fix merge bugs.
This commit is contained in:
Liu Zhicong
@@ -59,85 +59,84 @@ class OpenAI_ComputeNode(ComputeNode):
|
||||
|
||||
def _run_task(self, task: ComputeTask):
|
||||
task.state = ComputeTaskState.RUNNING
|
||||
if task.task_type == "text_embedding":
|
||||
model_name = task.params["model_name"]
|
||||
input = task.params["input"]
|
||||
logger.info(f"call openai {model_name} input: {input}")
|
||||
match task.task_type:
|
||||
case ComputeTaskType.TEXT_EMBEDDING:
|
||||
model_name = task.params["model_name"]
|
||||
input = task.params["input"]
|
||||
logger.info(f"call openai {model_name} input: {input}")
|
||||
|
||||
resp = openai.Embedding.create(model=model_name,
|
||||
input=input)
|
||||
|
||||
# resp = {
|
||||
# "object": "list",
|
||||
# "data": [
|
||||
# {
|
||||
# "object": "embedding",
|
||||
# "index": 0,
|
||||
# "embedding": [
|
||||
# -0.00930514745414257,
|
||||
# 0.00765434792265296,
|
||||
# -0.007167573552578688,
|
||||
# -0.012373941019177437,
|
||||
# -0.04884673282504082
|
||||
# ]}]
|
||||
# }
|
||||
resp = openai.Embedding.create(model=model_name,
|
||||
input=input)
|
||||
|
||||
# resp = {
|
||||
# "object": "list",
|
||||
# "data": [
|
||||
# {
|
||||
# "object": "embedding",
|
||||
# "index": 0,
|
||||
# "embedding": [
|
||||
# -0.00930514745414257,
|
||||
# 0.00765434792265296,
|
||||
# -0.007167573552578688,
|
||||
# -0.012373941019177437,
|
||||
# -0.04884673282504082
|
||||
# ]}]
|
||||
# }
|
||||
|
||||
logger.info(f"openai response: {resp}")
|
||||
logger.info(f"openai response: {resp}")
|
||||
|
||||
result = ComputeTaskResult()
|
||||
result.set_from_task(task)
|
||||
result.worker_id = self.node_id
|
||||
result.result = resp["data"][0]["embedding"]
|
||||
result = ComputeTaskResult()
|
||||
result.set_from_task(task)
|
||||
result.worker_id = self.node_id
|
||||
result.result = resp["data"][0]["embedding"]
|
||||
|
||||
return result
|
||||
|
||||
if task.task_type == "llm_completion":
|
||||
mode_name = task.params["model_name"]
|
||||
# max_token_size = task.params["max_token_size"]
|
||||
prompts = task.params["prompts"]
|
||||
return result
|
||||
case ComputeTaskType.LLM_COMPLETION:
|
||||
mode_name = task.params["model_name"]
|
||||
prompts = task.params["prompts"]
|
||||
max_token_size = task.params.get("max_token_size")
|
||||
llm_inner_functions = task.params["inner_functions"]
|
||||
if max_token_size is None:
|
||||
max_token_size = 4000
|
||||
|
||||
logger.info(f"call openai {mode_name} prompts: {prompts}")
|
||||
|
||||
mode_name = task.params["model_name"]
|
||||
# max_token_size = task.params["max_token_size"]
|
||||
prompts = task.params["prompts"]
|
||||
|
||||
|
||||
logger.info(f"call openai {mode_name} prompts: {prompts}")
|
||||
|
||||
if task.params.get("inner_functions") is None:
|
||||
resp = openai.ChatCompletion.create(model=mode_name,
|
||||
messages=prompts,
|
||||
max_tokens=task.params["max_token_size"],
|
||||
temperature=0.7)
|
||||
else:
|
||||
resp = openai.ChatCompletion.create(model=mode_name,
|
||||
if llm_inner_functions is None:
|
||||
resp = openai.ChatCompletion.create(model=mode_name,
|
||||
messages=prompts,
|
||||
functions=task.params["inner_functions"],
|
||||
max_tokens=task.params["max_token_size"],
|
||||
temperature=0.7) # TODO: add temperature to task params?
|
||||
max_tokens=max_token_size,
|
||||
temperature=0.7)
|
||||
else:
|
||||
resp = openai.ChatCompletion.create(model=mode_name,
|
||||
messages=prompts,
|
||||
functions=llm_inner_functions,
|
||||
max_tokens=max_token_size,
|
||||
temperature=0.7) # TODO: add temperature to task params?
|
||||
|
||||
|
||||
logger.info(f"openai response: {resp}")
|
||||
|
||||
logger.info(f"openai response: {resp}")
|
||||
|
||||
result = ComputeTaskResult()
|
||||
result.set_from_task(task)
|
||||
result = ComputeTaskResult()
|
||||
result.set_from_task(task)
|
||||
|
||||
status_code = resp["choices"][0]["finish_reason"]
|
||||
match status_code:
|
||||
case "function_call":
|
||||
task.state = ComputeTaskState.DONE
|
||||
case "stop":
|
||||
task.state = ComputeTaskState.DONE
|
||||
case _:
|
||||
task.state = ComputeTaskState.ERROR
|
||||
task.error_str = f"The status code was {status_code}."
|
||||
return None
|
||||
|
||||
result.worker_id = self.node_id
|
||||
result.result_str = resp["choices"][0]["message"]["content"]
|
||||
result.result_message = resp["choices"][0]["message"]
|
||||
|
||||
return result
|
||||
status_code = resp["choices"][0]["finish_reason"]
|
||||
match status_code:
|
||||
case "function_call":
|
||||
task.state = ComputeTaskState.DONE
|
||||
case "stop":
|
||||
task.state = ComputeTaskState.DONE
|
||||
case _:
|
||||
task.state = ComputeTaskState.ERROR
|
||||
task.error_str = f"The status code was {status_code}."
|
||||
return None
|
||||
|
||||
result.worker_id = self.node_id
|
||||
result.result_str = resp["choices"][0]["message"]["content"]
|
||||
result.result_message = resp["choices"][0]["message"]
|
||||
return result
|
||||
case _:
|
||||
task.state = ComputeTaskState.ERROR
|
||||
return None
|
||||
|
||||
def start(self):
|
||||
if self.is_start is True:
|
||||
@@ -167,9 +166,9 @@ class OpenAI_ComputeNode(ComputeNode):
|
||||
|
||||
def is_support(self, task: ComputeTask) -> bool:
|
||||
if task.task_type == ComputeTaskType.LLM_COMPLETION:
|
||||
if (not task.params["model_name"] or task.params["model_name"] == "gpt-4-0613")
|
||||
if not task.params["model_name"] or task.params["model_name"] == "gpt-4-0613":
|
||||
return True
|
||||
if task.task_type == "text_embedding":
|
||||
if task.task_type == ComputeTaskType.TEXT_EMBEDDING:
|
||||
if task.params["model_name"] == "text-embedding-ada-002":
|
||||
return True
|
||||
return False
|
||||
|
||||
Reference in New Issue
Block a user