move tools utils to utils.tools

backend/main.py

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

backend/utils/tools.py

@@ -1,5 +1,86 @@
 import inspect
-from typing import get_type_hints
+import logging
+from typing import Awaitable, Callable, get_type_hints
+
+from apps.webui.models.tools import Tools
+from apps.webui.models.users import UserModel
+from apps.webui.utils import load_toolkit_module_by_id
+
+log = logging.getLogger(__name__)
+
+
+def apply_extra_params_to_tool_function(
+    function: Callable, extra_params: dict
+) -> Callable[..., Awaitable]:
+    sig = inspect.signature(function)
+    extra_params = {
+        key: value for key, value in extra_params.items() if key in sig.parameters
+    }
+    is_coroutine = inspect.iscoroutinefunction(function)
+
+    async def new_function(**kwargs):
+        extra_kwargs = kwargs | extra_params
+        if is_coroutine:
+            return await function(**extra_kwargs)
+        return function(**extra_kwargs)
+
+    return new_function
+
+
+# Mutation on extra_params
+def get_tools(
+    webui_app, tool_ids: list[str], user: UserModel, extra_params: dict
+) -> dict[str, dict]:
+    tools = {}
+    for tool_id in tool_ids:
+        toolkit = Tools.get_tool_by_id(tool_id)
+        if toolkit is None:
+            continue
+
+        module = webui_app.state.TOOLS.get(tool_id, None)
+        if module is None:
+            module, _ = load_toolkit_module_by_id(tool_id)
+            webui_app.state.TOOLS[tool_id] = module
+
+        extra_params["__id__"] = tool_id
+        if hasattr(module, "valves") and hasattr(module, "Valves"):
+            valves = Tools.get_tool_valves_by_id(tool_id) or {}
+            module.valves = module.Valves(**valves)
+
+        if hasattr(module, "UserValves"):
+            extra_params["__user__"]["valves"] = module.UserValves(  # type: ignore
+                **Tools.get_user_valves_by_id_and_user_id(tool_id, user.id)
+            )
+
+        for spec in toolkit.specs:
+            # TODO: Fix hack for OpenAI API
+            for val in spec.get("parameters", {}).get("properties", {}).values():
+                if val["type"] == "str":
+                    val["type"] = "string"
+            function_name = spec["name"]
+
+            # convert to function that takes only model params and inserts custom params
+            callable = apply_extra_params_to_tool_function(
+                getattr(module, function_name), extra_params
+            )
+
+            # TODO: This needs to be a pydantic model
+            tool_dict = {
+                "toolkit_id": tool_id,
+                "callable": callable,
+                "spec": spec,
+                "file_handler": hasattr(module, "file_handler") and module.file_handler,
+                "citation": hasattr(module, "citation") and module.citation,
+            }
+
+            # TODO: if collision, prepend toolkit name
+            if function_name in tools:
+                log.warning(f"Tool {function_name} already exists in another toolkit!")
+                log.warning(f"Collision between {toolkit} and {tool_id}.")
+                log.warning(f"Discarding {toolkit}.{function_name}")
+            else:
+                tools[function_name] = tool_dict
+    return tools
 
 
 def doc_to_dict(docstring):