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removing model_server python module to brightstaff (function calling) (#615)

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* adding function_calling functionality via rust

* fixed rendered YAML file

* removed model_server from envoy.template and forwarding traffic to bright_staff

* fixed bugs in function_calling.rs that were breaking tests. All good now

* updating e2e test to clean up disk usage

* removing Arch* models to be used as a default model if one is not specified

* if the user sets arch-function base_url we should honor it

* fixing demos as we needed to pin to a particular version of huggingface_hub else the chatbot ui wouldn't build

* adding a constant for Arch-Function model name

* fixing some edge cases with calls made to Arch-Function

* fixed JSON parsing issues in function_calling.rs

* fixed bug where the raw response from Arch-Function was re-encoded

* removed debug from supervisord.conf

* commenting out disk cleanup

* adding back disk space

---------

Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-288.local>
Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-342.local>
This commit is contained in:
Salman Paracha 2025-11-22 12:55:00 -08:00 • committed by GitHub
parent 126b029345
commit 88c2bd1851
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40 changed files with 2517 additions and 1356 deletions
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30
tests/e2e/test_prompt_gateway.py
View file

@ -24,6 +24,28 @@ def cleanup_tool_call(tool_call):
return tool_call.strip()
def normalize_tool_call_arguments(tool_call):
"""
Normalize tool call arguments to ensure they are always a dict.
According to OpenAI API spec, the 'arguments' field should be a JSON string,
but for easier testing we parse it into a dict here.
Args:
tool_call: A tool call dict that may have 'arguments' as either a string or dict
Returns:
A tool call dict with 'arguments' guaranteed to be a dict
"""
if "arguments" in tool_call and isinstance(tool_call["arguments"], str):
try:
tool_call["arguments"] = json.loads(tool_call["arguments"])
except (json.JSONDecodeError, TypeError):
# If parsing fails, keep it as is
pass
return tool_call
@pytest.mark.parametrize("stream", [True, False])
def test_prompt_gateway(stream):
expected_tool_call = {
@ -62,7 +84,7 @@ def test_prompt_gateway(stream):
print("cleaned_tool_call_str: ", cleaned_tool_call_str)
tool_calls = json.loads(cleaned_tool_call_str).get("tool_calls", [])
assert len(tool_calls) > 0
tool_call = tool_calls[0]
tool_call = normalize_tool_call_arguments(tool_calls[0])
location = tool_call["arguments"]["location"]
assert expected_tool_call["arguments"]["location"] in location.lower()
del expected_tool_call["arguments"]["location"]
@ -106,7 +128,7 @@ def test_prompt_gateway(stream):
print("cleaned_tool_call_json: ", json.dumps(cleaned_tool_call_json))
tool_calls_list = cleaned_tool_call_json.get("tool_calls", [])
assert len(tool_calls_list) > 0
tool_call = tool_calls_list[0]
tool_call = normalize_tool_call_arguments(tool_calls_list[0])
location = tool_call["arguments"]["location"]
assert expected_tool_call["arguments"]["location"] in location.lower()
del expected_tool_call["arguments"]["location"]
@ -241,7 +263,7 @@ def test_prompt_gateway_param_tool_call(stream):
assert role == "assistant"
tool_calls = choices[0].get("delta", {}).get("tool_calls", [])
assert len(tool_calls) > 0
tool_call = tool_calls[0]["function"]
tool_call = normalize_tool_call_arguments(tool_calls[0]["function"])
diff = DeepDiff(tool_call, expected_tool_call, ignore_string_case=True)
assert not diff
@ -275,7 +297,7 @@ def test_prompt_gateway_param_tool_call(stream):
tool_calls_message = arch_messages[0]
tool_calls = tool_calls_message.get("tool_calls", [])
assert len(tool_calls) > 0
tool_call = tool_calls[0]["function"]
tool_call = normalize_tool_call_arguments(tool_calls[0]["function"])
diff = DeepDiff(tool_call, expected_tool_call, ignore_string_case=True)
assert not diff