forked from phoenix-oss/llama-stack-mirror
API Updates (#73)
* API Keys passed from Client instead of distro configuration * delete distribution registry * Rename the "package" word away * Introduce a "Router" layer for providers Some providers need to be factorized and considered as thin routing layers on top of other providers. Consider two examples: - The inference API should be a routing layer over inference providers, routed using the "model" key - The memory banks API is another instance where various memory bank types will be provided by independent providers (e.g., a vector store is served by Chroma while a keyvalue memory can be served by Redis or PGVector) This commit introduces a generalized routing layer for this purpose. * update `apis_to_serve` * llama_toolchain -> llama_stack * Codemod from llama_toolchain -> llama_stack - added providers/registry - cleaned up api/ subdirectories and moved impls away - restructured api/api.py - from llama_stack.apis.<api> import foo should work now - update imports to do llama_stack.apis.<api> - update many other imports - added __init__, fixed some registry imports - updated registry imports - create_agentic_system -> create_agent - AgenticSystem -> Agent * Moved some stuff out of common/; re-generated OpenAPI spec * llama-toolchain -> llama-stack (hyphens) * add control plane API * add redis adapter + sqlite provider * move core -> distribution * Some more toolchain -> stack changes * small naming shenanigans * Removing custom tool and agent utilities and moving them client side * Move control plane to distribution server for now * Remove control plane from API list * no codeshield dependency randomly plzzzzz * Add "fire" as a dependency * add back event loggers * stack configure fixes * use brave instead of bing in the example client * add init file so it gets packaged * add init files so it gets packaged * Update MANIFEST * bug fix --------- Co-authored-by: Hardik Shah <hjshah@fb.com> Co-authored-by: Xi Yan <xiyan@meta.com> Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
This commit is contained in:
Ashwin Bharambe
GitHub
parent
f294eac5f5
commit
9487ad8294
213 changed files with 1725 additions and 1204 deletions
245
llama_stack/providers/adapters/inference/fireworks/fireworks.py
Normal file
245
llama_stack/providers/adapters/inference/fireworks/fireworks.py
Normal file
|
|
@ -0,0 +1,245 @@
|
|||
# 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 AsyncGenerator
|
||||
|
||||
from llama_models.llama3.api.chat_format import ChatFormat
|
||||
|
||||
from llama_models.llama3.api.datatypes import Message, StopReason
|
||||
from llama_models.llama3.api.tokenizer import Tokenizer
|
||||
from llama_models.sku_list import resolve_model
|
||||
|
||||
from fireworks.client import Fireworks
|
||||
|
||||
from llama_stack.apis.inference import * # noqa: F403
|
||||
from llama_stack.providers.utils.inference.prepare_messages import prepare_messages
|
||||
|
||||
from .config import FireworksImplConfig
|
||||
|
||||
FIREWORKS_SUPPORTED_MODELS = {
|
||||
"Meta-Llama3.1-8B-Instruct": "fireworks/llama-v3p1-8b-instruct",
|
||||
"Meta-Llama3.1-70B-Instruct": "fireworks/llama-v3p1-70b-instruct",
|
||||
"Meta-Llama3.1-405B-Instruct": "fireworks/llama-v3p1-405b-instruct",
|
||||
}
|
||||
|
||||
|
||||
class FireworksInferenceAdapter(Inference):
|
||||
def __init__(self, config: FireworksImplConfig) -> None:
|
||||
self.config = config
|
||||
tokenizer = Tokenizer.get_instance()
|
||||
self.formatter = ChatFormat(tokenizer)
|
||||
|
||||
@property
|
||||
def client(self) -> Fireworks:
|
||||
return Fireworks(api_key=self.config.api_key)
|
||||
|
||||
async def initialize(self) -> None:
|
||||
return
|
||||
|
||||
async def shutdown(self) -> None:
|
||||
pass
|
||||
|
||||
async def completion(self, request: CompletionRequest) -> AsyncGenerator:
|
||||
raise NotImplementedError()
|
||||
|
||||
def _messages_to_fireworks_messages(self, messages: list[Message]) -> list:
|
||||
fireworks_messages = []
|
||||
for message in messages:
|
||||
if message.role == "ipython":
|
||||
role = "tool"
|
||||
else:
|
||||
role = message.role
|
||||
fireworks_messages.append({"role": role, "content": message.content})
|
||||
|
||||
return fireworks_messages
|
||||
|
||||
def resolve_fireworks_model(self, model_name: str) -> str:
|
||||
model = resolve_model(model_name)
|
||||
assert (
|
||||
model is not None
|
||||
and model.descriptor(shorten_default_variant=True)
|
||||
in FIREWORKS_SUPPORTED_MODELS
|
||||
), f"Unsupported model: {model_name}, use one of the supported models: {','.join(FIREWORKS_SUPPORTED_MODELS.keys())}"
|
||||
|
||||
return FIREWORKS_SUPPORTED_MODELS.get(
|
||||
model.descriptor(shorten_default_variant=True)
|
||||
)
|
||||
|
||||
def get_fireworks_chat_options(self, request: ChatCompletionRequest) -> dict:
|
||||
options = {}
|
||||
if request.sampling_params is not None:
|
||||
for attr in {"temperature", "top_p", "top_k", "max_tokens"}:
|
||||
if getattr(request.sampling_params, attr):
|
||||
options[attr] = getattr(request.sampling_params, attr)
|
||||
|
||||
return options
|
||||
|
||||
async def chat_completion(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Message],
|
||||
sampling_params: Optional[SamplingParams] = SamplingParams(),
|
||||
tools: Optional[List[ToolDefinition]] = None,
|
||||
tool_choice: Optional[ToolChoice] = ToolChoice.auto,
|
||||
tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
|
||||
stream: Optional[bool] = False,
|
||||
logprobs: Optional[LogProbConfig] = None,
|
||||
) -> AsyncGenerator:
|
||||
request = ChatCompletionRequest(
|
||||
model=model,
|
||||
messages=messages,
|
||||
sampling_params=sampling_params,
|
||||
tools=tools or [],
|
||||
tool_choice=tool_choice,
|
||||
tool_prompt_format=tool_prompt_format,
|
||||
stream=stream,
|
||||
logprobs=logprobs,
|
||||
)
|
||||
|
||||
messages = prepare_messages(request)
|
||||
|
||||
# accumulate sampling params and other options to pass to fireworks
|
||||
options = self.get_fireworks_chat_options(request)
|
||||
fireworks_model = self.resolve_fireworks_model(request.model)
|
||||
|
||||
if not request.stream:
|
||||
r = await self.client.chat.completions.acreate(
|
||||
model=fireworks_model,
|
||||
messages=self._messages_to_fireworks_messages(messages),
|
||||
stream=False,
|
||||
**options,
|
||||
)
|
||||
stop_reason = None
|
||||
if r.choices[0].finish_reason:
|
||||
if r.choices[0].finish_reason == "stop":
|
||||
stop_reason = StopReason.end_of_turn
|
||||
elif r.choices[0].finish_reason == "length":
|
||||
stop_reason = StopReason.out_of_tokens
|
||||
|
||||
completion_message = self.formatter.decode_assistant_message_from_content(
|
||||
r.choices[0].message.content, stop_reason
|
||||
)
|
||||
|
||||
yield ChatCompletionResponse(
|
||||
completion_message=completion_message,
|
||||
logprobs=None,
|
||||
)
|
||||
else:
|
||||
yield ChatCompletionResponseStreamChunk(
|
||||
event=ChatCompletionResponseEvent(
|
||||
event_type=ChatCompletionResponseEventType.start,
|
||||
delta="",
|
||||
)
|
||||
)
|
||||
|
||||
buffer = ""
|
||||
ipython = False
|
||||
stop_reason = None
|
||||
|
||||
async for chunk in self.client.chat.completions.acreate(
|
||||
model=fireworks_model,
|
||||
messages=self._messages_to_fireworks_messages(messages),
|
||||
stream=True,
|
||||
**options,
|
||||
):
|
||||
if chunk.choices[0].finish_reason:
|
||||
if stop_reason is None and chunk.choices[0].finish_reason == "stop":
|
||||
stop_reason = StopReason.end_of_turn
|
||||
elif (
|
||||
stop_reason is None
|
||||
and chunk.choices[0].finish_reason == "length"
|
||||
):
|
||||
stop_reason = StopReason.out_of_tokens
|
||||
break
|
||||
|
||||
text = chunk.choices[0].delta.content
|
||||
if text is None:
|
||||
continue
|
||||
|
||||
# check if its a tool call ( aka starts with <|python_tag|> )
|
||||
if not ipython and text.startswith("<|python_tag|>"):
|
||||
ipython = True
|
||||
yield ChatCompletionResponseStreamChunk(
|
||||
event=ChatCompletionResponseEvent(
|
||||
event_type=ChatCompletionResponseEventType.progress,
|
||||
delta=ToolCallDelta(
|
||||
content="",
|
||||
parse_status=ToolCallParseStatus.started,
|
||||
),
|
||||
)
|
||||
)
|
||||
buffer += text
|
||||
continue
|
||||
|
||||
if ipython:
|
||||
if text == "<|eot_id|>":
|
||||
stop_reason = StopReason.end_of_turn
|
||||
text = ""
|
||||
continue
|
||||
elif text == "<|eom_id|>":
|
||||
stop_reason = StopReason.end_of_message
|
||||
text = ""
|
||||
continue
|
||||
|
||||
buffer += text
|
||||
delta = ToolCallDelta(
|
||||
content=text,
|
||||
parse_status=ToolCallParseStatus.in_progress,
|
||||
)
|
||||
|
||||
yield ChatCompletionResponseStreamChunk(
|
||||
event=ChatCompletionResponseEvent(
|
||||
event_type=ChatCompletionResponseEventType.progress,
|
||||
delta=delta,
|
||||
stop_reason=stop_reason,
|
||||
)
|
||||
)
|
||||
else:
|
||||
buffer += text
|
||||
yield ChatCompletionResponseStreamChunk(
|
||||
event=ChatCompletionResponseEvent(
|
||||
event_type=ChatCompletionResponseEventType.progress,
|
||||
delta=text,
|
||||
stop_reason=stop_reason,
|
||||
)
|
||||
)
|
||||
|
||||
# parse tool calls and report errors
|
||||
message = self.formatter.decode_assistant_message_from_content(
|
||||
buffer, stop_reason
|
||||
)
|
||||
parsed_tool_calls = len(message.tool_calls) > 0
|
||||
if ipython and not parsed_tool_calls:
|
||||
yield ChatCompletionResponseStreamChunk(
|
||||
event=ChatCompletionResponseEvent(
|
||||
event_type=ChatCompletionResponseEventType.progress,
|
||||
delta=ToolCallDelta(
|
||||
content="",
|
||||
parse_status=ToolCallParseStatus.failure,
|
||||
),
|
||||
stop_reason=stop_reason,
|
||||
)
|
||||
)
|
||||
|
||||
for tool_call in message.tool_calls:
|
||||
yield ChatCompletionResponseStreamChunk(
|
||||
event=ChatCompletionResponseEvent(
|
||||
event_type=ChatCompletionResponseEventType.progress,
|
||||
delta=ToolCallDelta(
|
||||
content=tool_call,
|
||||
parse_status=ToolCallParseStatus.success,
|
||||
),
|
||||
stop_reason=stop_reason,
|
||||
)
|
||||
)
|
||||
|
||||
yield ChatCompletionResponseStreamChunk(
|
||||
event=ChatCompletionResponseEvent(
|
||||
event_type=ChatCompletionResponseEventType.complete,
|
||||
delta="",
|
||||
stop_reason=stop_reason,
|
||||
)
|
||||
)
|
||||
Loading…
Add table
Add a link
Reference in a new issue