chore(deps): migrate pipecat integration to pipecat-ai 1.x (clears 4 high-severity alerts)

hindsight-integrations/pipecat/README.md

@@ -49,14 +49,14 @@ See the [Hindsight installation guide](https://hindsight.vectorize.io/developer/
 
 ```
 New turn starts
-  └─ OpenAILLMContextFrame arrives
+  └─ LLMContextFrame arrives
        ├─ Retain previous complete turn (user+assistant) — fire-and-forget
        └─ Recall relevant memories for current user query
             └─ Inject as <hindsight_memories> system message
                  └─ Forward enriched context to LLM
 ```
 
-On each `OpenAILLMContextFrame`:
+On each `LLMContextFrame`:
 
 1. **Retain** — any new complete user+assistant turn pairs are sent to Hindsight asynchronously (non-blocking)
 2. **Recall** — the latest user message is used as the search query; results are injected as a system message before the LLM sees the context

hindsight-integrations/pipecat/examples/basic_pipeline.py

@@ -20,18 +20,19 @@
 import asyncio
 import os
 
+from hindsight_pipecat import HindsightMemoryService
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
-from hindsight_pipecat import HindsightMemoryService
-
 SYSTEM_PROMPT = """You are a friendly voice assistant with long-term memory.
 You remember details from past conversations and use them naturally.
 Keep responses concise — this is a voice interface."""
@@ -67,8 +68,8 @@ async def main() -> None:
         recall_budget="mid",
     )
 
-    context = OpenAILLMContext(messages=[{"role": "system", "content": SYSTEM_PROMPT}])
-    context_aggregator = llm.create_context_aggregator(context)
+    context = LLMContext(messages=[{"role": "system", "content": SYSTEM_PROMPT}])
+    context_aggregator = LLMContextAggregatorPair(context)
 
     pipeline = Pipeline(
         [
@@ -88,7 +89,7 @@ async def main() -> None:
     @transport.event_handler("on_first_participant_joined")
     async def on_first_participant_joined(transport, participant):  # type: ignore[misc]
         await transport.capture_participant_transcription(participant["id"])
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     runner = PipelineRunner()
     await runner.run(task)

hindsight-integrations/pipecat/examples/interactive_chat.py

@@ -50,10 +50,10 @@ def banner(label: str, color: str = CYAN) -> None:
 
 
 def _make_frame(messages: list[dict]) -> MagicMock:
-    """Build a mock OpenAILLMContextFrame (Pipecat's text context carrier)."""
-    from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame
+    """Build a mock LLMContextFrame (Pipecat's text context carrier)."""
+    from pipecat.frames.frames import LLMContextFrame
 
-    frame = MagicMock(spec=OpenAILLMContextFrame)
+    frame = MagicMock(spec=LLMContextFrame)
     ctx = MagicMock()
     ctx.messages = messages
     frame.context = ctx

hindsight-integrations/pipecat/hindsight_pipecat/memory.py

@@ -19,20 +19,10 @@
 import logging
 from typing import Any
 
+from hindsight_client import Hindsight
 from pipecat.frames.frames import Frame, LLMContextFrame
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
-# OpenAILLMContextFrame was deprecated in pipecat 0.0.99; keep the import
-# optional so the integration works with both old and future versions.
-try:
-    from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame as _OpenAILLMContextFrame
-
-    _LEGACY_FRAME_TYPES: tuple[type, ...] = (LLMContextFrame, _OpenAILLMContextFrame)
-except ImportError:  # removed in a future pipecat release
-    _LEGACY_FRAME_TYPES = (LLMContextFrame,)
-
-from hindsight_client import Hindsight
-
 from .config import get_config
 from .errors import HindsightPipecatError
 
@@ -81,7 +71,7 @@ class HindsightMemoryService(FrameProcessor):
             transport.output(),
         ])
 
-    On each ``OpenAILLMContextFrame``:
+    On each ``LLMContextFrame``:
 
     1. Retains any new complete user+assistant pairs from prior turns
        (non-blocking, fire-and-forget).
@@ -131,7 +121,7 @@ def __init__(
     async def process_frame(self, frame: Frame, direction: FrameDirection) -> None:
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, _LEGACY_FRAME_TYPES) and direction == FrameDirection.DOWNSTREAM:
+        if isinstance(frame, LLMContextFrame) and direction == FrameDirection.DOWNSTREAM:
             await self._handle_context_frame(frame)
         else:
             await self.push_frame(frame, direction)

hindsight-integrations/pipecat/pyproject.toml

@@ -2,7 +2,7 @@
 name = "hindsight-pipecat"
 version = "0.1.1"
 description = "Pipecat integration for Hindsight - persistent memory for voice AI pipelines"
-requires-python = ">=3.10"
+requires-python = ">=3.11"
 license = { text = "MIT" }
 authors = [
     { name = "Vectorize", email = "support@vectorize.io" }
@@ -20,14 +20,13 @@ classifiers = [
     "Intended Audience :: Developers",
     "License :: OSI Approved :: MIT License",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
     "Topic :: Scientific/Engineering :: Artificial Intelligence",
 ]
 
 dependencies = [
-    "pipecat-ai>=0.0.100,<1.0",  # 1.0+ restructured modules; needs migration
+    "pipecat-ai>=1.4.0,<2.0",  # 1.x universal LLMContext; 1.4.0 clears the file-read CVE advisories
     "hindsight-client>=0.4.0",
 ]
 

hindsight-integrations/pipecat/tests/test_live_integration.py

@@ -51,10 +51,10 @@ def _http_get(path: str) -> dict:
 
 
 def _make_frame(messages: list[dict[str, Any]]) -> MagicMock:
-    """Build a mock OpenAILLMContextFrame that the processor will recognize."""
-    from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame
+    """Build a mock LLMContextFrame that the processor will recognize."""
+    from pipecat.frames.frames import LLMContextFrame
 
-    frame = MagicMock(spec=OpenAILLMContextFrame)
+    frame = MagicMock(spec=LLMContextFrame)
     ctx = MagicMock()
     ctx.messages = messages
     frame.context = ctx

hindsight-integrations/pipecat/tests/test_memory.py

@@ -59,10 +59,10 @@ def _make_context(messages: list[dict]) -> MagicMock:
 
 
 def _make_frame(messages: list[dict]) -> MagicMock:
-    """Return a mock OpenAILLMContextFrame."""
-    from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame  # noqa: F401
+    """Return a mock LLMContextFrame."""
+    from pipecat.frames.frames import LLMContextFrame
 
-    frame = MagicMock(spec=OpenAILLMContextFrame)
+    frame = MagicMock(spec=LLMContextFrame)
     frame.context = _make_context(messages)
     return frame
 
@@ -303,3 +303,47 @@ async def test_multimodal_user_message_text_extracted(self) -> None:
 
         call_args = client.arecall.call_args
         assert call_args.kwargs["query"] == "voice transcription here"
+
+
+# ---------------------------------------------------------------------------
+# Real pipecat LLMContext contract
+#
+# The other tests mock the frame/context. These exercise the actual pipecat
+# 1.x universal `LLMContext`, pinning the API the integration relies on:
+# `LLMContextFrame.context.messages` is a live list of OpenAI-format dicts that
+# the service mutates in place. A future pipecat change to that contract would
+# fail here rather than silently breaking memory injection at runtime.
+# ---------------------------------------------------------------------------
+
+
+class TestRealLLMContext:
+    def _real_frame(self, messages: list[dict]) -> object:
+        from pipecat.frames.frames import LLMContextFrame
+        from pipecat.processors.aggregators.llm_context import LLMContext
+
+        return LLMContextFrame(context=LLMContext(messages=messages))
+
+    async def test_service_recognizes_real_context_frame(self) -> None:
+        from pipecat.processors.frame_processor import FrameDirection
+
+        client = _mock_client(recall_texts=["User prefers dark mode"])
+        frame = self._real_frame([{"role": "user", "content": "Set up my editor"}])
+
+        svc = HindsightMemoryService(bank_id="test", client=client)
+        with patch.object(svc, "push_frame", new_callable=AsyncMock):
+            await svc.process_frame(frame, FrameDirection.DOWNSTREAM)
+
+        client.arecall.assert_called_once()
+
+    async def test_memory_injected_into_real_context(self) -> None:
+        client = _mock_client(recall_texts=["User prefers dark mode"])
+        frame = self._real_frame([{"role": "user", "content": "Set up my editor"}])
+
+        svc = HindsightMemoryService(bank_id="test", client=client)
+        with patch.object(svc, "push_frame", new_callable=AsyncMock):
+            await svc._handle_context_frame(frame)
+
+        # Mutation must persist on the real context object the LLM will read.
+        sys_msgs = [m for m in frame.context.messages if m.get("role") == "system"]
+        assert any(_MEMORY_MARKER in m.get("content", "") for m in sys_msgs)
+        assert any("dark mode" in m.get("content", "") for m in sys_msgs)