fix: async functions must call async methods (#8612)

Critical fixes:
- llm_client_base.send_llm_request() now calls await self.request_async() instead of self.request()
- Remove unused sync get_openai_embedding() that used sync OpenAI client
- Remove deprecated compile_in_thread_async() from Memory

These were blocking the event loop during LLM requests and embeddings.

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

Co-authored-by: Letta <noreply@letta.com>

letta/llm_api/llm_client_base.py

@@ -67,7 +67,7 @@ class LLMClientBase:
 
         try:
             log_event(name="llm_request_sent", attributes=request_data)
-            response_data = self.request(request_data, llm_config)
+            response_data = await self.request_async(request_data, llm_config)
             if step_id and telemetry_manager:
                 telemetry_manager.create_provider_trace(
                     actor=self.actor,

letta/schemas/memory.py

@@ -318,14 +318,6 @@ class Memory(BaseModel, validate_assignment=True):
             llm_config=llm_config,
         )
 
-    @trace_method
-    async def compile_in_thread_async(self, tool_usage_rules=None, sources=None, max_files_open=None, llm_config=None) -> str:
-        """Deprecated: use compile() instead."""
-        import warnings
-
-        logger.warning("compile_in_thread_async is deprecated; use compile()", stacklevel=2)
-        return self.compile(tool_usage_rules=tool_usage_rules, sources=sources, max_files_open=max_files_open, llm_config=llm_config)
-
     def list_block_labels(self) -> List[str]:
         """Return a list of the block names held inside the memory object"""
         return [block.label for block in self.blocks]

letta/services/passage_manager.py

@@ -1,9 +1,8 @@
 import uuid
 from datetime import datetime, timezone
-from functools import lru_cache
 from typing import Dict, List, Optional
 
-from openai import AsyncOpenAI, OpenAI
+from openai import AsyncOpenAI
 from sqlalchemy import func, select
 from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy.orm import noload
@@ -31,16 +30,6 @@ from letta.utils import enforce_types
 logger = get_logger(__name__)
 
 
-# TODO: Add redis-backed caching for backend
-@lru_cache(maxsize=8192)
-def get_openai_embedding(text: str, model: str, endpoint: str) -> List[float]:
-    from letta.settings import model_settings
-
-    client = OpenAI(api_key=model_settings.openai_api_key, base_url=endpoint, max_retries=0)
-    response = client.embeddings.create(input=text, model=model)
-    return response.data[0].embedding
-
-
 @async_redis_cache(key_func=lambda text, model, endpoint: f"{model}:{endpoint}:{text}")
 async def get_openai_embedding_async(text: str, model: str, endpoint: str) -> list[float]:
     from letta.settings import model_settings