mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-06-27 18:50:41 +00:00
* add tools to chat completion request * use templates for generating system prompts * Moved ToolPromptFormat and jinja templates to llama_models.llama3.api * <WIP> memory changes - inlined AgenticSystemInstanceConfig so API feels more ergonomic - renamed it to AgentConfig, AgentInstance -> Agent - added a MemoryConfig and `memory` parameter - added `attachments` to input and `output_attachments` to the response - some naming changes * InterleavedTextAttachment -> InterleavedTextMedia, introduce memory tool * flesh out memory banks API * agentic loop has a RAG implementation * faiss provider implementation * memory client works * re-work tool definitions, fix FastAPI issues, fix tool regressions * fix agentic_system utils * basic RAG seems to work * small bug fixes for inline attachments * Refactor custom tool execution utilities * Bug fix, show memory retrieval steps in EventLogger * No need for api_key for Remote providers * add special unicode character ↵ to showcase newlines in model prompt templates * remove api.endpoints imports * combine datatypes.py and endpoints.py into api.py * Attachment / add TTL api * split batch_inference from inference * minor import fixes * use a single impl for ChatFormat.decode_assistant_mesage * use interleaved_text_media_as_str() utilityt * Fix api.datatypes imports * Add blobfile for tiktoken * Add ToolPromptFormat to ChatFormat.encode_message so that tools are encoded properly * templates take optional --format={json,function_tag} * Rag Updates * Add `api build` subcommand -- WIP * fix * build + run image seems to work * <WIP> adapters * bunch more work to make adapters work * api build works for conda now * ollama remote adapter works * Several smaller fixes to make adapters work Also, reorganized the pattern of __init__ inside providers so configuration can stay lightweight * llama distribution -> llama stack + containers (WIP) * All the new CLI for api + stack work * Make Fireworks and Together into the Adapter format * Some quick fixes to the CLI behavior to make it consistent * Updated README phew * Update cli_reference.md * llama_toolchain/distribution -> llama_toolchain/core * Add termcolor * update paths * Add a log just for consistency * chmod +x scripts * Fix api dependencies not getting added to configuration * missing import lol * Delete utils.py; move to agentic system * Support downloading of URLs for attachments for code interpreter * Simplify and generalize `llama api build` yay * Update `llama stack configure` to be very simple also * Fix stack start * Allow building an "adhoc" distribution * Remote `llama api []` subcommands * Fixes to llama stack commands and update docs * Update documentation again and add error messages to llama stack start * llama stack start -> llama stack run * Change name of build for less confusion * Add pyopenapi fork to the repository, update RFC assets * Remove conflicting annotation * Added a "--raw" option for model template printing --------- Co-authored-by: Hardik Shah <hjshah@fb.com> Co-authored-by: Ashwin Bharambe <ashwin@meta.com> Co-authored-by: Dalton Flanagan <6599399+dltn@users.noreply.github.com>
187 lines
7.1 KiB
Python
187 lines
7.1 KiB
Python
# 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.datatypes import * # noqa: F403
|
|
from llama_models.llama3.api.tool_utils import ToolUtils
|
|
|
|
from termcolor import cprint
|
|
|
|
from llama_toolchain.agentic_system.api import (
|
|
AgenticSystemTurnResponseEventType,
|
|
StepType,
|
|
)
|
|
|
|
|
|
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 = AgenticSystemTurnResponseEventType
|
|
|
|
|
|
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
|
|
):
|
|
response = event.payload.step_details.response
|
|
if not response.is_violation:
|
|
yield event, LogEvent(
|
|
role=step_type, content="No Violation", color="magenta"
|
|
)
|
|
else:
|
|
yield event, LogEvent(
|
|
role=step_type,
|
|
content=f"{response.violation_type} {response.violation_return_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"
|
|
)
|
|
|
|
if event.payload.tool_call_delta:
|
|
if isinstance(event.payload.tool_call_delta.content, str):
|
|
yield event, LogEvent(
|
|
role=None,
|
|
content=event.payload.tool_call_delta.content,
|
|
end="",
|
|
color="cyan",
|
|
)
|
|
else:
|
|
yield event, LogEvent(
|
|
role=None,
|
|
content=event.payload.model_response_text_delta,
|
|
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
|
|
content = interleaved_text_media_as_str(details.inserted_context)
|
|
content = content[:200] + "..." if len(content) > 200 else content
|
|
|
|
yield event, LogEvent(
|
|
role=step_type,
|
|
content=f"Retrieved context from banks: {details.memory_bank_ids}.\n====\n{content}\n>",
|
|
color="cyan",
|
|
)
|
|
|
|
preivous_event_type = event_type
|
|
previous_step_type = step_type
|