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Remove event logger from llama_stack.apis

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Ashwin Bharambe 2025-02-14 06:11:52 -08:00
parent 190b99294d
commit 6c4ddb1012
2 changed files with 0 additions and 236 deletions
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206
llama_stack/apis/agents/event_logger.py
View file

@ -1,206 +0,0 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Optional
from llama_models.llama3.api.tool_utils import ToolUtils
from termcolor import cprint
from llama_stack.apis.agents import AgentTurnResponseEventType, StepType
from llama_stack.apis.common.content_types import ToolCallParseStatus
from llama_stack.apis.inference import ToolResponseMessage
from llama_stack.models.llama.datatypes import ToolPromptFormat
from llama_stack.providers.utils.inference.prompt_adapter import (
interleaved_content_as_str,
)
class LogEvent:
def __init__(
self,
role: Optional[str] = None,
content: str = "",
end: str = "\n",
color="white",
):
self.role = role
self.content = content
self.color = color
self.end = "\n" if end is None else end
def __str__(self):
if self.role is not None:
return f"{self.role}> {self.content}"
else:
return f"{self.content}"
def print(self, flush=True):
cprint(f"{str(self)}", color=self.color, end=self.end, flush=flush)
EventType = AgentTurnResponseEventType
class EventLogger:
async def log(
self,
event_generator,
stream=True,
tool_prompt_format: ToolPromptFormat = ToolPromptFormat.json,
):
previous_event_type = None
previous_step_type = None
async for chunk in event_generator:
if not hasattr(chunk, "event"):
# Need to check for custom tool first
# since it does not produce event but instead
# a Message
if isinstance(chunk, ToolResponseMessage):
yield (
chunk,
LogEvent(role="CustomTool", content=chunk.content, color="grey"),
)
continue
event = chunk.event
event_type = event.payload.event_type
if event_type in {
EventType.turn_start.value,
EventType.turn_complete.value,
}:
# Currently not logging any turn realted info
yield event, None
continue
step_type = event.payload.step_type
# handle safety
if step_type == StepType.shield_call and event_type == EventType.step_complete.value:
violation = event.payload.step_details.violation
if not violation:
yield (
event,
LogEvent(role=step_type, content="No Violation", color="magenta"),
)
else:
yield (
event,
LogEvent(
role=step_type,
content=f"{violation.metadata} {violation.user_message}",
color="red",
),
)
# handle inference
if step_type == StepType.inference:
if stream:
if event_type == EventType.step_start.value:
# TODO: Currently this event is never received
yield (
event,
LogEvent(role=step_type, content="", end="", color="yellow"),
)
elif event_type == EventType.step_progress.value:
# HACK: if previous was not step/event was not inference's step_progress
# this is the first time we are getting model inference response
# aka equivalent to step_start for inference. Hence,
# start with "Model>".
if (
previous_event_type != EventType.step_progress.value
and previous_step_type != StepType.inference
):
yield (
event,
LogEvent(role=step_type, content="", end="", color="yellow"),
)
delta = event.payload.delta
if delta.type == "tool_call":
if delta.parse_status == ToolCallParseStatus.succeeded:
yield (
event,
LogEvent(
role=None,
content=delta.tool_call,
end="",
color="cyan",
),
)
else:
yield (
event,
LogEvent(
role=None,
content=delta.text,
end="",
color="yellow",
),
)
else:
# step_complete
yield event, LogEvent(role=None, content="")
else:
# Not streaming
if event_type == EventType.step_complete.value:
response = event.payload.step_details.model_response
if response.tool_calls:
content = ToolUtils.encode_tool_call(response.tool_calls[0], tool_prompt_format)
else:
content = response.content
yield (
event,
LogEvent(
role=step_type,
content=content,
color="yellow",
),
)
# handle tool_execution
if (
step_type == StepType.tool_execution
and
# Only print tool calls and responses at the step_complete event
event_type == EventType.step_complete.value
):
details = event.payload.step_details
for t in details.tool_calls:
yield (
event,
LogEvent(
role=step_type,
content=f"Tool:{t.tool_name} Args:{t.arguments}",
color="green",
),
)
for r in details.tool_responses:
yield (
event,
LogEvent(
role=step_type,
content=f"Tool:{r.tool_name} Response:{r.content}",
color="green",
),
)
if step_type == StepType.memory_retrieval and event_type == EventType.step_complete.value:
details = event.payload.step_details
inserted_context = interleaved_content_as_str(details.inserted_context)
content = f"fetched {len(inserted_context)} bytes from {details.vector_db_ids}"
yield (
event,
LogEvent(
role=step_type,
content=content,
color="cyan",
),
)
previous_event_type = event_type
previous_step_type = step_type

30
llama_stack/distribution/client.py
View file

@ -186,33 +186,3 @@ def extract_async_iterator_type(type_hint):
inner_args = get_args(arg) inner_args = get_args(arg)
return inner_args[0] return inner_args[0]
return None return None
async def example(model: str = None):
from llama_stack.apis.inference import Inference, UserMessage # noqa: F403
from llama_stack.apis.inference.event_logger import EventLogger
client_class = create_api_client_class(Inference)
client = client_class("http://localhost:5003")
if not model:
model = "Llama3.2-3B-Instruct"
message = UserMessage(content="hello world, write me a 2 sentence poem about the moon")
cprint(f"User>{message.content}", "green")
stream = True
iterator = await client.chat_completion(
model=model,
messages=[message],
stream=stream,
)
async for log in EventLogger().log(iterator):
log.print()
if __name__ == "__main__":
import asyncio
asyncio.run(example())