mirror of
https://github.com/open-webui/open-webui
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move tools utils to utils.tools
This commit is contained in:
Michael Poluektov
parent
fd422d2e3c
commit
a4a7d678f9
@ -51,15 +51,13 @@ from apps.webui.internal.db import Session
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from pydantic import BaseModel
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from typing import Optional, Callable, Awaitable
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from apps.webui.models.auths import Auths
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from apps.webui.models.models import Models
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from apps.webui.models.tools import Tools
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from apps.webui.models.functions import Functions
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from apps.webui.models.users import Users, UserModel
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from apps.webui.utils import load_toolkit_module_by_id, load_function_module_by_id
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from apps.webui.utils import load_function_module_by_id
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from utils.utils import (
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get_admin_user,
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@ -75,6 +73,8 @@ from utils.task import (
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tools_function_calling_generation_template,
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moa_response_generation_template,
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)
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from utils.tools import get_tools
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from utils.misc import (
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get_last_user_message,
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add_or_update_system_message,
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@ -353,80 +353,6 @@ def get_tools_function_calling_payload(messages, task_model_id, content):
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}
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def apply_extra_params_to_tool_function(
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function: Callable, extra_params: dict
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) -> Callable[..., Awaitable]:
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sig = inspect.signature(function)
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extra_params = {
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key: value for key, value in extra_params.items() if key in sig.parameters
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}
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is_coroutine = inspect.iscoroutinefunction(function)
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async def new_function(**kwargs):
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extra_kwargs = kwargs | extra_params
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if is_coroutine:
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return await function(**extra_kwargs)
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return function(**extra_kwargs)
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return new_function
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# Mutation on extra_params
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def get_tools(
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tool_ids: list[str], user: UserModel, extra_params: dict
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) -> dict[str, dict]:
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tools = {}
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for tool_id in tool_ids:
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toolkit = Tools.get_tool_by_id(tool_id)
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if toolkit is None:
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continue
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module = webui_app.state.TOOLS.get(tool_id, None)
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if module is None:
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module, _ = load_toolkit_module_by_id(tool_id)
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webui_app.state.TOOLS[tool_id] = module
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extra_params["__id__"] = tool_id
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if hasattr(module, "valves") and hasattr(module, "Valves"):
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valves = Tools.get_tool_valves_by_id(tool_id) or {}
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module.valves = module.Valves(**valves)
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if hasattr(module, "UserValves"):
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extra_params["__user__"]["valves"] = module.UserValves( # type: ignore
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**Tools.get_user_valves_by_id_and_user_id(tool_id, user.id)
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)
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for spec in toolkit.specs:
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# TODO: Fix hack for OpenAI API
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for val in spec.get("parameters", {}).get("properties", {}).values():
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if val["type"] == "str":
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val["type"] = "string"
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function_name = spec["name"]
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# convert to function that takes only model params and inserts custom params
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callable = apply_extra_params_to_tool_function(
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getattr(module, function_name), extra_params
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)
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# TODO: This needs to be a pydantic model
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tool_dict = {
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"toolkit_id": tool_id,
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"callable": callable,
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"spec": spec,
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"file_handler": hasattr(module, "file_handler") and module.file_handler,
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"citation": hasattr(module, "citation") and module.citation,
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}
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# TODO: if collision, prepend toolkit name
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if function_name in tools:
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log.warning(f"Tool {function_name} already exists in another toolkit!")
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log.warning(f"Collision between {toolkit} and {tool_id}.")
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log.warning(f"Discarding {toolkit}.{function_name}")
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else:
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tools[function_name] = tool_dict
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return tools
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async def get_content_from_response(response) -> Optional[str]:
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content = None
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if hasattr(response, "body_iterator"):
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@ -467,7 +393,7 @@ async def chat_completion_tools_handler(
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"__messages__": body["messages"],
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"__files__": body.get("files", []),
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}
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tools = get_tools(tool_ids, user, custom_params)
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tools = get_tools(webui_app, tool_ids, user, custom_params)
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log.info(f"{tools=}")
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specs = [tool["spec"] for tool in tools.values()]
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@ -1,5 +1,86 @@
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import inspect
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from typing import get_type_hints
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import logging
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from typing import Awaitable, Callable, get_type_hints
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from apps.webui.models.tools import Tools
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from apps.webui.models.users import UserModel
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from apps.webui.utils import load_toolkit_module_by_id
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log = logging.getLogger(__name__)
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def apply_extra_params_to_tool_function(
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function: Callable, extra_params: dict
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) -> Callable[..., Awaitable]:
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sig = inspect.signature(function)
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extra_params = {
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key: value for key, value in extra_params.items() if key in sig.parameters
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}
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is_coroutine = inspect.iscoroutinefunction(function)
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async def new_function(**kwargs):
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extra_kwargs = kwargs | extra_params
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if is_coroutine:
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return await function(**extra_kwargs)
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return function(**extra_kwargs)
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return new_function
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# Mutation on extra_params
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def get_tools(
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webui_app, tool_ids: list[str], user: UserModel, extra_params: dict
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) -> dict[str, dict]:
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tools = {}
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for tool_id in tool_ids:
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toolkit = Tools.get_tool_by_id(tool_id)
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if toolkit is None:
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continue
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module = webui_app.state.TOOLS.get(tool_id, None)
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if module is None:
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module, _ = load_toolkit_module_by_id(tool_id)
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webui_app.state.TOOLS[tool_id] = module
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extra_params["__id__"] = tool_id
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if hasattr(module, "valves") and hasattr(module, "Valves"):
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valves = Tools.get_tool_valves_by_id(tool_id) or {}
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module.valves = module.Valves(**valves)
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if hasattr(module, "UserValves"):
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extra_params["__user__"]["valves"] = module.UserValves( # type: ignore
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**Tools.get_user_valves_by_id_and_user_id(tool_id, user.id)
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)
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for spec in toolkit.specs:
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# TODO: Fix hack for OpenAI API
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for val in spec.get("parameters", {}).get("properties", {}).values():
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if val["type"] == "str":
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val["type"] = "string"
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function_name = spec["name"]
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# convert to function that takes only model params and inserts custom params
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callable = apply_extra_params_to_tool_function(
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getattr(module, function_name), extra_params
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)
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# TODO: This needs to be a pydantic model
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tool_dict = {
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"toolkit_id": tool_id,
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"callable": callable,
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"spec": spec,
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"file_handler": hasattr(module, "file_handler") and module.file_handler,
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"citation": hasattr(module, "citation") and module.citation,
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}
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# TODO: if collision, prepend toolkit name
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if function_name in tools:
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log.warning(f"Tool {function_name} already exists in another toolkit!")
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log.warning(f"Collision between {toolkit} and {tool_id}.")
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log.warning(f"Discarding {toolkit}.{function_name}")
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else:
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tools[function_name] = tool_dict
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return tools
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def doc_to_dict(docstring):
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