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Merge branch 'main' into feat/support-knowledge-metadata

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# Conflicts:
#	api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py
#	api/core/rag/datasource/vdb/pgvector/pgvector.py
This commit is contained in:
jyong 2025-03-18 15:38:10 +08:00
commit 5c34d41aea
13 changed files with 123 additions and 20 deletions
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4
CONTRIBUTING_CN.md
View File

@ -26,7 +26,7 @@
| [@jyong](https://github.com/JohnJyong) | RAG 流水线设计 |
| [@GarfieldDai](https://github.com/GarfieldDai) | 构建 workflow 编排 |
| [@iamjoel](https://github.com/iamjoel) & [@zxhlyh](https://github.com/zxhlyh) | 让我们的前端更易用 |
| [@guchenhe](https://github.com/guchenhe) & [@crazywoola](https://github.com/crazywoola) | 开发人员体验, 综合事项联系人 |
| [@guchenhe](https://github.com/guchenhe) & [@crazywoola](https://github.com/crazywoola) | 开发人员体验，综合事项联系人 |
| [@takatost](https://github.com/takatost) | 产品整体方向和架构 |
事项优先级：
@ -47,7 +47,7 @@
| ------------------------------------------------------------ | --------------- |
| 核心功能的 Bugs（例如无法登录、应用无法工作、安全漏洞） | 紧急 |
| 非紧急 bugs, 性能提升 | 中等优先级 |
| 小幅修复(错别字, 能正常工作但存在误导的 UI) | 低优先级 |
| 小幅修复 (错别字，能正常工作但存在误导的 UI) | 低优先级 |
## 安装

6
README_CN.md
View File

@ -79,7 +79,7 @@ Dify 是一个开源的 LLM 应用开发平台。其直观的界面结合了 AI
广泛的 RAG 功能，涵盖从文档摄入到检索的所有内容，支持从 PDF、PPT 和其他常见文档格式中提取文本的开箱即用的支持。
**5. Agent 智能体**:
您可以基于 LLM 函数调用或 ReAct 定义 Agent，并为 Agent 添加预构建或自定义工具。Dify 为 AI Agent 提供了50多种内置工具，如谷歌搜索、DALL·E、Stable Diffusion 和 WolframAlpha 等。
您可以基于 LLM 函数调用或 ReAct 定义 Agent，并为 Agent 添加预构建或自定义工具。Dify 为 AI Agent 提供了 50 多种内置工具，如谷歌搜索、DALL·E、Stable Diffusion 和 WolframAlpha 等。
**6. LLMOps**:
随时间监视和分析应用程序日志和性能。您可以根据生产数据和标注持续改进提示、数据集和模型。
@ -112,7 +112,7 @@ Dify 是一个开源的 LLM 应用开发平台。其直观的界面结合了 AI
<td align="center">仅限 OpenAI</td>
</tr>
<tr>
<td align="center">RAG引擎</td>
<td align="center">RAG 引擎</td>
<td align="center">✅</td>
<td align="center">✅</td>
<td align="center">✅</td>
@ -234,7 +234,7 @@ docker compose up -d
对于那些想要贡献代码的人，请参阅我们的[贡献指南](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)。
同时，请考虑通过社交媒体、活动和会议来支持 Dify 的分享。
> 我们正在寻找贡献者来帮助将Dify翻译成除了中文和英文之外的其他语言。如果您有兴趣帮助，请参阅我们的[i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md)获取更多信息，并在我们的[Discord社区服务器](https://discord.gg/8Tpq4AcN9c)的`global-users`频道中留言。
> 我们正在寻找贡献者来帮助将 Dify 翻译成除了中文和英文之外的其他语言。如果您有兴趣帮助，请参阅我们的[i18n README](https://github.com/langgenius/dify/blob/main/web/i18n/README.md)获取更多信息，并在我们的[Discord 社区服务器](https://discord.gg/8Tpq4AcN9c)的`global-users`频道中留言。
**Contributors**

9
api/core/app/apps/base_app_runner.py
View File

@ -17,7 +17,11 @@ from core.external_data_tool.external_data_fetch import ExternalDataFetch
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_manager import ModelInstance
from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage
from core.model_runtime.entities.message_entities import (
AssistantPromptMessage,
ImagePromptMessageContent,
PromptMessage,
)
from core.model_runtime.entities.model_entities import ModelPropertyKey
from core.model_runtime.errors.invoke import InvokeBadRequestError
from core.moderation.input_moderation import InputModeration
@ -141,6 +145,7 @@ class AppRunner:
query: Optional[str] = None,
context: Optional[str] = None,
memory: Optional[TokenBufferMemory] = None,
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> tuple[list[PromptMessage], Optional[list[str]]]:
"""
Organize prompt messages
@ -167,6 +172,7 @@ class AppRunner:
context=context,
memory=memory,
model_config=model_config,
image_detail_config=image_detail_config,
)
else:
memory_config = MemoryConfig(window=MemoryConfig.WindowConfig(enabled=False))
@ -201,6 +207,7 @@ class AppRunner:
memory_config=memory_config,
memory=memory,
model_config=model_config,
image_detail_config=image_detail_config,
)
stop = model_config.stop

13
api/core/app/apps/chat/app_runner.py
View File

@ -11,6 +11,7 @@ from core.app.entities.queue_entities import QueueAnnotationReplyEvent
from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_manager import ModelInstance
from core.model_runtime.entities.message_entities import ImagePromptMessageContent
from core.moderation.base import ModerationError
from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
from extensions.ext_database import db
@ -50,6 +51,16 @@ class ChatAppRunner(AppRunner):
query = application_generate_entity.query
files = application_generate_entity.files
image_detail_config = (
application_generate_entity.file_upload_config.image_config.detail
if (
application_generate_entity.file_upload_config
and application_generate_entity.file_upload_config.image_config
)
else None
)
image_detail_config = image_detail_config or ImagePromptMessageContent.DETAIL.LOW
# Pre-calculate the number of tokens of the prompt messages,
# and return the rest number of tokens by model context token size limit and max token size limit.
# If the rest number of tokens is not enough, raise exception.
@ -85,6 +96,7 @@ class ChatAppRunner(AppRunner):
files=files,
query=query,
memory=memory,
image_detail_config=image_detail_config,
)
# moderation
@ -183,6 +195,7 @@ class ChatAppRunner(AppRunner):
query=query,
context=context,
memory=memory,
image_detail_config=image_detail_config,
)
# check hosting moderation

13
api/core/app/apps/completion/app_runner.py
View File

@ -9,6 +9,7 @@ from core.app.entities.app_invoke_entities import (
)
from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
from core.model_manager import ModelInstance
from core.model_runtime.entities.message_entities import ImagePromptMessageContent
from core.moderation.base import ModerationError
from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
from extensions.ext_database import db
@ -43,6 +44,16 @@ class CompletionAppRunner(AppRunner):
query = application_generate_entity.query
files = application_generate_entity.files
image_detail_config = (
application_generate_entity.file_upload_config.image_config.detail
if (
application_generate_entity.file_upload_config
and application_generate_entity.file_upload_config.image_config
)
else None
)
image_detail_config = image_detail_config or ImagePromptMessageContent.DETAIL.LOW
# Pre-calculate the number of tokens of the prompt messages,
# and return the rest number of tokens by model context token size limit and max token size limit.
# If the rest number of tokens is not enough, raise exception.
@ -66,6 +77,7 @@ class CompletionAppRunner(AppRunner):
inputs=inputs,
files=files,
query=query,
image_detail_config=image_detail_config,
)
# moderation
@ -141,6 +153,7 @@ class CompletionAppRunner(AppRunner):
files=files,
query=query,
context=context,
image_detail_config=image_detail_config,
)
# check hosting moderation

25
api/core/prompt/advanced_prompt_transform.py
View File

@ -46,6 +46,7 @@ class AdvancedPromptTransform(PromptTransform):
memory_config: Optional[MemoryConfig],
memory: Optional[TokenBufferMemory],
model_config: ModelConfigWithCredentialsEntity,
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> list[PromptMessage]:
prompt_messages = []
@ -59,6 +60,7 @@ class AdvancedPromptTransform(PromptTransform):
memory_config=memory_config,
memory=memory,
model_config=model_config,
image_detail_config=image_detail_config,
)
elif isinstance(prompt_template, list) and all(isinstance(item, ChatModelMessage) for item in prompt_template):
prompt_messages = self._get_chat_model_prompt_messages(
@ -70,6 +72,7 @@ class AdvancedPromptTransform(PromptTransform):
memory_config=memory_config,
memory=memory,
model_config=model_config,
image_detail_config=image_detail_config,
)
return prompt_messages
@ -84,6 +87,7 @@ class AdvancedPromptTransform(PromptTransform):
memory_config: Optional[MemoryConfig],
memory: Optional[TokenBufferMemory],
model_config: ModelConfigWithCredentialsEntity,
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> list[PromptMessage]:
"""
Get completion model prompt messages.
@ -124,7 +128,9 @@ class AdvancedPromptTransform(PromptTransform):
prompt_message_contents: list[PromptMessageContent] = []
prompt_message_contents.append(TextPromptMessageContent(data=prompt))
for file in files:
prompt_message_contents.append(file_manager.to_prompt_message_content(file))
prompt_message_contents.append(
file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
)
prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
else:
@ -142,6 +148,7 @@ class AdvancedPromptTransform(PromptTransform):
memory_config: Optional[MemoryConfig],
memory: Optional[TokenBufferMemory],
model_config: ModelConfigWithCredentialsEntity,
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> list[PromptMessage]:
"""
Get chat model prompt messages.
@ -197,7 +204,9 @@ class AdvancedPromptTransform(PromptTransform):
prompt_message_contents: list[PromptMessageContent] = []
prompt_message_contents.append(TextPromptMessageContent(data=query))
for file in files:
prompt_message_contents.append(file_manager.to_prompt_message_content(file))
prompt_message_contents.append(
file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
)
prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
else:
prompt_messages.append(UserPromptMessage(content=query))
@ -209,19 +218,25 @@ class AdvancedPromptTransform(PromptTransform):
# get last user message content and add files
prompt_message_contents = [TextPromptMessageContent(data=cast(str, last_message.content))]
for file in files:
prompt_message_contents.append(file_manager.to_prompt_message_content(file))
prompt_message_contents.append(
file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
)
last_message.content = prompt_message_contents
else:
prompt_message_contents = [TextPromptMessageContent(data="")] # not for query
for file in files:
prompt_message_contents.append(file_manager.to_prompt_message_content(file))
prompt_message_contents.append(
file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
)
prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
else:
prompt_message_contents = [TextPromptMessageContent(data=query)]
for file in files:
prompt_message_contents.append(file_manager.to_prompt_message_content(file))
prompt_message_contents.append(
file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
)
prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
elif query:

23
api/core/prompt/simple_prompt_transform.py
View File

@ -9,6 +9,7 @@ from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEnti
from core.file import file_manager
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_runtime.entities.message_entities import (
ImagePromptMessageContent,
PromptMessage,
PromptMessageContent,
SystemPromptMessage,
@ -60,6 +61,7 @@ class SimplePromptTransform(PromptTransform):
context: Optional[str],
memory: Optional[TokenBufferMemory],
model_config: ModelConfigWithCredentialsEntity,
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> tuple[list[PromptMessage], Optional[list[str]]]:
inputs = {key: str(value) for key, value in inputs.items()}
@ -74,6 +76,7 @@ class SimplePromptTransform(PromptTransform):
context=context,
memory=memory,
model_config=model_config,
image_detail_config=image_detail_config,
)
else:
prompt_messages, stops = self._get_completion_model_prompt_messages(
@ -85,6 +88,7 @@ class SimplePromptTransform(PromptTransform):
context=context,
memory=memory,
model_config=model_config,
image_detail_config=image_detail_config,
)
return prompt_messages, stops
@ -175,6 +179,7 @@ class SimplePromptTransform(PromptTransform):
files: Sequence["File"],
memory: Optional[TokenBufferMemory],
model_config: ModelConfigWithCredentialsEntity,
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> tuple[list[PromptMessage], Optional[list[str]]]:
prompt_messages: list[PromptMessage] = []
@ -204,9 +209,9 @@ class SimplePromptTransform(PromptTransform):
)
if query:
prompt_messages.append(self.get_last_user_message(query, files))
prompt_messages.append(self.get_last_user_message(query, files, image_detail_config))
else:
prompt_messages.append(self.get_last_user_message(prompt, files))
prompt_messages.append(self.get_last_user_message(prompt, files, image_detail_config))
return prompt_messages, None
@ -220,6 +225,7 @@ class SimplePromptTransform(PromptTransform):
files: Sequence["File"],
memory: Optional[TokenBufferMemory],
model_config: ModelConfigWithCredentialsEntity,
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> tuple[list[PromptMessage], Optional[list[str]]]:
# get prompt
prompt, prompt_rules = self.get_prompt_str_and_rules(
@ -262,14 +268,21 @@ class SimplePromptTransform(PromptTransform):
if stops is not None and len(stops) == 0:
stops = None
return [self.get_last_user_message(prompt, files)], stops
return [self.get_last_user_message(prompt, files, image_detail_config)], stops
def get_last_user_message(self, prompt: str, files: Sequence["File"]) -> UserPromptMessage:
def get_last_user_message(
self,
prompt: str,
files: Sequence["File"],
image_detail_config: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> UserPromptMessage:
if files:
prompt_message_contents: list[PromptMessageContent] = []
prompt_message_contents.append(TextPromptMessageContent(data=prompt))
for file in files:
prompt_message_contents.append(file_manager.to_prompt_message_content(file))
prompt_message_contents.append(
file_manager.to_prompt_message_content(file, image_detail_config=image_detail_config)
)
prompt_message = UserPromptMessage(content=prompt_message_contents)
else:

21
api/core/provider_manager.py
View File

@ -149,6 +149,11 @@ class ProviderManager:
provider_name = provider_entity.provider
provider_records = provider_name_to_provider_records_dict.get(provider_entity.provider, [])
provider_model_records = provider_name_to_provider_model_records_dict.get(provider_entity.provider, [])
provider_id_entity = ModelProviderID(provider_name)
if provider_id_entity.is_langgenius():
provider_model_records.extend(
provider_name_to_provider_model_records_dict.get(provider_id_entity.provider_name, [])
)
# Convert to custom configuration
custom_configuration = self._to_custom_configuration(
@ -190,6 +195,20 @@ class ProviderManager:
provider_name
)
provider_id_entity = ModelProviderID(provider_name)
if provider_id_entity.is_langgenius():
if provider_model_settings is not None:
provider_model_settings.extend(
provider_name_to_provider_model_settings_dict.get(provider_id_entity.provider_name, [])
)
if provider_load_balancing_configs is not None:
provider_load_balancing_configs.extend(
provider_name_to_provider_load_balancing_model_configs_dict.get(
provider_id_entity.provider_name, []
)
)
# Convert to model settings
model_settings = self._to_model_settings(
provider_entity=provider_entity,
@ -207,7 +226,7 @@ class ProviderManager:
model_settings=model_settings,
)
provider_configurations[str(ModelProviderID(provider_name))] = provider_configuration
provider_configurations[str(provider_id_entity)] = provider_configuration
# Return the encapsulated object
return provider_configurations

4
api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py
View File

@ -194,6 +194,8 @@ class AnalyticdbVectorBySql:
def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
top_k = kwargs.get("top_k", 4)
if not isinstance(top_k, int) or top_k <= 0:
raise ValueError("top_k must be a positive integer")
document_ids_filter = kwargs.get("document_ids_filter")
where_clause = "WHERE 1=1"
if document_ids_filter:
@ -225,6 +227,8 @@ class AnalyticdbVectorBySql:
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
top_k = kwargs.get("top_k", 4)
if not isinstance(top_k, int) or top_k <= 0:
raise ValueError("top_k must be a positive integer")
document_ids_filter = kwargs.get("document_ids_filter")
where_clause = ""
if document_ids_filter:

2
api/core/rag/datasource/vdb/myscale/myscale_vector.py
View File

@ -125,6 +125,8 @@ class MyScaleVector(BaseVector):
def _search(self, dist: str, order: SortOrder, **kwargs: Any) -> list[Document]:
top_k = kwargs.get("top_k", 4)
if not isinstance(top_k, int) or top_k <= 0:
raise ValueError("top_k must be a positive integer")
score_threshold = float(kwargs.get("score_threshold") or 0.0)
where_str = (
f"WHERE dist < {1 - score_threshold}"

6
api/core/rag/datasource/vdb/opengauss/opengauss.py
View File

@ -155,7 +155,8 @@ class OpenGauss(BaseVector):
:return: List of Documents that are nearest to the query vector.
"""
top_k = kwargs.get("top_k", 4)
if not isinstance(top_k, int) or top_k <= 0:
raise ValueError("top_k must be a positive integer")
with self._get_cursor() as cur:
cur.execute(
f"SELECT meta, text, embedding <=> %s AS distance FROM {self.table_name}"
@ -174,7 +175,8 @@ class OpenGauss(BaseVector):
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
top_k = kwargs.get("top_k", 5)
if not isinstance(top_k, int) or top_k <= 0:
raise ValueError("top_k must be a positive integer")
with self._get_cursor() as cur:
cur.execute(
f"""SELECT meta, text, ts_rank(to_tsvector(coalesce(text, '')), plainto_tsquery(%s)) AS score

5
api/core/rag/datasource/vdb/pgvector/pgvector.py
View File

@ -171,6 +171,8 @@ class PGVector(BaseVector):
:return: List of Documents that are nearest to the query vector.
"""
top_k = kwargs.get("top_k", 4)
if not isinstance(top_k, int) or top_k <= 0:
raise ValueError("top_k must be a positive integer")
document_ids_filter = kwargs.get("document_ids_filter")
where_clause = ""
if document_ids_filter:
@ -196,7 +198,8 @@ class PGVector(BaseVector):
def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
top_k = kwargs.get("top_k", 5)
if not isinstance(top_k, int) or top_k <= 0:
raise ValueError("top_k must be a positive integer")
with self._get_cursor() as cur:
document_ids_filter = kwargs.get("document_ids_filter")
where_clause = ""

12
api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py
View File

@ -7,6 +7,7 @@ from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEnti
from core.file import File
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_manager import ModelInstance
from core.model_runtime.entities import ImagePromptMessageContent
from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
from core.model_runtime.entities.message_entities import (
AssistantPromptMessage,
@ -129,6 +130,7 @@ class ParameterExtractorNode(LLMNode):
model_config=model_config,
memory=memory,
files=files,
vision_detail=node_data.vision.configs.detail,
)
else:
# use prompt engineering
@ -139,6 +141,7 @@ class ParameterExtractorNode(LLMNode):
model_config=model_config,
memory=memory,
files=files,
vision_detail=node_data.vision.configs.detail,
)
prompt_message_tools = []
@ -267,6 +270,7 @@ class ParameterExtractorNode(LLMNode):
model_config: ModelConfigWithCredentialsEntity,
memory: Optional[TokenBufferMemory],
files: Sequence[File],
vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> tuple[list[PromptMessage], list[PromptMessageTool]]:
"""
Generate function call prompt.
@ -289,6 +293,7 @@ class ParameterExtractorNode(LLMNode):
memory_config=node_data.memory,
memory=None,
model_config=model_config,
image_detail_config=vision_detail,
)
# find last user message
@ -347,6 +352,7 @@ class ParameterExtractorNode(LLMNode):
model_config: ModelConfigWithCredentialsEntity,
memory: Optional[TokenBufferMemory],
files: Sequence[File],
vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> list[PromptMessage]:
"""
Generate prompt engineering prompt.
@ -361,6 +367,7 @@ class ParameterExtractorNode(LLMNode):
model_config=model_config,
memory=memory,
files=files,
vision_detail=vision_detail,
)
elif model_mode == ModelMode.CHAT:
return self._generate_prompt_engineering_chat_prompt(
@ -370,6 +377,7 @@ class ParameterExtractorNode(LLMNode):
model_config=model_config,
memory=memory,
files=files,
vision_detail=vision_detail,
)
else:
raise InvalidModelModeError(f"Invalid model mode: {model_mode}")
@ -382,6 +390,7 @@ class ParameterExtractorNode(LLMNode):
model_config: ModelConfigWithCredentialsEntity,
memory: Optional[TokenBufferMemory],
files: Sequence[File],
vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> list[PromptMessage]:
"""
Generate completion prompt.
@ -402,6 +411,7 @@ class ParameterExtractorNode(LLMNode):
memory_config=node_data.memory,
memory=memory,
model_config=model_config,
image_detail_config=vision_detail,
)
return prompt_messages
@ -414,6 +424,7 @@ class ParameterExtractorNode(LLMNode):
model_config: ModelConfigWithCredentialsEntity,
memory: Optional[TokenBufferMemory],
files: Sequence[File],
vision_detail: Optional[ImagePromptMessageContent.DETAIL] = None,
) -> list[PromptMessage]:
"""
Generate chat prompt.
@ -441,6 +452,7 @@ class ParameterExtractorNode(LLMNode):
memory_config=node_data.memory,
memory=None,
model_config=model_config,
image_detail_config=vision_detail,
)
# find last user message