llama-stack-mirror/llama_toolchain/agentic_system/client.py
Ashwin Bharambe e830814399
Introduce Llama stack distributions (#22)
* Add distribution CLI scaffolding

* More progress towards `llama distribution install`

* getting closer to a distro definition, distro install + configure works

* Distribution server now functioning

* read existing configuration, save enums properly

* Remove inference uvicorn server entrypoint and llama inference CLI command

* updated dependency and client model name

* Improved exception handling

* local imports for faster cli

* undo a typo, add a passthrough distribution

* implement full-passthrough in the server

* add safety adapters, configuration handling, server + clients

* cleanup, moving stuff to common, nuke utils

* Add a Path() wrapper at the earliest place

* fixes

* Bring agentic system api to toolchain

Add adapter dependencies and resolve adapters using a topological sort

* refactor to reduce size of `agentic_system`

* move straggler files and fix some important existing bugs

* ApiSurface -> Api

* refactor a method out

* Adapter -> Provider

* Make each inference provider into its own subdirectory

* installation fixes

* Rename Distribution -> DistributionSpec, simplify RemoteProviders

* dict key instead of attr

* update inference config to take model and not model_dir

* Fix passthrough streaming, send headers properly not part of body :facepalm

* update safety to use model sku ids and not model dirs

* Update cli_reference.md

* minor fixes

* add DistributionConfig, fix a bug in model download

* Make install + start scripts do proper configuration automatically

* Update CLI_reference

* Nuke fp8_requirements, fold fbgemm into common requirements

* Update README, add newline between API surface configurations

* Refactor download functionality out of the Command so can be reused

* Add `llama model download` alias for `llama download`

* Show message about checksum file so users can check themselves

* Simpler intro statements

* get ollama working

* Reduce a bunch of dependencies from toolchain

Some improvements to the distribution install script

* Avoid using `conda run` since it buffers everything

* update dependencies and rely on LLAMA_TOOLCHAIN_DIR for dev purposes

* add validation for configuration input

* resort imports

* make optional subclasses default to yes for configuration

* Remove additional_pip_packages; move deps to providers

* for inline make 8b model the default

* Add scripts to MANIFEST

* allow installing from test.pypi.org

* Fix #2 to help with testing packages

* Must install llama-models at that same version first

* fix PIP_ARGS

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Hardik Shah <hjshah@meta.com>
2024-08-08 13:38:41 -07:00

130 lines
4.1 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.
import asyncio
import json
from typing import AsyncGenerator
import fire
import httpx
from llama_models.llama3_1.api.datatypes import BuiltinTool, SamplingParams
from .api import (
AgenticSystem,
AgenticSystemCreateRequest,
AgenticSystemCreateResponse,
AgenticSystemInstanceConfig,
AgenticSystemSessionCreateRequest,
AgenticSystemSessionCreateResponse,
AgenticSystemToolDefinition,
AgenticSystemTurnCreateRequest,
AgenticSystemTurnResponseStreamChunk,
)
async def get_client_impl(base_url: str):
return AgenticSystemClient(base_url)
class AgenticSystemClient(AgenticSystem):
def __init__(self, base_url: str):
self.base_url = base_url
async def create_agentic_system(
self, request: AgenticSystemCreateRequest
) -> AgenticSystemCreateResponse:
async with httpx.AsyncClient() as client:
response = await client.post(
f"{self.base_url}/agentic_system/create",
data=request.json(),
headers={"Content-Type": "application/json"},
)
response.raise_for_status()
return AgenticSystemCreateResponse(**response.json())
async def create_agentic_system_session(
self,
request: AgenticSystemSessionCreateRequest,
) -> AgenticSystemSessionCreateResponse:
async with httpx.AsyncClient() as client:
response = await client.post(
f"{self.base_url}/agentic_system/session/create",
data=request.json(),
headers={"Content-Type": "application/json"},
)
response.raise_for_status()
return AgenticSystemSessionCreateResponse(**response.json())
async def create_agentic_system_turn(
self,
request: AgenticSystemTurnCreateRequest,
) -> AsyncGenerator:
async with httpx.AsyncClient() as client:
async with client.stream(
"POST",
f"{self.base_url}/agentic_system/turn/create",
data=request.json(),
headers={"Content-Type": "application/json"},
timeout=20,
) as response:
async for line in response.aiter_lines():
if line.startswith("data:"):
data = line[len("data: ") :]
try:
yield AgenticSystemTurnResponseStreamChunk(
**json.loads(data)
)
except Exception as e:
print(data)
print(f"Error with parsing or validation: {e}")
async def run_main(host: str, port: int):
# client to test remote impl of agentic system
api = await AgenticSystemClient(f"http://{host}:{port}")
tool_definitions = [
AgenticSystemToolDefinition(
tool_name=BuiltinTool.brave_search,
),
AgenticSystemToolDefinition(
tool_name=BuiltinTool.wolfram_alpha,
),
AgenticSystemToolDefinition(
tool_name=BuiltinTool.photogen,
),
AgenticSystemToolDefinition(
tool_name=BuiltinTool.code_interpreter,
),
]
create_request = AgenticSystemCreateRequest(
model="Meta-Llama3.1-8B-Instruct",
instance_config=AgenticSystemInstanceConfig(
instructions="You are a helpful assistant",
sampling_params=SamplingParams(),
available_tools=tool_definitions,
input_shields=[],
output_shields=[],
quantization_config=None,
debug_prefix_messages=[],
),
)
create_response = await api.create_agentic_system(create_request)
print(create_response)
# TODO: Add chat session / turn apis to test e2e
def main(host: str, port: int):
asyncio.run(run_main(host, port))
if __name__ == "__main__":
fire.Fire(main)