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jarvis-v3/_debug_out2.txt
T
bruno 09984d49fa feat: JARVIS v3 Phase 1 — WebSocket relay vers Hermes A.L.E.X.A.
- Serveur WebSocket direct avec websockets 16.0
- Interface HTML/CSS/JS dark theme avec chat
- Relay vers API Hermes sur port 8642
- Historique de conversation (20 messages)
- Clé API via Infisical
- Testé et fonctionnel sur openclaw1.dev.home:7081
2026-06-19 22:46:32 -04:00

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2026-06-19 17:09:30.215 | INFO | pipecat:<module>:28 - ᓚᘏᗢ Pipecat 1.4.0 (Python 3.13.5 (main, May 5 2026, 21:05:52) [GCC 14.2.0]) ᓚᘏᗢ
=== LLMContextFrame ===
@dataclass
class LLMContextFrame(Frame):
"""Frame containing a universal LLM context.
Used as a signal to LLM services to ingest the provided context and
generate a response based on it.
Parameters:
context: The LLM context containing messages, tools, and configuration.
"""
context: LLMContext
=== LLMMessagesAppendFrame ===
@dataclass
class LLMMessagesAppendFrame(DataFrame):
"""Frame containing LLM messages to append to current context.
A frame containing a list of LLM messages that need to be added to the
current context.
Parameters:
messages: List of context messages to append.
run_llm: Whether the context update should be sent to the LLM.
"""
messages: list[LLMContextMessage]
run_llm: bool | None = None
=== LLMMessagesUpdateFrame ===
@dataclass
class LLMMessagesUpdateFrame(DataFrame):
"""Frame containing LLM messages to replace current context.
A frame containing a list of new LLM messages to replace the current
context LLM messages.
Parameters:
messages: List of context messages to replace current context.
run_llm: Whether the context update should be sent to the LLM.
"""
messages: list[LLMContextMessage]
run_llm: bool | None = None
=== LLMContext.__init__ ===
def __init__(
self,
messages: list[LLMContextMessage] | None = None,
tools: ToolsSchema | list[FunctionSchema | DirectFunction] | NotGiven = NOT_GIVEN,
tool_choice: LLMContextToolChoice | NotGiven = NOT_GIVEN,
):
"""Initialize the LLM context.
Args:
messages: Initial list of conversation messages.
tools: Available tools for the LLM to use. May be a ``ToolsSchema``
or a plain list of direct functions and/or ``FunctionSchema``
objects (normalized to a ``ToolsSchema`` internally). Any tool
that carries a handler — a direct function, or a
``FunctionSchema`` with its ``handler`` set — is registered with
the LLM service automatically, so no separate
``register_function`` call is needed.
tool_choice: Tool selection strategy for the LLM.
"""
self._messages: list[LLMContextMessage] = messages if messages else []
self._tools: ToolsSchema | NotGiven = LLMContext._normalize_and_validate_tools(tools)
self._tool_choice: LLMContextToolChoice | NotGiven = tool_choice