Merge pull request #19 from pipecat-ai/pk/use-llm-context-elide-large-values

Use LLMContext instead of removed OpenAILLMContext

Author: aconchillo

CHANGELOG.md

@@ -7,6 +7,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+### Changed
+
+- Switched from removed `OpenAILLMContext` to universal `LLMContext` for
+  Pipecat 1.0 compatibility. Context messages are now serialized using
+  `get_messages(truncate_large_values=True)` for compact output.
+
+- Bumped `pipecat-ai` dependency to `>=1.0.0`.
+
 ### Fixed
 
 - Fixed a Whisker client issue that caused processor blinking to be delayed

pipecat/pyproject.toml

@@ -9,7 +9,7 @@ description = "A real-time debugger for Pipecat"
 license = "BSD-2-Clause"
 license-files = ["LICENSE"]
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 keywords = ["pipecat", "debug", "ai"]
 classifiers = [
     "Development Status :: 5 - Production/Stable",
@@ -23,7 +23,7 @@ dependencies = [
     "aiofiles>=24.1.0,<25",
     "loguru>=0.7.3,<1",
     "msgpack>=1.1.1,<2",
-    "pipecat-ai>=0.0.81",
+    "pipecat-ai>=1.0.0",
     "websockets>=13.1,<16.0",
 ]
 

pipecat/src/pipecat_whisker/observer.py

@@ -37,7 +37,7 @@
 from pipecat.frames.frames import BotSpeakingFrame, Frame, InputAudioRawFrame
 from pipecat.observers.base_observer import BaseObserver, FrameProcessed, FramePushed
 from pipecat.pipeline.base_pipeline import BasePipeline
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.frame_processor import FrameProcessor
 from pydantic import BaseModel
 from websockets import ConnectionClosedOK, serve
@@ -73,8 +73,8 @@ def whisker_obj_serializer(obj: Any) -> Any:
         return {k: whisker_obj_serializer(v) for k, v in obj.items() if v is not None}
     elif isinstance(obj, BaseModel):
         return obj.model_dump(exclude_none=True)
-    elif isinstance(obj, OpenAILLMContext):
-        return obj.get_messages_for_logging()
+    elif isinstance(obj, LLMContext):
+        return [whisker_obj_serializer(m) for m in obj.get_messages(truncate_large_values=True)]
     elif isinstance(obj, (int, float, bool, str)):
         return obj
     else: