refactor: update imports and move functions out of MCPToolsComponent (#8976)

src/backend/base/langflow/base/agents/utils.py

@@ -1,3 +1,4 @@
+import re
 from collections.abc import Callable, Sequence
 from typing import Any
 
@@ -14,7 +15,10 @@ from langchain_core.prompts import BasePromptTemplate, ChatPromptTemplate
 from langchain_core.tools import BaseTool
 from pydantic import BaseModel
 
+from langflow.logging import logger
 from langflow.schema.data import Data
+from langflow.services.cache.base import CacheService
+from langflow.services.cache.utils import CacheMiss
 
 from .default_prompts import XML_AGENT_PROMPT
 
@@ -141,3 +145,61 @@ AGENTS: dict[str, AgentSpec] = {
 
 def get_agents_list():
     return list(AGENTS.keys())
+
+
+def safe_cache_get(cache: CacheService, key, default=None):
+    """Safely get a value from cache, handling CacheMiss objects."""
+    try:
+        value = cache.get(key)
+        if isinstance(value, CacheMiss):
+            return default
+    except (AttributeError, KeyError, TypeError):
+        return default
+    else:
+        return value
+
+
+def safe_cache_set(cache: CacheService, key, value):
+    """Safely set a value in cache, handling potential errors."""
+    try:
+        cache.set(key, value)
+    except (AttributeError, TypeError) as e:
+        logger.warning(f"Failed to set cache key '{key}': {e}")
+
+
+def maybe_unflatten_dict(flat: dict[str, Any]) -> dict[str, Any]:
+    """If any key looks nested (contains a dot or "[index]"), rebuild the.
+
+    full nested structure; otherwise return flat as is.
+    """
+    # Quick check: do we have any nested keys?
+    if not any(re.search(r"\.|\[\d+\]", key) for key in flat):
+        return flat
+
+    # Otherwise, unflatten into dicts/lists
+    nested: dict[str, Any] = {}
+    array_re = re.compile(r"^(.+)\[(\d+)\]$")
+
+    for key, val in flat.items():
+        parts = key.split(".")
+        cur = nested
+        for i, part in enumerate(parts):
+            m = array_re.match(part)
+            # Array segment?
+            if m:
+                name, idx = m.group(1), int(m.group(2))
+                lst = cur.setdefault(name, [])
+                # Ensure list is big enough
+                while len(lst) <= idx:
+                    lst.append({})
+                if i == len(parts) - 1:
+                    lst[idx] = val
+                else:
+                    cur = lst[idx]
+            # Normal object key
+            elif i == len(parts) - 1:
+                cur[part] = val
+            else:
+                cur = cur.setdefault(part, {})
+
+    return nested

src/backend/base/langflow/components/agents/mcp_component.py

@@ -1,11 +1,13 @@
 from __future__ import annotations
 
 import asyncio
-import re
 import uuid
-from typing import TYPE_CHECKING, Any
+from typing import Any
+
+from langchain_core.tools import StructuredTool  # noqa: TC002
 
 from langflow.api.v2.mcp import get_server
+from langflow.base.agents.utils import maybe_unflatten_dict, safe_cache_get, safe_cache_set
 from langflow.base.mcp.util import (
     MCPSseClient,
     MCPStdioClient,
@@ -13,82 +15,18 @@ from langflow.base.mcp.util import (
     update_tools,
 )
 from langflow.custom.custom_component.component_with_cache import ComponentWithCache
+from langflow.inputs.inputs import InputTypes  # noqa: TC001
 from langflow.io import DropdownInput, McpInput, MessageTextInput, Output
 from langflow.io.schema import flatten_schema, schema_to_langflow_inputs
 from langflow.logging import logger
 from langflow.schema.dataframe import DataFrame
 from langflow.schema.message import Message
 from langflow.services.auth.utils import create_user_longterm_token
-from langflow.services.cache.utils import CacheMiss
 
 # Import get_server from the backend API
 from langflow.services.database.models.user.crud import get_user_by_id
 from langflow.services.deps import get_session, get_settings_service, get_storage_service
 
-if TYPE_CHECKING:
-    from langchain_core.tools import StructuredTool
-
-    from langflow.inputs.inputs import InputTypes
-    from langflow.services.cache.base import CacheService
-
-
-def maybe_unflatten_dict(flat: dict[str, Any]) -> dict[str, Any]:
-    """If any key looks nested (contains a dot or "[index]"), rebuild the.
-
-    full nested structure; otherwise return flat as is.
-    """
-    # Quick check: do we have any nested keys?
-    if not any(re.search(r"\.|\[\d+\]", key) for key in flat):
-        return flat
-
-    # Otherwise, unflatten into dicts/lists
-    nested: dict[str, Any] = {}
-    array_re = re.compile(r"^(.+)\[(\d+)\]$")
-
-    for key, val in flat.items():
-        parts = key.split(".")
-        cur = nested
-        for i, part in enumerate(parts):
-            m = array_re.match(part)
-            # Array segment?
-            if m:
-                name, idx = m.group(1), int(m.group(2))
-                lst = cur.setdefault(name, [])
-                # Ensure list is big enough
-                while len(lst) <= idx:
-                    lst.append({})
-                if i == len(parts) - 1:
-                    lst[idx] = val
-                else:
-                    cur = lst[idx]
-            # Normal object key
-            elif i == len(parts) - 1:
-                cur[part] = val
-            else:
-                cur = cur.setdefault(part, {})
-
-    return nested
-
-
-def safe_cache_get(cache: CacheService, key, default=None):
-    """Safely get a value from cache, handling CacheMiss objects."""
-    try:
-        value = cache.get(key)
-        if isinstance(value, CacheMiss):
-            return default
-    except (AttributeError, KeyError, TypeError):
-        return default
-    else:
-        return value
-
-
-def safe_cache_set(cache: CacheService, key, value):
-    """Safely set a value in cache, handling potential errors."""
-    try:
-        cache.set(key, value)
-    except (AttributeError, TypeError) as e:
-        logger.warning(f"Failed to set cache key '{key}': {e}")
-
 
 class MCPToolsComponent(ComponentWithCache):
     schema_inputs: list = []