Add a few missing LLMContext type hints

src/pipecat/services/grok/llm.py

@@ -16,6 +16,7 @@ from dataclasses import dataclass
 from loguru import logger
 
 from pipecat.metrics.metrics import LLMTokenUsage
+from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response import (
     LLMAssistantAggregatorParams,
     LLMUserAggregatorParams,
@@ -107,7 +108,7 @@ class GrokLLMService(OpenAILLMService):
         logger.debug(f"Creating Grok client with api {base_url}")
         return super().create_client(api_key, base_url, **kwargs)
 
-    async def _process_context(self, context: OpenAILLMContext):
+    async def _process_context(self, context: OpenAILLMContext | LLMContext):
         """Process a context through the LLM and accumulate token usage metrics.
 
         This method overrides the parent class implementation to handle Grok's

src/pipecat/services/nim/llm.py

@@ -11,6 +11,7 @@ Microservice) API while maintaining compatibility with the OpenAI-style interfac
 """
 
 from pipecat.metrics.metrics import LLMTokenUsage
+from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.openai.llm import OpenAILLMService
 
@@ -47,7 +48,7 @@ class NimLLMService(OpenAILLMService):
         self._has_reported_prompt_tokens = False
         self._is_processing = False
 
-    async def _process_context(self, context: OpenAILLMContext):
+    async def _process_context(self, context: OpenAILLMContext | LLMContext):
         """Process a context through the LLM and accumulate token usage metrics.
 
         This method overrides the parent class implementation to handle NVIDIA's

src/pipecat/services/perplexity/llm.py

@@ -15,6 +15,7 @@ from openai import NOT_GIVEN
 
 from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams
 from pipecat.metrics.metrics import LLMTokenUsage
+from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.openai.llm import OpenAILLMService
 
@@ -84,7 +85,7 @@ class PerplexityLLMService(OpenAILLMService):
 
         return params
 
-    async def _process_context(self, context: OpenAILLMContext):
+    async def _process_context(self, context: OpenAILLMContext | LLMContext):
         """Process a context through the LLM and accumulate token usage metrics.
 
         This method overrides the parent class implementation to handle