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fix: LLMResultChunk cause concatenate str and list exception (#18852)

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非法操作 2025-04-27 11:32:14 +08:00 committed by GitHub
parent 993ef87dca
commit c1559a7c8e
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3 changed files with 25 additions and 15 deletions
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7
api/core/model_runtime/model_providers/__base/large_language_model.py
View File

@ -2,7 +2,7 @@ import logging
import time
import uuid
from collections.abc import Generator, Sequence
from typing import Optional, Union
from typing import Optional, Union, cast
from pydantic import ConfigDict
@ -20,6 +20,7 @@ from core.model_runtime.entities.model_entities import (
PriceType,
)
from core.model_runtime.model_providers.__base.ai_model import AIModel
from core.model_runtime.utils.helper import convert_llm_result_chunk_to_str
from core.plugin.manager.model import PluginModelManager
logger = logging.getLogger(__name__)
@ -280,7 +281,9 @@ class LargeLanguageModel(AIModel):
callbacks=callbacks,
)
assistant_message.content += chunk.delta.message.content
text = convert_llm_result_chunk_to_str(chunk.delta.message.content)
current_content = cast(str, assistant_message.content)
assistant_message.content = current_content + text
real_model = chunk.model
if chunk.delta.usage:
usage = chunk.delta.usage

17
api/core/model_runtime/utils/helper.py
View File

@ -1,6 +1,8 @@
import pydantic
from pydantic import BaseModel
from core.model_runtime.entities.message_entities import PromptMessageContentUnionTypes
def dump_model(model: BaseModel) -> dict:
if hasattr(pydantic, "model_dump"):
@ -8,3 +10,18 @@ def dump_model(model: BaseModel) -> dict:
return pydantic.model_dump(model) # type: ignore
else:
return model.model_dump()
def convert_llm_result_chunk_to_str(content: None | str | list[PromptMessageContentUnionTypes]) -> str:
if content is None:
message_text = ""
elif isinstance(content, str):
message_text = content
elif isinstance(content, list):
# Assuming the list contains PromptMessageContent objects with a "data" attribute
message_text = "".join(
item.data if hasattr(item, "data") and isinstance(item.data, str) else str(item) for item in content
)
else:
message_text = str(content)
return message_text

16
api/core/workflow/nodes/llm/node.py
View File

@ -38,6 +38,7 @@ from core.model_runtime.entities.model_entities import (
)
from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
from core.model_runtime.utils.encoders import jsonable_encoder
from core.model_runtime.utils.helper import convert_llm_result_chunk_to_str
from core.plugin.entities.plugin import ModelProviderID
from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptTemplate, MemoryConfig
from core.prompt.utils.prompt_message_util import PromptMessageUtil
@ -269,18 +270,7 @@ class LLMNode(BaseNode[LLMNodeData]):
def _handle_invoke_result(self, invoke_result: LLMResult | Generator) -> Generator[NodeEvent, None, None]:
if isinstance(invoke_result, LLMResult):
content = invoke_result.message.content
if content is None:
message_text = ""
elif isinstance(content, str):
message_text = content
elif isinstance(content, list):
# Assuming the list contains PromptMessageContent objects with a "data" attribute
message_text = "".join(
item.data if hasattr(item, "data") and isinstance(item.data, str) else str(item) for item in content
)
else:
message_text = str(content)
message_text = convert_llm_result_chunk_to_str(invoke_result.message.content)
yield ModelInvokeCompletedEvent(
text=message_text,
@ -295,7 +285,7 @@ class LLMNode(BaseNode[LLMNodeData]):
usage = None
finish_reason = None
for result in invoke_result:
text = result.delta.message.content
text = convert_llm_result_chunk_to_str(result.delta.message.content)
full_text += text
yield RunStreamChunkEvent(chunk_content=text, from_variable_selector=[self.node_id, "text"])