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fix(core): handle protocol errors and foreign key violations (#9308)

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* fix(core): handle PermissionDeniedError in provider API key validation

Fixed OpenAI PermissionDeniedError being raised as unknown error when
validating provider API keys. The check_api_key methods in OpenAI-based
providers (OpenAI, OpenRouter, Azure, Together) now properly catch and
re-raise PermissionDeniedError as LLMPermissionDeniedError.

🐛 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix(core): handle Unicode surrogates in OpenAI requests

Sanitize invalid UTF-16 surrogates before sending requests to OpenAI API.
Fixes UnicodeEncodeError when message content contains unpaired surrogates
from corrupted emoji data or malformed Unicode sequences.

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix(core): handle MCP tool schema validation errors gracefully

Catch fastmcp.exceptions.ToolError in execute_mcp_tool endpoint and
convert to LettaInvalidArgumentError (400) instead of letting it
propagate as 500 error. This is an expected user error when tool
arguments don't match the MCP tool's schema.

Fixes Datadog issue 8f2d874a-f8e5-11f0-9b25-da7ad0900000

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix(core): handle ExceptionGroup-wrapped ToolError in MCP executor

When MCP tools fail with validation errors (e.g., missing required parameters),
fastmcp raises ToolError exceptions that may be wrapped in ExceptionGroup by
Python's async TaskGroup. The exception handler now unwraps single-exception
groups before checking if the error should be handled gracefully.

Fixes Calendly API "organization parameter missing" errors being logged to
Datadog instead of returning friendly error messages to users.

🐾 Generated with [Letta Code](https://letta.com)

Co-Authored-By: Letta <noreply@letta.com>

* fix: handle missing agent in create_conversation to prevent foreign key violation

* Update .gitignore

---------

Co-authored-by: Letta <noreply@letta.com>
This commit is contained in:
Kian Jones
2026-02-05 17:28:21 -08:00
committed by Caren Thomas
parent 85ee7ed7b4
commit be60697a62
8 changed files with 67 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
letta/llm_api/openai_client.py
View File

@@ -67,6 +67,33 @@ from letta.settings import model_settings
logger = get_logger(__name__)
def sanitize_unicode_surrogates(obj: Any) -> Any:
"""Recursively sanitize invalid Unicode surrogates in strings within nested data structures.
This fixes UnicodeEncodeError when the OpenAI SDK tries to encode requests containing
unpaired UTF-16 surrogates (e.g., '\ud83c' without its pair) which can occur in corrupted
emoji data or malformed Unicode sequences.
Args:
obj: The object to sanitize (dict, list, str, or other types)
Returns:
The sanitized object with invalid surrogates replaced by the Unicode replacement character
"""
if isinstance(obj, dict):
return {k: sanitize_unicode_surrogates(v) for k, v in obj.items()}
elif isinstance(obj, list):
return [sanitize_unicode_surrogates(item) for item in obj]
elif isinstance(obj, str):
try:
obj.encode("utf-8")
return obj
except UnicodeEncodeError:
return obj.encode("utf-8", errors="replace").decode("utf-8")
else:
return obj
def is_openai_reasoning_model(model: str) -> bool:
"""Utility function to check if the model is a 'reasoner'"""

10
letta/schemas/providers/azure.py
View File

@@ -2,11 +2,11 @@ from collections import defaultdict
from typing import ClassVar, Literal
import httpx
from openai import AsyncAzureOpenAI
from openai import AsyncAzureOpenAI, AuthenticationError, PermissionDeniedError
from pydantic import Field, field_validator
from letta.constants import DEFAULT_EMBEDDING_CHUNK_SIZE, LLM_MAX_CONTEXT_WINDOW
from letta.errors import ErrorCode, LLMAuthenticationError
from letta.errors import ErrorCode, LLMAuthenticationError, LLMPermissionDeniedError
from letta.schemas.embedding_config import EmbeddingConfig
from letta.schemas.enums import ProviderCategory, ProviderType
from letta.schemas.llm_config import LLMConfig
@@ -65,6 +65,9 @@ class AzureProvider(Provider):
try:
models_list = await client.models.list()
except (AuthenticationError, PermissionDeniedError):
# Re-raise auth/permission errors so they're properly handled upstream
raise
except Exception:
return []
@@ -176,5 +179,8 @@ class AzureProvider(Provider):
try:
await self.list_llm_models_async()
except (LLMAuthenticationError, LLMPermissionDeniedError):
# Re-raise specific LLM errors as-is
raise
except Exception as e:
raise LLMAuthenticationError(message=f"Failed to authenticate with Azure: {e}", code=ErrorCode.UNAUTHENTICATED)

6
letta/schemas/providers/openai.py
View File

@@ -1,10 +1,10 @@
from typing import Literal
from openai import AsyncOpenAI, AuthenticationError
from openai import AsyncOpenAI, AuthenticationError, PermissionDeniedError
from pydantic import Field
from letta.constants import DEFAULT_EMBEDDING_CHUNK_SIZE, LLM_MAX_CONTEXT_WINDOW
from letta.errors import ErrorCode, LLMAuthenticationError, LLMError
from letta.errors import ErrorCode, LLMAuthenticationError, LLMError, LLMPermissionDeniedError
from letta.log import get_logger
from letta.schemas.embedding_config import EmbeddingConfig
from letta.schemas.enums import ProviderCategory, ProviderType
@@ -38,6 +38,8 @@ class OpenAIProvider(Provider):
await client.models.list()
except AuthenticationError as e:
raise LLMAuthenticationError(message=f"Failed to authenticate with OpenAI: {e}", code=ErrorCode.UNAUTHENTICATED)
except PermissionDeniedError as e:
raise LLMPermissionDeniedError(message=f"Permission denied by OpenAI: {e}", code=ErrorCode.PERMISSION_DENIED)
except Exception as e:
raise LLMError(message=f"{e}", code=ErrorCode.INTERNAL_SERVER_ERROR)

6
letta/schemas/providers/openrouter.py
View File

@@ -1,9 +1,9 @@
from typing import Literal
from openai import AsyncOpenAI, AuthenticationError
from openai import AsyncOpenAI, AuthenticationError, PermissionDeniedError
from pydantic import Field
from letta.errors import ErrorCode, LLMAuthenticationError, LLMError
from letta.errors import ErrorCode, LLMAuthenticationError, LLMError, LLMPermissionDeniedError
from letta.log import get_logger
from letta.schemas.enums import ProviderCategory, ProviderType
from letta.schemas.llm_config import LLMConfig
@@ -41,6 +41,8 @@ class OpenRouterProvider(OpenAIProvider):
await client.models.list()
except AuthenticationError as e:
raise LLMAuthenticationError(message=f"Failed to authenticate with OpenRouter: {e}", code=ErrorCode.UNAUTHENTICATED)
except PermissionDeniedError as e:
raise LLMPermissionDeniedError(message=f"Permission denied by OpenRouter: {e}", code=ErrorCode.PERMISSION_DENIED)
except Exception as e:
raise LLMError(message=f"{e}", code=ErrorCode.INTERNAL_SERVER_ERROR)

5
letta/schemas/providers/together.py
View File

@@ -11,7 +11,7 @@ logger = get_logger(__name__)
from pydantic import Field
from letta.constants import MIN_CONTEXT_WINDOW
from letta.errors import ErrorCode, LLMAuthenticationError
from letta.errors import ErrorCode, LLMAuthenticationError, LLMPermissionDeniedError
from letta.schemas.embedding_config import EmbeddingConfig
from letta.schemas.enums import ProviderCategory, ProviderType
from letta.schemas.llm_config import LLMConfig
@@ -99,5 +99,8 @@ class TogetherProvider(OpenAIProvider):
try:
await self.list_llm_models_async()
except (LLMAuthenticationError, LLMPermissionDeniedError):
# Re-raise specific LLM errors as-is
raise
except Exception as e:
raise LLMAuthenticationError(message=f"Failed to authenticate with Together: {e}", code=ErrorCode.UNAUTHENTICATED)

6
letta/server/rest_api/routers/v1/tools.py
View File

@@ -3,6 +3,7 @@ from collections.abc import AsyncGenerator
from typing import Any, Dict, List, Literal, Optional, Union
from fastapi import APIRouter, Body, Depends, HTTPException, Query, Request
from fastmcp.exceptions import ToolError as FastMCPToolError
from httpx import ConnectError, HTTPStatusError
from pydantic import BaseModel, Field
from starlette.responses import StreamingResponse
@@ -819,7 +820,10 @@ async def execute_mcp_tool(
await client.connect_to_server()
# Execute the tool
result, success = await client.execute_tool(tool_name, request.args)
try:
result, success = await client.execute_tool(tool_name, request.args)
except FastMCPToolError as e:
raise LettaInvalidArgumentError(f"Invalid arguments for MCP tool '{tool_name}': {str(e)}", argument_name="args")
return {
"result": result,

4
letta/services/conversation_manager.py
View File

@@ -12,7 +12,6 @@ from letta.orm.block import Block as BlockModel
from letta.orm.blocks_conversations import BlocksConversations
from letta.orm.conversation import Conversation as ConversationModel
from letta.orm.conversation_messages import ConversationMessage as ConversationMessageModel
from letta.orm.errors import NoResultFound
from letta.orm.message import Message as MessageModel
from letta.otel.tracing import trace_method
from letta.schemas.agent import AgentState
@@ -22,6 +21,7 @@ from letta.schemas.letta_message import LettaMessage
from letta.schemas.message import Message as PydanticMessage
from letta.schemas.user import User as PydanticUser
from letta.server.db import db_registry
from letta.services.helpers.agent_manager_helper import validate_agent_exists_async
from letta.utils import enforce_types
@@ -48,6 +48,8 @@ class ConversationManager:
The created conversation with isolated_block_ids if any were created
"""
async with db_registry.async_session() as session:
# Validate that the agent exists before creating the conversation
await validate_agent_exists_async(session, agent_id, actor)
conversation = ConversationModel(
agent_id=agent_id,
summary=conversation_create.summary,

16
letta/services/tool_executor/mcp_tool_executor.py
View File

@@ -65,12 +65,20 @@ class ExternalMCPToolExecutor(ToolExecutor):
# Check if this is an expected MCP error (ToolError, McpError)
# These are user-facing errors from the external MCP server (e.g., "No connected account found")
# We handle them gracefully instead of letting them propagate as exceptions
if e.__class__.__name__ in MCP_EXPECTED_ERROR_CLASSES:
logger.info(f"MCP tool '{function_name}' returned expected error: {str(e)}")
# Handle ExceptionGroup wrapping (Python 3.11+ async TaskGroup can wrap exceptions)
exception_to_check = e
if hasattr(e, "exceptions") and e.exceptions:
# If it's an ExceptionGroup with a single wrapped exception, unwrap it
if len(e.exceptions) == 1:
exception_to_check = e.exceptions[0]
if exception_to_check.__class__.__name__ in MCP_EXPECTED_ERROR_CLASSES:
logger.info(f"MCP tool '{function_name}' returned expected error: {str(exception_to_check)}")
error_message = get_friendly_error_msg(
function_name=function_name,
exception_name=e.__class__.__name__,
exception_message=str(e),
exception_name=exception_to_check.__class__.__name__,
exception_message=str(exception_to_check),
)
return ToolExecutionResult(
status="error",