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refactor(openai.py): moving openai text completion calls to http

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This commit is contained in:
Krrish Dholakia 2023-11-08 18:39:56 -08:00
parent db0e032d53
commit c2cbdb23fd
6 changed files with 211 additions and 66 deletions
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55
litellm/utils.py
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@ -2890,19 +2890,19 @@ def exception_type(
exception_type = type(original_exception).__name__
else:
exception_type = ""
if custom_llm_provider == "openai":
if custom_llm_provider == "openai" or custom_llm_provider == "text-completion-openai":
if "This model's maximum context length is" in error_str:
exception_mapping_worked = True
raise ContextWindowExceededError(
message=f"AzureException - {original_exception.message}",
llm_provider="azure",
message=f"OpenAIException - {original_exception.message}",
llm_provider="openai",
model=model
)
elif "invalid_request_error" in error_str:
exception_mapping_worked = True
raise InvalidRequestError(
message=f"AzureException - {original_exception.message}",
llm_provider="azure",
message=f"OpenAIException - {original_exception.message}",
llm_provider="openai",
model=model
)
elif hasattr(original_exception, "status_code"):
@ -4013,16 +4013,33 @@ class CustomStreamWrapper:
else:
return {"text": text, "is_finished": is_finished, "finish_reason": finish_reason}
except:
except Exception as e:
traceback.print_exc()
pass
raise e
def handle_openai_text_completion_chunk(self, chunk):
try:
return chunk["choices"][0]["text"]
except:
raise ValueError(f"Unable to parse response. Original response: {chunk}")
try:
str_line = chunk.decode("utf-8") # Convert bytes to string
text = ""
is_finished = False
finish_reason = None
if str_line.startswith("data:"):
data_json = json.loads(str_line[5:])
print_verbose(f"delta content: {data_json['choices'][0]['text']}")
text = data_json["choices"][0].get("text", "")
if data_json["choices"][0].get("finish_reason", None):
is_finished = True
finish_reason = data_json["choices"][0]["finish_reason"]
return {"text": text, "is_finished": is_finished, "finish_reason": finish_reason}
elif "error" in str_line:
raise ValueError(f"Unable to parse response. Original response: {str_line}")
else:
return {"text": text, "is_finished": is_finished, "finish_reason": finish_reason}
except Exception as e:
traceback.print_exc()
raise e
def handle_baseten_chunk(self, chunk):
try:
@ -4146,9 +4163,6 @@ class CustomStreamWrapper:
completion_obj["content"] = response_obj["text"]
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj["finish_reason"]
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":
try:
chunk = next(self.completion_stream)
@ -4235,12 +4249,15 @@ class CustomStreamWrapper:
print_verbose(f"completion obj content: {completion_obj['content']}")
if response_obj["is_finished"]:
model_response.choices[0].finish_reason = response_obj["finish_reason"]
else: # openai chat/azure models
elif self.custom_llm_provider == "text-completion-openai":
chunk = next(self.completion_stream)
model_response = chunk
# LOGGING
threading.Thread(target=self.logging_obj.success_handler, args=(model_response,)).start()
return model_response
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"]
else: # openai chat/azure models
raise Exception("Unmapped Model Error")
model_response.model = self.model
if len(completion_obj["content"]) > 0: # cannot set content of an OpenAI Object to be an empty string