API 参考¶

本页面提供 openwebui-chat-client 的完整 API 参考，从源代码文档字符串自动生成。

OpenWebUIClient¶

用于同步操作的主客户端类。

`OpenWebUIClient(base_url, token, default_model_id, skip_model_refresh=False)` ¶

An intelligent, stateful Python client for the Open WebUI API. Supports single/multi-model chats, tagging, and RAG with both direct file uploads and knowledge base collections, matching the backend format.

This refactored version uses a modular architecture with specialized managers while maintaining 100% backward compatibility with the original API.

Initialize the OpenWebUI client with modular architecture.

Parameters:

Name	Type	Description	Default
`base_url`	`str`	The base URL of the OpenWebUI instance	required
`token`	`str`	Authentication token	required
`default_model_id`	`str`	Default model identifier to use	required
`skip_model_refresh`	`bool`	If True, skip initial model refresh (useful for testing)	`False`

`chat(question, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_follow_up=False, enable_auto_tagging=False, enable_auto_titling=False)` ¶

Send a chat message with a single model.

`stream_chat(question, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_follow_up=False, cleanup_placeholder_messages=False, placeholder_pool_size=30, min_available_messages=10, wait_before_request=10.0, enable_auto_tagging=False, enable_auto_titling=False)` ¶

Initiates a streaming chat session. Yields content chunks as they are received. At the end of the stream, returns the full response content, sources, and follow-up suggestions.

`parallel_chat(question, chat_title, model_ids, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_follow_up=False, enable_auto_tagging=False, enable_auto_titling=False)` ¶

Send a chat message to multiple models in parallel.

`continuous_chat(initial_question, num_questions, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False)` ¶

Perform continuous conversation with automatic follow-up questions.

`continuous_parallel_chat(initial_question, num_questions, chat_title, model_ids, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False)` ¶

Perform continuous conversation with multiple models in parallel.

`continuous_stream_chat(initial_question, num_questions, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False)` ¶

Perform continuous conversation with streaming responses.

`deep_research(topic, chat_title=None, num_steps=3, general_models=None, search_models=None)` ¶

Performs an advanced, autonomous, multi-step research process on a given topic using intelligent model routing.

The agent will iteratively plan questions and decide which type of model to use (general vs. search-capable), with the entire process being visible as a multi-turn chat in the UI.

Parameters:

Name	Type	Description	Default
`topic`	`str`	The topic to be researched.	required
`chat_title`	`Optional[str]`	Optional title for the research chat. If not provided, it will be generated from the topic.	`None`
`num_steps`	`int`	The number of research steps (plan -> execute cycles).	`3`
`general_models`	`Optional[List[str]]`	A list of model IDs for general reasoning and summarization. If not provided, the client's default model will be used.	`None`
`search_models`	`Optional[List[str]]`	A list of model IDs with search capabilities. If not provided, the agent will not have the option to use a search model.	`None`

Returns:

Type	Description
`Optional[Dict[str, Any]]`	A dictionary containing the research results and chat information, or None if it fails.

`process_task(question, model_id, tool_server_ids, knowledge_base_name=None, max_iterations=25, summarize_history=False, decision_model_id=None)` ¶

Processes a task using an AI model and a tool server in a multi-step process.

Parameters:

Name	Type	Description	Default
`question`	`str`	The task to process.	required
`model_id`	`str`	The ID of the model to use for task execution.	required
`tool_server_ids`	`Union[str, List[str]]`	The ID(s) of the tool server(s) to use.	required
`knowledge_base_name`	`Optional[str]`	The name of the knowledge base to use.	`None`
`max_iterations`	`int`	The maximum number of iterations to attempt.	`25`
`summarize_history`	`bool`	If True, the conversation history will be summarized.	`False`
`decision_model_id`	`Optional[str]`	Optional model ID for automatic decision-making when the AI presents multiple options. If provided, this model will analyze the options and select the best one automatically, eliminating the need for user input when choices arise.	`None`

Returns:

Type	Description
`Optional[Dict[str, Any]]`	A dictionary containing: - solution: The final answer or error message - conversation_history: Either the full message list or a summarized string (if summarize_history=True) - todo_list: The last parsed to-do list from the agent's thought process
`Optional[Dict[str, Any]]`	Returns None if initialization fails.

`stream_process_task(question, model_id, tool_server_ids, knowledge_base_name=None, max_iterations=25, summarize_history=False, decision_model_id=None)` ¶

Processes a task in a streaming fashion, yielding results for each step.

Parameters:

Name	Type	Description	Default
`question`	`str`	The task to process.	required
`model_id`	`str`	The ID of the model to use for task execution.	required
`tool_server_ids`	`Union[str, List[str]]`	The ID(s) of the tool server(s) to use.	required
`knowledge_base_name`	`Optional[str]`	The name of the knowledge base to use.	`None`
`max_iterations`	`int`	The maximum number of iterations to attempt.	`25`
`summarize_history`	`bool`	If True, the conversation history will be summarized.	`False`
`decision_model_id`	`Optional[str]`	Optional model ID for automatic decision-making when the AI presents multiple options. If provided, this model will analyze the options and select the best one automatically.	`None`

`rename_chat(chat_id, new_title)` ¶

Rename an existing chat.

`set_chat_tags(chat_id, tags)` ¶

Set tags for a chat conversation.

`update_chat_metadata(chat_id, regenerate_tags=False, regenerate_title=False, title=None, tags=None, folder_name=None)` ¶

Regenerates and updates the tags and/or title for an existing chat based on its history.

Parameters:

Name	Type	Description	Default
`chat_id`	`str`	The ID of the chat to update.	required
`regenerate_tags`	`bool`	If True, new tags will be generated and applied.	`False`
`regenerate_title`	`bool`	If True, a new title will be generated and applied.	`False`
`title`	`Optional[str]`	Direct title to set (alternative to regenerate_title)	`None`
`tags`	`Optional[List[str]]`	Direct tags to set (alternative to regenerate_tags)	`None`
`folder_name`	`Optional[str]`	Folder to move chat to	`None`

Returns:

Type	Description
`Optional[Dict[str, Any]]`	A dictionary containing the 'suggested_tags' and/or 'suggested_title' that were updated,
`Optional[Dict[str, Any]]`	or None if the chat could not be found or no action was requested.

`switch_chat_model(chat_id, model_ids)` ¶

Switch the model(s) for an existing chat.

`list_chats(page=None)` ¶

List all chats for the current user.

`get_chats_by_folder(folder_id)` ¶

Get all chats in a specific folder.

`archive_chat(chat_id)` ¶

Archive a chat conversation.

`archive_chats_by_age(days_since_update=30, folder_name=None, dry_run=False)` ¶

Archive chats that haven't been updated for a specified number of days.

Parameters:

Name	Type	Description	Default
`days_since_update`	`int`	Number of days since last update (default: 30)	`30`
`folder_name`	`Optional[str]`	Optional folder name to filter chats. If None, only archives chats NOT in folders. If provided, only archives chats IN that folder.	`None`
`dry_run`	`bool`	If True, only shows what would be archived without actually archiving	`False`

Returns:

Type	Description
`Dict[str, Any]`	Dictionary with archive results including counts and details

`delete_all_chats()` ¶

Delete ALL chat conversations for the current user.

⚠️ WARNING: This is a DESTRUCTIVE operation! This method will permanently delete ALL chats associated with the current user account. This action CANNOT be undone. Use with extreme caution.

This method is useful for: - Cleaning up test data after integration tests - Resetting an account to a clean state - Bulk cleanup operations

Returns:

Type	Description
`bool`	True if deletion was successful, False otherwise

Example

# ⚠️ WARNING: This will delete ALL your chats!
success = client.delete_all_chats()
if success:
    print("All chats have been permanently deleted")

`create_folder(name)` ¶

Create a new folder for organizing chats.

`get_folder_id_by_name(name, suppress_log=False)` ¶

Get folder ID by folder name.

`move_chat_to_folder(chat_id, folder_id)` ¶

Move a chat to a specific folder.

`list_models()` ¶

Lists all available models for the user, including base models and user-created custom models. Excludes disabled base models. This corresponds to the model list shown in the top left of the chat page.

`list_base_models()` ¶

Lists all base models that can be used to create variants. Includes disabled base models. Corresponds to the model list in the admin settings page, including PIPE type models.

`list_custom_models()` ¶

Lists custom models that users can use or have created (not base models). A list of custom models available in the user's workspace.

`list_groups()` ¶

Lists all available groups from the Open WebUI instance.

`get_model(model_id)` ¶

Fetches the details of a specific model by its ID.

`create_model(model_id, name, base_model_id=None, description=None, params=None, permission_type='public', group_identifiers=None, user_ids=None, profile_image_url='/static/favicon.png', suggestion_prompts=None, tags=None, capabilities=None, is_active=True)` ¶

Creates a new model configuration with detailed metadata. This method delegates directly to the ModelManager.

`update_model(model_id, name=None, base_model_id=None, description=None, params=None, permission_type=None, group_identifiers=None, user_ids=None, profile_image_url=None, suggestion_prompts=None, tags=None, capabilities=None, is_active=None)` ¶

Updates an existing model configuration with detailed metadata. This method delegates directly to the ModelManager.

`delete_model(model_id)` ¶

Deletes a model configuration.

`batch_update_model_permissions(models=None, permission_type='public', group_identifiers=None, user_ids=None, max_workers=5, model_identifiers=None, model_keyword=None)` ¶

Updates permissions for multiple models in parallel.

`get_knowledge_base_by_name(name)` ¶

Get a knowledge base by its name.

`create_knowledge_base(name, description='')` ¶

Create a new knowledge base.

`add_file_to_knowledge_base(file_path, knowledge_base_name)` ¶

Add a file to a knowledge base.

`delete_knowledge_base(kb_id)` ¶

Deletes a knowledge base by its ID.

`delete_all_knowledge_bases()` ¶

Deletes all knowledge bases for the current user.

`delete_knowledge_bases_by_keyword(keyword, case_sensitive=False)` ¶

Deletes knowledge bases whose names contain a specific keyword.

`create_knowledge_bases_with_files(kb_configs, max_workers=3)` ¶

Creates multiple knowledge bases with files in parallel.

`get_notes()` ¶

Get all notes for the current user.

`get_notes_list()` ¶

Get a simplified list of notes with only id, title, and timestamps.

`create_note(title, data=None, meta=None, access_control=None)` ¶

Create a new note.

`get_note_by_id(note_id)` ¶

Get a specific note by its ID.

`update_note_by_id(note_id, title=None, data=None, meta=None, access_control=None)` ¶

Update an existing note by its ID.

`delete_note_by_id(note_id)` ¶

Delete a note by its ID.

`get_prompts()` ¶

Get all prompts for the current user.

`get_prompts_list()` ¶

Get a detailed list of prompts with user information.

`create_prompt(command, title, content, access_control=None)` ¶

Create a new prompt.

`get_prompt_by_command(command)` ¶

Get a specific prompt by its command.

`update_prompt_by_command(command, title=None, content=None, access_control=None)` ¶

Update an existing prompt by its command (title/content only).

`replace_prompt_by_command(old_command, new_command, title, content, access_control=None)` ¶

Replace a prompt completely including command (delete + recreate).

`delete_prompt_by_command(command)` ¶

Delete a prompt by its command.

`search_prompts(query=None, by_command=False, by_title=True, by_content=False)` ¶

Search prompts by various criteria.

`extract_variables(content)` ¶

Extract variable names from prompt content.

`substitute_variables(content, variables, system_variables=None)` ¶

Substitute variables in prompt content.

`get_system_variables()` ¶

Get current system variables for substitution.

`batch_create_prompts(prompts_data, continue_on_error=True)` ¶

Create multiple prompts in batch.

`batch_delete_prompts(commands, continue_on_error=True)` ¶

Delete multiple prompts by their commands.

`get_users(skip=0, limit=50)` ¶

Get a list of all users.

`get_user_by_id(user_id)` ¶

Get a specific user by their ID.

`update_user_role(user_id, role)` ¶

Update a user's role (admin/user).

`delete_user(user_id)` ¶

Delete a user.

AsyncOpenWebUIClient¶

用于异步操作的异步客户端类。

`AsyncOpenWebUIClient(base_url, token, default_model_id, timeout=60.0, **kwargs)` ¶

Asynchronous Python client for the Open WebUI API.

`close()` `async` ¶

Close the client.

`delete_all_chats()` `async` ¶

Delete ALL chat conversations for the current user.

⚠️ WARNING: This is a DESTRUCTIVE operation! This method will permanently delete ALL chats associated with the current user account. This action CANNOT be undone. Use with extreme caution.

This method is useful for: - Cleaning up test data after integration tests - Resetting an account to a clean state - Bulk cleanup operations

Returns:

Type	Description
`bool`	True if deletion was successful, False otherwise

Example

# ⚠️ WARNING: This will delete ALL your chats!
success = await client.delete_all_chats()
if success:
    print("All chats have been permanently deleted")

返回值示例¶

聊天操作¶

{
    "response": "生成的响应文本",
    "chat_id": "chat-uuid-string",
    "message_id": "message-uuid-string",
    "sources": [...]  # 用于 RAG 操作
}

并行聊天¶

{
    "responses": {
        "model-1": "模型 1 的响应",
        "model-2": "模型 2 的响应"
    },
    "chat_id": "chat-uuid-string",
    "message_ids": {
        "model-1": "message-uuid-1",
        "model-2": "message-uuid-2"
    }
}

知识库 / 笔记¶

{
    "id": "resource-uuid",
    "name": "资源名称",
    "created_at": "2024-01-01T00:00:00Z",
    "updated_at": "2024-01-01T00:00:00Z",
    ...
}

任务处理¶

{
    "solution": "最终解决方案文本",
    "conversation_history": [...],  # 或摘要字符串
    "todo_list": [
        {"task": "研究主题", "status": "completed"},
        {"task": "撰写摘要", "status": "completed"}
    ]
}

快速参考表¶

聊天操作¶

方法	描述
`chat()`	带可选功能的单模型对话
`stream_chat()`	带实时更新的流式对话
`parallel_chat()`	多模型并行对话
`continuous_chat()`	带后续问题的连续对话
`process_task()`	自主多步骤任务处理
`deep_research()`	多步骤研究代理

聊天管理¶

方法	描述
`rename_chat()`	重命名现有聊天
`set_chat_tags()`	为聊天应用标签
`update_chat_metadata()`	重新生成标签和/或标题
`switch_chat_model()`	切换现有聊天的模型
`list_chats()`	获取用户的聊天列表
`archive_chat()`	归档特定聊天
`archive_chats_by_age()`	批量归档旧聊天
`create_folder()`	创建聊天文件夹

模型管理¶

方法	描述
`list_models()`	列出可用模型
`list_base_models()`	列出基础模型
`list_custom_models()`	列出自定义模型
`get_model()`	获取模型详情
`create_model()`	创建自定义模型
`update_model()`	更新模型
`delete_model()`	删除模型
`batch_update_model_permissions()`	批量更新权限

知识库操作¶

方法	描述
`create_knowledge_base()`	创建知识库
`add_file_to_knowledge_base()`	向知识库添加文件
`get_knowledge_base_by_name()`	按名称获取知识库
`delete_knowledge_base()`	删除知识库
`delete_all_knowledge_bases()`	删除所有知识库
`create_knowledge_bases_with_files()`	批量创建知识库

笔记 API¶

方法	描述
`get_notes()`	获取所有笔记
`create_note()`	创建笔记
`get_note_by_id()`	按 ID 获取笔记
`update_note_by_id()`	更新笔记
`delete_note_by_id()`	删除笔记

提示词 API¶

方法	描述
`get_prompts()`	获取所有提示词
`create_prompt()`	创建提示词
`get_prompt_by_command()`	按命令获取提示词
`update_prompt_by_command()`	更新提示词
`delete_prompt_by_command()`	删除提示词
`extract_variables()`	提取提示词变量
`substitute_variables()`	替换变量

用户管理¶

方法	描述
`get_users()`	列出用户
`get_user_by_id()`	获取用户详情
`update_user_role()`	更新用户角色
`delete_user()`	删除用户

API 参考¶

OpenWebUIClient¶

OpenWebUIClient(base_url, token, default_model_id, skip_model_refresh=False) ¶

chat(question, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_follow_up=False, enable_auto_tagging=False, enable_auto_titling=False) ¶

parallel_chat(question, chat_title, model_ids, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_follow_up=False, enable_auto_tagging=False, enable_auto_titling=False) ¶

continuous_chat(initial_question, num_questions, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False) ¶

continuous_parallel_chat(initial_question, num_questions, chat_title, model_ids, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False) ¶

continuous_stream_chat(initial_question, num_questions, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False) ¶

deep_research(topic, chat_title=None, num_steps=3, general_models=None, search_models=None) ¶

process_task(question, model_id, tool_server_ids, knowledge_base_name=None, max_iterations=25, summarize_history=False, decision_model_id=None) ¶

stream_process_task(question, model_id, tool_server_ids, knowledge_base_name=None, max_iterations=25, summarize_history=False, decision_model_id=None) ¶

rename_chat(chat_id, new_title) ¶

set_chat_tags(chat_id, tags) ¶

update_chat_metadata(chat_id, regenerate_tags=False, regenerate_title=False, title=None, tags=None, folder_name=None) ¶

switch_chat_model(chat_id, model_ids) ¶

list_chats(page=None) ¶

get_chats_by_folder(folder_id) ¶

archive_chat(chat_id) ¶

archive_chats_by_age(days_since_update=30, folder_name=None, dry_run=False) ¶

delete_all_chats() ¶

create_folder(name) ¶

get_folder_id_by_name(name, suppress_log=False) ¶

move_chat_to_folder(chat_id, folder_id) ¶

list_models() ¶

list_base_models() ¶

list_custom_models() ¶

list_groups() ¶

get_model(model_id) ¶

create_model(model_id, name, base_model_id=None, description=None, params=None, permission_type='public', group_identifiers=None, user_ids=None, profile_image_url='/static/favicon.png', suggestion_prompts=None, tags=None, capabilities=None, is_active=True) ¶

update_model(model_id, name=None, base_model_id=None, description=None, params=None, permission_type=None, group_identifiers=None, user_ids=None, profile_image_url=None, suggestion_prompts=None, tags=None, capabilities=None, is_active=None) ¶

delete_model(model_id) ¶

batch_update_model_permissions(models=None, permission_type='public', group_identifiers=None, user_ids=None, max_workers=5, model_identifiers=None, model_keyword=None) ¶

get_knowledge_base_by_name(name) ¶

create_knowledge_base(name, description='') ¶

add_file_to_knowledge_base(file_path, knowledge_base_name) ¶

delete_knowledge_base(kb_id) ¶

delete_all_knowledge_bases() ¶

delete_knowledge_bases_by_keyword(keyword, case_sensitive=False) ¶

create_knowledge_bases_with_files(kb_configs, max_workers=3) ¶

get_notes() ¶

get_notes_list() ¶

create_note(title, data=None, meta=None, access_control=None) ¶

get_note_by_id(note_id) ¶

update_note_by_id(note_id, title=None, data=None, meta=None, access_control=None) ¶

delete_note_by_id(note_id) ¶

get_prompts() ¶

get_prompts_list() ¶

create_prompt(command, title, content, access_control=None) ¶

get_prompt_by_command(command) ¶

update_prompt_by_command(command, title=None, content=None, access_control=None) ¶

replace_prompt_by_command(old_command, new_command, title, content, access_control=None) ¶

delete_prompt_by_command(command) ¶

search_prompts(query=None, by_command=False, by_title=True, by_content=False) ¶

extract_variables(content) ¶

substitute_variables(content, variables, system_variables=None) ¶

get_system_variables() ¶

batch_create_prompts(prompts_data, continue_on_error=True) ¶

batch_delete_prompts(commands, continue_on_error=True) ¶

get_users(skip=0, limit=50) ¶

get_user_by_id(user_id) ¶

update_user_role(user_id, role) ¶

delete_user(user_id) ¶

AsyncOpenWebUIClient¶

AsyncOpenWebUIClient(base_url, token, default_model_id, timeout=60.0, **kwargs) ¶

close() async ¶

delete_all_chats() async ¶

返回值示例¶

聊天操作¶

并行聊天¶

知识库 / 笔记¶

任务处理¶

快速参考表¶

聊天操作¶

聊天管理¶

模型管理¶

知识库操作¶

笔记 API¶

提示词 API¶

用户管理¶

`OpenWebUIClient(base_url, token, default_model_id, skip_model_refresh=False)` ¶

`chat(question, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_follow_up=False, enable_auto_tagging=False, enable_auto_titling=False)` ¶

`parallel_chat(question, chat_title, model_ids, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_follow_up=False, enable_auto_tagging=False, enable_auto_titling=False)` ¶

`continuous_chat(initial_question, num_questions, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False)` ¶

`continuous_parallel_chat(initial_question, num_questions, chat_title, model_ids, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False)` ¶

`continuous_stream_chat(initial_question, num_questions, chat_title, model_id=None, folder_name=None, image_paths=None, tags=None, rag_files=None, rag_collections=None, tool_ids=None, enable_auto_tagging=False, enable_auto_titling=False)` ¶

`deep_research(topic, chat_title=None, num_steps=3, general_models=None, search_models=None)` ¶

`process_task(question, model_id, tool_server_ids, knowledge_base_name=None, max_iterations=25, summarize_history=False, decision_model_id=None)` ¶

`stream_process_task(question, model_id, tool_server_ids, knowledge_base_name=None, max_iterations=25, summarize_history=False, decision_model_id=None)` ¶

`rename_chat(chat_id, new_title)` ¶

`set_chat_tags(chat_id, tags)` ¶

`update_chat_metadata(chat_id, regenerate_tags=False, regenerate_title=False, title=None, tags=None, folder_name=None)` ¶

`switch_chat_model(chat_id, model_ids)` ¶

`list_chats(page=None)` ¶

`get_chats_by_folder(folder_id)` ¶

`archive_chat(chat_id)` ¶

`archive_chats_by_age(days_since_update=30, folder_name=None, dry_run=False)` ¶

`delete_all_chats()` ¶

`create_folder(name)` ¶

`get_folder_id_by_name(name, suppress_log=False)` ¶

`move_chat_to_folder(chat_id, folder_id)` ¶

`list_models()` ¶

`list_base_models()` ¶

`list_custom_models()` ¶

`list_groups()` ¶

`get_model(model_id)` ¶

`create_model(model_id, name, base_model_id=None, description=None, params=None, permission_type='public', group_identifiers=None, user_ids=None, profile_image_url='/static/favicon.png', suggestion_prompts=None, tags=None, capabilities=None, is_active=True)` ¶

`update_model(model_id, name=None, base_model_id=None, description=None, params=None, permission_type=None, group_identifiers=None, user_ids=None, profile_image_url=None, suggestion_prompts=None, tags=None, capabilities=None, is_active=None)` ¶

`delete_model(model_id)` ¶

`batch_update_model_permissions(models=None, permission_type='public', group_identifiers=None, user_ids=None, max_workers=5, model_identifiers=None, model_keyword=None)` ¶

`get_knowledge_base_by_name(name)` ¶

`create_knowledge_base(name, description='')` ¶

`add_file_to_knowledge_base(file_path, knowledge_base_name)` ¶

`delete_knowledge_base(kb_id)` ¶

`delete_all_knowledge_bases()` ¶

`delete_knowledge_bases_by_keyword(keyword, case_sensitive=False)` ¶

`create_knowledge_bases_with_files(kb_configs, max_workers=3)` ¶

`get_notes()` ¶

`get_notes_list()` ¶

`create_note(title, data=None, meta=None, access_control=None)` ¶

`get_note_by_id(note_id)` ¶

`update_note_by_id(note_id, title=None, data=None, meta=None, access_control=None)` ¶

`delete_note_by_id(note_id)` ¶

`get_prompts()` ¶

`get_prompts_list()` ¶

`create_prompt(command, title, content, access_control=None)` ¶

`get_prompt_by_command(command)` ¶

`update_prompt_by_command(command, title=None, content=None, access_control=None)` ¶

`replace_prompt_by_command(old_command, new_command, title, content, access_control=None)` ¶

`delete_prompt_by_command(command)` ¶

`search_prompts(query=None, by_command=False, by_title=True, by_content=False)` ¶

`extract_variables(content)` ¶

`substitute_variables(content, variables, system_variables=None)` ¶

`get_system_variables()` ¶

`batch_create_prompts(prompts_data, continue_on_error=True)` ¶

`batch_delete_prompts(commands, continue_on_error=True)` ¶

`get_users(skip=0, limit=50)` ¶

`get_user_by_id(user_id)` ¶

`update_user_role(user_id, role)` ¶

`delete_user(user_id)` ¶

`AsyncOpenWebUIClient(base_url, token, default_model_id, timeout=60.0, **kwargs)` ¶

`close()` `async` ¶

`delete_all_chats()` `async` ¶