@ def test_text_chat_completion_streaming(client_with_models, text_model_id, test_
         "inference:chat_completion:tool_calling",
     ],
 )
-def test_text_chat_completion_with_tool_calling_and_non_streaming(
-    client_with_models, text_model_id, provider_tool_format, test_case
-):
-    # TODO: more dynamic lookup on tool_prompt_format for model family
-    tool_prompt_format = "json" if "3.1" in text_model_id else "python_list"
-
+def test_text_chat_completion_with_tool_calling_and_non_streaming(client_with_models, text_model_id, test_case):
+    tool_prompt_format = get_tool_prompt_format(client_with_models, text_model_id)
     tc = TestCase(test_case)
 
     response = client_with_models.inference.chat_completion(
@@ -280,12 +285,8 @@ def extract_tool_invocation_content(response):
         "inference:chat_completion:tool_calling",
     ],
 )
-def test_text_chat_completion_with_tool_calling_and_streaming(
-    client_with_models, text_model_id, provider_tool_format, test_case
-):
-    # TODO: more dynamic lookup on tool_prompt_format for model family
-    tool_prompt_format = "json" if "3.1" in text_model_id else "python_list"
-
+def test_text_chat_completion_with_tool_calling_and_streaming(client_with_models, text_model_id, test_case):
+    tool_prompt_format = get_tool_prompt_format(client_with_models, text_model_id)
     tc = TestCase(test_case)
 
     response = client_with_models.inference.chat_completion(
@@ -308,14 +309,8 @@ def test_text_chat_completion_with_tool_calling_and_streaming(
         "inference:chat_completion:tool_calling",
     ],
 )
-def test_text_chat_completion_with_tool_choice_required(
-    client_with_models,
-    text_model_id,
-    provider_tool_format,
-    test_case,
-):
-    # TODO: more dynamic lookup on tool_prompt_format for model family
-    tool_prompt_format = "json" if "3.1" in text_model_id else "python_list"
+def test_text_chat_completion_with_tool_choice_required(client_with_models, text_model_id, test_case):
+    tool_prompt_format = get_tool_prompt_format(client_with_models, text_model_id)
 
     tc = TestCase(test_case)
 
@@ -341,14 +336,15 @@ def test_text_chat_completion_with_tool_choice_required(
         "inference:chat_completion:tool_calling",
     ],
 )
-def test_text_chat_completion_with_tool_choice_none(client_with_models, text_model_id, provider_tool_format, test_case):
+def test_text_chat_completion_with_tool_choice_none(client_with_models, text_model_id, test_case):
+    tool_prompt_format = get_tool_prompt_format(client_with_models, text_model_id)
     tc = TestCase(test_case)
 
     response = client_with_models.inference.chat_completion(
         model_id=text_model_id,
         messages=tc["messages"],
         tools=tc["tools"],
-        tool_config={"tool_choice": "none", "tool_prompt_format": provider_tool_format},
+        tool_config={"tool_choice": "none", "tool_prompt_format": tool_prompt_format},
         stream=True,
     )
     tool_invocation_content = extract_tool_invocation_content(response)