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