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fix streaming formatting for non-openai models

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This commit is contained in:
Krrish Dholakia 2023-09-16 19:20:07 -07:00
parent a63784d5b3
commit e44c218c1b
6 changed files with 16 additions and 14 deletions
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2
fastrepl-proxy

@ -1 +1 @@
Subproject commit c765f07b74f9a8cae211584ee70bad10e1a847a9
Subproject commit f2fe83e002a7c3ddedf4e500665644adfd31b9fc

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litellm/__pycache__/main.cpython-311.pyc
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litellm/__pycache__/utils.cpython-311.pyc
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11
litellm/main.py
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@ -163,6 +163,7 @@ def completion(
custom_llm_provider = model.split("/", 1)[0]
model = model.split("/", 1)[1]
model, custom_llm_provider = get_llm_provider(model=model, custom_llm_provider=custom_llm_provider)
print(f"model: {model}; llm provider: {custom_llm_provider}")
# check if user passed in any of the OpenAI optional params
optional_params = get_optional_params(
functions=functions,
@ -245,7 +246,7 @@ def completion(
**optional_params,
)
if "stream" in optional_params and optional_params["stream"] == True:
response = CustomStreamWrapper(response, model, logging_obj=logging)
response = CustomStreamWrapper(response, model, custom_llm_provider="openai", logging_obj=logging)
return response
## LOGGING
logging.post_call(
@ -310,7 +311,7 @@ def completion(
raise e
if "stream" in optional_params and optional_params["stream"] == True:
response = CustomStreamWrapper(response, model, logging_obj=logging)
response = CustomStreamWrapper(response, model, custom_llm_provider="openai", logging_obj=logging)
return response
## LOGGING
logging.post_call(
@ -374,7 +375,7 @@ def completion(
**optional_params
)
if "stream" in optional_params and optional_params["stream"] == True:
response = CustomStreamWrapper(response, model, custom_llm_provider="openai", logging_obj=logging)
response = CustomStreamWrapper(response, model, custom_llm_provider="text-completion-openai", logging_obj=logging)
return response
## LOGGING
logging.post_call(
@ -446,7 +447,7 @@ def completion(
)
if "stream" in optional_params and optional_params["stream"] == True:
# don't try to access stream object,
response = CustomStreamWrapper(model_response, model, logging_obj=logging)
response = CustomStreamWrapper(model_response, model, custom_llm_provider="anthropic", logging_obj=logging)
return response
response = model_response
elif model in litellm.nlp_cloud_models or custom_llm_provider == "nlp_cloud":
@ -493,7 +494,7 @@ def completion(
if "stream" in optional_params and optional_params["stream"] == True:
# don't try to access stream object,
response = CustomStreamWrapper(model_response, model, logging_obj=logging)
response = CustomStreamWrapper(model_response, model, custom_llm_provider="aleph-alpha", logging_obj=logging)
return response
response = model_response
elif model in litellm.openrouter_models or custom_llm_provider == "openrouter":

15
litellm/utils.py
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@ -2510,11 +2510,11 @@ class CustomStreamWrapper:
model_response = ModelResponse(stream=True, model=self.model)
try:
# return this for all models
completion_obj = {"content": ""}
if self.sent_first_chunk == False:
model_response.choices[0].delta.role = "assistant"
completion_obj["role"] = "assistant"
self.sent_first_chunk = True
completion_obj = {"content": ""} # default to role being assistant
if self.model in litellm.anthropic_models:
if self.custom_llm_provider and self.custom_llm_provider == "anthropic":
chunk = next(self.completion_stream)
completion_obj["content"] = self.handle_anthropic_chunk(chunk)
elif self.model == "replicate" or self.custom_llm_provider == "replicate":
@ -2539,10 +2539,10 @@ class CustomStreamWrapper:
elif self.custom_llm_provider and self.custom_llm_provider == "vllm":
chunk = next(self.completion_stream)
completion_obj["content"] = chunk[0].outputs[0].text
elif self.model in litellm.aleph_alpha_models: #aleph alpha doesn't provide streaming
elif self.custom_llm_provider and self.custom_llm_provider == "aleph-alpha": #aleph alpha doesn't provide streaming
chunk = next(self.completion_stream)
completion_obj["content"] = self.handle_aleph_alpha_chunk(chunk)
elif self.model in litellm.open_ai_text_completion_models:
elif self.custom_llm_provider and self.custom_llm_provider == "text-completion-openai":
chunk = next(self.completion_stream)
completion_obj["content"] = self.handle_openai_text_completion_chunk(chunk)
elif self.model in litellm.nlp_cloud_models or self.custom_llm_provider == "nlp_cloud":
@ -2551,7 +2551,7 @@ class CustomStreamWrapper:
elif self.model in (litellm.vertex_chat_models + litellm.vertex_code_chat_models + litellm.vertex_text_models + litellm.vertex_code_text_models):
chunk = next(self.completion_stream)
completion_obj["content"] = str(chunk)
elif self.model in litellm.cohere_models or self.custom_llm_provider == "cohere":
elif self.custom_llm_provider == "cohere":
chunk = next(self.completion_stream)
completion_obj["content"] = self.handle_cohere_chunk(chunk)
elif self.custom_llm_provider == "bedrock":
@ -2566,7 +2566,8 @@ class CustomStreamWrapper:
# LOGGING
threading.Thread(target=self.logging_obj.success_handler, args=(completion_obj,)).start()
model_response.model = self.model
model_response.choices[0].delta["content"] = completion_obj["content"]
if len(completion_obj["content"]) > 0: # cannot set content of an OpenAI Object to be an empty string
model_response.choices[0].delta = Delta(**completion_obj)
return model_response
except StopIteration:
raise StopIteration

2
pyproject.toml
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@ -1,6 +1,6 @@
[tool.poetry]
name = "litellm"
version = "0.1.683"
version = "0.1.684"
description = "Library to easily interface with LLM API providers"
authors = ["BerriAI"]
license = "MIT License"