fix(utils.py): ensure last chunk is always empty delta w/ finish reason

makes sure we're openai-compatible with our streaming. Adds stricter tests for this as well
This commit is contained in:
Krrish Dholakia 2024-03-25 16:33:41 -07:00
parent f153889738
commit 9e1e97528d
3 changed files with 221 additions and 285 deletions

View file

@ -1,119 +1,6 @@
============================= test session starts ==============================
platform darwin -- Python 3.11.6, pytest-7.3.1, pluggy-1.3.0
rootdir: /Users/krrishdholakia/Documents/litellm/litellm/tests
plugins: timeout-2.2.0, asyncio-0.23.2, anyio-3.7.1, xdist-3.3.1
asyncio: mode=Mode.STRICT
collected 1 item
test_completion.py . [100%]
=============================== warnings summary ===============================
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
../../../../../../opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271
/opt/homebrew/lib/python3.11/site-packages/pydantic/_internal/_config.py:271: PydanticDeprecatedSince20: Support for class-based `config` is deprecated, use ConfigDict instead. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
warnings.warn(DEPRECATION_MESSAGE, DeprecationWarning)
../proxy/_types.py:102
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:102: PydanticDeprecatedSince20: `pydantic.config.Extra` is deprecated, use literal values instead (e.g. `extra='allow'`). Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
extra = Extra.allow # Allow extra fields
../proxy/_types.py:105
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:105: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:134
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:134: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:180
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:180: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:241
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:241: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:253
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:253: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:292
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:292: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:319
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:319: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:570
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:570: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../proxy/_types.py:591
/Users/krrishdholakia/Documents/litellm/litellm/proxy/_types.py:591: PydanticDeprecatedSince20: Pydantic V1 style `@root_validator` validators are deprecated. You should migrate to Pydantic V2 style `@model_validator` validators, see the migration guide for more details. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.5/migration/
@root_validator(pre=True)
../utils.py:35
/Users/krrishdholakia/Documents/litellm/litellm/utils.py:35: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
import pkg_resources
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: 10 warnings
/opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
/opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google.cloud')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350
/opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2350: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(parent)
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
/opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google.logging')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
/opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('google.iam')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
/opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('mpl_toolkits')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
../../../../../../opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871
/opt/homebrew/lib/python3.11/site-packages/pkg_resources/__init__.py:2871: DeprecationWarning: Deprecated call to `pkg_resources.declare_namespace('sphinxcontrib')`.
Implementing implicit namespace packages (as specified in PEP 420) is preferred to `pkg_resources.declare_namespace`. See https://setuptools.pypa.io/en/latest/references/keywords.html#keyword-namespace-packages
declare_namespace(pkg)
../llms/prompt_templates/factory.py:6
/Users/krrishdholakia/Documents/litellm/litellm/llms/prompt_templates/factory.py:6: DeprecationWarning: 'imghdr' is deprecated and slated for removal in Python 3.13
import imghdr, base64
test_completion.py::test_completion_claude_3_stream
../utils.py:3249
../utils.py:3249
/Users/krrishdholakia/Documents/litellm/litellm/utils.py:3249: DeprecationWarning: open_text is deprecated. Use files() instead. Refer to https://importlib-resources.readthedocs.io/en/latest/using.html#migrating-from-legacy for migration advice.
with resources.open_text(
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
======================== 1 passed, 46 warnings in 3.14s ========================
<litellm.utils.CustomStreamWrapper object at 0x118bd82d0>
chunk: ModelResponse(id='chatcmpl-95b7d389-ff5a-4e09-a084-02584ba2cf1e', choices=[StreamingChoices(finish_reason=None, index=0, delta=Delta(content='In the United States of America, the Supreme Court has ultimate judicial authority, and it is the one that rules on legal disputes between the states, or on the interpretation of the', role='assistant', function_call=None, tool_calls=None), logprobs=None)], created=1711406570, model='ai21.j2-mid-v1', object='chat.completion.chunk', system_fingerprint=None, usage=Usage())
extracted chunk: In the United States of America, the Supreme Court has ultimate judicial authority, and it is the one that rules on legal disputes between the states, or on the interpretation of the
chunk: ModelResponse(id='chatcmpl-95b7d389-ff5a-4e09-a084-02584ba2cf1e', choices=[StreamingChoices(finish_reason='stop', index=0, delta=Delta(content=None, role=None, function_call=None, tool_calls=None), logprobs=None)], created=1711406570, model='ai21.j2-mid-v1', object='chat.completion.chunk', system_fingerprint=None, usage=Usage())
extracted chunk:
completion_response: In the United States of America, the Supreme Court has ultimate judicial authority, and it is the one that rules on legal disputes between the states, or on the interpretation of the

View file

@ -108,8 +108,19 @@ last_openai_chunk_example = {
"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}],
}
"""
Final chunk (sdk):
chunk: ChatCompletionChunk(id='chatcmpl-96mM3oNBlxh2FDWVLKsgaFBBcULmI',
choices=[Choice(delta=ChoiceDelta(content=None, function_call=None, role=None,
tool_calls=None), finish_reason='stop', index=0, logprobs=None)],
created=1711402871, model='gpt-3.5-turbo-0125', object='chat.completion.chunk', system_fingerprint='fp_3bc1b5746c')
"""
def validate_last_format(chunk):
"""
Ensure last chunk has no remaining content or tools
"""
assert isinstance(chunk, ModelResponse), "Chunk should be a dictionary."
assert isinstance(chunk["id"], str), "'id' should be a string."
assert isinstance(chunk["object"], str), "'object' should be a string."
@ -119,6 +130,10 @@ def validate_last_format(chunk):
for choice in chunk["choices"]:
assert isinstance(choice["index"], int), "'index' should be an integer."
assert choice["delta"]["content"] is None
assert choice["delta"]["function_call"] is None
assert choice["delta"]["role"] is None
assert choice["delta"]["tool_calls"] is None
assert isinstance(
choice["finish_reason"], str
), "'finish_reason' should be a string."
@ -493,13 +508,15 @@ def test_completion_mistral_api_stream():
stream=True,
)
complete_response = ""
has_finish_reason = False
for idx, chunk in enumerate(response):
print(chunk)
# print(chunk.choices[0].delta)
chunk, finished = streaming_format_tests(idx, chunk)
if finished:
has_finish_reason = True
break
complete_response += chunk
if has_finish_reason == False:
raise Exception("finish reason not set")
if complete_response.strip() == "":
raise Exception("Empty response received")
print(f"completion_response: {complete_response}")
@ -534,11 +551,15 @@ def test_completion_deep_infra_stream():
complete_response = ""
# Add any assertions here to check the response
has_finish_reason = False
for idx, chunk in enumerate(response):
chunk, finished = streaming_format_tests(idx, chunk)
if finished:
has_finish_reason = True
break
complete_response += chunk
if has_finish_reason == False:
raise Exception("finish reason not set")
if complete_response.strip() == "":
raise Exception("Empty response received")
print(f"completion_response: {complete_response}")
@ -608,11 +629,15 @@ def test_completion_claude_stream_bad_key():
)
complete_response = ""
# Add any assertions here to check the response
has_finish_reason = False
for idx, chunk in enumerate(response):
chunk, finished = streaming_format_tests(idx, chunk)
if finished:
has_finish_reason = True
break
complete_response += chunk
if has_finish_reason == False:
raise Exception("finish reason not set")
if complete_response.strip() == "":
raise Exception("Empty response received")
print(f"1234completion_response: {complete_response}")
@ -626,6 +651,45 @@ def test_completion_claude_stream_bad_key():
# test_completion_claude_stream_bad_key()
# test_completion_replicate_stream()
def test_vertex_ai_stream():
from litellm.tests.test_amazing_vertex_completion import load_vertex_ai_credentials
load_vertex_ai_credentials()
litellm.set_verbose = True
litellm.vertex_project = "reliablekeys"
import random
test_models = ["gemini-1.0-pro"]
for model in test_models:
try:
print("making request", model)
response = completion(
model=model,
messages=[
{"role": "user", "content": "write 10 line code code for saying hi"}
],
stream=True,
)
complete_response = ""
is_finished = False
for idx, chunk in enumerate(response):
print(f"chunk in response: {chunk}")
chunk, finished = streaming_format_tests(idx, chunk)
if finished:
is_finished = True
break
complete_response += chunk
if complete_response.strip() == "":
raise Exception("Empty response received")
print(f"completion_response: {complete_response}")
assert is_finished == True
except litellm.RateLimitError as e:
pass
except Exception as e:
pytest.fail(f"Error occurred: {e}")
# def test_completion_vertexai_stream():
# try:
# import os
@ -742,11 +806,15 @@ def test_bedrock_claude_3_streaming():
)
complete_response = ""
# Add any assertions here to check the response
has_finish_reason = False
for idx, chunk in enumerate(response):
chunk, finished = streaming_format_tests(idx, chunk)
if finished:
has_finish_reason = True
break
complete_response += chunk
if has_finish_reason == False:
raise Exception("finish reason not set")
if complete_response.strip() == "":
raise Exception("Empty response received")
print(f"completion_response: {complete_response}")
@ -1705,7 +1773,7 @@ def test_success_callback_streaming():
messages = [{"role": "user", "content": "hello"}]
print("TESTING LITELLM COMPLETION CALL")
response = litellm.completion(
model="j2-light",
model="gpt-3.5-turbo",
messages=messages,
stream=True,
max_tokens=5,
@ -2072,7 +2140,7 @@ def test_completion_claude_3_function_call_with_streaming():
)
idx = 0
for chunk in response:
# print(f"chunk: {chunk}")
print(f"chunk in response: {chunk}")
if idx == 0:
assert (
chunk.choices[0].delta.tool_calls[0].function.arguments is not None
@ -2081,7 +2149,7 @@ def test_completion_claude_3_function_call_with_streaming():
chunk.choices[0].delta.tool_calls[0].function.arguments, str
)
validate_first_streaming_function_calling_chunk(chunk=chunk)
elif idx == 1:
elif idx == 1 and chunk.choices[0].finish_reason is None:
validate_second_streaming_function_calling_chunk(chunk=chunk)
elif chunk.choices[0].finish_reason is not None: # last chunk
validate_final_streaming_function_calling_chunk(chunk=chunk)
@ -2136,7 +2204,7 @@ async def test_acompletion_claude_3_function_call_with_streaming():
chunk.choices[0].delta.tool_calls[0].function.arguments, str
)
validate_first_streaming_function_calling_chunk(chunk=chunk)
elif idx == 1:
elif idx == 1 and chunk.choices[0].finish_reason is None:
validate_second_streaming_function_calling_chunk(chunk=chunk)
elif chunk.choices[0].finish_reason is not None: # last chunk
validate_final_streaming_function_calling_chunk(chunk=chunk)

View file

@ -8458,6 +8458,7 @@ class CustomStreamWrapper:
self.completion_stream = completion_stream
self.sent_first_chunk = False
self.sent_last_chunk = False
self.received_finish_reason: Optional[str] = None
self.special_tokens = ["<|assistant|>", "<|system|>", "<|user|>", "<s>", "</s>"]
self.holding_chunk = ""
self.complete_response = ""
@ -9131,7 +9132,7 @@ class CustomStreamWrapper:
"finish_reason": finish_reason,
}
def chunk_creator(self, chunk):
def model_response_creator(self):
model_response = ModelResponse(stream=True, model=self.model)
if self.response_id is not None:
model_response.id = self.response_id
@ -9141,6 +9142,20 @@ class CustomStreamWrapper:
model_response._hidden_params["created_at"] = time.time()
model_response.choices = [StreamingChoices()]
model_response.choices[0].finish_reason = None
return model_response
def is_delta_empty(self, delta: Delta) -> bool:
is_empty = True
if delta.content is not None:
is_empty = False
elif delta.tool_calls is not None:
is_empty = False
elif delta.function_call is not None:
is_empty = False
return is_empty
def chunk_creator(self, chunk):
model_response = self.model_response_creator()
response_obj = {}
try:
# return this for all models
@ -9149,30 +9164,22 @@ class CustomStreamWrapper:
response_obj = self.handle_anthropic_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.model == "replicate" or self.custom_llm_provider == "replicate":
response_obj = self.handle_replicate_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider and self.custom_llm_provider == "together_ai":
response_obj = self.handle_together_ai_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider and self.custom_llm_provider == "huggingface":
response_obj = self.handle_huggingface_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif (
self.custom_llm_provider and self.custom_llm_provider == "baseten"
): # baseten doesn't provide streaming
@ -9183,16 +9190,12 @@ class CustomStreamWrapper:
response_obj = self.handle_ai21_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider and self.custom_llm_provider == "maritalk":
response_obj = self.handle_maritalk_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider and self.custom_llm_provider == "vllm":
completion_obj["content"] = chunk[0].outputs[0].text
elif (
@ -9201,35 +9204,29 @@ class CustomStreamWrapper:
response_obj = self.handle_aleph_alpha_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "nlp_cloud":
try:
response_obj = self.handle_nlp_cloud_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
except Exception as e:
if self.sent_last_chunk:
if self.received_finish_reason:
raise e
else:
if self.sent_first_chunk is False:
raise Exception("An unknown error occurred with the stream")
model_response.choices[0].finish_reason = "stop"
self.sent_last_chunk = True
self.received_finish_reason = "stop"
elif self.custom_llm_provider == "gemini":
try:
if hasattr(chunk, "parts") == True:
try:
if len(chunk.parts) > 0:
completion_obj["content"] = chunk.parts[0].text
if hasattr(chunk.parts[0], "finish_reason"):
model_response.choices[0].finish_reason = (
map_finish_reason(chunk.parts[0].finish_reason.name)
)
self.received_finish_reason = chunk.parts[
0
].finish_reason.name
except:
if chunk.parts[0].finish_reason.name == "SAFETY":
raise Exception(
@ -9237,14 +9234,7 @@ class CustomStreamWrapper:
)
else:
completion_obj["content"] = str(chunk)
except StopIteration as e:
if self.sent_last_chunk:
raise e
else:
model_response.choices[0].finish_reason = "stop"
self.sent_last_chunk = True
elif self.custom_llm_provider and (self.custom_llm_provider == "vertex_ai"):
try:
if hasattr(chunk, "candidates") == True:
try:
try:
@ -9253,9 +9243,7 @@ class CustomStreamWrapper:
if "Part has no text." in str(e):
## check for function calling
function_call = (
chunk.candidates[0]
.content.parts[0]
.function_call
chunk.candidates[0].content.parts[0].function_call
)
args_dict = {}
for k, v in function_call.args.items():
@ -9274,9 +9262,7 @@ class CustomStreamWrapper:
}
],
)
_streaming_response = StreamingChoices(
delta=_delta_obj
)
_streaming_response = StreamingChoices(delta=_delta_obj)
_model_response = ModelResponse(stream=True)
_model_response.choices = [_streaming_response]
response_obj = {"original_chunk": _model_response}
@ -9287,11 +9273,9 @@ class CustomStreamWrapper:
and chunk.candidates[0].finish_reason.name
!= "FINISH_REASON_UNSPECIFIED"
): # every non-final chunk in vertex ai has this
model_response.choices[0].finish_reason = (
map_finish_reason(
chunk.candidates[0].finish_reason.name
)
)
self.received_finish_reason = chunk.candidates[
0
].finish_reason.name
except Exception as e:
if chunk.candidates[0].finish_reason.name == "SAFETY":
raise Exception(
@ -9299,54 +9283,37 @@ class CustomStreamWrapper:
)
else:
completion_obj["content"] = str(chunk)
except StopIteration as e:
if self.sent_last_chunk:
raise e
else:
model_response.choices[0].finish_reason = "stop"
self.sent_last_chunk = True
elif self.custom_llm_provider == "cohere":
response_obj = self.handle_cohere_chunk(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "cohere_chat":
response_obj = self.handle_cohere_chat_chunk(chunk)
if response_obj is None:
return
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "bedrock":
if self.sent_last_chunk:
if self.received_finish_reason is not None:
raise StopIteration
response_obj = self.handle_bedrock_stream(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.sent_last_chunk = True
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "sagemaker":
verbose_logger.debug(f"ENTERS SAGEMAKER STREAMING for chunk {chunk}")
print_verbose(f"ENTERS SAGEMAKER STREAMING for chunk {chunk}")
response_obj = self.handle_sagemaker_stream(chunk)
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.sent_last_chunk = True
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "petals":
if len(self.completion_stream) == 0:
if self.sent_last_chunk:
if self.received_finish_reason is not None:
raise StopIteration
else:
model_response.choices[0].finish_reason = "stop"
self.sent_last_chunk = True
self.received_finish_reason = "stop"
chunk_size = 30
new_chunk = self.completion_stream[:chunk_size]
completion_obj["content"] = new_chunk
@ -9356,11 +9323,10 @@ class CustomStreamWrapper:
# fake streaming
response_obj = {}
if len(self.completion_stream) == 0:
if self.sent_last_chunk:
if self.received_finish_reason is not None:
raise StopIteration
else:
model_response.choices[0].finish_reason = "stop"
self.sent_last_chunk = True
self.received_finish_reason = "stop"
chunk_size = 30
new_chunk = self.completion_stream[:chunk_size]
completion_obj["content"] = new_chunk
@ -9371,41 +9337,31 @@ class CustomStreamWrapper:
completion_obj["content"] = response_obj["text"]
print_verbose(f"completion obj content: {completion_obj['content']}")
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "ollama_chat":
response_obj = self.handle_ollama_chat_stream(chunk)
completion_obj["content"] = response_obj["text"]
print_verbose(f"completion obj content: {completion_obj['content']}")
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "cloudflare":
response_obj = self.handle_cloudlfare_stream(chunk)
completion_obj["content"] = response_obj["text"]
print_verbose(f"completion obj content: {completion_obj['content']}")
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "text-completion-openai":
response_obj = self.handle_openai_text_completion_chunk(chunk)
completion_obj["content"] = response_obj["text"]
print_verbose(f"completion obj content: {completion_obj['content']}")
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "azure_text":
response_obj = self.handle_azure_text_completion_chunk(chunk)
completion_obj["content"] = response_obj["text"]
print_verbose(f"completion obj content: {completion_obj['content']}")
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
elif self.custom_llm_provider == "cached_response":
response_obj = {
"text": chunk.choices[0].delta.content,
@ -9419,9 +9375,7 @@ class CustomStreamWrapper:
if hasattr(chunk, "id"):
model_response.id = chunk.id
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
else: # openai / azure chat model
if self.custom_llm_provider == "azure":
if hasattr(chunk, "model"):
@ -9437,9 +9391,7 @@ class CustomStreamWrapper:
raise Exception(
"Mistral API raised a streaming error - finish_reason: error, no content string given."
)
model_response.choices[0].finish_reason = response_obj[
"finish_reason"
]
self.received_finish_reason = response_obj["finish_reason"]
if response_obj.get("original_chunk", None) is not None:
model_response.system_fingerprint = getattr(
response_obj["original_chunk"], "system_fingerprint", None
@ -9451,7 +9403,7 @@ class CustomStreamWrapper:
model_response.model = self.model
print_verbose(
f"model_response finish reason 3: {model_response.choices[0].finish_reason}; response_obj={response_obj}"
f"model_response finish reason 3: {self.received_finish_reason}; response_obj={response_obj}"
)
## FUNCTION CALL PARSING
if (
@ -9580,7 +9532,7 @@ class CustomStreamWrapper:
return model_response
else:
return
elif model_response.choices[0].finish_reason is not None:
elif self.received_finish_reason is not None:
# flush any remaining holding chunk
if len(self.holding_chunk) > 0:
if model_response.choices[0].delta.content is None:
@ -9590,10 +9542,17 @@ class CustomStreamWrapper:
self.holding_chunk + model_response.choices[0].delta.content
)
self.holding_chunk = ""
# if delta is None
is_delta_empty = self.is_delta_empty(
delta=model_response.choices[0].delta
)
if is_delta_empty:
# get any function call arguments
model_response.choices[0].finish_reason = map_finish_reason(
model_response.choices[0].finish_reason
finish_reason=self.received_finish_reason
) # ensure consistent output to openai
self.sent_last_chunk = True
return model_response
elif (
model_response.choices[0].delta.tool_calls is not None
@ -9653,6 +9612,16 @@ class CustomStreamWrapper:
## SYNC LOGGING
self.logging_obj.success_handler(processed_chunk)
def finish_reason_handler(self):
model_response = self.model_response_creator()
if self.received_finish_reason is not None:
model_response.choices[0].finish_reason = map_finish_reason(
finish_reason=self.received_finish_reason
)
else:
model_response.choices[0].finish_reason = "stop"
return model_response
## needs to handle the empty string case (even starting chunk can be an empty string)
def __next__(self):
try:
@ -9687,7 +9656,11 @@ class CustomStreamWrapper:
# RETURN RESULT
return response
except StopIteration:
if self.sent_last_chunk == True:
raise # Re-raise StopIteration
else:
self.sent_last_chunk = True
return self.finish_reason_handler()
except Exception as e:
traceback_exception = traceback.format_exc()
# LOG FAILURE - handle streaming failure logging in the _next_ object, remove `handle_failure` once it's deprecated
@ -9792,9 +9765,17 @@ class CustomStreamWrapper:
# RETURN RESULT
return processed_chunk
except StopAsyncIteration:
raise
if self.sent_last_chunk == True:
raise # Re-raise StopIteration
else:
self.sent_last_chunk = True
return self.finish_reason_handler()
except StopIteration:
raise StopAsyncIteration # Re-raise StopIteration
if self.sent_last_chunk == True:
raise StopAsyncIteration
else:
self.sent_last_chunk = True
return self.finish_reason_handler()
except Exception as e:
traceback_exception = traceback.format_exc()
# Handle any exceptions that might occur during streaming