|
|
|
|
@ -22,18 +22,6 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
|
|
|
|
|
from core.model_runtime.model_providers.zhipuai._common import _CommonZhipuaiAI
|
|
|
|
|
from core.model_runtime.utils import helper
|
|
|
|
|
|
|
|
|
|
GLM_JSON_MODE_PROMPT = """You should always follow the instructions and output a valid JSON object.
|
|
|
|
|
The structure of the JSON object you can found in the instructions, use {"answer": "$your_answer"} as the default structure
|
|
|
|
|
if you are not sure about the structure.
|
|
|
|
|
|
|
|
|
|
And you should always end the block with a "```" to indicate the end of the JSON object.
|
|
|
|
|
|
|
|
|
|
<instructions>
|
|
|
|
|
{{instructions}}
|
|
|
|
|
</instructions>
|
|
|
|
|
|
|
|
|
|
```JSON""" # noqa: E501
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
|
|
|
|
def _invoke(
|
|
|
|
|
@ -64,42 +52,8 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
|
|
|
|
credentials_kwargs = self._to_credential_kwargs(credentials)
|
|
|
|
|
|
|
|
|
|
# invoke model
|
|
|
|
|
# stop = stop or []
|
|
|
|
|
# self._transform_json_prompts(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user)
|
|
|
|
|
return self._generate(model, credentials_kwargs, prompt_messages, model_parameters, tools, stop, stream, user)
|
|
|
|
|
|
|
|
|
|
# def _transform_json_prompts(self, model: str, credentials: dict,
|
|
|
|
|
# prompt_messages: list[PromptMessage], model_parameters: dict,
|
|
|
|
|
# tools: list[PromptMessageTool] | None = None, stop: list[str] | None = None,
|
|
|
|
|
# stream: bool = True, user: str | None = None) \
|
|
|
|
|
# -> None:
|
|
|
|
|
# """
|
|
|
|
|
# Transform json prompts to model prompts
|
|
|
|
|
# """
|
|
|
|
|
# if "}\n\n" not in stop:
|
|
|
|
|
# stop.append("}\n\n")
|
|
|
|
|
|
|
|
|
|
# # check if there is a system message
|
|
|
|
|
# if len(prompt_messages) > 0 and isinstance(prompt_messages[0], SystemPromptMessage):
|
|
|
|
|
# # override the system message
|
|
|
|
|
# prompt_messages[0] = SystemPromptMessage(
|
|
|
|
|
# content=GLM_JSON_MODE_PROMPT.replace("{{instructions}}", prompt_messages[0].content)
|
|
|
|
|
# )
|
|
|
|
|
# else:
|
|
|
|
|
# # insert the system message
|
|
|
|
|
# prompt_messages.insert(0, SystemPromptMessage(
|
|
|
|
|
# content=GLM_JSON_MODE_PROMPT.replace("{{instructions}}", "Please output a valid JSON object.")
|
|
|
|
|
# ))
|
|
|
|
|
# # check if the last message is a user message
|
|
|
|
|
# if len(prompt_messages) > 0 and isinstance(prompt_messages[-1], UserPromptMessage):
|
|
|
|
|
# # add ```JSON\n to the last message
|
|
|
|
|
# prompt_messages[-1].content += "\n```JSON\n"
|
|
|
|
|
# else:
|
|
|
|
|
# # append a user message
|
|
|
|
|
# prompt_messages.append(UserPromptMessage(
|
|
|
|
|
# content="```JSON\n"
|
|
|
|
|
# ))
|
|
|
|
|
|
|
|
|
|
def get_num_tokens(
|
|
|
|
|
self,
|
|
|
|
|
model: str,
|
|
|
|
|
@ -170,7 +124,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
|
|
|
|
:return: full response or stream response chunk generator result
|
|
|
|
|
"""
|
|
|
|
|
extra_model_kwargs = {}
|
|
|
|
|
# request to glm-4v-plus with stop words will always response "finish_reason":"network_error"
|
|
|
|
|
# request to glm-4v-plus with stop words will always respond "finish_reason":"network_error"
|
|
|
|
|
if stop and model != "glm-4v-plus":
|
|
|
|
|
extra_model_kwargs["stop"] = stop
|
|
|
|
|
|
|
|
|
|
@ -186,7 +140,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
|
|
|
|
# resolve zhipuai model not support system message and user message, assistant message must be in sequence
|
|
|
|
|
new_prompt_messages: list[PromptMessage] = []
|
|
|
|
|
for prompt_message in prompt_messages:
|
|
|
|
|
copy_prompt_message = prompt_message.copy()
|
|
|
|
|
copy_prompt_message = prompt_message.model_copy()
|
|
|
|
|
if copy_prompt_message.role in {PromptMessageRole.USER, PromptMessageRole.SYSTEM, PromptMessageRole.TOOL}:
|
|
|
|
|
if isinstance(copy_prompt_message.content, list):
|
|
|
|
|
# check if model is 'glm-4v'
|
|
|
|
|
@ -238,59 +192,38 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
|
|
|
|
params = self._construct_glm_4v_parameter(model, new_prompt_messages, model_parameters)
|
|
|
|
|
else:
|
|
|
|
|
params = {"model": model, "messages": [], **model_parameters}
|
|
|
|
|
# glm model
|
|
|
|
|
if not model.startswith("chatglm"):
|
|
|
|
|
for prompt_message in new_prompt_messages:
|
|
|
|
|
if prompt_message.role == PromptMessageRole.TOOL:
|
|
|
|
|
for prompt_message in new_prompt_messages:
|
|
|
|
|
if prompt_message.role == PromptMessageRole.TOOL:
|
|
|
|
|
params["messages"].append(
|
|
|
|
|
{
|
|
|
|
|
"role": "tool",
|
|
|
|
|
"content": prompt_message.content,
|
|
|
|
|
"tool_call_id": prompt_message.tool_call_id,
|
|
|
|
|
}
|
|
|
|
|
)
|
|
|
|
|
elif isinstance(prompt_message, AssistantPromptMessage):
|
|
|
|
|
if prompt_message.tool_calls:
|
|
|
|
|
params["messages"].append(
|
|
|
|
|
{
|
|
|
|
|
"role": "tool",
|
|
|
|
|
"role": "assistant",
|
|
|
|
|
"content": prompt_message.content,
|
|
|
|
|
"tool_call_id": prompt_message.tool_call_id,
|
|
|
|
|
"tool_calls": [
|
|
|
|
|
{
|
|
|
|
|
"id": tool_call.id,
|
|
|
|
|
"type": tool_call.type,
|
|
|
|
|
"function": {
|
|
|
|
|
"name": tool_call.function.name,
|
|
|
|
|
"arguments": tool_call.function.arguments,
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
for tool_call in prompt_message.tool_calls
|
|
|
|
|
],
|
|
|
|
|
}
|
|
|
|
|
)
|
|
|
|
|
elif isinstance(prompt_message, AssistantPromptMessage):
|
|
|
|
|
if prompt_message.tool_calls:
|
|
|
|
|
params["messages"].append(
|
|
|
|
|
{
|
|
|
|
|
"role": "assistant",
|
|
|
|
|
"content": prompt_message.content,
|
|
|
|
|
"tool_calls": [
|
|
|
|
|
{
|
|
|
|
|
"id": tool_call.id,
|
|
|
|
|
"type": tool_call.type,
|
|
|
|
|
"function": {
|
|
|
|
|
"name": tool_call.function.name,
|
|
|
|
|
"arguments": tool_call.function.arguments,
|
|
|
|
|
},
|
|
|
|
|
}
|
|
|
|
|
for tool_call in prompt_message.tool_calls
|
|
|
|
|
],
|
|
|
|
|
}
|
|
|
|
|
)
|
|
|
|
|
else:
|
|
|
|
|
params["messages"].append({"role": "assistant", "content": prompt_message.content})
|
|
|
|
|
else:
|
|
|
|
|
params["messages"].append(
|
|
|
|
|
{"role": prompt_message.role.value, "content": prompt_message.content}
|
|
|
|
|
)
|
|
|
|
|
else:
|
|
|
|
|
# chatglm model
|
|
|
|
|
for prompt_message in new_prompt_messages:
|
|
|
|
|
# merge system message to user message
|
|
|
|
|
if prompt_message.role in {
|
|
|
|
|
PromptMessageRole.SYSTEM,
|
|
|
|
|
PromptMessageRole.TOOL,
|
|
|
|
|
PromptMessageRole.USER,
|
|
|
|
|
}:
|
|
|
|
|
if len(params["messages"]) > 0 and params["messages"][-1]["role"] == "user":
|
|
|
|
|
params["messages"][-1]["content"] += "\n\n" + prompt_message.content
|
|
|
|
|
else:
|
|
|
|
|
params["messages"].append({"role": "user", "content": prompt_message.content})
|
|
|
|
|
else:
|
|
|
|
|
params["messages"].append(
|
|
|
|
|
{"role": prompt_message.role.value, "content": prompt_message.content}
|
|
|
|
|
)
|
|
|
|
|
params["messages"].append({"role": "assistant", "content": prompt_message.content})
|
|
|
|
|
else:
|
|
|
|
|
params["messages"].append({"role": prompt_message.role.value, "content": prompt_message.content})
|
|
|
|
|
|
|
|
|
|
if tools and len(tools) > 0:
|
|
|
|
|
params["tools"] = [{"type": "function", "function": helper.dump_model(tool)} for tool in tools]
|
|
|
|
|
@ -406,7 +339,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
|
|
|
|
Handle llm stream response
|
|
|
|
|
|
|
|
|
|
:param model: model name
|
|
|
|
|
:param response: response
|
|
|
|
|
:param responses: response
|
|
|
|
|
:param prompt_messages: prompt messages
|
|
|
|
|
:return: llm response chunk generator result
|
|
|
|
|
"""
|
|
|
|
|
@ -505,7 +438,7 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
|
|
|
|
if tools and len(tools) > 0:
|
|
|
|
|
text += "\n\nTools:"
|
|
|
|
|
for tool in tools:
|
|
|
|
|
text += f"\n{tool.json()}"
|
|
|
|
|
text += f"\n{tool.model_dump_json()}"
|
|
|
|
|
|
|
|
|
|
# trim off the trailing ' ' that might come from the "Assistant: "
|
|
|
|
|
return text.rstrip()
|
|
|
|
|
|
非法操作
1 year ago
committed by
GitHub