mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 10:44:24 +00:00
fix - unhandled jsonDecodeError in convert_to_model_response_object (#6338)
* fix unhandled jsonDecodeError * add unit testing for convert dict to chat completion
This commit is contained in:
Ishaan Jaff
GitHub
parent
905ebeb924
commit
f4630a09bb
2 changed files with 729 additions and 29 deletions
|
|
@ -5642,38 +5642,41 @@ def _handle_invalid_parallel_tool_calls(
|
|||
|
||||
if tool_calls is None:
|
||||
return
|
||||
|
||||
replacements: Dict[int, List[ChatCompletionMessageToolCall]] = defaultdict(list)
|
||||
for i, tool_call in enumerate(tool_calls):
|
||||
current_function = tool_call.function.name
|
||||
function_args = json.loads(tool_call.function.arguments)
|
||||
if current_function == "multi_tool_use.parallel":
|
||||
verbose_logger.debug(
|
||||
"OpenAI did a weird pseudo-multi-tool-use call, fixing call structure.."
|
||||
)
|
||||
for _fake_i, _fake_tool_use in enumerate(function_args["tool_uses"]):
|
||||
_function_args = _fake_tool_use["parameters"]
|
||||
_current_function = _fake_tool_use["recipient_name"]
|
||||
if _current_function.startswith("functions."):
|
||||
_current_function = _current_function[len("functions.") :]
|
||||
|
||||
fixed_tc = ChatCompletionMessageToolCall(
|
||||
id=f"{tool_call.id}_{_fake_i}",
|
||||
type="function",
|
||||
function=Function(
|
||||
name=_current_function, arguments=json.dumps(_function_args)
|
||||
),
|
||||
try:
|
||||
replacements: Dict[int, List[ChatCompletionMessageToolCall]] = defaultdict(list)
|
||||
for i, tool_call in enumerate(tool_calls):
|
||||
current_function = tool_call.function.name
|
||||
function_args = json.loads(tool_call.function.arguments)
|
||||
if current_function == "multi_tool_use.parallel":
|
||||
verbose_logger.debug(
|
||||
"OpenAI did a weird pseudo-multi-tool-use call, fixing call structure.."
|
||||
)
|
||||
replacements[i].append(fixed_tc)
|
||||
for _fake_i, _fake_tool_use in enumerate(function_args["tool_uses"]):
|
||||
_function_args = _fake_tool_use["parameters"]
|
||||
_current_function = _fake_tool_use["recipient_name"]
|
||||
if _current_function.startswith("functions."):
|
||||
_current_function = _current_function[len("functions.") :]
|
||||
|
||||
shift = 0
|
||||
for i, replacement in replacements.items():
|
||||
tool_calls[:] = (
|
||||
tool_calls[: i + shift] + replacement + tool_calls[i + shift + 1 :]
|
||||
)
|
||||
shift += len(replacement)
|
||||
fixed_tc = ChatCompletionMessageToolCall(
|
||||
id=f"{tool_call.id}_{_fake_i}",
|
||||
type="function",
|
||||
function=Function(
|
||||
name=_current_function, arguments=json.dumps(_function_args)
|
||||
),
|
||||
)
|
||||
replacements[i].append(fixed_tc)
|
||||
|
||||
return tool_calls
|
||||
shift = 0
|
||||
for i, replacement in replacements.items():
|
||||
tool_calls[:] = (
|
||||
tool_calls[: i + shift] + replacement + tool_calls[i + shift + 1 :]
|
||||
)
|
||||
shift += len(replacement)
|
||||
|
||||
return tool_calls
|
||||
except json.JSONDecodeError:
|
||||
# if there is a JSONDecodeError, return the original tool_calls
|
||||
return tool_calls
|
||||
|
||||
|
||||
def convert_to_model_response_object( # noqa: PLR0915
|
||||
|
|
|
|||
|
|
@ -0,0 +1,697 @@
|
|||
import json
|
||||
import os
|
||||
import sys
|
||||
from datetime import datetime
|
||||
|
||||
sys.path.insert(
|
||||
0, os.path.abspath("../../")
|
||||
) # Adds the parent directory to the system path
|
||||
|
||||
import litellm
|
||||
import pytest
|
||||
from datetime import timedelta
|
||||
from litellm.utils import convert_to_model_response_object
|
||||
|
||||
from litellm.types.utils import (
|
||||
ModelResponse,
|
||||
Message,
|
||||
Choices,
|
||||
PromptTokensDetailsWrapper,
|
||||
CompletionTokensDetailsWrapper,
|
||||
)
|
||||
|
||||
|
||||
def test_convert_to_model_response_object_basic():
|
||||
"""Test basic conversion with all fields present."""
|
||||
response_object = {
|
||||
"id": "chatcmpl-123456",
|
||||
"object": "chat.completion",
|
||||
"created": 1728933352,
|
||||
"model": "gpt-4o-2024-08-06",
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "Hi there! How can I assist you today?",
|
||||
"refusal": None,
|
||||
},
|
||||
"finish_reason": "stop",
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"prompt_tokens": 19,
|
||||
"completion_tokens": 10,
|
||||
"total_tokens": 29,
|
||||
"prompt_tokens_details": {"cached_tokens": 0},
|
||||
"completion_tokens_details": {"reasoning_tokens": 0},
|
||||
},
|
||||
"system_fingerprint": "fp_6b68a8204b",
|
||||
}
|
||||
|
||||
result = convert_to_model_response_object(
|
||||
model_response_object=ModelResponse(),
|
||||
response_object=response_object,
|
||||
stream=False,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=False,
|
||||
)
|
||||
|
||||
assert isinstance(result, ModelResponse)
|
||||
assert result.id == "chatcmpl-123456"
|
||||
assert len(result.choices) == 1
|
||||
assert isinstance(result.choices[0], Choices)
|
||||
|
||||
# Model details
|
||||
assert result.model == "gpt-4o-2024-08-06"
|
||||
assert result.object == "chat.completion"
|
||||
assert result.created == 1728933352
|
||||
|
||||
# Choices assertions
|
||||
choice = result.choices[0]
|
||||
print("choice[0]", choice)
|
||||
assert choice.index == 0
|
||||
assert isinstance(choice.message, Message)
|
||||
assert choice.message.role == "assistant"
|
||||
assert choice.message.content == "Hi there! How can I assist you today?"
|
||||
assert choice.finish_reason == "stop"
|
||||
|
||||
# Usage assertions
|
||||
assert result.usage.prompt_tokens == 19
|
||||
assert result.usage.completion_tokens == 10
|
||||
assert result.usage.total_tokens == 29
|
||||
assert result.usage.prompt_tokens_details == PromptTokensDetailsWrapper(
|
||||
cached_tokens=0
|
||||
)
|
||||
assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
|
||||
reasoning_tokens=0
|
||||
)
|
||||
|
||||
# Other fields
|
||||
assert result.system_fingerprint == "fp_6b68a8204b"
|
||||
|
||||
# hidden params
|
||||
assert result._hidden_params is not None
|
||||
|
||||
|
||||
def test_convert_image_input_dict_response_to_chat_completion_response():
|
||||
"""Test conversion on a response with an image input."""
|
||||
response_object = {
|
||||
"id": "chatcmpl-123",
|
||||
"object": "chat.completion",
|
||||
"created": 1677652288,
|
||||
"model": "gpt-4o-mini",
|
||||
"system_fingerprint": "fp_44709d6fcb",
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "\n\nThis image shows a wooden boardwalk extending through a lush green marshland.",
|
||||
},
|
||||
"logprobs": None,
|
||||
"finish_reason": "stop",
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"prompt_tokens": 9,
|
||||
"completion_tokens": 12,
|
||||
"total_tokens": 21,
|
||||
"completion_tokens_details": {"reasoning_tokens": 0},
|
||||
},
|
||||
}
|
||||
|
||||
result = convert_to_model_response_object(
|
||||
model_response_object=ModelResponse(),
|
||||
response_object=response_object,
|
||||
stream=False,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=False,
|
||||
)
|
||||
|
||||
assert isinstance(result, ModelResponse)
|
||||
assert result.id == "chatcmpl-123"
|
||||
assert result.object == "chat.completion"
|
||||
assert result.created == 1677652288
|
||||
assert result.model == "gpt-4o-mini"
|
||||
assert result.system_fingerprint == "fp_44709d6fcb"
|
||||
|
||||
assert len(result.choices) == 1
|
||||
choice = result.choices[0]
|
||||
assert choice.index == 0
|
||||
assert isinstance(choice.message, Message)
|
||||
assert choice.message.role == "assistant"
|
||||
assert (
|
||||
choice.message.content
|
||||
== "\n\nThis image shows a wooden boardwalk extending through a lush green marshland."
|
||||
)
|
||||
assert choice.finish_reason == "stop"
|
||||
|
||||
assert result.usage.prompt_tokens == 9
|
||||
assert result.usage.completion_tokens == 12
|
||||
assert result.usage.total_tokens == 21
|
||||
assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
|
||||
reasoning_tokens=0
|
||||
)
|
||||
|
||||
assert result._hidden_params is not None
|
||||
|
||||
|
||||
def test_convert_to_model_response_object_tool_calls_invalid_json_arguments():
|
||||
"""
|
||||
Critical test - this is a basic response from OpenAI API
|
||||
|
||||
Test conversion with tool calls.
|
||||
|
||||
"""
|
||||
response_object = {
|
||||
"id": "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz",
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"finish_reason": "length",
|
||||
"logprobs": None,
|
||||
"message": {
|
||||
"content": None,
|
||||
"refusal": None,
|
||||
"role": "assistant",
|
||||
"audio": None,
|
||||
"function_call": None,
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_GED1Xit8lU7cNsjVM6dt2fTq",
|
||||
"function": {
|
||||
"arguments": '{"location":"Boston, MA","unit":"fahren',
|
||||
"name": "get_current_weather",
|
||||
},
|
||||
"type": "function",
|
||||
}
|
||||
],
|
||||
},
|
||||
}
|
||||
],
|
||||
"created": 1729337288,
|
||||
"model": "gpt-4o-2024-08-06",
|
||||
"object": "chat.completion",
|
||||
"service_tier": None,
|
||||
"system_fingerprint": "fp_45c6de4934",
|
||||
"usage": {
|
||||
"completion_tokens": 10,
|
||||
"prompt_tokens": 92,
|
||||
"total_tokens": 102,
|
||||
"completion_tokens_details": {"audio_tokens": None, "reasoning_tokens": 0},
|
||||
"prompt_tokens_details": {"audio_tokens": None, "cached_tokens": 0},
|
||||
},
|
||||
}
|
||||
result = convert_to_model_response_object(
|
||||
model_response_object=ModelResponse(),
|
||||
response_object=response_object,
|
||||
stream=False,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=False,
|
||||
)
|
||||
|
||||
assert isinstance(result, ModelResponse)
|
||||
assert result.id == "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz"
|
||||
assert len(result.choices) == 1
|
||||
assert result.choices[0].message.content is None
|
||||
assert len(result.choices[0].message.tool_calls) == 1
|
||||
assert (
|
||||
result.choices[0].message.tool_calls[0].function.name == "get_current_weather"
|
||||
)
|
||||
assert (
|
||||
result.choices[0].message.tool_calls[0].function.arguments
|
||||
== '{"location":"Boston, MA","unit":"fahren'
|
||||
)
|
||||
assert result.choices[0].finish_reason == "length"
|
||||
assert result.model == "gpt-4o-2024-08-06"
|
||||
assert result.created == 1729337288
|
||||
assert result.usage.completion_tokens == 10
|
||||
assert result.usage.prompt_tokens == 92
|
||||
assert result.usage.total_tokens == 102
|
||||
assert result.system_fingerprint == "fp_45c6de4934"
|
||||
|
||||
|
||||
def test_convert_to_model_response_object_tool_calls_valid_json_arguments():
|
||||
"""
|
||||
Critical test - this is a basic response from OpenAI API
|
||||
|
||||
Test conversion with tool calls.
|
||||
|
||||
"""
|
||||
response_object = {
|
||||
"id": "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz",
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"finish_reason": "length",
|
||||
"logprobs": None,
|
||||
"message": {
|
||||
"content": None,
|
||||
"refusal": None,
|
||||
"role": "assistant",
|
||||
"audio": None,
|
||||
"function_call": None,
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_GED1Xit8lU7cNsjVM6dt2fTq",
|
||||
"function": {
|
||||
"arguments": '{"location":"Boston, MA","unit":"fahrenheit"}',
|
||||
"name": "get_current_weather",
|
||||
},
|
||||
"type": "function",
|
||||
}
|
||||
],
|
||||
},
|
||||
}
|
||||
],
|
||||
"created": 1729337288,
|
||||
"model": "gpt-4o-2024-08-06",
|
||||
"object": "chat.completion",
|
||||
"service_tier": None,
|
||||
"system_fingerprint": "fp_45c6de4934",
|
||||
"usage": {
|
||||
"completion_tokens": 10,
|
||||
"prompt_tokens": 92,
|
||||
"total_tokens": 102,
|
||||
"completion_tokens_details": {"audio_tokens": None, "reasoning_tokens": 0},
|
||||
"prompt_tokens_details": {"audio_tokens": None, "cached_tokens": 0},
|
||||
},
|
||||
}
|
||||
result = convert_to_model_response_object(
|
||||
model_response_object=ModelResponse(),
|
||||
response_object=response_object,
|
||||
stream=False,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=False,
|
||||
)
|
||||
|
||||
assert isinstance(result, ModelResponse)
|
||||
assert result.id == "chatcmpl-AK1uqisVA9OjUNkEuE53GJc8HPYlz"
|
||||
assert len(result.choices) == 1
|
||||
assert result.choices[0].message.content is None
|
||||
assert len(result.choices[0].message.tool_calls) == 1
|
||||
assert (
|
||||
result.choices[0].message.tool_calls[0].function.name == "get_current_weather"
|
||||
)
|
||||
assert (
|
||||
result.choices[0].message.tool_calls[0].function.arguments
|
||||
== '{"location":"Boston, MA","unit":"fahrenheit"}'
|
||||
)
|
||||
assert result.choices[0].finish_reason == "length"
|
||||
assert result.model == "gpt-4o-2024-08-06"
|
||||
assert result.created == 1729337288
|
||||
assert result.usage.completion_tokens == 10
|
||||
assert result.usage.prompt_tokens == 92
|
||||
assert result.usage.total_tokens == 102
|
||||
assert result.system_fingerprint == "fp_45c6de4934"
|
||||
|
||||
|
||||
def test_convert_to_model_response_object_json_mode():
|
||||
"""
|
||||
This test is verifying that when convert_tool_call_to_json_mode is True, a single tool call's arguments are correctly converted into the message content of the response.
|
||||
"""
|
||||
model_response_object = ModelResponse(model="gpt-3.5-turbo")
|
||||
response_object = {
|
||||
"choices": [
|
||||
{
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"tool_calls": [{"function": {"arguments": '{"key": "value"}'}}],
|
||||
},
|
||||
"finish_reason": None,
|
||||
}
|
||||
],
|
||||
"usage": {"total_tokens": 10, "prompt_tokens": 5, "completion_tokens": 5},
|
||||
"model": "gpt-3.5-turbo",
|
||||
}
|
||||
|
||||
# Call the function
|
||||
result = convert_to_model_response_object(
|
||||
model_response_object=model_response_object,
|
||||
response_object=response_object,
|
||||
stream=False,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=True,
|
||||
)
|
||||
|
||||
# Assertions
|
||||
assert isinstance(result, ModelResponse)
|
||||
assert len(result.choices) == 1
|
||||
assert result.choices[0].message.content == '{"key": "value"}'
|
||||
assert result.choices[0].finish_reason == "stop"
|
||||
assert result.model == "gpt-3.5-turbo"
|
||||
assert result.usage.total_tokens == 10
|
||||
assert result.usage.prompt_tokens == 5
|
||||
assert result.usage.completion_tokens == 5
|
||||
|
||||
|
||||
def test_convert_to_model_response_object_function_output():
|
||||
"""
|
||||
Test conversion with function output.
|
||||
|
||||
From here: https://platform.openai.com/docs/api-reference/chat/create
|
||||
|
||||
"""
|
||||
response_object = {
|
||||
"id": "chatcmpl-abc123",
|
||||
"object": "chat.completion",
|
||||
"created": 1699896916,
|
||||
"model": "gpt-4o-mini",
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": None,
|
||||
"tool_calls": [
|
||||
{
|
||||
"id": "call_abc123",
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_current_weather",
|
||||
"arguments": '{\n"location": "Boston, MA"\n}',
|
||||
},
|
||||
}
|
||||
],
|
||||
},
|
||||
"logprobs": None,
|
||||
"finish_reason": "tool_calls",
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"prompt_tokens": 82,
|
||||
"completion_tokens": 17,
|
||||
"total_tokens": 99,
|
||||
"completion_tokens_details": {"reasoning_tokens": 0},
|
||||
},
|
||||
}
|
||||
|
||||
result = convert_to_model_response_object(
|
||||
model_response_object=ModelResponse(),
|
||||
response_object=response_object,
|
||||
stream=False,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=False,
|
||||
)
|
||||
|
||||
assert isinstance(result, ModelResponse)
|
||||
assert result.id == "chatcmpl-abc123"
|
||||
assert result.object == "chat.completion"
|
||||
assert result.created == 1699896916
|
||||
assert result.model == "gpt-4o-mini"
|
||||
|
||||
assert len(result.choices) == 1
|
||||
choice = result.choices[0]
|
||||
assert choice.index == 0
|
||||
assert isinstance(choice.message, Message)
|
||||
assert choice.message.role == "assistant"
|
||||
assert choice.message.content is None
|
||||
assert choice.finish_reason == "tool_calls"
|
||||
|
||||
assert len(choice.message.tool_calls) == 1
|
||||
tool_call = choice.message.tool_calls[0]
|
||||
assert tool_call.id == "call_abc123"
|
||||
assert tool_call.type == "function"
|
||||
assert tool_call.function.name == "get_current_weather"
|
||||
assert tool_call.function.arguments == '{\n"location": "Boston, MA"\n}'
|
||||
|
||||
assert result.usage.prompt_tokens == 82
|
||||
assert result.usage.completion_tokens == 17
|
||||
assert result.usage.total_tokens == 99
|
||||
assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
|
||||
reasoning_tokens=0
|
||||
)
|
||||
|
||||
assert result._hidden_params is not None
|
||||
|
||||
|
||||
def test_convert_to_model_response_object_with_logprobs():
|
||||
"""
|
||||
|
||||
Test conversion with logprobs in the response.
|
||||
|
||||
From here: https://platform.openai.com/docs/api-reference/chat/create
|
||||
|
||||
"""
|
||||
response_object = {
|
||||
"id": "chatcmpl-123",
|
||||
"object": "chat.completion",
|
||||
"created": 1702685778,
|
||||
"model": "gpt-4o-mini",
|
||||
"choices": [
|
||||
{
|
||||
"index": 0,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "Hello! How can I assist you today?",
|
||||
},
|
||||
"logprobs": {
|
||||
"content": [
|
||||
{
|
||||
"token": "Hello",
|
||||
"logprob": -0.31725305,
|
||||
"bytes": [72, 101, 108, 108, 111],
|
||||
"top_logprobs": [
|
||||
{
|
||||
"token": "Hello",
|
||||
"logprob": -0.31725305,
|
||||
"bytes": [72, 101, 108, 108, 111],
|
||||
},
|
||||
{
|
||||
"token": "Hi",
|
||||
"logprob": -1.3190403,
|
||||
"bytes": [72, 105],
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": "!",
|
||||
"logprob": -0.02380986,
|
||||
"bytes": [33],
|
||||
"top_logprobs": [
|
||||
{"token": "!", "logprob": -0.02380986, "bytes": [33]},
|
||||
{
|
||||
"token": " there",
|
||||
"logprob": -3.787621,
|
||||
"bytes": [32, 116, 104, 101, 114, 101],
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": " How",
|
||||
"logprob": -0.000054669687,
|
||||
"bytes": [32, 72, 111, 119],
|
||||
"top_logprobs": [
|
||||
{
|
||||
"token": " How",
|
||||
"logprob": -0.000054669687,
|
||||
"bytes": [32, 72, 111, 119],
|
||||
},
|
||||
{
|
||||
"token": "<|end|>",
|
||||
"logprob": -10.953937,
|
||||
"bytes": None,
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": " can",
|
||||
"logprob": -0.015801601,
|
||||
"bytes": [32, 99, 97, 110],
|
||||
"top_logprobs": [
|
||||
{
|
||||
"token": " can",
|
||||
"logprob": -0.015801601,
|
||||
"bytes": [32, 99, 97, 110],
|
||||
},
|
||||
{
|
||||
"token": " may",
|
||||
"logprob": -4.161023,
|
||||
"bytes": [32, 109, 97, 121],
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": " I",
|
||||
"logprob": -3.7697225e-6,
|
||||
"bytes": [32, 73],
|
||||
"top_logprobs": [
|
||||
{
|
||||
"token": " I",
|
||||
"logprob": -3.7697225e-6,
|
||||
"bytes": [32, 73],
|
||||
},
|
||||
{
|
||||
"token": " assist",
|
||||
"logprob": -13.596657,
|
||||
"bytes": [32, 97, 115, 115, 105, 115, 116],
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": " assist",
|
||||
"logprob": -0.04571125,
|
||||
"bytes": [32, 97, 115, 115, 105, 115, 116],
|
||||
"top_logprobs": [
|
||||
{
|
||||
"token": " assist",
|
||||
"logprob": -0.04571125,
|
||||
"bytes": [32, 97, 115, 115, 105, 115, 116],
|
||||
},
|
||||
{
|
||||
"token": " help",
|
||||
"logprob": -3.1089056,
|
||||
"bytes": [32, 104, 101, 108, 112],
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": " you",
|
||||
"logprob": -5.4385737e-6,
|
||||
"bytes": [32, 121, 111, 117],
|
||||
"top_logprobs": [
|
||||
{
|
||||
"token": " you",
|
||||
"logprob": -5.4385737e-6,
|
||||
"bytes": [32, 121, 111, 117],
|
||||
},
|
||||
{
|
||||
"token": " today",
|
||||
"logprob": -12.807695,
|
||||
"bytes": [32, 116, 111, 100, 97, 121],
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": " today",
|
||||
"logprob": -0.0040071653,
|
||||
"bytes": [32, 116, 111, 100, 97, 121],
|
||||
"top_logprobs": [
|
||||
{
|
||||
"token": " today",
|
||||
"logprob": -0.0040071653,
|
||||
"bytes": [32, 116, 111, 100, 97, 121],
|
||||
},
|
||||
{"token": "?", "logprob": -5.5247097, "bytes": [63]},
|
||||
],
|
||||
},
|
||||
{
|
||||
"token": "?",
|
||||
"logprob": -0.0008108172,
|
||||
"bytes": [63],
|
||||
"top_logprobs": [
|
||||
{"token": "?", "logprob": -0.0008108172, "bytes": [63]},
|
||||
{
|
||||
"token": "?\n",
|
||||
"logprob": -7.184561,
|
||||
"bytes": [63, 10],
|
||||
},
|
||||
],
|
||||
},
|
||||
]
|
||||
},
|
||||
"finish_reason": "stop",
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"prompt_tokens": 9,
|
||||
"completion_tokens": 9,
|
||||
"total_tokens": 18,
|
||||
"completion_tokens_details": {"reasoning_tokens": 0},
|
||||
},
|
||||
"system_fingerprint": None,
|
||||
}
|
||||
|
||||
result = convert_to_model_response_object(
|
||||
model_response_object=ModelResponse(),
|
||||
response_object=response_object,
|
||||
stream=False,
|
||||
start_time=datetime.now(),
|
||||
end_time=datetime.now(),
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=False,
|
||||
)
|
||||
|
||||
assert isinstance(result, ModelResponse)
|
||||
assert result.id == "chatcmpl-123"
|
||||
assert result.object == "chat.completion"
|
||||
assert result.created == 1702685778
|
||||
assert result.model == "gpt-4o-mini"
|
||||
|
||||
assert len(result.choices) == 1
|
||||
choice = result.choices[0]
|
||||
assert choice.index == 0
|
||||
assert isinstance(choice.message, Message)
|
||||
assert choice.message.role == "assistant"
|
||||
assert choice.message.content == "Hello! How can I assist you today?"
|
||||
assert choice.finish_reason == "stop"
|
||||
|
||||
# Check logprobs
|
||||
assert choice.logprobs is not None
|
||||
assert len(choice.logprobs["content"]) == 9
|
||||
|
||||
# Check each logprob entry
|
||||
expected_tokens = [
|
||||
"Hello",
|
||||
"!",
|
||||
" How",
|
||||
" can",
|
||||
" I",
|
||||
" assist",
|
||||
" you",
|
||||
" today",
|
||||
"?",
|
||||
]
|
||||
for i, logprob in enumerate(choice.logprobs["content"]):
|
||||
assert logprob["token"] == expected_tokens[i]
|
||||
assert isinstance(logprob["logprob"], float)
|
||||
assert isinstance(logprob["bytes"], list)
|
||||
assert len(logprob["top_logprobs"]) == 2
|
||||
assert isinstance(logprob["top_logprobs"][0]["token"], str)
|
||||
assert isinstance(logprob["top_logprobs"][0]["logprob"], float)
|
||||
assert isinstance(logprob["top_logprobs"][0]["bytes"], (list, type(None)))
|
||||
|
||||
assert result.usage.prompt_tokens == 9
|
||||
assert result.usage.completion_tokens == 9
|
||||
assert result.usage.total_tokens == 18
|
||||
assert result.usage.completion_tokens_details == CompletionTokensDetailsWrapper(
|
||||
reasoning_tokens=0
|
||||
)
|
||||
|
||||
assert result.system_fingerprint is None
|
||||
assert result._hidden_params is not None
|
||||
|
||||
|
||||
def test_convert_to_model_response_object_error():
|
||||
"""Test error handling for None response object."""
|
||||
with pytest.raises(Exception, match="Error in response object format"):
|
||||
convert_to_model_response_object(
|
||||
model_response_object=None,
|
||||
response_object=None,
|
||||
stream=False,
|
||||
start_time=None,
|
||||
end_time=None,
|
||||
hidden_params=None,
|
||||
_response_headers=None,
|
||||
convert_tool_call_to_json_mode=False,
|
||||
)
|
||||
Loading…
Add table
Add a link
Reference in a new issue