From 89665dfbdbc8a55accc04e9a1f9e1e8c630d811f Mon Sep 17 00:00:00 2001 From: "OKH@nd" Date: Fri, 8 Nov 2024 09:29:14 +0800 Subject: [PATCH 01/26] add inference mlx run local model in single node --- exo/inference/mlx/sharded_inference_engine.py | 11 ++++-- exo/inference/tokenizers.py | 5 +++ exo/main.py | 35 +++++++++++++++---- 3 files changed, 42 insertions(+), 9 deletions(-) diff --git a/exo/inference/mlx/sharded_inference_engine.py b/exo/inference/mlx/sharded_inference_engine.py index 943b58610..46a2652d2 100644 --- a/exo/inference/mlx/sharded_inference_engine.py +++ b/exo/inference/mlx/sharded_inference_engine.py @@ -9,7 +9,9 @@ import asyncio from concurrent.futures import ThreadPoolExecutor from functools import partial - +# OKHand.zy add library +import os +from pathlib import Path class MLXDynamicShardInferenceEngine(InferenceEngine): def __init__(self, shard_downloader: ShardDownloader): @@ -40,8 +42,11 @@ async def infer_tensor(self, request_id: str, shard: Shard, input_data: np.ndarr async def ensure_shard(self, shard: Shard): if self.shard == shard: return - - model_path = await self.shard_downloader.ensure_shard(shard) + + if os.path.isdir(shard.model_id): # if local model + model_path = Path(shard.model_id) + else: + model_path = await self.shard_downloader.ensure_shard(shard) if self.shard != shard: loop = asyncio.get_running_loop() diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index 0b8ffa7e6..929134a68 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -22,7 +22,12 @@ def decode(self, tokens): async def resolve_tokenizer(model_id: str): if model_id == "dummy": return DummyTokenizer() + local_path = await get_local_snapshot_dir(model_id) + if not local_path: # local model path + local_path = model_id.rstrip('/') + model_id = 'local/'+str(local_path.split('/')[-1]) + if DEBUG >= 2: print(f"Checking if local path exists to load tokenizer from local {local_path=}") try: if local_path and await aios.path.exists(local_path): diff --git a/exo/main.py b/exo/main.py index a51c38b98..487a952fb 100644 --- a/exo/main.py +++ b/exo/main.py @@ -25,6 +25,9 @@ from exo.orchestration.node import Node from exo.models import model_base_shards from exo.viz.topology_viz import TopologyViz +# OKHand.zy add library +import os +import json # parse args parser = argparse.ArgumentParser(description="Initialize GRPC Discovery") @@ -133,14 +136,18 @@ def preemptively_start_download(request_id: str, opaque_status: str): status = json.loads(opaque_status) if status.get("type") == "node_status" and status.get("status") == "start_process_prompt": current_shard = node.get_current_shard(Shard.from_dict(status.get("shard"))) - if DEBUG >= 2: print(f"Preemptively starting download for {current_shard}") - asyncio.create_task(shard_downloader.ensure_shard(current_shard)) + if os.path.isdir(current_shard.model_id): + # TODO: open ftp to share download model + pass + else: + if DEBUG >= 2: print(f"Preemptively starting download for {current_shard}") + asyncio.create_task(shard_downloader.ensure_shard(current_shard)) + except Exception as e: if DEBUG >= 2: print(f"Failed to preemptively start download: {e}") traceback.print_exc() - node.on_opaque_status.register("start_download").on_next(preemptively_start_download) if args.prometheus_client_port: @@ -175,11 +182,27 @@ async def shutdown(signal, loop): async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name: str, prompt: str): - shard = model_base_shards.get(model_name, {}).get(inference_engine.__class__.__name__) - if not shard: + if model_base_shards.get(model_name) : + shard = model_base_shards.get(model_name, {}).get(inference_engine.__class__.__name__) + if not shard: + print(f"Error: Unsupported model '{model_name}' for inference engine {inference_engine.__class__.__name__}") + return + tokenizer = await resolve_tokenizer(shard.model_id) + elif os.path.isdir(model_name): + # local model + # local model shard + model_path = model_name.rstrip('/') + model_name = model_path.split('/')[-1] + if os.path.isfile(model_path+'/config.json'): + with open(model_path+'/config.json', 'r') as file: + config = json.load(file) + config_n_layers = config['num_hidden_layers'] + shard = Shard(model_id=model_path, start_layer=0, end_layer=0, n_layers=config_n_layers) + tokenizer = await resolve_tokenizer(model_path) + else: print(f"Error: Unsupported model '{model_name}' for inference engine {inference_engine.__class__.__name__}") return - tokenizer = await resolve_tokenizer(shard.model_id) + request_id = str(uuid.uuid4()) callback_id = f"cli-wait-response-{request_id}" callback = node.on_token.register(callback_id) From 0b87eb9fbce386c1107280338484b07886760e06 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Fri, 15 Nov 2024 10:41:30 +0800 Subject: [PATCH 02/26] filter merge erro --- exo/main.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/exo/main.py b/exo/main.py index 4b1787224..1eea7284c 100644 --- a/exo/main.py +++ b/exo/main.py @@ -23,7 +23,7 @@ from exo.inference.dummy_inference_engine import DummyInferenceEngine from exo.inference.tokenizers import resolve_tokenizer from exo.orchestration.node import Node -from exo.models import build_base_shard, get_repo +from exo.models import model_cards, build_base_shard, get_repo from exo.viz.topology_viz import TopologyViz # OKHand.zy add library import os @@ -182,7 +182,7 @@ async def shutdown(signal, loop): async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name: str, prompt: str): - if model_base_shards.get(model_name) : + if model_cards.get(model_name): inference_class = inference_engine.__class__.__name__ shard = build_base_shard(model_name, inference_class) if not shard: From e2f072301b13ab48a0defdfa53ecd39ade5fcb99 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Fri, 15 Nov 2024 16:42:42 +0800 Subject: [PATCH 03/26] filter f1eec9f model change --- exo/api/chatgpt_api.py | 19 ++++++++++++++++++- exo/inference/tokenizers.py | 2 +- exo/main.py | 18 +++++++++++++----- exo/models.py | 10 ++++++++++ 4 files changed, 42 insertions(+), 7 deletions(-) diff --git a/exo/api/chatgpt_api.py b/exo/api/chatgpt_api.py index 26951d73f..275581493 100644 --- a/exo/api/chatgpt_api.py +++ b/exo/api/chatgpt_api.py @@ -224,7 +224,24 @@ async def handle_model_support(self, request): }) async def handle_get_models(self, request): - return web.json_response([{"id": model_name, "object": "model", "owned_by": "exo", "ready": True} for model_name, _ in model_cards.items()]) + models_list = [] + for model_name, _ in model_cards.items(): + if "Local" in model_name: + model_data = { + "id": model_name, + "object": "model", + "owned_by": "Local", + "ready": True + } + else: + model_data = { + "id": model_name, + "object": "model", + "owned_by": "exo", + "ready": True + } + models_list.append(model_data) + return web.json_response(models_list) async def handle_post_chat_token_encode(self, request): data = await request.json() diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index 929134a68..0587194b8 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -26,7 +26,7 @@ async def resolve_tokenizer(model_id: str): local_path = await get_local_snapshot_dir(model_id) if not local_path: # local model path local_path = model_id.rstrip('/') - model_id = 'local/'+str(local_path.split('/')[-1]) + model_id = 'Local/'+str(local_path.split('/')[-1]) if DEBUG >= 2: print(f"Checking if local path exists to load tokenizer from local {local_path=}") try: diff --git a/exo/main.py b/exo/main.py index 1eea7284c..dc1aa7427 100644 --- a/exo/main.py +++ b/exo/main.py @@ -23,7 +23,7 @@ from exo.inference.dummy_inference_engine import DummyInferenceEngine from exo.inference.tokenizers import resolve_tokenizer from exo.orchestration.node import Node -from exo.models import model_cards, build_base_shard, get_repo +from exo.models import model_cards, build_local_model_card, build_base_shard, get_repo from exo.viz.topology_viz import TopologyViz # OKHand.zy add library import os @@ -62,16 +62,18 @@ system_info = get_system_info() print(f"Detected system: {system_info}") -shard_downloader: ShardDownloader = HFShardDownloader(quick_check=args.download_quick_check, - max_parallel_downloads=args.max_parallel_downloads) if args.inference_engine != "dummy" else NoopShardDownloader() inference_engine_name = args.inference_engine or ("mlx" if system_info == "Apple Silicon Mac" else "tinygrad") print(f"Inference engine name after selection: {inference_engine_name}") +# default use HF Downloader Model +shard_downloader: ShardDownloader = HFShardDownloader(quick_check=args.download_quick_check, + max_parallel_downloads=args.max_parallel_downloads) if args.inference_engine != "dummy" else NoopShardDownloader() + inference_engine = get_inference_engine(inference_engine_name, shard_downloader) print(f"Using inference engine: {inference_engine.__class__.__name__} with shard downloader: {shard_downloader.__class__.__name__}") if args.node_port is None: - args.node_port = find_available_port(args.node_host) + args.node_port = find_available_port(args.node_host) # 0.0.0.0:49152 ~ 65535 if DEBUG >= 1: print(f"Using available port: {args.node_port}") args.node_id = args.node_id or get_or_create_node_id() @@ -85,6 +87,7 @@ for chatgpt_api_endpoint in chatgpt_api_endpoints: print(f" - {terminal_link(chatgpt_api_endpoint)}") +# Default use udp discovery if args.discovery_module == "udp": discovery = UDPDiscovery( args.node_id, @@ -107,6 +110,7 @@ if not args.discovery_config_path: raise ValueError(f"--discovery-config-path is required when using manual discovery. Please provide a path to a config json file.") discovery = ManualDiscovery(args.discovery_config_path, args.node_id, create_peer_handle=lambda peer_id, address, device_capabilities: GRPCPeerHandle(peer_id, address, device_capabilities)) + topology_viz = TopologyViz(chatgpt_api_endpoints=chatgpt_api_endpoints, web_chat_urls=web_chat_urls) if not args.disable_tui else None node = StandardNode( args.node_id, @@ -186,7 +190,7 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam inference_class = inference_engine.__class__.__name__ shard = build_base_shard(model_name, inference_class) if not shard: - print(f"Error: Unsupported model '{model_name}' for inference engine {inference_engine.__class__.__name__}") + print(f"Error: exo Unsupported model '{model_name}' for inference engine {inference_engine.__class__.__name__}") return tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) elif os.path.isdir(model_name): @@ -197,8 +201,12 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam with open(model_path+'/config.json', 'r') as file: config = json.load(file) config_n_layers = config['num_hidden_layers'] + build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, config_n_layers) shard = Shard(model_id=model_path, start_layer=0, end_layer=0, n_layers=config_n_layers) tokenizer = await resolve_tokenizer(model_path) + else: + print(f"Error: Not Find Local model '{model_name}' for inference engine {inference_engine.__class__.__name__}") + return else: print(f"Error: Unsupported model '{model_name}' for inference engine {inference_engine.__class__.__name__}") return diff --git a/exo/models.py b/exo/models.py index 0561220ff..29522622f 100644 --- a/exo/models.py +++ b/exo/models.py @@ -125,3 +125,13 @@ def build_base_shard(model_id: str, inference_engine_classname: str) -> Optional return None return Shard(model_id, 0, 0, n_layers) +def build_local_model_card(model_name: str, model_path: str, inference_engine: str, config_n_layers: int): + short_model_name = f"Local/{model_name}" + pretty_model_name = f"{model_name} (Local)".replace('-', ' ') + model_cards[short_model_name] = { + "layers": config_n_layers, + "repo": { + inference_engine: model_path + }, + } + pretty_name[short_model_name]=pretty_model_name From 2a2e3b29e6f742d52ae96bf76b7b9ceffe684cc5 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Mon, 18 Nov 2024 14:12:39 +0800 Subject: [PATCH 04/26] futuer:(i-e:mlx)suppoert local model and HF model terminal complet --- exo/inference/tokenizers.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index 0587194b8..ef75f7cbe 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -7,6 +7,8 @@ from exo.download.hf.hf_helpers import get_local_snapshot_dir from exo.helpers import DEBUG +# OKHand.ziyu add library +import os class DummyTokenizer: def __init__(self): @@ -23,10 +25,11 @@ async def resolve_tokenizer(model_id: str): if model_id == "dummy": return DummyTokenizer() - local_path = await get_local_snapshot_dir(model_id) - if not local_path: # local model path + if os.path.isdir(model_id): # local model local_path = model_id.rstrip('/') model_id = 'Local/'+str(local_path.split('/')[-1]) + else: + local_path = await get_local_snapshot_dir(model_id) if DEBUG >= 2: print(f"Checking if local path exists to load tokenizer from local {local_path=}") try: From d8bbb2b640ca172149ffa93e38ad7325fb27aac1 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Tue, 19 Nov 2024 15:05:42 +0800 Subject: [PATCH 05/26] futur:support cli and chatapi local model complet --- README.md | 43 +++++++++++++ exo/api/chatgpt_api.py | 12 +++- exo/inference/mlx/sharded_inference_engine.py | 7 ++- exo/main.py | 60 ++++++++++++++++++- 4 files changed, 115 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 392ef2973..009d79b38 100644 --- a/README.md +++ b/README.md @@ -28,6 +28,12 @@ Forget expensive NVIDIA GPUs, unify your existing devices into one powerful GPU:

Update: exo is hiring. See here for more details.

+OKHand.zy fork add new feature: +- support CLI and ChatAPI use local model (only support mlx inference engine) +- add new args "--add-local-model" +- add init exo folder and model config file in /.cache/exo + + ## Get Involved exo is **experimental** software. Expect bugs early on. Create issues so they can be fixed. The [exo labs](https://x.com/exolabs) team will strive to resolve issues quickly. @@ -208,12 +214,49 @@ With a custom prompt: exo run llama-3.2-3b --prompt "What is the meaning of exo?" ``` +### Example Usage on a single device with Local Model +- Step1. Download the model from huggingface +- Step2. + ```shell + exo --add-local-model + ``` +- Step3. + ```shell + exo --inference-engine mlx --run-model + or + exo --inference-engine mlx --run-model + ``` + +### Example Usage on Multiple Devices with Local Model +#### Both devices are on MacOS: +- Step1. Download the model from huggingface and put it in the exo folder(/.cache/exo) +- Step2. + ```shell + exo --add-local-model + ``` +#### Choose one device to run the following command: +```shell +curl http://localhost:8000/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "Local/", + "messages": [{"role": "user", "content": "What is the meaning of exo?"}], + "temperature": 0.7 + }' +``` + ### Model Storage Models by default are stored in `~/.cache/huggingface/hub`. You can set a different model storage location by setting the `HF_HOME` env var. +### Local Model Storage + +Please stored models in `~/.cache/exo`. + +You can set a different model storage location by setting the `HOME` env var + ## Debugging Enable debug logs with the DEBUG environment variable (0-9). diff --git a/exo/api/chatgpt_api.py b/exo/api/chatgpt_api.py index 275581493..d321dfff5 100644 --- a/exo/api/chatgpt_api.py +++ b/exo/api/chatgpt_api.py @@ -247,7 +247,11 @@ async def handle_post_chat_token_encode(self, request): data = await request.json() shard = build_base_shard(self.default_model, self.inference_engine_classname) messages = [parse_message(msg) for msg in data.get("messages", [])] - tokenizer = await resolve_tokenizer(get_repo(shard.model_id, self.inference_engine_classname)) + if "Local" in shard.model_id: + model_path = model_cards.get(shard.model_id, {}).get("repo", {}).get(self.inference_engine_classname,{}) + tokenizer = await resolve_tokenizer(model_path) + else: + tokenizer = await resolve_tokenizer(get_repo(shard.model_id, self.inference_engine_classname)) return web.json_response({"length": len(build_prompt(tokenizer, messages)[0])}) async def handle_get_download_progress(self, request): @@ -277,7 +281,11 @@ async def handle_post_chat_completions(self, request): status=400, ) - tokenizer = await resolve_tokenizer(get_repo(shard.model_id, self.inference_engine_classname)) + if "Local" in shard.model_id: + model_path = model_cards.get(shard.model_id, {}).get("repo", {}).get(self.inference_engine_classname,{}) + tokenizer = await resolve_tokenizer(model_path) + else: + tokenizer = await resolve_tokenizer(get_repo(shard.model_id, self.inference_engine_classname)) if DEBUG >= 4: print(f"Resolved tokenizer: {tokenizer}") prompt = build_prompt(tokenizer, chat_request.messages) diff --git a/exo/inference/mlx/sharded_inference_engine.py b/exo/inference/mlx/sharded_inference_engine.py index aff8a071c..8f8b709cf 100644 --- a/exo/inference/mlx/sharded_inference_engine.py +++ b/exo/inference/mlx/sharded_inference_engine.py @@ -13,6 +13,7 @@ # OKHand.zy add library import os from pathlib import Path +from exo.models import get_repo def sample_logits( logits: mx.array, @@ -66,8 +67,10 @@ async def ensure_shard(self, shard: Shard): if self.shard == shard: return - if os.path.isdir(shard.model_id): # if local model - model_path = Path(shard.model_id) + if os.path.isdir(shard.model_id): # cli mode + model_path = Path(shard.model_id) + elif "Local" in shard.model_id: # api mode + model_path = Path(get_repo(shard.model_id, self.__class__.__name__)) else: model_path = await self.shard_downloader.ensure_shard(shard, self.__class__.__name__) diff --git a/exo/main.py b/exo/main.py index dc1aa7427..0bc3709e0 100644 --- a/exo/main.py +++ b/exo/main.py @@ -27,7 +27,9 @@ from exo.viz.topology_viz import TopologyViz # OKHand.zy add library import os +import sys import json +from pathlib import Path # parse args parser = argparse.ArgumentParser(description="Initialize GRPC Discovery") @@ -54,11 +56,60 @@ parser.add_argument("--prompt", type=str, help="Prompt for the model when using --run-model", default="Who are you?") parser.add_argument("--tailscale-api-key", type=str, default=None, help="Tailscale API key") parser.add_argument("--tailnet-name", type=str, default=None, help="Tailnet name") +parser.add_argument("--add-local-model", type=str, nargs=2, metavar=('Model_name', 'Inference_engine'), help="Add local model: MODEL_NAME is the name of model, ENGINE_NAME is mlx/tinygrad/dummy") args = parser.parse_args() print(f"Selected inference engine: {args.inference_engine}") print_yellow_exo() +# init folder for Local Model +exo_path = os.environ.get("Home", Path.home()/".cache"/"exo") +os.makedirs(exo_path, exist_ok=True) +print(f"Init exo folder: {exo_path}") +local_model_config = Path(f'{exo_path}/model_config.txt') +local_model_config.parent.mkdir(parents=True, exist_ok=True) +with local_model_config.open('a') as file: + file.close() +print(f"Init local model config: {exo_path}") + +# import Local Model +if args.add_local_model: + model_name = args.add_local_model[0] + inference_engine = args.add_local_model[1].lower() + if inference_engine == "mlx" or inference_engine == "mlxdynamicshardinferenceengine": + inference_engine_name = "MLXDynamicShardInferenceEngine" + elif inference_engine == "tinygrad" or inference_engine == "tinygradshardinferenceengine": + inference_engine_name = "TinyGradShardInferenceEngine" + elif inference_engine == "dummy" or inference_engine == "dummyinferenceengine": + inference_engine_name = "DummyInferenceEngine" + else: + sys.exit(f"Invalid inference engine: {inference_engine}") + + with open(str(exo_path)+f'/{model_name}/config.json', 'r') as file: + config = json.load(file) + config_n_layers = config['num_hidden_layers'] + new_model = f"{model_name}:{config_n_layers}:{inference_engine_name}:{str(exo_path)}/{model_name}\n" + + with local_model_config.open('r') as file: + existing_content = file.read() + file.close() + if new_model in existing_content: + sys.exit(f"Model already: {model_name} with inference engine: {inference_engine_name}") + else: + with local_model_config.open('a') as file: + file.write(new_model) + file.close() + sys.exit(f"Add local model: {model_name} with inference engine: {inference_engine_name}") + +# Build Local Model Card +with local_model_config.open('r') as file: + all_model = file.read() + model_config_list = all_model.split('\n')[:-1] +for model_config in model_config_list: + model_name, config_n_layers, inference_engine, model_path = model_config.split(':') + build_local_model_card(model_name, model_path, inference_engine, int(config_n_layers)) +print(f"Init local model card complete") + system_info = get_system_info() print(f"Detected system: {system_info}") @@ -140,8 +191,10 @@ def preemptively_start_download(request_id: str, opaque_status: str): status = json.loads(opaque_status) if status.get("type") == "node_status" and status.get("status") == "start_process_prompt": current_shard = node.get_current_shard(Shard.from_dict(status.get("shard"))) - if os.path.isdir(current_shard.model_id): + + if "Local" in current_shard.model_id: # TODO: open ftp to share download model + print("Local model detected, skip download") pass else: if DEBUG >= 2: print(f"Preemptively starting download for {current_shard}") @@ -195,8 +248,9 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) elif os.path.isdir(model_name): # local model and shard - model_path = model_name.rstrip('/') - model_name = model_path.split('/')[-1] + model_name = model_name.rstrip('/').split('/')[-1] + model_path = str(os.environ.get("Home", Path.home()/exo_path/model_name)) + if os.path.isfile(model_path+'/config.json'): with open(model_path+'/config.json', 'r') as file: config = json.load(file) From 9ab3513096f229694fc9bf9e8956b46806a3eaef Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Wed, 20 Nov 2024 09:14:30 +0800 Subject: [PATCH 06/26] filter run_model_cli --- exo/main.py | 25 +++++++++++++------------ 1 file changed, 13 insertions(+), 12 deletions(-) diff --git a/exo/main.py b/exo/main.py index 0bc3709e0..c8a12ca7e 100644 --- a/exo/main.py +++ b/exo/main.py @@ -238,21 +238,22 @@ async def shutdown(signal, loop): loop.stop() -async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name: str, prompt: str): - if model_cards.get(model_name): +async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name_or_path: str, prompt: str): + if model_cards.get(model_name_or_path): inference_class = inference_engine.__class__.__name__ - shard = build_base_shard(model_name, inference_class) + shard = build_base_shard(model_name_or_path, inference_class) if not shard: - print(f"Error: exo Unsupported model '{model_name}' for inference engine {inference_engine.__class__.__name__}") + print(f"Error: exo Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") return tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) - elif os.path.isdir(model_name): + elif os.path.isdir(model_name_or_path): # local model and shard - model_name = model_name.rstrip('/').split('/')[-1] - model_path = str(os.environ.get("Home", Path.home()/exo_path/model_name)) + model_path = model_name_or_path.rstrip('/') + model_config_path = Path(model_path)/'config.json' + model_name = str(model_path.split('/')[-1]) - if os.path.isfile(model_path+'/config.json'): - with open(model_path+'/config.json', 'r') as file: + if os.path.isfile(model_config_path): + with open(model_config_path, 'r') as file: config = json.load(file) config_n_layers = config['num_hidden_layers'] build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, config_n_layers) @@ -300,11 +301,11 @@ def handle_exit(): await node.start(wait_for_peers=args.wait_for_peers) if args.command == "run" or args.run_model: - model_name = args.model_name or args.run_model - if not model_name: + model_name_or_path = args.model_name or args.run_model + if not model_name_or_path: print("Error: Model name is required when using 'run' command or --run-model") return - await run_model_cli(node, inference_engine, model_name, args.prompt) + await run_model_cli(node, inference_engine, model_name_or_path, args.prompt) else: asyncio.create_task(api.run(port=args.chatgpt_api_port)) # Start the API server as a non-blocking task await asyncio.Event().wait() From a9c345a8420d177baa44c3a6ea8b2e852a97bb39 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Wed, 20 Nov 2024 10:20:04 +0800 Subject: [PATCH 07/26] add init_exo_function (helpers.py) --- exo/helpers.py | 10 ++++++++++ exo/main.py | 17 ++++++----------- 2 files changed, 16 insertions(+), 11 deletions(-) diff --git a/exo/helpers.py b/exo/helpers.py index b657b2775..9a49ccad5 100644 --- a/exo/helpers.py +++ b/exo/helpers.py @@ -86,6 +86,16 @@ def terminal_link(uri, label=None): return escape_mask.format(parameters, uri, label) +def init_exo_env(): + exo_path = os.environ.get("Home", Path.home()/".cache"/"exo") + os.makedirs(exo_path, exist_ok=True) + print(f"Init exo folder: {exo_path}") + local_model_config = Path(f'{exo_path}/model_config.txt') + local_model_config.parent.mkdir(parents=True, exist_ok=True) + with local_model_config.open('a') as file: + file.close() + print(f"Init local model config: {exo_path}") + return exo_path, local_model_config T = TypeVar("T") K = TypeVar("K") diff --git a/exo/main.py b/exo/main.py index c8a12ca7e..4777f5570 100644 --- a/exo/main.py +++ b/exo/main.py @@ -17,7 +17,7 @@ from exo.api import ChatGPTAPI from exo.download.shard_download import ShardDownloader, RepoProgressEvent, NoopShardDownloader from exo.download.hf.hf_shard_download import HFShardDownloader -from exo.helpers import print_yellow_exo, find_available_port, DEBUG, get_system_info, get_or_create_node_id, get_all_ip_addresses, terminal_link +from exo.helpers import print_yellow_exo, init_exo_env, find_available_port, DEBUG, get_system_info, get_or_create_node_id, get_all_ip_addresses, terminal_link from exo.inference.shard import Shard from exo.inference.inference_engine import get_inference_engine, InferenceEngine from exo.inference.dummy_inference_engine import DummyInferenceEngine @@ -63,14 +63,7 @@ print_yellow_exo() # init folder for Local Model -exo_path = os.environ.get("Home", Path.home()/".cache"/"exo") -os.makedirs(exo_path, exist_ok=True) -print(f"Init exo folder: {exo_path}") -local_model_config = Path(f'{exo_path}/model_config.txt') -local_model_config.parent.mkdir(parents=True, exist_ok=True) -with local_model_config.open('a') as file: - file.close() -print(f"Init local model config: {exo_path}") +exo_path, local_model_config = init_exo_env() # import Local Model if args.add_local_model: @@ -85,9 +78,11 @@ else: sys.exit(f"Invalid inference engine: {inference_engine}") - with open(str(exo_path)+f'/{model_name}/config.json', 'r') as file: + config_file_path = Path(exo_path/model_name/'config.json') + with open(config_file_path, 'r') as file: config = json.load(file) config_n_layers = config['num_hidden_layers'] + new_model = f"{model_name}:{config_n_layers}:{inference_engine_name}:{str(exo_path)}/{model_name}\n" with local_model_config.open('r') as file: @@ -124,7 +119,7 @@ print(f"Using inference engine: {inference_engine.__class__.__name__} with shard downloader: {shard_downloader.__class__.__name__}") if args.node_port is None: - args.node_port = find_available_port(args.node_host) # 0.0.0.0:49152 ~ 65535 + args.node_port = find_available_port(args.node_host) if DEBUG >= 1: print(f"Using available port: {args.node_port}") args.node_id = args.node_id or get_or_create_node_id() From cdba915697606ba0ed4dbe3485310a05ba9d4d56 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Wed, 20 Nov 2024 10:57:40 +0800 Subject: [PATCH 08/26] filter read me --- README.md | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/README.md b/README.md index b550c5e50..bfe8af220 100644 --- a/README.md +++ b/README.md @@ -28,12 +28,6 @@ Forget expensive NVIDIA GPUs, unify your existing devices into one powerful GPU:

Update: exo is hiring. See here for more details.

-OKHand.zy fork add new feature: -- support CLI and ChatAPI use local model (only support mlx inference engine) -- add new args "--add-local-model" -- add init exo folder and model config file in /.cache/exo - - ## Get Involved exo is **experimental** software. Expect bugs early on. Create issues so they can be fixed. The [exo labs](https://x.com/exolabs) team will strive to resolve issues quickly. @@ -236,7 +230,7 @@ exo run llama-3.2-3b --prompt "What is the meaning of exo?" ``` #### Choose one device to run the following command: ```shell -curl http://localhost:8000/v1/chat/completions \ +curl http://localhost:52415/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "Local/", From 0b06fe16dc3cdd63718bd487abba746a07650d58 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Wed, 20 Nov 2024 11:38:39 +0800 Subject: [PATCH 09/26] filter cli local model error --- exo/inference/mlx/sharded_inference_engine.py | 2 +- exo/inference/tokenizers.py | 4 ++-- exo/main.py | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/exo/inference/mlx/sharded_inference_engine.py b/exo/inference/mlx/sharded_inference_engine.py index 8f8b709cf..c0c054757 100644 --- a/exo/inference/mlx/sharded_inference_engine.py +++ b/exo/inference/mlx/sharded_inference_engine.py @@ -66,7 +66,7 @@ async def infer_tensor(self, request_id: str, shard: Shard, input_data: np.ndarr async def ensure_shard(self, shard: Shard): if self.shard == shard: return - + if os.path.isdir(shard.model_id): # cli mode model_path = Path(shard.model_id) elif "Local" in shard.model_id: # api mode diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index ef75f7cbe..182f8c4ee 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -24,9 +24,9 @@ def decode(self, tokens): async def resolve_tokenizer(model_id: str): if model_id == "dummy": return DummyTokenizer() - + if os.path.isdir(model_id): # local model - local_path = model_id.rstrip('/') + local_path = str(model_id).rstrip('/') model_id = 'Local/'+str(local_path.split('/')[-1]) else: local_path = await get_local_snapshot_dir(model_id) diff --git a/exo/main.py b/exo/main.py index 07dba2c17..02983b38a 100644 --- a/exo/main.py +++ b/exo/main.py @@ -189,7 +189,7 @@ def preemptively_start_download(request_id: str, opaque_status: str): if status.get("type") == "node_status" and status.get("status") == "start_process_prompt": current_shard = node.get_current_shard(Shard.from_dict(status.get("shard"))) - if "Local" in current_shard.model_id: + if "Local" in current_shard.model_id or os.path.isdir(current_shard.model_id): # TODO: open ftp to share download model print("Local model detected, skip download") pass From 438eae4b4f6f11081cfec69f128ad8e3eaac6758 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Wed, 20 Nov 2024 14:04:59 +0800 Subject: [PATCH 10/26] filter some mark --- exo/inference/mlx/sharded_inference_engine.py | 5 ++--- exo/inference/tokenizers.py | 3 +-- exo/main.py | 7 ------- 3 files changed, 3 insertions(+), 12 deletions(-) diff --git a/exo/inference/mlx/sharded_inference_engine.py b/exo/inference/mlx/sharded_inference_engine.py index c0c054757..1d6e4a6b7 100644 --- a/exo/inference/mlx/sharded_inference_engine.py +++ b/exo/inference/mlx/sharded_inference_engine.py @@ -1,6 +1,8 @@ +import os import numpy as np import mlx.core as mx import mlx.nn as nn +from pathlib import Path from ..inference_engine import InferenceEngine from .stateful_model import StatefulModel from .sharded_utils import load_shard, get_image_from_str @@ -10,9 +12,6 @@ import asyncio from concurrent.futures import ThreadPoolExecutor from functools import partial -# OKHand.zy add library -import os -from pathlib import Path from exo.models import get_repo def sample_logits( diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index 182f8c4ee..ec8d7972e 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -1,3 +1,4 @@ +import os import traceback from aiofiles import os as aios from os import PathLike @@ -7,8 +8,6 @@ from exo.download.hf.hf_helpers import get_local_snapshot_dir from exo.helpers import DEBUG -# OKHand.ziyu add library -import os class DummyTokenizer: def __init__(self): diff --git a/exo/main.py b/exo/main.py index 02983b38a..8dd51e73d 100644 --- a/exo/main.py +++ b/exo/main.py @@ -64,10 +64,8 @@ print_yellow_exo() -# init folder for Local Model exo_path, local_model_config = init_exo_env() -# import Local Model if args.add_local_model: model_name = args.add_local_model[0] inference_engine = args.add_local_model[1].lower() @@ -98,7 +96,6 @@ file.close() sys.exit(f"Add local model: {model_name} with inference engine: {inference_engine_name}") -# Build Local Model Card with local_model_config.open('r') as file: all_model = file.read() model_config_list = all_model.split('\n')[:-1] @@ -113,7 +110,6 @@ inference_engine_name = args.inference_engine or ("mlx" if system_info == "Apple Silicon Mac" else "tinygrad") print(f"Inference engine name after selection: {inference_engine_name}") -# default use HF Downloader Model shard_downloader: ShardDownloader = HFShardDownloader(quick_check=args.download_quick_check, max_parallel_downloads=args.max_parallel_downloads) if args.inference_engine != "dummy" else NoopShardDownloader() @@ -135,7 +131,6 @@ for chatgpt_api_endpoint in chatgpt_api_endpoints: print(f" - {terminal_link(chatgpt_api_endpoint)}") -# Default use udp discovery if args.discovery_module == "udp": discovery = UDPDiscovery( args.node_id, @@ -190,7 +185,6 @@ def preemptively_start_download(request_id: str, opaque_status: str): current_shard = node.get_current_shard(Shard.from_dict(status.get("shard"))) if "Local" in current_shard.model_id or os.path.isdir(current_shard.model_id): - # TODO: open ftp to share download model print("Local model detected, skip download") pass else: @@ -230,7 +224,6 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam return tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) elif os.path.isdir(model_name_or_path): - # local model and shard model_path = model_name_or_path.rstrip('/') model_config_path = Path(model_path)/'config.json' model_name = str(model_path.split('/')[-1]) From 535cb44a876bd106bc4b8d98a4d873fec5b4f0c5 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Fri, 22 Nov 2024 10:10:17 +0800 Subject: [PATCH 11/26] filter name miss --- exo/main.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/exo/main.py b/exo/main.py index 8dd51e73d..b6cf770c9 100644 --- a/exo/main.py +++ b/exo/main.py @@ -239,7 +239,7 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam print(f"Error: Not Find Local model '{model_name}' for inference engine {inference_engine.__class__.__name__}") return else: - print(f"Error: Unsupported model '{model_name}' for inference engine {inference_engine.__class__.__name__}") + print(f"Error: Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") return request_id = str(uuid.uuid4()) From 1e5429d5db1db39158d1aa4e47dab9da75b03177 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Thu, 28 Nov 2024 11:12:50 +0800 Subject: [PATCH 12/26] remove:add lcoal model arg --- exo/helpers.py | 11 +++-------- exo/main.py | 52 ++++++++++++-------------------------------------- exo/models.py | 2 +- 3 files changed, 16 insertions(+), 49 deletions(-) diff --git a/exo/helpers.py b/exo/helpers.py index 7ab74ad41..7db180250 100644 --- a/exo/helpers.py +++ b/exo/helpers.py @@ -88,15 +88,10 @@ def terminal_link(uri, label=None): return escape_mask.format(parameters, uri, label) def init_exo_env(): - exo_path = os.environ.get("Home", Path.home()/".cache"/"exo") + exo_path = Path(Path.home()/".cache"/"exo") os.makedirs(exo_path, exist_ok=True) - print(f"Init exo folder: {exo_path}") - local_model_config = Path(f'{exo_path}/model_config.txt') - local_model_config.parent.mkdir(parents=True, exist_ok=True) - with local_model_config.open('a') as file: - file.close() - print(f"Init local model config: {exo_path}") - return exo_path, local_model_config + if DEBUG >= 1: print(f"Init exo folder: {exo_path}") + return exo_path T = TypeVar("T") K = TypeVar("K") diff --git a/exo/main.py b/exo/main.py index b6cf770c9..29b163b41 100644 --- a/exo/main.py +++ b/exo/main.py @@ -58,51 +58,12 @@ parser.add_argument("--prompt", type=str, help="Prompt for the model when using --run-model", default="Who are you?") parser.add_argument("--tailscale-api-key", type=str, default=None, help="Tailscale API key") parser.add_argument("--tailnet-name", type=str, default=None, help="Tailnet name") -parser.add_argument("--add-local-model", type=str, nargs=2, metavar=('Model_name', 'Inference_engine'), help="Add local model: MODEL_NAME is the name of model, ENGINE_NAME is mlx/tinygrad/dummy") args = parser.parse_args() print(f"Selected inference engine: {args.inference_engine}") print_yellow_exo() -exo_path, local_model_config = init_exo_env() - -if args.add_local_model: - model_name = args.add_local_model[0] - inference_engine = args.add_local_model[1].lower() - if inference_engine == "mlx" or inference_engine == "mlxdynamicshardinferenceengine": - inference_engine_name = "MLXDynamicShardInferenceEngine" - elif inference_engine == "tinygrad" or inference_engine == "tinygradshardinferenceengine": - inference_engine_name = "TinyGradShardInferenceEngine" - elif inference_engine == "dummy" or inference_engine == "dummyinferenceengine": - inference_engine_name = "DummyInferenceEngine" - else: - sys.exit(f"Invalid inference engine: {inference_engine}") - - config_file_path = Path(exo_path/model_name/'config.json') - with open(config_file_path, 'r') as file: - config = json.load(file) - config_n_layers = config['num_hidden_layers'] - - new_model = f"{model_name}:{config_n_layers}:{inference_engine_name}:{str(exo_path)}/{model_name}\n" - - with local_model_config.open('r') as file: - existing_content = file.read() - file.close() - if new_model in existing_content: - sys.exit(f"Model already: {model_name} with inference engine: {inference_engine_name}") - else: - with local_model_config.open('a') as file: - file.write(new_model) - file.close() - sys.exit(f"Add local model: {model_name} with inference engine: {inference_engine_name}") - -with local_model_config.open('r') as file: - all_model = file.read() - model_config_list = all_model.split('\n')[:-1] -for model_config in model_config_list: - model_name, config_n_layers, inference_engine, model_path = model_config.split(':') - build_local_model_card(model_name, model_path, inference_engine, int(config_n_layers)) -print(f"Init local model card complete") +exo_path = init_exo_env() system_info = get_system_info() print(f"Detected system: {system_info}") @@ -116,6 +77,17 @@ inference_engine = get_inference_engine(inference_engine_name, shard_downloader) print(f"Using inference engine: {inference_engine.__class__.__name__} with shard downloader: {shard_downloader.__class__.__name__}") +for folder_path in Path(exo_path).iterdir(): + if folder_path.is_dir(): + model_path = folder_path + model_name = folder_path.name + config_file_path = Path(folder_path/'config.json') + with open(config_file_path, 'r') as file: + config = json.load(file) + config_n_layers = config['num_hidden_layers'] + build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, int(config_n_layers)) +print(f"Init local model card complete") + if args.node_port is None: args.node_port = find_available_port(args.node_host) if DEBUG >= 1: print(f"Using available port: {args.node_port}") diff --git a/exo/models.py b/exo/models.py index f9b2d2569..565bcdc1c 100644 --- a/exo/models.py +++ b/exo/models.py @@ -125,7 +125,7 @@ def build_base_shard(model_id: str, inference_engine_classname: str) -> Optional return None return Shard(model_id, 0, 0, n_layers) -def build_local_model_card(model_name: str, model_path: str, inference_engine: str, config_n_layers: int): +def build_local_model_card(model_name: str, model_path: str, inference_engine: str, config_n_layers: int) -> None: short_model_name = f"Local/{model_name}" pretty_model_name = f"{model_name} (Local)".replace('-', ' ') model_cards[short_model_name] = { From 880682a71e5b4860dfcad03e98c86b041ea45f5e Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Fri, 6 Dec 2024 11:40:11 +0800 Subject: [PATCH 13/26] filter: other dir no config error --- exo/main.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/exo/main.py b/exo/main.py index 29b163b41..48bc40a06 100644 --- a/exo/main.py +++ b/exo/main.py @@ -82,10 +82,11 @@ model_path = folder_path model_name = folder_path.name config_file_path = Path(folder_path/'config.json') - with open(config_file_path, 'r') as file: - config = json.load(file) - config_n_layers = config['num_hidden_layers'] - build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, int(config_n_layers)) + if config_file_path.is_file(): + with open(config_file_path, 'r') as file: + config = json.load(file) + config_n_layers = config['num_hidden_layers'] + build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, int(config_n_layers)) print(f"Init local model card complete") if args.node_port is None: From c4e18aea6574fce7630228a6a26da187aafc8753 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Fri, 6 Dec 2024 14:59:35 +0800 Subject: [PATCH 14/26] merge: new image --- .gitattributes | 2 + docs/exo-logo-transparent-black-text.png | Bin 1296 -> 129 bytes docs/exo-logo-transparent.png | Bin 1296 -> 129 bytes docs/exo-rounded.png | Bin 28651 -> 130 bytes docs/exo-screenshot.png | Bin 479724 -> 131 bytes docs/ring-topology.png | Bin 55857 -> 130 bytes exo/apputil/__init__.py | 1 + exo/apputil/anim.py | 161 +++ exo/apputil/baseimages/image1.png | 3 + exo/apputil/baseimages/image2.png | 3 + exo/apputil/baseimages/image3.png | 3 + exo/apputil/baseimages/image4.png | 3 + extra/dashboard/dashboard.py | 1147 +++++++++++++++++++++ extra/dashboard/requirements.txt | 5 + extra/dashboard/sounds/gta5_wasted.mp3 | 3 + extra/dashboard/sounds/pokemon_evolve.mp3 | 3 + extra/line_counter.py | 210 ++++ extra/pipsize.py | 113 ++ 18 files changed, 1657 insertions(+) create mode 100644 .gitattributes create mode 100644 exo/apputil/__init__.py create mode 100644 exo/apputil/anim.py create mode 100644 exo/apputil/baseimages/image1.png create mode 100644 exo/apputil/baseimages/image2.png create mode 100644 exo/apputil/baseimages/image3.png create mode 100644 exo/apputil/baseimages/image4.png create mode 100644 extra/dashboard/dashboard.py create mode 100644 extra/dashboard/requirements.txt create mode 100644 extra/dashboard/sounds/gta5_wasted.mp3 create mode 100644 extra/dashboard/sounds/pokemon_evolve.mp3 create mode 100644 extra/line_counter.py create mode 100644 extra/pipsize.py diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 000000000..ab26661da --- /dev/null +++ b/.gitattributes @@ -0,0 +1,2 @@ +*.mp3 filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text diff --git 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z{XV}p?<(*X;yq_#T=#wJd)n3kyl~KAqWxkPV2%m=w8&^CX!DhW&D;6A!fI) zo-;ks$(E7C=i7fx{O(#0lMbH<$CfiD?osmpJq$Pu|GnO}b?scekmP=LnF0r6;1QYA z{!gnANWA_~{4{W`>6Z-9V7q$9nR{FkyaXIF^i-boeaLbA4!q)J-yip)w8>TpKS6ha zL|S)72&&tkFxq8z^RmfA4M902*N%CuW+!v1cjwoAo}J1ItP#!}na^>$K2uPv7&#_q zf%3+Qi;ERJp0r+=AOu__RrVTmti&_mt_=OOClxQ3PB#PH8D1zY-B~RCki)n`{NzpZ zug&s*5)>W2nH&Wk>#|Q^g~iQQj>Dp}(ggBs&I4OT??J7s-_obPs4`7fJffU0&d3IXW=|yi;wtsy}XjiMz5nx*JbQ<%i&g+%a*%)xc@-L z6^l z{C_`inE~+33(%Q0>>!6TeCaWQ^8W)Xus8q9r)YxC`~+?qe!&Pd*OtL{F^pdiY;*no zFPq8*JR(d1sHqB6V)Hwk*MRbW$pd5XU%mUxLttr?o(b5FVd8{;_Win_9{)8vvx@-; NJYD@<);T3K0RWbz)Di#y diff --git a/exo/apputil/__init__.py b/exo/apputil/__init__.py new file mode 100644 index 000000000..b6ac6e259 --- /dev/null +++ b/exo/apputil/__init__.py @@ -0,0 +1 @@ +from exo.apputil.anim import create_animation_mp4 \ No newline at end of file diff --git a/exo/apputil/anim.py b/exo/apputil/anim.py new file mode 100644 index 000000000..654ca4703 --- /dev/null +++ b/exo/apputil/anim.py @@ -0,0 +1,161 @@ +from PIL import Image, ImageDraw, ImageFont, ImageFilter +import os +import numpy as np +import cv2 + +def draw_rounded_rectangle(draw, coords, radius, fill): + left, top, right, bottom = coords + diameter = radius * 2 + draw.rectangle([left + radius, top, right - radius, bottom], fill=fill) + draw.rectangle([left, top + radius, right, bottom - radius], fill=fill) + draw.pieslice([left, top, left + diameter, top + diameter], 180, 270, fill=fill) + draw.pieslice([right - diameter, top, right, top + diameter], 270, 360, fill=fill) + draw.pieslice([left, bottom - diameter, left + diameter, bottom], 90, 180, fill=fill) + draw.pieslice([right - diameter, bottom - diameter, right, bottom], 0, 90, fill=fill) + +def draw_centered_text_rounded(draw, text, font, rect_coords, radius=10, text_color="yellow", bg_color=(43,33,44)): + bbox = font.getbbox(text) + text_width = bbox[2] - bbox[0] + text_height = bbox[3] - bbox[1] + rect_left, rect_top, rect_right, rect_bottom = rect_coords + rect_width = rect_right - rect_left + rect_height = rect_bottom - rect_top + text_x = rect_left + (rect_width - text_width) // 2 + text_y = rect_top + (rect_height - text_height) // 2 + draw_rounded_rectangle(draw, rect_coords, radius, bg_color) + draw.text((text_x, text_y), text, fill=text_color, font=font) + +def draw_left_aligned_text_rounded(draw, text, font, rect_coords, padding_left=20, radius=10, text_color="yellow", bg_color=(43,33,44)): + bbox = font.getbbox(text) + text_height = bbox[3] - bbox[1] + rect_left, rect_top, rect_right, rect_bottom = rect_coords + rect_height = rect_bottom - rect_top + text_y = rect_top + (rect_height - text_height) // 2 + text_x = rect_left + padding_left + draw_rounded_rectangle(draw, rect_coords, radius, bg_color) + draw.text((text_x, text_y), text, fill=text_color, font=font) + +def draw_right_text_dynamic_width_rounded(draw, text, font, base_coords, padding=20, radius=10, text_color="yellow", bg_color=(43,33,44)): + bbox = font.getbbox(text) + text_width = bbox[2] - bbox[0] + text_height = bbox[3] - bbox[1] + _, rect_top, rect_right, rect_bottom = base_coords + rect_height = rect_bottom - rect_top + new_rect_left = rect_right - (text_width + (padding * 2)) + text_y = rect_top + (rect_height - text_height) // 2 + text_x = new_rect_left + padding + draw_rounded_rectangle(draw, (new_rect_left, rect_top, rect_right, rect_bottom), radius, bg_color) + draw.text((text_x, text_y), text, fill=text_color, font=font) + return new_rect_left + +def draw_progress_bar(draw, progress, coords, color="yellow", bg_color=(70, 70, 70)): + left, top, right, bottom = coords + total_width = right - left + draw.rectangle(coords, fill=bg_color) + progress_width = int(total_width * progress) + if progress_width > 0: + draw.rectangle((left, top, left + progress_width, bottom), fill=color) + +def crop_image(image, top_crop=70): + width, height = image.size + return image.crop((0, top_crop, width, height)) + +def create_animation_mp4( + replacement_image_path, + output_path, + device_name, + prompt_text, + fps=30, + target_size=(512, 512), + target_position=(139, 755), + progress_coords=(139, 1285, 655, 1295), + device_coords=(1240, 370, 1640, 416), + prompt_coords=(332, 1702, 2662, 1745) +): + frames = [] + try: + font = ImageFont.truetype("/System/Library/Fonts/SFNSMono.ttf", 20) + promptfont = ImageFont.truetype("/System/Library/Fonts/SFNSMono.ttf", 24) + except: + font = ImageFont.load_default() + promptfont = ImageFont.load_default() + + # Process first frame + base_img = Image.open(os.path.join(os.path.dirname(__file__), "baseimages", "image1.png")) + draw = ImageDraw.Draw(base_img) + draw_centered_text_rounded(draw, device_name, font, device_coords) + frames.extend([crop_image(base_img)] * 30) # 1 second at 30fps + + # Process second frame with typing animation + base_img2 = Image.open(os.path.join(os.path.dirname(__file__), "baseimages", "image2.png")) + for i in range(len(prompt_text) + 1): + current_frame = base_img2.copy() + draw = ImageDraw.Draw(current_frame) + draw_centered_text_rounded(draw, device_name, font, device_coords) + if i > 0: # Only draw if we have at least one character + draw_left_aligned_text_rounded(draw, prompt_text[:i], promptfont, prompt_coords) + frames.extend([crop_image(current_frame)] * 2) # 2 frames per character for smooth typing + + # Hold the complete prompt for a moment + frames.extend([frames[-1]] * 30) # Hold for 1 second + + # Create blur sequence + replacement_img = Image.open(replacement_image_path) + base_img = Image.open(os.path.join(os.path.dirname(__file__), "baseimages", "image3.png")) + blur_steps = [int(80 * (1 - i/8)) for i in range(9)] + + for i, blur_amount in enumerate(blur_steps): + new_frame = base_img.copy() + draw = ImageDraw.Draw(new_frame) + + replacement_copy = replacement_img.copy() + replacement_copy.thumbnail(target_size, Image.Resampling.LANCZOS) + if blur_amount > 0: + replacement_copy = replacement_copy.filter(ImageFilter.GaussianBlur(radius=blur_amount)) + + mask = replacement_copy.split()[-1] if replacement_copy.mode in ('RGBA', 'LA') else None + new_frame.paste(replacement_copy, target_position, mask) + + draw_progress_bar(draw, (i + 1) / 9, progress_coords) + draw_centered_text_rounded(draw, device_name, font, device_coords) + draw_right_text_dynamic_width_rounded(draw, prompt_text, promptfont, (None, 590, 2850, 685), padding=30) + + frames.extend([crop_image(new_frame)] * 15) # 0.5 seconds at 30fps + + # Create and add final frame (image4) + final_base = Image.open(os.path.join(os.path.dirname(__file__), "baseimages", "image4.png")) + draw = ImageDraw.Draw(final_base) + + draw_centered_text_rounded(draw, device_name, font, device_coords) + draw_right_text_dynamic_width_rounded(draw, prompt_text, promptfont, (None, 590, 2850, 685), padding=30) + + replacement_copy = replacement_img.copy() + replacement_copy.thumbnail(target_size, Image.Resampling.LANCZOS) + mask = replacement_copy.split()[-1] if replacement_copy.mode in ('RGBA', 'LA') else None + final_base.paste(replacement_copy, target_position, mask) + + frames.extend([crop_image(final_base)] * 30) # 1 second at 30fps + + # Convert frames to video using H.264 codec + if frames: + first_frame = np.array(frames[0]) + height, width = first_frame.shape[:2] + fourcc = cv2.VideoWriter_fourcc(*'avc1') + out = cv2.VideoWriter( + output_path, + fourcc, + fps, + (width, height), + isColor=True + ) + + if not out.isOpened(): + print("Error: VideoWriter failed to open") + return + + for frame in frames: + frame_array = cv2.cvtColor(np.array(frame), cv2.COLOR_RGB2BGR) + out.write(frame_array) + + out.release() + print(f"Video saved successfully to {output_path}") \ No newline at end of file diff --git a/exo/apputil/baseimages/image1.png b/exo/apputil/baseimages/image1.png new file mode 100644 index 000000000..b8375e7eb --- /dev/null +++ b/exo/apputil/baseimages/image1.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:361fdadd67c277d45cd18b0bfc8c5ceea5fd89f2d65aef157fd915ce9cbb8599 +size 814460 diff --git a/exo/apputil/baseimages/image2.png b/exo/apputil/baseimages/image2.png new file mode 100644 index 000000000..b2d4f31c9 --- /dev/null +++ b/exo/apputil/baseimages/image2.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f0e3891bc6b4f4dfa7444af53fcaa4b3ba06b0549546202be3243f08a0e6bd7e +size 814235 diff --git a/exo/apputil/baseimages/image3.png b/exo/apputil/baseimages/image3.png new file mode 100644 index 000000000..9ee38a572 --- /dev/null +++ b/exo/apputil/baseimages/image3.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a2dc5b3378aef397d60fd1252da8a1c578ad97e202a859590ffa416b49551d19 +size 146633 diff --git a/exo/apputil/baseimages/image4.png b/exo/apputil/baseimages/image4.png new file mode 100644 index 000000000..e0959d7b0 --- /dev/null +++ b/exo/apputil/baseimages/image4.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dbc6883e2a3c5233ec7b844c98646922bdc4f5e42e1f424857eaff56f785dbcd +size 668550 diff --git a/extra/dashboard/dashboard.py b/extra/dashboard/dashboard.py new file mode 100644 index 000000000..0ef6d3edd --- /dev/null +++ b/extra/dashboard/dashboard.py @@ -0,0 +1,1147 @@ +import os +import json +import logging +import asyncio +import aiohttp +import pandas as pd +import plotly.express as px +from typing import List, Dict, Optional +from pathlib import Path +from plotly.subplots import make_subplots +import plotly.graph_objects as go +import time +import pygame.mixer +from datetime import datetime + +class AsyncCircleCIClient: + def __init__(self, token: str, project_slug: str): + self.token = token + self.project_slug = project_slug + self.base_url = "https://circleci.com/api/v2" + self.headers = { + "Circle-Token": token, + "Accept": "application/json" + } + self.logger = logging.getLogger("CircleCI") + + async def get_json(self, session: aiohttp.ClientSession, url: str, params: Dict = None) -> Dict: + async with session.get(url, params=params) as response: + response.raise_for_status() + return await response.json() + + async def get_recent_pipelines( + self, + session: aiohttp.ClientSession, + org_slug: str = None, + page_token: str = None, + limit: int = None, + branch: str = None + ): + """ + Get recent pipelines for a project with pagination support + """ + params = { + "branch": branch, + "page-token": page_token + } + + # Remove None values + params = {k: v for k, v in params.items() if v is not None} + + url = f"{self.base_url}/project/{self.project_slug}/pipeline" + data = await self.get_json(session, url, params) + pipelines = data["items"] + + next_page_token = data.get("next_page_token") + + # If we have a limit, check if we need more pages + if limit and len(pipelines) >= limit: + return pipelines + + # If there are more pages and we haven't hit the limit, recursively get them + if next_page_token: + next_pipelines = await self.get_recent_pipelines( + session, + org_slug, + page_token=next_page_token, + limit=limit - len(pipelines) if limit else None, # Adjust limit for next page + branch=branch + ) + pipelines.extend(next_pipelines) + + return pipelines + + async def get_workflow_jobs(self, session: aiohttp.ClientSession, pipeline_id: str) -> List[Dict]: + self.logger.debug(f"Fetching workflows for pipeline {pipeline_id}") + url = f"{self.base_url}/pipeline/{pipeline_id}/workflow" + workflows_data = await self.get_json(session, url) + workflows = workflows_data["items"] + + # Fetch all jobs for all workflows in parallel + jobs_tasks = [] + for workflow in workflows: + url = f"{self.base_url}/workflow/{workflow['id']}/job" + jobs_tasks.append(self.get_json(session, url)) + + jobs_responses = await asyncio.gather(*jobs_tasks, return_exceptions=True) + + all_jobs = [] + for jobs_data in jobs_responses: + if isinstance(jobs_data, Exception): + continue + all_jobs.extend(jobs_data["items"]) + + return all_jobs + + async def get_artifacts(self, session: aiohttp.ClientSession, job_number: str) -> List[Dict]: + url = f"{self.base_url}/project/{self.project_slug}/{job_number}/artifacts" + data = await self.get_json(session, url) + return data["items"] + +class PackageSizeTracker: + def __init__(self, token: str, project_slug: str, debug: bool = False): + self.setup_logging(debug) + self.client = AsyncCircleCIClient(token, project_slug) + self.logger = logging.getLogger("PackageSizeTracker") + self.last_data_hash = None + self.debug = debug + + # Initialize pygame mixer + pygame.mixer.init() + + # Sound file paths - can use MP3 files with pygame + sounds_dir = Path(__file__).parent / "sounds" + self.sounds = { + 'lines_up': sounds_dir / "gta5_wasted.mp3", + 'lines_down': sounds_dir / "pokemon_evolve.mp3", + 'tokens_up': sounds_dir / "pokemon_evolve.mp3", + 'tokens_down': sounds_dir / "gta5_wasted.mp3", + 'size_up': sounds_dir / "gta5_wasted.mp3", + 'size_down': sounds_dir / "pokemon_evolve.mp3" + } + + def test_sound_effects(self): + """Test all sound effects with a small delay between each""" + self.logger.info("Testing sound effects...") + for sound_key in self.sounds: + self.logger.info(f"Playing {sound_key}") + self._play_sound(sound_key) + time.sleep(1) # Wait 1 second between sounds + + def setup_logging(self, debug: bool): + level = logging.DEBUG if debug else logging.INFO + logging.basicConfig( + level=level, + format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', + datefmt='%H:%M:%S' + ) + + def extract_commit_info(self, pipeline: Dict) -> Optional[Dict]: + try: + # Extract from github_app first (preferred) + if 'trigger_parameters' in pipeline and 'github_app' in pipeline['trigger_parameters']: + github_app = pipeline['trigger_parameters']['github_app'] + return { + 'commit_hash': github_app.get('checkout_sha'), + 'web_url': f"{github_app.get('repo_url')}/commit/{github_app.get('checkout_sha')}", + 'branch': github_app.get('branch', 'unknown'), + 'author': { + 'name': github_app.get('commit_author_name'), + 'email': github_app.get('commit_author_email'), + 'username': github_app.get('user_username') + }, + 'message': github_app.get('commit_message') + } + + # Fallback to git parameters + if 'trigger_parameters' in pipeline and 'git' in pipeline['trigger_parameters']: + git = pipeline['trigger_parameters']['git'] + return { + 'commit_hash': git.get('checkout_sha'), + 'web_url': f"{git.get('repo_url')}/commit/{git.get('checkout_sha')}", + 'branch': git.get('branch', 'unknown'), + 'author': { + 'name': git.get('commit_author_name'), + 'email': git.get('commit_author_email'), + 'username': git.get('author_login') + }, + 'message': git.get('commit_message') + } + + self.logger.warning(f"Could not find commit info in pipeline {pipeline['id']}") + return None + + except Exception as e: + self.logger.error(f"Error extracting commit info: {str(e)}") + return None + + async def process_pipeline(self, session: aiohttp.ClientSession, pipeline: Dict) -> Optional[Dict]: + try: + commit_info = self.extract_commit_info(pipeline) + if not commit_info: + return None + + data_point = { + "commit_hash": commit_info['commit_hash'], + "commit_url": commit_info['web_url'], + "timestamp": pipeline.get("created_at", pipeline.get("updated_at")), + "pipeline_status": pipeline.get("state", "unknown"), + "branch": commit_info['branch'], + "author": commit_info['author'], + "commit_message": commit_info['message'] + } + + jobs = await self.client.get_workflow_jobs(session, pipeline["id"]) + + # Get package size data + size_job = next( + (j for j in jobs if j["name"] == "measure_pip_sizes" and j["status"] == "success"), + None + ) + + # Get line count data + linecount_job = next( + (j for j in jobs if j["name"] == "check_line_count" and j["status"] == "success"), + None + ) + + # Get benchmark data from runner job + benchmark_job = next( + (j for j in jobs if j["name"] == "runner" and j["status"] == "success"), + None + ) + + # Return None if no relevant jobs found + if not size_job and not linecount_job and not benchmark_job: + self.logger.debug(f"No relevant jobs found for pipeline {pipeline['id']}") + return None + + # Process benchmark data if available + if benchmark_job: + benchmark_artifacts = await self.client.get_artifacts(session, benchmark_job["job_number"]) + benchmark_report = next( + (a for a in benchmark_artifacts if a["path"].endswith("benchmark.json")), + None + ) + if benchmark_report: + benchmark_data = await self.client.get_json(session, benchmark_report["url"]) + data_point.update({ + "tokens_per_second": benchmark_data["tokens_per_second"], + "time_to_first_token": benchmark_data.get("time_to_first_token", 0) + }) + self.logger.info( + f"Processed benchmark data for pipeline {pipeline['id']}: " + f"commit {commit_info['commit_hash'][:7]}, " + f"tokens/s {benchmark_data['tokens_per_second']:.2f}" + ) + + # Process size data if available + if size_job: + size_artifacts = await self.client.get_artifacts(session, size_job["job_number"]) + size_report = next( + (a for a in size_artifacts if a["path"].endswith("pip-sizes.json")), + None + ) + if size_report: + size_data = await self.client.get_json(session, size_report["url"]) + data_point.update({ + "total_size_mb": size_data["total_size_mb"], + "packages": size_data["packages"] + }) + self.logger.info( + f"Processed size data for pipeline {pipeline['id']}: " + f"commit {commit_info['commit_hash'][:7]}, " + f"size {size_data['total_size_mb']:.2f}MB" + ) + + # Process linecount data if available + if linecount_job: + linecount_artifacts = await self.client.get_artifacts(session, linecount_job["job_number"]) + linecount_report = next( + (a for a in linecount_artifacts if a["path"].endswith("line-count-snapshot.json")), + None + ) + if linecount_report: + linecount_data = await self.client.get_json(session, linecount_report["url"]) + data_point.update({ + "total_lines": linecount_data["total_lines"], + "total_files": linecount_data["total_files"], + "files": linecount_data["files"] + }) + self.logger.info( + f"Processed line count data for pipeline {pipeline['id']}: " + f"commit {commit_info['commit_hash'][:7]}, " + f"lines {linecount_data['total_lines']:,}" + ) + + return data_point + + except Exception as e: + self.logger.error(f"Error processing pipeline {pipeline['id']}: {str(e)}") + return None + + async def process_pipeline_batch( + self, + session: aiohttp.ClientSession, + pipelines: List[Dict], + batch_size: int = 5 + ) -> List[Dict]: + """ + Process a batch of pipelines with rate limiting. + + Args: + session: aiohttp client session + pipelines: List of pipelines to process + batch_size: Number of pipelines to process in parallel + + Returns: + List of processed pipeline data points + """ + data_points = [] + + for i in range(0, len(pipelines), batch_size): + batch = pipelines[i:i + batch_size] + + # Process batch in parallel + tasks = [self.process_pipeline(session, pipeline) for pipeline in batch] + batch_results = await asyncio.gather(*tasks) + + # Filter out None results + batch_data = [r for r in batch_results if r is not None] + data_points.extend(batch_data) + + # Add delay between batches if there are more to process + if i + batch_size < len(pipelines): + await asyncio.sleep(1) # 1 second delay between batches + + return data_points + + async def collect_data(self) -> List[Dict]: + self.logger.info("Starting data collection...") + async with aiohttp.ClientSession(headers=self.client.headers) as session: + # Get pipelines from main branch + main_pipelines = await self.client.get_recent_pipelines( + session, + org_slug=self.client.project_slug, + limit=20, + branch="main" + ) + + # Add delay between branch requests + await asyncio.sleep(2) + + # Get pipelines from circleci branch + circleci_pipelines = await self.client.get_recent_pipelines( + session, + org_slug=self.client.project_slug, + limit=20, + branch="circleci" + ) + + # Combine pipelines and sort by created_at date + pipelines = main_pipelines + circleci_pipelines + pipelines.sort( + key=lambda x: datetime.fromisoformat( + x.get("created_at", x.get("updated_at")).replace('Z', '+00:00') + ), + reverse=True # Most recent first + ) + + self.logger.info(f"Found {len(pipelines)} recent pipelines") + + # Process pipelines in batches + data_points = await self.process_pipeline_batch(session, pipelines) + + # Sort by timestamp + data_points.sort( + key=lambda x: datetime.fromisoformat( + x.get("timestamp").replace('Z', '+00:00') + ), + reverse=True # Most recent first + ) + + return data_points + + def generate_report(self, data: List[Dict], output_dir: str = "reports") -> Optional[str]: + self.logger.info("Generating report...") + if not data: + self.logger.error("No data to generate report from!") + return None + + # Get latest pipeline status based on errors + latest_main_pipeline = next((d for d in data if d.get('branch') == 'main'), None) + latest_pipeline_status = 'success' if latest_main_pipeline and not latest_main_pipeline.get('errors') else 'failure' + + # Log the pipeline status + if latest_main_pipeline: + self.logger.info( + f"Latest main branch pipeline status: {latest_pipeline_status} " + f"(commit: {latest_main_pipeline['commit_hash'][:7]})" + ) + else: + self.logger.warning("No pipeline data found for main branch") + + # Convert output_dir to Path object + output_dir = Path(output_dir) + + # Create output directory if it doesn't exist + output_dir.mkdir(parents=True, exist_ok=True) + + # Create separate dataframes for each metric + df_size = pd.DataFrame([d for d in data if 'total_size_mb' in d]) + df_lines = pd.DataFrame([d for d in data if 'total_lines' in d]) + df_benchmark = pd.DataFrame([d for d in data if 'tokens_per_second' in d]) + + # Create a single figure with subplots + fig = make_subplots( + rows=3, cols=2, + subplot_titles=('', 'Package Size', '', 'Line Count', '', 'Tokens per Second'), + vertical_spacing=0.2, + column_widths=[0.2, 0.8], + specs=[[{"type": "indicator"}, {"type": "scatter"}], + [None, {"type": "scatter"}], + [None, {"type": "scatter"}]] + ) + + # Add package size trace if we have data + if not df_size.empty: + df_size['timestamp'] = pd.to_datetime(df_size['timestamp']) + df_size = df_size.sort_values('timestamp') + + fig.add_trace( + go.Scatter( + x=df_size['timestamp'], + y=df_size['total_size_mb'], + mode='lines+markers', + name='Package Size', + customdata=df_size[['commit_hash', 'commit_url']].values, + hovertemplate="
".join([ + "Size: %{y:.2f}MB", + "Date: %{x}", + "Commit: %{customdata[0]}", + "" + ]) + ), + row=1, col=2 + ) + fig.update_yaxes(title_text="Size (MB)", row=1, col=2) + + # Add line count trace if we have data + if not df_lines.empty: + df_lines['timestamp'] = pd.to_datetime(df_lines['timestamp']) + df_lines = df_lines.sort_values('timestamp') + + fig.add_trace( + go.Scatter( + x=df_lines['timestamp'], + y=df_lines['total_lines'], + mode='lines+markers', + name='Line Count', + customdata=df_lines[['commit_hash', 'commit_url']].values, + hovertemplate="
".join([ + "Lines: %{y:,.0f}", + "Date: %{x}", + "Commit: %{customdata[0]}", + "" + ]) + ), + row=2, col=2 + ) + fig.update_yaxes(title_text="Total Lines", row=2, col=2) + + # Add tokens per second trace if we have data + if not df_benchmark.empty: + df_benchmark['timestamp'] = pd.to_datetime(df_benchmark['timestamp']) + df_benchmark = df_benchmark.sort_values('timestamp') + + fig.add_trace( + go.Scatter( + x=df_benchmark['timestamp'], + y=df_benchmark['tokens_per_second'], + mode='lines+markers', + name='Tokens/Second', + customdata=df_benchmark[['commit_hash', 'commit_url']].values, + hovertemplate="
".join([ + "Tokens/s: %{y:.2f}", + "Date: %{x}", + "Commit: %{customdata[0]}", + "" + ]) + ), + row=3, col=2 + ) + fig.update_yaxes(title_text="Tokens per Second", row=3, col=2) + + # Update layout + fig.update_layout( + height=800, + showlegend=False, + title_text="Package Metrics Dashboard", + title_x=0.5, + plot_bgcolor='white', + paper_bgcolor='white', + font=dict(size=12), + hovermode='x unified' + ) + + # Update the dashboard HTML with date range picker + dashboard_html = f""" + + + Package Metrics Dashboard + + + + +

+ +
+ + + + + + +
+
+ +
+
+
Pipeline Status
+
+
+ {'✓ Pipeline Passing' if latest_pipeline_status == 'success' else '✗ Pipeline Failing'} +
+
+
+
+
Package Size
+
+
+
+
Line Count
+
+
+
+
+
+
Tokens per Second
+
+
+
+
+ + + + + + + + + """ + + # Write the dashboard + dashboard_path = output_dir / "dashboard.html" + with open(dashboard_path, "w") as f: + f.write(dashboard_html) + + # Generate summary with available metrics + latest_data = {} + + if not df_size.empty: + latest = df_size.iloc[-1] + previous = df_size.iloc[-2] if len(df_size) > 1 else latest + size_change = float(latest['total_size_mb'] - previous['total_size_mb']) + latest_data.update({ + 'timestamp': latest['timestamp'].isoformat(), + 'commit_hash': latest['commit_hash'], + 'commit_url': latest['commit_url'], + 'total_size_mb': float(latest['total_size_mb']), + 'size_change_mb': size_change, + 'packages': latest.get('packages', []) + }) + + if not df_lines.empty: + latest = df_lines.iloc[-1] + previous = df_lines.iloc[-2] if len(df_lines) > 1 else latest + linecount_change = int(latest['total_lines'] - previous['total_lines']) + if not latest_data: # Only add timestamp and commit info if not already added + latest_data.update({ + 'timestamp': latest['timestamp'].isoformat(), + 'commit_hash': latest['commit_hash'], + 'commit_url': latest['commit_url'], + }) + latest_data.update({ + 'total_lines': int(latest['total_lines']), + 'linecount_change': linecount_change + }) + + if not df_benchmark.empty: + latest = df_benchmark.iloc[-1] + previous = df_benchmark.iloc[-2] if len(df_benchmark) > 1 else latest + tokens_change = float(latest['tokens_per_second'] - previous['tokens_per_second']) + if not latest_data: # Only add timestamp and commit info if not already added + latest_data.update({ + 'timestamp': latest['timestamp'].isoformat(), + 'commit_hash': latest['commit_hash'], + 'commit_url': latest['commit_url'], + }) + latest_data.update({ + 'tokens_per_second': float(latest['tokens_per_second']), + 'tokens_change': tokens_change + }) + + if latest_data: + with open(output_dir / 'latest_data.json', 'w') as f: + json.dump(latest_data, f, indent=2) + + self._print_summary(latest_data) + self.logger.info(f"Report generated in {output_dir}") + return str(output_dir) + + return None + + def _print_summary(self, latest_data: Dict): + print("\n=== Package Size Summary ===") + print(f"Timestamp: {latest_data['timestamp']}") + print(f"Commit: {latest_data['commit_hash'][:7]}") + + if 'total_size_mb' in latest_data: + print(f"Total Size: {latest_data['total_size_mb']:.2f}MB") + change = latest_data['size_change_mb'] + change_symbol = "↓" if change <= 0 else "↑" + print(f"Change: {change_symbol} {abs(change):.2f}MB") + + if latest_data.get('packages'): + print("\nTop 5 Largest Packages:") + sorted_packages = sorted(latest_data['packages'], key=lambda x: x['size_mb'], reverse=True) + for pkg in sorted_packages[:5]: + print(f"- {pkg['name']}: {pkg['size_mb']:.2f}MB") + + if 'total_lines' in latest_data: + print("\nLine Count Stats:") + print(f"Total Lines: {latest_data['total_lines']:,}") + change = latest_data['linecount_change'] + change_symbol = "↓" if change <= 0 else "↑" + print(f"Change: {change_symbol} {abs(change):,}") + + if 'tokens_per_second' in latest_data: + print("\nBenchmark Stats:") + print(f"Tokens per Second: {latest_data['tokens_per_second']:.2f}") + if 'time_to_first_token' in latest_data: + print(f"Time to First Token: {latest_data['time_to_first_token']:.3f}s") + + print("\n") + + def _calculate_data_hash(self, data: List[Dict]) -> str: + """Calculate a hash of the data to detect changes""" + return hash(str(sorted([ + (d.get('commit_hash'), d.get('timestamp')) + for d in data + ]))) + + def _play_sound(self, sound_key: str): + """Play a specific notification sound using pygame""" + try: + sound_path = self.sounds.get(sound_key) + if sound_path and sound_path.exists(): + sound = pygame.mixer.Sound(str(sound_path)) + sound.play() + # Wait for the sound to finish playing + pygame.time.wait(int(sound.get_length() * 1000)) + else: + self.logger.warning(f"Sound file not found: {sound_key} at {sound_path}") + except Exception as e: + self.logger.error(f"Failed to play sound {sound_key}: {e}") + + def _check_metrics_changes(self, current_data: List[Dict], previous_data: List[Dict]): + # Sort data by timestamp in descending order (most recent first) + def sort_by_timestamp(data): + return sorted( + data, + key=lambda x: x.get('timestamp', ''), + reverse=True # Most recent first + ) + + current_data = sort_by_timestamp(current_data) + previous_data = sort_by_timestamp(previous_data) + + # Helper to find latest entry with a specific metric + def find_latest_with_metric(data: List[Dict], metric: str) -> Optional[Dict]: + return next((d for d in data if metric in d), None) + + # Check line count changes + current_lines = find_latest_with_metric(current_data, 'total_lines') + previous_lines = find_latest_with_metric(previous_data, 'total_lines') + + if current_lines and previous_lines: + diff = current_lines['total_lines'] - previous_lines['total_lines'] + self.logger.debug(f"Lines of code diff: {diff}") + if diff > 0: + self.logger.info(f"Lines of code increased by {diff:,}") + self._play_sound('lines_up') + elif diff < 0: + self.logger.info(f"Lines of code decreased by {abs(diff):,}") + self._play_sound('lines_down') + else: + self.logger.debug("No lines of code data found") + + # Check tokens per second changes + current_tokens = find_latest_with_metric(current_data, 'tokens_per_second') + previous_tokens = find_latest_with_metric(previous_data, 'tokens_per_second') + + if current_tokens and previous_tokens: + diff = current_tokens['tokens_per_second'] - previous_tokens['tokens_per_second'] + self.logger.debug(f"Tokens per second diff: {diff}") + if diff > 0: + self.logger.info(f"Tokens per second increased by {diff:.2f}") + self._play_sound('tokens_up') + elif diff < 0: + self.logger.info(f"Tokens per second decreased by {abs(diff):.2f}") + self._play_sound('tokens_down') + else: + self.logger.debug("No tokens per second data found") + + # Check package size changes + current_size = find_latest_with_metric(current_data, 'total_size_mb') + previous_size = find_latest_with_metric(previous_data, 'total_size_mb') + + if current_size and previous_size: + diff = current_size['total_size_mb'] - previous_size['total_size_mb'] + self.logger.debug(f"Package size diff: {diff:.2f}MB") + if diff > 0: + self.logger.info(f"Package size increased by {diff:.2f}MB") + self._play_sound('size_up') + elif diff < 0: + self.logger.info(f"Package size decreased by {abs(diff):.2f}MB") + self._play_sound('size_down') + else: + self.logger.debug("No package size data found") + + async def run_dashboard(self, update_interval: int = 10): + """Run the dashboard with periodic updates""" + try: + update_interval = float(update_interval) + self.logger.debug(f"Update interval type: {type(update_interval)}, value: {update_interval}") + except ValueError as e: + self.logger.error(f"Failed to convert update_interval to float: {update_interval}") + raise + + self.logger.info(f"Starting real-time dashboard with {update_interval}s updates") + previous_data = None + + while True: + try: + start_time = time.time() + + # Collect new data + current_data = await self.collect_data() + if not current_data: + self.logger.warning("No data collected") + await asyncio.sleep(update_interval) + continue + + # Generate report + report_path = self.generate_report(current_data) + if report_path: + self.logger.info( + f"Dashboard updated at {datetime.now().strftime('%H:%M:%S')}" + ) + + print("Curr:", len(current_data)) + print("Prev:", len(previous_data) if previous_data else "None") + if previous_data: + # Check for metric changes and play appropriate sounds + self.logger.debug(f"Checking metrics changes between {len(current_data)} current and {len(previous_data)} previous data points") + self._check_metrics_changes(current_data, previous_data) + + # Update previous data + previous_data = current_data.copy() # Make a copy to prevent reference issues + + # Calculate sleep time + elapsed = float(time.time() - start_time) + sleep_time = max(0.0, update_interval - elapsed) + await asyncio.sleep(sleep_time) + + except Exception as e: + self.logger.error(f"Error in dashboard update loop: {e}", exc_info=True) + if self.debug: + raise + await asyncio.sleep(update_interval) + +async def main(): + token = os.getenv("CIRCLECI_TOKEN") + project_slug = os.getenv("CIRCLECI_PROJECT_SLUG") + debug = os.getenv("DEBUG", "").lower() in ("true", "1", "yes") + + try: + # Get update interval from environment or use default + update_interval = float(os.getenv("UPDATE_INTERVAL", "10")) + print(f"Update interval type: {type(update_interval)}, value: {update_interval}") # Debug print + except ValueError as e: + print(f"Error converting UPDATE_INTERVAL to float: {os.getenv('UPDATE_INTERVAL')}") + update_interval = 10.0 + + if not token or not project_slug: + print("Error: Please set CIRCLECI_TOKEN and CIRCLECI_PROJECT_SLUG environment variables") + return + + tracker = PackageSizeTracker(token, project_slug, debug) + + try: + await tracker.run_dashboard(update_interval) + except KeyboardInterrupt: + print("\nDashboard stopped by user") + except Exception as e: + logging.error(f"Error: {str(e)}", exc_info=True) + if debug: + raise + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/extra/dashboard/requirements.txt b/extra/dashboard/requirements.txt new file mode 100644 index 000000000..7b978bc0e --- /dev/null +++ b/extra/dashboard/requirements.txt @@ -0,0 +1,5 @@ +plotly +pandas +requests +aiohttp +pygame \ No newline at end of file diff --git a/extra/dashboard/sounds/gta5_wasted.mp3 b/extra/dashboard/sounds/gta5_wasted.mp3 new file mode 100644 index 000000000..2723ff8a4 --- /dev/null +++ b/extra/dashboard/sounds/gta5_wasted.mp3 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fb3fb66dd02827fbff86ef1ce3bc6438371c823aed7d4c3803ed522f008e4947 +size 206399 diff --git a/extra/dashboard/sounds/pokemon_evolve.mp3 b/extra/dashboard/sounds/pokemon_evolve.mp3 new file mode 100644 index 000000000..35b014323 --- /dev/null +++ b/extra/dashboard/sounds/pokemon_evolve.mp3 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d99cc9bdab4a4639d50f439b424547000e7c79f195b5b121734ad4ead435911c +size 633345 diff --git a/extra/line_counter.py b/extra/line_counter.py new file mode 100644 index 000000000..e5bf04289 --- /dev/null +++ b/extra/line_counter.py @@ -0,0 +1,210 @@ +#!/usr/bin/env python3 +import os +import sys +import json +import token +import tokenize +from datetime import datetime, timezone + +TOKEN_WHITELIST = [token.OP, token.NAME, token.NUMBER, token.STRING] + +def is_docstring(t): + return t.type == token.STRING and t.string.startswith('"""') and t.line.strip().startswith('"""') + +def gen_stats(base_path="."): + table = [] + exo_path = os.path.join(base_path, "exo") + if not os.path.exists(exo_path): + print(f"Warning: {exo_path} directory not found") + return table + + for path, _, files in os.walk(exo_path): + for name in files: + if not name.endswith(".py"): + continue + + filepath = os.path.join(path, name) + relfilepath = os.path.relpath(filepath, base_path).replace('\\', '/') + + try: + with tokenize.open(filepath) as file_: + tokens = [t for t in tokenize.generate_tokens(file_.readline) + if t.type in TOKEN_WHITELIST and not is_docstring(t)] + token_count = len(tokens) + line_count = len(set([x for t in tokens + for x in range(t.start[0], t.end[0]+1)])) + if line_count > 0: + table.append([relfilepath, line_count, token_count/line_count]) + except Exception as e: + print(f"Error processing {filepath}: {e}") + continue + + return table + +def gen_diff(table_old, table_new): + table = [] + files_new = set([x[0] for x in table_new]) + files_old = set([x[0] for x in table_old]) + + added = files_new - files_old + deleted = files_old - files_new + unchanged = files_new & files_old + + for file in added: + file_stat = [stats for stats in table_new if file in stats][0] + table.append([file_stat[0], file_stat[1], file_stat[1], file_stat[2], file_stat[2]]) + + for file in deleted: + file_stat = [stats for stats in table_old if file in stats][0] + table.append([file_stat[0], 0, -file_stat[1], 0, -file_stat[2]]) + + for file in unchanged: + file_stat_old = [stats for stats in table_old if file in stats][0] + file_stat_new = [stats for stats in table_new if file in stats][0] + if file_stat_new[1] != file_stat_old[1] or file_stat_new[2] != file_stat_old[2]: + table.append([ + file_stat_new[0], + file_stat_new[1], + file_stat_new[1] - file_stat_old[1], + file_stat_new[2], + file_stat_new[2] - file_stat_old[2] + ]) + + return table + +def create_json_report(table, is_diff=False): + timestamp = datetime.now(timezone.utc).isoformat() + commit_sha = os.environ.get('CIRCLE_SHA1', 'unknown') + branch = os.environ.get('CIRCLE_BRANCH', 'unknown') + pr_number = os.environ.get('CIRCLE_PR_NUMBER', '') + + if is_diff: + files = [{ + 'name': row[0], + 'current_lines': row[1], + 'line_diff': row[2], + 'current_tokens_per_line': row[3], + 'tokens_per_line_diff': row[4] + } for row in table] + + report = { + 'type': 'diff', + 'timestamp': timestamp, + 'commit_sha': commit_sha, + 'branch': branch, + 'pr_number': pr_number, + 'files': files, + 'total_line_changes': sum(row[2] for row in table), + 'total_files_changed': len(files) + } + else: + files = [{ + 'name': row[0], + 'lines': row[1], + 'tokens_per_line': row[2] + } for row in table] + + report = { + 'type': 'snapshot', + 'timestamp': timestamp, + 'commit_sha': commit_sha, + 'branch': branch, + 'files': files, + 'total_lines': sum(row[1] for row in table), + 'total_files': len(files) + } + + return report + +def display_diff(diff): + return "+" + str(diff) if diff > 0 else str(diff) + +def format_table(rows, headers, floatfmt): + if not rows: + return "" + + # Add headers as first row + all_rows = [headers] + rows + + # Calculate column widths + col_widths = [] + for col in range(len(headers)): + col_width = max(len(str(row[col])) for row in all_rows) + col_widths.append(col_width) + + # Format rows + output = [] + for row_idx, row in enumerate(all_rows): + formatted_cols = [] + for col_idx, (value, width) in enumerate(zip(row, col_widths)): + if isinstance(value, float): + # Handle float formatting based on floatfmt + fmt = floatfmt[col_idx] + if fmt.startswith('+'): + value = f"{value:+.1f}" + else: + value = f"{value:.1f}" + elif isinstance(value, int) and col_idx > 0: # Skip filename column + # Handle integer formatting based on floatfmt + fmt = floatfmt[col_idx] + if fmt.startswith('+'): + value = f"{value:+d}" + else: + value = f"{value:d}" + formatted_cols.append(str(value).ljust(width)) + output.append(" ".join(formatted_cols)) + + # Add separator line after headers + if row_idx == 0: + separator = [] + for width in col_widths: + separator.append("-" * width) + output.append(" ".join(separator)) + + return "\n".join(output) + +if __name__ == "__main__": + if len(sys.argv) == 3: + # Comparing two directories + headers = ["File", "Lines", "Diff", "Tokens/Line", "Diff"] + table = gen_diff(gen_stats(sys.argv[1]), gen_stats(sys.argv[2])) + + if table: + # Print table output + print("### Code Changes in 'exo' Directory") + print("```") + print(format_table( + sorted(table, key=lambda x: abs(x[2]) if len(x) > 2 else 0, reverse=True), + headers, + (".1f", "d", "+d", ".1f", "+.1f") + )) + total_changes = sum(row[2] for row in table) + print(f"\nTotal line changes: {display_diff(total_changes)}") + print("```") + + # Generate JSON report + report = create_json_report(table, is_diff=True) + with open('line-count-diff.json', 'w') as f: + json.dump(report, f, indent=2) + else: + # Single directory analysis + headers = ["File", "Lines", "Tokens/Line"] + table = gen_stats(sys.argv[1] if len(sys.argv) > 1 else ".") + + if table: + # Print table output + print("### Code Statistics for 'exo' Directory") + print("```") + print(format_table( + sorted(table, key=lambda x: x[1], reverse=True), + headers, + (".1f", "d", ".1f") + )) + total_lines = sum(row[1] for row in table) + print(f"\nTotal lines: {total_lines}") + print("```") + + # Generate JSON report + report = create_json_report(table, is_diff=False) + with open('line-count-snapshot.json', 'w') as f: + json.dump(report, f, indent=2) diff --git a/extra/pipsize.py b/extra/pipsize.py new file mode 100644 index 000000000..406d177cc --- /dev/null +++ b/extra/pipsize.py @@ -0,0 +1,113 @@ +import os +import importlib.metadata +import importlib.util +import json +import sys + + +def calc_container(path): + """Calculate total size of a directory or file.""" + if os.path.isfile(path): + try: + return os.path.getsize(path) + except (OSError, FileNotFoundError): + return 0 + + total_size = 0 + for dirpath, dirnames, filenames in os.walk(path): + for f in filenames: + fp = os.path.join(dirpath, f) + try: + total_size += os.path.getsize(fp) + except (OSError, FileNotFoundError): + continue + return total_size + + +def get_package_location(package_name): + """Get the actual location of a package's files.""" + try: + spec = importlib.util.find_spec(package_name) + if spec is None: + return None + + if spec.submodule_search_locations: + # Return the first location for namespace packages + return spec.submodule_search_locations[0] + elif spec.origin: + # For single-file modules, return the file path itself + return spec.origin + except ImportError: + return None + + +def get_package_sizes(min_size_mb=0.1): + """Get sizes of installed packages above minimum size threshold.""" + package_sizes = [] + + # Get all installed distributions + for dist in importlib.metadata.distributions(): + try: + package_name = dist.metadata["Name"] + location = get_package_location(package_name.replace("-", "_")) + + if location and os.path.exists(location): + size = calc_container(location) + size_mb = size / (1024 * 1024) + + if size_mb > min_size_mb: + package_sizes.append((package_name, size)) + except Exception as e: + print( + f"Error processing {dist.metadata.get('Name', 'Unknown package')}: {e}" + ) + + return package_sizes + + +def main(): + # Get and sort package sizes + package_sizes = get_package_sizes() + package_sizes.sort(key=lambda x: x[1], reverse=True) + + # Convert sizes to MB and prepare data + table_data = [(name, size/(1024*1024)) for name, size in package_sizes] + total_size = sum(size for _, size in package_sizes)/(1024*1024) + + # Check if --json flag is present + if "--json" in sys.argv: + try: + output_file = sys.argv[sys.argv.index("--json") + 1] + json_data = { + "packages": [{ + "name": name, + "size_mb": round(size, 2) + } for name, size in table_data], + "total_size_mb": round(total_size, 2) + } + + with open(output_file, 'w') as f: + json.dump(json_data, f, indent=2) + print(f"JSON data written to {output_file}") + return + except IndexError: + print("Error: Please provide a filename after --json") + sys.exit(1) + except Exception as e: + print(f"Error writing JSON file: {e}") + sys.exit(1) + + # Original table output code + max_name_width = max(len(name) for name, _ in table_data) + max_name_width = max(max_name_width, len("Package")) + + print(f"\n{'Package':<{max_name_width}} | Size (MB)") + print("-" * max_name_width + "-+-" + "-" * 10) + + for name, size in table_data: + print(f"{name:<{max_name_width}} | {size:>8.2f}") + + print(f"\nTotal size: {total_size:.2f} MB\n") + +if __name__ == "__main__": + main() \ No newline at end of file From cb270ed0e6272b1630a97945c7d9c7aad774ff23 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Thu, 12 Dec 2024 11:52:27 +0800 Subject: [PATCH 15/26] filter: chat-api modelpool for Local model --- exo/api/chatgpt_api.py | 21 ++++++++++++------- exo/inference/mlx/sharded_inference_engine.py | 4 ++-- exo/main.py | 2 +- 3 files changed, 16 insertions(+), 11 deletions(-) diff --git a/exo/api/chatgpt_api.py b/exo/api/chatgpt_api.py index 8f07c594e..b05a78788 100644 --- a/exo/api/chatgpt_api.py +++ b/exo/api/chatgpt_api.py @@ -241,14 +241,19 @@ async def handle_model_support(self, request): if self.inference_engine_classname in model_info.get("repo", {}): shard = build_base_shard(model_name, self.inference_engine_classname) if shard: - downloader = HFShardDownloader(quick_check=True) - downloader.current_shard = shard - downloader.current_repo_id = get_repo(shard.model_id, self.inference_engine_classname) - status = await downloader.get_shard_download_status() - - download_percentage = status.get("overall") if status else None - total_size = status.get("total_size") if status else None - total_downloaded = status.get("total_downloaded") if status else False + if 'Local/' in model_name: + download_percentage = 100.0 + total_size = "Unknown" + total_downloaded = "Unknown" + else: + downloader = HFShardDownloader(quick_check=True) + downloader.current_shard = shard + downloader.current_repo_id = get_repo(shard.model_id, self.inference_engine_classname) + status = await downloader.get_shard_download_status() + + download_percentage = status.get("overall") if status else None + total_size = status.get("total_size") if status else None + total_downloaded = status.get("total_downloaded") if status else False model_data = { model_name: { diff --git a/exo/inference/mlx/sharded_inference_engine.py b/exo/inference/mlx/sharded_inference_engine.py index 8a4bb6328..e81023a8e 100644 --- a/exo/inference/mlx/sharded_inference_engine.py +++ b/exo/inference/mlx/sharded_inference_engine.py @@ -140,9 +140,9 @@ async def ensure_shard(self, shard: Shard): if self.shard == shard: return - if os.path.isdir(shard.model_id): # cli mode + if os.path.isdir(shard.model_id): # path mode model_path = Path(shard.model_id) - elif "Local" in shard.model_id: # api mode + elif "Local" in shard.model_id: # Local card mode model_path = Path(get_repo(shard.model_id, self.__class__.__name__)) else: model_path = await self.shard_downloader.ensure_shard(shard, self.__class__.__name__) diff --git a/exo/main.py b/exo/main.py index 3113b0ec2..30fb1d32f 100644 --- a/exo/main.py +++ b/exo/main.py @@ -100,7 +100,7 @@ config = json.load(file) config_n_layers = config['num_hidden_layers'] build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, int(config_n_layers)) -print(f"Init local model card complete") +print(f"Add Local Model Complete!!") if args.node_port is None: args.node_port = find_available_port(args.node_host) From 316e58b0b6d1f86f2052097bb6cdcca5a9888110 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Thu, 12 Dec 2024 16:14:20 +0800 Subject: [PATCH 16/26] add: Local Model Api --- exo/localmodel/http_helpers.py | 42 +++++++++ exo/localmodel/http_server.py | 166 +++++++++++++++++++++++++++++++++ exo/main.py | 29 +++++- exo/viz/topology_viz.py | 5 +- 4 files changed, 236 insertions(+), 6 deletions(-) create mode 100644 exo/localmodel/http_helpers.py create mode 100644 exo/localmodel/http_server.py diff --git a/exo/localmodel/http_helpers.py b/exo/localmodel/http_helpers.py new file mode 100644 index 000000000..19ed00a84 --- /dev/null +++ b/exo/localmodel/http_helpers.py @@ -0,0 +1,42 @@ +from aiohttp import web +import aiohttp_cors +import os +import json +from pathlib import Path +from datetime import datetime +from typing import Dict +from exo import DEBUG + +async def download_model(model_name, target_dir): + url = f"http://localhost:52525/models/{model_name}/download" + async with aiohttp.ClientSession() as session: + async with session.get(url) as response: + current_file = None + current_writer = None + + async for line in response.content: + try: + # Try parsing as metadata + metadata = json.loads(line) + if current_writer: + await current_writer.close() + + # Setup new file + filepath = os.path.join(target_dir, metadata['filename']) + os.makedirs(os.path.dirname(filepath), exist_ok=True) + current_file = open(filepath, 'wb') + current_writer = current_file + continue + except json.JSONDecodeError: + pass + + # Check for EOF marker + if line.strip() == b'EOF': + if current_writer: + await current_writer.close() + current_writer = None + continue + + # Write chunk to current file + if current_writer: + current_writer.write(line) \ No newline at end of file diff --git a/exo/localmodel/http_server.py b/exo/localmodel/http_server.py new file mode 100644 index 000000000..55bf434ab --- /dev/null +++ b/exo/localmodel/http_server.py @@ -0,0 +1,166 @@ +from aiohttp import web +import aiohttp_cors +import os +import json +from pathlib import Path +from datetime import datetime +from typing import Dict +from exo import DEBUG + +class LocalModelAPI: + def __init__(self): + self.app = web.Application() + self.cache_dir = os.path.expanduser('~/.cache/exo') + Path(self.cache_dir).mkdir(parents=True, exist_ok=True) + + # Setup CORS + cors = aiohttp_cors.setup(self.app) + cors_options = aiohttp_cors.ResourceOptions( + allow_credentials=True, + expose_headers="*", + allow_headers="*", + allow_methods="*" + ) + + # Add routes with CORS + routes = [ + ('GET', '/files/{filename}', self.handle_download_file), + ('GET', '/files', self.handle_list_files), + ('GET', '/models', self.handle_list_models), + ('GET', '/models/{foldername}/files', self.handle_list_model_files), + ('GET', '/models/{model_name}/download', self.handle_model_download) + ] + + for method, path, handler in routes: + cors.add(self.app.router.add_route(method, path, handler), {"*": cors_options}) + + # Add middleware + self.app.middlewares.append(self.log_request) + + async def log_request(self, app, handler): + async def middleware(request): + if DEBUG >= 2: + print(f"Received request: {request.method} {request.path}") + return await handler(request) + return middleware + + async def handle_download_file(self, request): + filename = request.match_info['filename'] + file_path = os.path.join(self.cache_dir, filename) + + if not os.path.exists(file_path): + return web.json_response({"error": "File not found"}, status=404) + + return web.FileResponse(file_path) + + async def handle_list_files(self, request): + files = [] + for entry in os.scandir(self.cache_dir): + if entry.is_file() and not entry.name.startswith('.'): + stat = entry.stat() + files.append({ + 'name': entry.name, + 'size': stat.st_size, + 'modified': datetime.fromtimestamp(stat.st_mtime).isoformat() + }) + return web.json_response({'files': files}) + + async def handle_model_download(self, request): + model_name = request.match_info['model_name'] + chunk_size = 32768 # 32KB chunks for better performance + model_path = os.path.join(self.cache_dir, model_name) + + if not os.path.exists(model_path): + return web.json_response({"error": "Model not found"}, status=404) + + if not os.path.isdir(model_path): + return web.json_response({"error": "Not a valid model directory"}, status=400) + + # Setup streaming response + response = web.StreamResponse( + status=200, + reason='OK', + headers={ + 'Content-Type': 'application/octet-stream' + } + ) + await response.prepare(request) + + # Walk through directory and stream files + for root, _, files in os.walk(model_path): + for filename in files: + if filename.startswith('.'): + continue + + file_path = os.path.join(root, filename) + rel_path = os.path.relpath(file_path, model_path) + + if DEBUG >= 2: + print(f"Streaming file: {rel_path}") + + # Send file metadata + metadata = { + 'filename': rel_path, + 'size': os.path.getsize(file_path) + } + await response.write(json.dumps(metadata).encode() + b'\n') + + # Stream file content in chunks + with open(file_path, 'rb') as f: + while True: + chunk = f.read(chunk_size) + if not chunk: + break + await response.write(chunk) + + # Send end of file marker + await response.write(b'EOF\n') + + await response.write_eof() + return response + + async def handle_list_models(self, request): + folders = [] + for entry in os.scandir(self.cache_dir): + if entry.is_dir() and not entry.name.startswith('.'): + folder_size = sum( + f.stat().st_size for f in Path(entry.path).rglob('*') if f.is_file() + ) + folders.append({ + 'name': entry.name, + 'size': folder_size, + 'modified': datetime.fromtimestamp(entry.stat().st_mtime).isoformat() + }) + return web.json_response({'models': folders}) + + async def handle_list_model_files(self, request): + foldername = request.match_info['foldername'] + folder_path = os.path.join(self.cache_dir, foldername) + + if not os.path.exists(folder_path): + return web.json_response({"error": "Folder not found"}, status=404) + + if not os.path.isdir(folder_path): + return web.json_response({"error": "Not a valid folder"}, status=400) + + files = [] + for root, dirs, filenames in os.walk(folder_path): + dirs[:] = [d for d in dirs if not d.startswith('.')] + for filename in filenames: + if filename.startswith('.'): + continue + file_path = os.path.join(root, filename) + rel_path = os.path.relpath(file_path, folder_path) + files.append({ + 'name': rel_path, + 'size': os.path.getsize(file_path), + 'modified': datetime.fromtimestamp(os.path.getmtime(file_path)).isoformat() + }) + + return web.json_response({'files': files}) + + async def run(self, host: str = "0.0.0.0", port: int = 52525): + runner = web.AppRunner(self.app) + await runner.setup() + site = web.TCPSite(runner, host, port) + await site.start() diff --git a/exo/main.py b/exo/main.py index 30fb1d32f..99a6fc07a 100644 --- a/exo/main.py +++ b/exo/main.py @@ -36,6 +36,8 @@ from exo.viz.topology_viz import TopologyViz from exo.download.hf.hf_helpers import has_hf_home_read_access, has_hf_home_write_access, get_hf_home, move_models_to_hf +from exo.localmodel.http_server import LocalModelAPI + # parse args parser = argparse.ArgumentParser(description="Initialize GRPC Discovery") parser.add_argument("command", nargs="?", choices=["run", "eval", "train"], help="Command to run") @@ -71,6 +73,7 @@ parser.add_argument("--tailscale-api-key", type=str, default=None, help="Tailscale API key") parser.add_argument("--tailnet-name", type=str, default=None, help="Tailnet name") parser.add_argument("--node-id-filter", type=str, default=None, help="Comma separated list of allowed node IDs (only for UDP and Tailscale discovery)") +parser.add_argument("--local-model-api-port", type=int, default=52525, help="Local Model API port") args = parser.parse_args() print(f"Selected inference engine: {args.inference_engine}") @@ -107,16 +110,30 @@ if DEBUG >= 1: print(f"Using available port: {args.node_port}") args.node_id = args.node_id or get_or_create_node_id() -chatgpt_api_endpoints = [f"http://{ip}:{args.chatgpt_api_port}/v1/chat/completions" for ip, _ in get_all_ip_addresses_and_interfaces()] -web_chat_urls = [f"http://{ip}:{args.chatgpt_api_port}" for ip, _ in get_all_ip_addresses_and_interfaces()] + + +if args.node_host == "0.0.0.0": + chatgpt_api_endpoints = [f"http://{ip}:{args.chatgpt_api_port}/v1/chat/completions" for ip, _ in get_all_ip_addresses_and_interfaces()] + local_model_api_endpoints = [f"http://{ip}:{args.local_model_api_port}" for ip, _ in get_all_ip_addresses_and_interfaces()] + web_chat_urls = [f"http://{ip}:{args.chatgpt_api_port}" for ip, _ in get_all_ip_addresses_and_interfaces()] +else: + chatgpt_api_endpoints = [f"http://{args.node_host}:{args.chatgpt_api_port}/v1/chat/completions"] + local_model_api_endpoints = [f"http://{args.node_host}:{args.local_model_api_port}"] + web_chat_urls = [f"http://{args.node_host}:{args.chatgpt_api_port}"] + if DEBUG >= 0: print("Chat interface started:") for web_chat_url in web_chat_urls: print(f" - {terminal_link(web_chat_url)}") + print("ChatGPT API endpoint served at:") for chatgpt_api_endpoint in chatgpt_api_endpoints: print(f" - {terminal_link(chatgpt_api_endpoint)}") + print("Local Model API endpoint served at:") + for local_model_api_endpoint in local_model_api_endpoints: + print(f" - {terminal_link(local_model_api_endpoint)}") + # Convert node-id-filter to list if provided allowed_node_ids = args.node_id_filter.split(',') if args.node_id_filter else None @@ -144,7 +161,7 @@ if not args.discovery_config_path: raise ValueError(f"--discovery-config-path is required when using manual discovery. Please provide a path to a config json file.") discovery = ManualDiscovery(args.discovery_config_path, args.node_id, create_peer_handle=lambda peer_id, address, description, device_capabilities: GRPCPeerHandle(peer_id, address, description, device_capabilities)) -topology_viz = TopologyViz(chatgpt_api_endpoints=chatgpt_api_endpoints, web_chat_urls=web_chat_urls) if not args.disable_tui else None +topology_viz = TopologyViz(chatgpt_api_endpoints=chatgpt_api_endpoints, web_chat_urls=web_chat_urls, local_model_api_endpoints=local_model_api_endpoints) if not args.disable_tui else None node = Node( args.node_id, None, @@ -158,13 +175,14 @@ ) server = GRPCServer(node, args.node_host, args.node_port) node.server = server -api = ChatGPTAPI( +chatgpt_api = ChatGPTAPI( node, inference_engine.__class__.__name__, response_timeout=args.chatgpt_api_response_timeout, on_chat_completion_request=lambda req_id, __, prompt: topology_viz.update_prompt(req_id, prompt) if topology_viz else None, default_model=args.default_model ) +local_model_api = LocalModelAPI() node.on_token.register("update_topology_viz").on_next( lambda req_id, tokens, __: topology_viz.update_prompt_output(req_id, inference_engine.tokenizer.decode(tokens)) if topology_viz and hasattr(inference_engine, "tokenizer") else None ) @@ -372,7 +390,8 @@ def handle_exit(): await train_model_cli(node, inference_engine, model_name, dataloader, args.batch_size, args.iters, save_interval=args.save_every, checkpoint_dir=args.save_checkpoint_dir) else: - asyncio.create_task(api.run(port=args.chatgpt_api_port)) # Start the API server as a non-blocking task + asyncio.create_task(chatgpt_api.run(host=args.node_host, port=args.chatgpt_api_port)) # Start the API server as a non-blocking task + asyncio.create_task(local_model_api.run(host=args.node_host, port=args.local_model_api_port)) # Start the local model server as a non-blocking task await asyncio.Event().wait() if args.wait_for_peers > 0: diff --git a/exo/viz/topology_viz.py b/exo/viz/topology_viz.py index 1519612fd..bd59a1cd9 100644 --- a/exo/viz/topology_viz.py +++ b/exo/viz/topology_viz.py @@ -18,8 +18,9 @@ class TopologyViz: - def __init__(self, chatgpt_api_endpoints: List[str] = [], web_chat_urls: List[str] = []): + def __init__(self, chatgpt_api_endpoints: List[str] = [], web_chat_urls: List[str] = [], local_model_api_endpoints: List[str] = []): self.chatgpt_api_endpoints = chatgpt_api_endpoints + self.local_model_api_endpoints = local_model_api_endpoints self.web_chat_urls = web_chat_urls self.topology = Topology() self.partitions: List[Partition] = [] @@ -149,6 +150,8 @@ def _generate_main_layout(self) -> str: info_lines = [] if len(self.web_chat_urls) > 0: info_lines.append(f"Web Chat URL (tinychat): {' '.join(self.web_chat_urls[:1])}") + if len(self.local_model_api_endpoints) > 0: + info_lines.append(f"Local Model API endpoint: {' '.join(self.local_model_api_endpoints[:1])}") if len(self.chatgpt_api_endpoints) > 0: info_lines.append(f"ChatGPT API endpoint: {' '.join(self.chatgpt_api_endpoints[:1])}") From 961c0dc5a5fe09ba81c9620bb59cb666205b4a37 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Thu, 12 Dec 2024 17:41:27 +0800 Subject: [PATCH 17/26] filter: file&code to other palce --- exo/download/hf/hf_shard_download.py | 8 +- exo/helpers.py | 7 - exo/localmodel/{ => http}/http_helpers.py | 0 exo/localmodel/{ => http}/http_server.py | 0 exo/localmodel/lh_helpers.py | 447 ++++++++++++++++++++++ exo/main.py | 25 +- 6 files changed, 473 insertions(+), 14 deletions(-) rename exo/localmodel/{ => http}/http_helpers.py (100%) rename exo/localmodel/{ => http}/http_server.py (100%) create mode 100644 exo/localmodel/lh_helpers.py diff --git a/exo/download/hf/hf_shard_download.py b/exo/download/hf/hf_shard_download.py index 7428909f5..438590f8f 100644 --- a/exo/download/hf/hf_shard_download.py +++ b/exo/download/hf/hf_shard_download.py @@ -16,6 +16,7 @@ import aiohttp from aiofiles import os as aios +from exo.localmodel.lh_helpers import get_exo_home class HFShardDownloader(ShardDownloader): def __init__(self, quick_check: bool = False, max_parallel_downloads: int = 4): @@ -36,7 +37,12 @@ async def ensure_shard(self, shard: Shard, inference_engine_name: str) -> Path: return self.completed_downloads[shard] if self.quick_check: repo_root = get_repo_root(repo_name) - snapshots_dir = repo_root/"snapshots" + if 'Local' in shard.model_id: + model_name = shard.model_id.split('/')[1] + snapshots_dir = Path(get_exo_home()/model_name) + else: + snapshots_dir = repo_root/"snapshots" + if snapshots_dir.exists(): visible_dirs = [d for d in snapshots_dir.iterdir() if not d.name.startswith('.')] if visible_dirs: diff --git a/exo/helpers.py b/exo/helpers.py index 24d4bf9af..5552524e8 100644 --- a/exo/helpers.py +++ b/exo/helpers.py @@ -93,16 +93,9 @@ def terminal_link(uri, label=None): return escape_mask.format(parameters, uri, label) -def init_exo_env(): - exo_path = Path(Path.home()/".cache"/"exo") - os.makedirs(exo_path, exist_ok=True) - if DEBUG >= 1: print(f"Init exo folder: {exo_path}") - return exo_path - T = TypeVar("T") K = TypeVar("K") - class AsyncCallback(Generic[T]): def __init__(self) -> None: self.condition: asyncio.Condition = asyncio.Condition() diff --git a/exo/localmodel/http_helpers.py b/exo/localmodel/http/http_helpers.py similarity index 100% rename from exo/localmodel/http_helpers.py rename to exo/localmodel/http/http_helpers.py diff --git a/exo/localmodel/http_server.py b/exo/localmodel/http/http_server.py similarity index 100% rename from exo/localmodel/http_server.py rename to exo/localmodel/http/http_server.py diff --git a/exo/localmodel/lh_helpers.py b/exo/localmodel/lh_helpers.py new file mode 100644 index 000000000..103efc210 --- /dev/null +++ b/exo/localmodel/lh_helpers.py @@ -0,0 +1,447 @@ +import aiofiles.os as aios +from typing import Union +import asyncio +import aiohttp +import json +import os +import sys +import shutil +from urllib.parse import urljoin +from typing import Callable, Optional, Coroutine, Any, Dict, List, Union, Literal +from datetime import datetime, timedelta +from fnmatch import fnmatch +from pathlib import Path +from typing import Generator, Iterable, TypeVar, TypedDict +from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type +from exo.helpers import DEBUG, is_frozen +from exo.download.download_progress import RepoProgressEvent, RepoFileProgressEvent, RepoProgressCallback, RepoFileProgressCallback +from exo.inference.shard import Shard +import aiofiles +from aiofiles import os as aios + +T = TypeVar("T") +# Ori: get_local_snapshot_dir +async def get_local_model_dir(repo_id: str, revision: str = "main") -> Optional[Path]: + refs_dir = get_repo_root(repo_id)/"refs" + refs_file = refs_dir/revision + if await aios.path.exists(refs_file): + async with aiofiles.open(refs_file, 'r') as f: + commit_hash = (await f.read()).strip() + snapshot_dir = get_repo_root(repo_id)/"snapshots"/commit_hash + return snapshot_dir + return None + + +def filter_repo_objects( + items: Iterable[T], + *, + allow_patterns: Optional[Union[List[str], str]] = None, + ignore_patterns: Optional[Union[List[str], str]] = None, + key: Optional[Callable[[T], str]] = None, +) -> Generator[T, None, None]: + if isinstance(allow_patterns, str): + allow_patterns = [allow_patterns] + if isinstance(ignore_patterns, str): + ignore_patterns = [ignore_patterns] + if allow_patterns is not None: + allow_patterns = [_add_wildcard_to_directories(p) for p in allow_patterns] + if ignore_patterns is not None: + ignore_patterns = [_add_wildcard_to_directories(p) for p in ignore_patterns] + + if key is None: + + def _identity(item: T) -> str: + if isinstance(item, str): + return item + if isinstance(item, Path): + return str(item) + raise ValueError(f"Please provide `key` argument in `filter_repo_objects`: `{item}` is not a string.") + + key = _identity + + for item in items: + path = key(item) + if allow_patterns is not None and not any(fnmatch(path, r) for r in allow_patterns): + continue + if ignore_patterns is not None and any(fnmatch(path, r) for r in ignore_patterns): + continue + yield item + + +def _add_wildcard_to_directories(pattern: str) -> str: + if pattern[-1] == "/": + return pattern + "*" + return pattern + + +def get_hf_endpoint() -> str: + #need http ip address + return os.environ.get('HF_ENDPOINT', "http://huggingface.co") + + +def get_exo_home() -> Path: # Ori: get_hf_home + """Get the exo home directory.""" + exo_path = Path(Path.home()/".cache"/"exo") + os.makedirs(exo_path, exist_ok=True) + if DEBUG >= 1: print(f"Init exo folder: {exo_path}") + return exo_path + + +async def get_lh_token(): # Ori: get_hf_token + """get Localhost user's token. + + if await aios.path.exists(token_path): + async with aiofiles.open(token_path, 'r') as f: + return (await f.read()).strip() + """ + return None + +async def get_auth_headers(): + """Get/Custom authentication headers if a token is available.""" + token = await get_hf_token() + if token: + # custom auth header + return {"Authorization": f"Bearer {token}"} + return {} + + +def get_repo_root(model_id: str) -> Path: + """Get the model directory for a given model ID.""" + sanitized_model_id = str(model_id).split("/")[-1] + return get_exo_home()/f"{sanitized_repo_id}" + +async def move_models_to_exo(seed_dir: Union[str, Path]): # Ori: move_models_to_hf + """Move model in resources folder of app to .cache/exo/""" + source_dir = Path(seed_dir) + dest_dir = get_exo_home() + async for path in source_dir.iterdir(): + print("Start Move") + if path.is_dir(): + dest_path = dest_dir / path.name + if dest_path.exists(): + if DEBUG>=1: print(f"skipping moving {dest_path}. File already exists") + else: + await aios.rename(str(path), str(dest_path)) + + print("Done Move") + +async def fetch_file_list(session, repo_id, revision, path=""): + api_url = f"{get_hf_endpoint()}/api/models/{repo_id}/tree/{revision}" + url = f"{api_url}/{path}" if path else api_url + + headers = await get_auth_headers() + async with session.get(url, headers=headers) as response: + if response.status == 200: + data = await response.json() + files = [] + for item in data: + if item["type"] == "file": + files.append({"path": item["path"], "size": item["size"]}) + elif item["type"] == "directory": + subfiles = await fetch_file_list(session, repo_id, revision, item["path"]) + files.extend(subfiles) + return files + else: + raise Exception(f"Failed to fetch file list: {response.status}") + + +@retry( + stop=stop_after_attempt(5), wait=wait_exponential(multiplier=1, min=4, max=60), retry=retry_if_exception_type((aiohttp.ClientError, asyncio.TimeoutError, aiohttp.ClientResponseError)), reraise=True +) +async def download_file( + session: aiohttp.ClientSession, repo_id: str, revision: str, file_path: str, save_directory: str, progress_callback: Optional[RepoFileProgressCallback] = None, use_range_request: bool = True +): + base_url = f"{get_hf_endpoint()}/{repo_id}/resolve/{revision}/" + url = urljoin(base_url, file_path) + local_path = os.path.join(save_directory, file_path) + + await aios.makedirs(os.path.dirname(local_path), exist_ok=True) + + # Check if file already exists and get its size + local_file_size = await aios.path.getsize(local_path) if await aios.path.exists(local_path) else 0 + + headers = await get_auth_headers() + if use_range_request: + headers["Range"] = f"bytes={local_file_size}-" + + async with session.get(url, headers=headers) as response: + total_size = int(response.headers.get('Content-Length', 0)) + downloaded_size = local_file_size + downloaded_this_session = 0 + mode = 'ab' if use_range_request else 'wb' + if downloaded_size == total_size: + if DEBUG >= 2: print(f"File already downloaded: {file_path}") + if progress_callback: + await progress_callback(RepoFileProgressEvent(repo_id, revision, file_path, downloaded_size, downloaded_this_session, total_size, 0, timedelta(0), "complete")) + return + + if response.status == 200: + # File doesn't support range requests or we're not using them, start from beginning + mode = 'wb' + downloaded_size = 0 + elif response.status == 206: + # Partial content, resume download + content_range = response.headers.get('Content-Range', '') + try: + total_size = int(content_range.split('/')[-1]) + except ValueError: + if DEBUG >= 1: print(f"Failed to parse Content-Range header: {content_range}. Starting download from scratch...") + return await download_file(session, repo_id, revision, file_path, save_directory, progress_callback, use_range_request=False) + elif response.status == 416: + # Range not satisfiable, get the actual file size + content_range = response.headers.get('Content-Range', '') + try: + total_size = int(content_range.split('/')[-1]) + if downloaded_size == total_size: + if DEBUG >= 2: print(f"File fully downloaded on first pass: {file_path}") + if progress_callback: + await progress_callback(RepoFileProgressEvent(repo_id, revision, file_path, downloaded_size, downloaded_this_session, total_size, 0, timedelta(0), "complete")) + return + except ValueError: + if DEBUG >= 1: print(f"Failed to parse Content-Range header: {content_range}. Starting download from scratch...") + return await download_file(session, repo_id, revision, file_path, save_directory, progress_callback, use_range_request=False) + else: + raise aiohttp.ClientResponseError(response.request_info, response.history, status=response.status, message=f"Failed to download {file_path}: {response.status}") + + if downloaded_size == total_size: + print(f"File already downloaded: {file_path}") + if progress_callback: + await progress_callback(RepoFileProgressEvent(repo_id, revision, file_path, downloaded_size, downloaded_this_session, total_size, 0, timedelta(0), "complete")) + return + + DOWNLOAD_CHUNK_SIZE = 32768 + start_time = datetime.now() + async with aiofiles.open(local_path, mode) as f: + async for chunk in response.content.iter_chunked(DOWNLOAD_CHUNK_SIZE): + await f.write(chunk) + downloaded_size += len(chunk) + downloaded_this_session += len(chunk) + if progress_callback and total_size: + elapsed_time = (datetime.now() - start_time).total_seconds() + speed = int(downloaded_this_session/elapsed_time) if elapsed_time > 0 else 0 + remaining_size = total_size - downloaded_size + eta = timedelta(seconds=remaining_size/speed) if speed > 0 else timedelta(0) + status = "in_progress" if downloaded_size < total_size else "complete" + if DEBUG >= 8: print(f"HF repo file download progress: {file_path=} {elapsed_time=} {speed=} Downloaded={downloaded_size}/{total_size} {remaining_size=} {eta=} {status=}") + await progress_callback(RepoFileProgressEvent(repo_id, revision, file_path, downloaded_size, downloaded_this_session, total_size, speed, eta, status)) + if DEBUG >= 2: print(f"Downloaded: {file_path}") + + +async def resolve_revision_to_commit_hash(repo_id: str, revision: str) -> str: + repo_root = get_repo_root(repo_id) + refs_dir = repo_root/"refs" + refs_file = refs_dir/revision + + # Check if we have a cached commit hash + if await aios.path.exists(refs_file): + async with aiofiles.open(refs_file, 'r') as f: + commit_hash = (await f.read()).strip() + if DEBUG >= 2: print(f"Commit hash is already cached at {refs_file}: {commit_hash}") + return commit_hash + + # Fetch the commit hash for the given revision + async with aiohttp.ClientSession() as session: + api_url = f"{get_hf_endpoint()}/api/models/{repo_id}/revision/{revision}" + headers = await get_auth_headers() + async with session.get(api_url, headers=headers) as response: + if response.status != 200: + raise Exception(f"Failed to fetch revision info from {api_url}: {response.status}") + revision_info = await response.json() + commit_hash = revision_info['sha'] + + # Cache the commit hash + await aios.makedirs(refs_dir, exist_ok=True) + async with aiofiles.open(refs_file, 'w') as f: + await f.write(commit_hash) + + return commit_hash + + +async def download_repo_files( + repo_id: str, + revision: str = "main", + progress_callback: Optional[RepoProgressCallback] = None, + allow_patterns: Optional[Union[List[str], str]] = None, + ignore_patterns: Optional[Union[List[str], str]] = None, + max_parallel_downloads: int = 4 +) -> Path: + repo_root = get_repo_root(repo_id) + snapshots_dir = repo_root/"snapshots" + cachedreqs_dir = repo_root/"cachedreqs" + + # Ensure directories exist + await aios.makedirs(snapshots_dir, exist_ok=True) + await aios.makedirs(cachedreqs_dir, exist_ok=True) + + # Resolve revision to commit hash + commit_hash = await resolve_revision_to_commit_hash(repo_id, revision) + + # Set up the snapshot directory + snapshot_dir = snapshots_dir/commit_hash + await aios.makedirs(snapshot_dir, exist_ok=True) + + # Set up the cached file list directory + cached_file_list_dir = cachedreqs_dir/commit_hash + await aios.makedirs(cached_file_list_dir, exist_ok=True) + cached_file_list_path = cached_file_list_dir/"fetch_file_list.json" + + async with aiohttp.ClientSession() as session: + # Check if we have a cached file list + if await aios.path.exists(cached_file_list_path): + async with aiofiles.open(cached_file_list_path, 'r') as f: + file_list = json.loads(await f.read()) + if DEBUG >= 2: print(f"Using cached file list from {cached_file_list_path}") + else: + file_list = await fetch_file_list(session, repo_id, revision) + # Cache the file list + async with aiofiles.open(cached_file_list_path, 'w') as f: + await f.write(json.dumps(file_list)) + if DEBUG >= 2: print(f"Cached file list at {cached_file_list_path}") + + filtered_file_list = list(filter_repo_objects(file_list, allow_patterns=allow_patterns, ignore_patterns=ignore_patterns, key=lambda x: x["path"])) + total_files = len(filtered_file_list) + total_bytes = sum(file["size"] for file in filtered_file_list) + file_progress: Dict[str, RepoFileProgressEvent] = { + file["path"]: RepoFileProgressEvent(repo_id, revision, file["path"], 0, 0, file["size"], 0, timedelta(0), "not_started") + for file in filtered_file_list + } + start_time = datetime.now() + + async def download_with_progress(file_info, progress_state): + local_path = snapshot_dir/file_info["path"] + if await aios.path.exists(local_path) and (await aios.stat(local_path)).st_size == file_info["size"]: + if DEBUG >= 2: print(f"File already fully downloaded: {file_info['path']}") + progress_state['completed_files'] += 1 + progress_state['downloaded_bytes'] += file_info["size"] + file_progress[file_info["path"]] = RepoFileProgressEvent(repo_id, revision, file_info["path"], file_info["size"], 0, file_info["size"], 0, timedelta(0), "complete") + if progress_callback: + elapsed_time = (datetime.now() - start_time).total_seconds() + overall_speed = int(progress_state['downloaded_bytes_this_session']/elapsed_time) if elapsed_time > 0 else 0 + remaining_bytes = total_bytes - progress_state['downloaded_bytes'] + overall_eta = timedelta(seconds=remaining_bytes/overall_speed) if overall_speed > 0 else timedelta(seconds=0) + status = "in_progress" if progress_state['completed_files'] < total_files else "complete" + await progress_callback( + RepoProgressEvent( + repo_id, revision, progress_state['completed_files'], total_files, progress_state['downloaded_bytes'], progress_state['downloaded_bytes_this_session'], total_bytes, overall_speed, + overall_eta, file_progress, status + ) + ) + return + + async def file_progress_callback(event: RepoFileProgressEvent): + progress_state['downloaded_bytes'] += event.downloaded - file_progress[event.file_path].downloaded + progress_state['downloaded_bytes_this_session'] += event.downloaded_this_session - file_progress[event.file_path].downloaded_this_session + file_progress[event.file_path] = event + if progress_callback: + elapsed_time = (datetime.now() - start_time).total_seconds() + overall_speed = int(progress_state['downloaded_bytes_this_session']/elapsed_time) if elapsed_time > 0 else 0 + remaining_bytes = total_bytes - progress_state['downloaded_bytes'] + overall_eta = timedelta(seconds=remaining_bytes/overall_speed) if overall_speed > 0 else timedelta(seconds=0) + status = "in_progress" if progress_state['downloaded_bytes'] < total_bytes else "complete" + await progress_callback( + RepoProgressEvent( + repo_id, revision, progress_state['completed_files'], total_files, progress_state['downloaded_bytes'], progress_state['downloaded_bytes_this_session'], total_bytes, overall_speed, + overall_eta, file_progress, status + ) + ) + + await download_file(session, repo_id, revision, file_info["path"], snapshot_dir, file_progress_callback) + progress_state['completed_files'] += 1 + file_progress[ + file_info["path"] + ] = RepoFileProgressEvent(repo_id, revision, file_info["path"], file_info["size"], file_progress[file_info["path"]].downloaded_this_session, file_info["size"], 0, timedelta(0), "complete") + if progress_callback: + elapsed_time = (datetime.now() - start_time).total_seconds() + overall_speed = int(progress_state['downloaded_bytes_this_session']/elapsed_time) if elapsed_time > 0 else 0 + remaining_bytes = total_bytes - progress_state['downloaded_bytes'] + overall_eta = timedelta(seconds=remaining_bytes/overall_speed) if overall_speed > 0 else timedelta(seconds=0) + status = "in_progress" if progress_state['completed_files'] < total_files else "complete" + await progress_callback( + RepoProgressEvent( + repo_id, revision, progress_state['completed_files'], total_files, progress_state['downloaded_bytes'], progress_state['downloaded_bytes_this_session'], total_bytes, overall_speed, + overall_eta, file_progress, status + ) + ) + + progress_state = {'completed_files': 0, 'downloaded_bytes': 0, 'downloaded_bytes_this_session': 0} + + semaphore = asyncio.Semaphore(max_parallel_downloads) + + async def download_with_semaphore(file_info): + async with semaphore: + await download_with_progress(file_info, progress_state) + + tasks = [asyncio.create_task(download_with_semaphore(file_info)) for file_info in filtered_file_list] + await asyncio.gather(*tasks) + + return snapshot_dir + + +async def get_weight_map(repo_id: str, revision: str = "main") -> Optional[Dict[str, str]]: + """ + Retrieve the weight map from the model.safetensors.index.json file. + + Args: + repo_id (str): The Hugging Face repository ID. + revision (str): The revision of the repository to use. + + Returns: + Optional[Dict[str, str]]: The weight map if it exists, otherwise None. + """ + + # Download the index file + await download_repo_files(repo_id=repo_id, revision=revision, allow_patterns="model.safetensors.index.json") + + # Check if the file exists + repo_root = get_repo_root(repo_id) + commit_hash = await resolve_revision_to_commit_hash(repo_id, revision) + snapshot_dir = repo_root/"snapshots"/commit_hash + index_file = next((f for f in await aios.listdir(snapshot_dir) if f.endswith("model.safetensors.index.json")), None) + + if index_file: + index_file_path = snapshot_dir/index_file + if await aios.path.exists(index_file_path): + async with aiofiles.open(index_file_path, 'r') as f: + index_data = json.loads(await f.read()) + return index_data.get("weight_map") + + return None + + +def extract_layer_num(tensor_name: str) -> Optional[int]: + # This is a simple example and might need to be adjusted based on the actual naming convention + parts = tensor_name.split('.') + for part in parts: + if part.isdigit(): + return int(part) + return None + + +def get_allow_patterns(weight_map: Dict[str, str], shard: Shard) -> List[str]: + default_patterns = set(["*.json", "*.py", "tokenizer.model", "*.tiktoken", "*.txt"]) + shard_specific_patterns = set() + if weight_map: + for tensor_name, filename in weight_map.items(): + layer_num = extract_layer_num(tensor_name) + if layer_num is not None and shard.start_layer <= layer_num <= shard.end_layer: + shard_specific_patterns.add(filename) + sorted_file_names = sorted(weight_map.values()) + if shard.is_first_layer(): + shard_specific_patterns.add(sorted_file_names[0]) + elif shard.is_last_layer(): + shard_specific_patterns.add(sorted_file_names[-1]) + else: + shard_specific_patterns = set(["*.safetensors"]) + if DEBUG >= 2: print(f"get_allow_patterns {weight_map=} {shard=} {shard_specific_patterns=}") + return list(default_patterns | shard_specific_patterns) + +async def has_exo_home_read_access() -> bool: # Ori: has_hf_home_read_access + lh_home = get_exo_home() + try: return await aios.access(lh_home, os.R_OK) + except OSError: return False + +async def has_exo_home_write_access() -> bool: # Ori: has_hf_home_write_access + lh_home = get_exo_home() + try: return await aios.access(lh_home, os.W_OK) + except OSError: return False + diff --git a/exo/main.py b/exo/main.py index 99a6fc07a..fc0ac3d0c 100644 --- a/exo/main.py +++ b/exo/main.py @@ -28,7 +28,7 @@ from exo.api import ChatGPTAPI from exo.download.shard_download import ShardDownloader, RepoProgressEvent, NoopShardDownloader from exo.download.hf.hf_shard_download import HFShardDownloader -from exo.helpers import print_yellow_exo, init_exo_env, find_available_port, DEBUG, get_system_info, get_or_create_node_id, get_all_ip_addresses_and_interfaces, terminal_link, shutdown +from exo.helpers import print_yellow_exo, find_available_port, DEBUG, get_system_info, get_or_create_node_id, get_all_ip_addresses_and_interfaces, terminal_link, shutdown from exo.inference.shard import Shard from exo.inference.inference_engine import get_inference_engine, InferenceEngine from exo.inference.tokenizers import resolve_tokenizer @@ -36,7 +36,8 @@ from exo.viz.topology_viz import TopologyViz from exo.download.hf.hf_helpers import has_hf_home_read_access, has_hf_home_write_access, get_hf_home, move_models_to_hf -from exo.localmodel.http_server import LocalModelAPI +from exo.localmodel.http.http_server import LocalModelAPI +from exo.localmodel.lh_helpers import has_exo_home_read_access, has_exo_home_write_access, get_exo_home # parse args parser = argparse.ArgumentParser(description="Initialize GRPC Discovery") @@ -79,8 +80,6 @@ print_yellow_exo() -exo_path = init_exo_env() - system_info = get_system_info() print(f"Detected system: {system_info}") @@ -93,9 +92,10 @@ inference_engine = get_inference_engine(inference_engine_name, shard_downloader) print(f"Using inference engine: {inference_engine.__class__.__name__} with shard downloader: {shard_downloader.__class__.__name__}") -for folder_path in Path(exo_path).iterdir(): +exo_home = get_exo_home() +for folder_path in Path(exo_home).iterdir(): if folder_path.is_dir(): - model_path = folder_path + model_path = f"http://{args.node_host}:{args.local_model_api_port}/models/{folder_path.name}" model_name = folder_path.name config_file_path = Path(folder_path/'config.json') if config_file_path.is_file(): @@ -195,6 +195,8 @@ def preemptively_start_download(request_id: str, opaque_status: str): if "Local" in current_shard.model_id or os.path.isdir(current_shard.model_id): print("Local model detected, skip download") + # borcast download model + #asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) pass else: if DEBUG >= 2: print(f"Preemptively starting download for {current_shard}") @@ -343,6 +345,17 @@ async def main(): {"❌ No read access" if not has_read else ""} {"❌ No write access" if not has_write else ""} """) + # Check exo directory permissions + exo_home, has_read, has_write = get_exo_home(), await has_exo_home_read_access(), await has_exo_home_write_access() + if DEBUG >= 1: print(f"Model storage directory: {exo_home}") + print(f"{has_read=}, {has_write=}") + if not has_read or not has_write: + print(f""" + WARNING: Limited permissions for model storage directory: {exo_home}. + This may prevent model downloads from working correctly. + {"❌ No read access" if not has_read else ""} + {"❌ No write access" if not has_write else ""} + """) if not args.models_seed_dir is None: try: From 85d41f0b564b62c940fa09d18aca3eedb119b265 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Mon, 16 Dec 2024 10:53:46 +0800 Subject: [PATCH 18/26] future: enhance lh_helpers but download_file function not complete --- exo/download/hf/hf_shard_download.py | 30 ++-- exo/inference/mlx/sharded_inference_engine.py | 4 +- exo/inference/tokenizers.py | 5 + exo/localmodel/http/http_server.py | 49 ++++--- exo/localmodel/lh_helpers.py | 137 +++++++----------- exo/main.py | 12 +- exo/models.py | 9 +- 7 files changed, 127 insertions(+), 119 deletions(-) diff --git a/exo/download/hf/hf_shard_download.py b/exo/download/hf/hf_shard_download.py index 438590f8f..4553fa200 100644 --- a/exo/download/hf/hf_shard_download.py +++ b/exo/download/hf/hf_shard_download.py @@ -16,7 +16,9 @@ import aiohttp from aiofiles import os as aios -from exo.localmodel.lh_helpers import get_exo_home +from exo.localmodel.lh_helpers import ( + get_exo_home, get_lh_weight_map, fetch_lh_file_list, download_model_dir +) class HFShardDownloader(ShardDownloader): def __init__(self, quick_check: bool = False, max_parallel_downloads: int = 4): @@ -40,7 +42,7 @@ async def ensure_shard(self, shard: Shard, inference_engine_name: str) -> Path: if 'Local' in shard.model_id: model_name = shard.model_id.split('/')[1] snapshots_dir = Path(get_exo_home()/model_name) - else: + else: # HF model snapshots_dir = repo_root/"snapshots" if snapshots_dir.exists(): @@ -86,11 +88,16 @@ async def ensure_shard(self, shard: Shard, inference_engine_name: str) -> Path: async def _download_shard(self, shard: Shard, repo_name: str) -> Path: async def wrapped_progress_callback(event: RepoProgressEvent): self._on_progress.trigger_all(shard, event) - - weight_map = await get_weight_map(repo_name) - allow_patterns = get_allow_patterns(weight_map, shard) - - return await download_repo_files(repo_name, progress_callback=wrapped_progress_callback, allow_patterns=allow_patterns, max_parallel_downloads=self.max_parallel_downloads) + + if 'Local' in repo_name: + weight_map = await get_lh_weight_map(repo_name) + allow_patterns = get_allow_patterns(weight_map, shard) + return await download_model_dir(repo_name, progress_callback=wrapped_progress_callback, allow_patterns=allow_patterns, max_parallel_downloads=self.max_parallel_downloads) + else: # HF + weight_map = await get_weight_map(repo_name) + allow_patterns = get_allow_patterns(weight_map, shard) + return await download_repo_files(repo_name, progress_callback=wrapped_progress_callback, allow_patterns=allow_patterns, max_parallel_downloads=self.max_parallel_downloads) + @property def on_progress(self) -> AsyncCallbackSystem[str, Tuple[Shard, RepoProgressEvent]]: @@ -125,8 +132,13 @@ async def get_shard_download_status(self) -> Optional[Dict[str, Union[float, int total_bytes = 0 downloaded_bytes = 0 - async with aiohttp.ClientSession() as session: - file_list = await fetch_file_list(session, self.current_repo_id, self.revision) + conn = aiohttp.TCPConnector(limit=100) + async with aiohttp.ClientSession(connector=conn) as session: + if self.current_repo_id.startswith("Local"): + file_list = await fetch_lh_file_list(session, self.current_repo_id) + else: + file_list = await fetch_file_list(session, self.current_repo_id, self.revision) + relevant_files = list( filter_repo_objects( file_list, allow_patterns=patterns, key=lambda x: x["path"])) diff --git a/exo/inference/mlx/sharded_inference_engine.py b/exo/inference/mlx/sharded_inference_engine.py index e81023a8e..1637d64f6 100644 --- a/exo/inference/mlx/sharded_inference_engine.py +++ b/exo/inference/mlx/sharded_inference_engine.py @@ -143,10 +143,10 @@ async def ensure_shard(self, shard: Shard): if os.path.isdir(shard.model_id): # path mode model_path = Path(shard.model_id) elif "Local" in shard.model_id: # Local card mode - model_path = Path(get_repo(shard.model_id, self.__class__.__name__)) + model_path = await self.shard_downloader.ensure_shard(shard, self.__class__.__name__) else: model_path = await self.shard_downloader.ensure_shard(shard, self.__class__.__name__) - + if self.shard != shard: def load_shard_wrapper(): diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index 7b3a94bf4..a8cd6212f 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -9,6 +9,8 @@ from exo.download.hf.hf_helpers import get_local_snapshot_dir from exo.helpers import DEBUG +from exo.localmodel.lh_helpers import get_local_model_dir + class DummyTokenizer: def __init__(self): @@ -30,8 +32,11 @@ async def resolve_tokenizer(model_id: str): return DummyTokenizer() if os.path.isdir(model_id): # local model + # model_path = model_id ex: ~/.cach/exo/llama-3.3-70b local_path = str(model_id).rstrip('/') model_id = 'Local/'+str(local_path.split('/')[-1]) + elif "Local" in model_id: + local_path = await get_local_model_dir(model_id) else: local_path = await get_local_snapshot_dir(model_id) diff --git a/exo/localmodel/http/http_server.py b/exo/localmodel/http/http_server.py index 55bf434ab..eeb58f894 100644 --- a/exo/localmodel/http/http_server.py +++ b/exo/localmodel/http/http_server.py @@ -12,7 +12,7 @@ def __init__(self): self.app = web.Application() self.cache_dir = os.path.expanduser('~/.cache/exo') Path(self.cache_dir).mkdir(parents=True, exist_ok=True) - + # Setup CORS cors = aiohttp_cors.setup(self.app) cors_options = aiohttp_cors.ResourceOptions( @@ -24,10 +24,11 @@ def __init__(self): # Add routes with CORS routes = [ + ('GET', '/health', self.health_check), ('GET', '/files/{filename}', self.handle_download_file), ('GET', '/files', self.handle_list_files), ('GET', '/models', self.handle_list_models), - ('GET', '/models/{foldername}/files', self.handle_list_model_files), + ('GET', '/models/{foldername:.*}/list', self.handle_list_model_items), ('GET', '/models/{model_name}/download', self.handle_model_download) ] @@ -133,9 +134,10 @@ async def handle_list_models(self, request): }) return web.json_response({'models': folders}) - async def handle_list_model_files(self, request): - foldername = request.match_info['foldername'] - folder_path = os.path.join(self.cache_dir, foldername) + async def handle_list_model_items(self, request): + # Get the full path including potential subfolders from URL + path_parts = request.match_info['foldername'].split('/') + folder_path = os.path.join(self.cache_dir, *path_parts) if not os.path.exists(folder_path): return web.json_response({"error": "Folder not found"}, status=404) @@ -143,21 +145,32 @@ async def handle_list_model_files(self, request): if not os.path.isdir(folder_path): return web.json_response({"error": "Not a valid folder"}, status=400) - files = [] - for root, dirs, filenames in os.walk(folder_path): - dirs[:] = [d for d in dirs if not d.startswith('.')] - for filename in filenames: - if filename.startswith('.'): - continue - file_path = os.path.join(root, filename) - rel_path = os.path.relpath(file_path, folder_path) - files.append({ - 'name': rel_path, - 'size': os.path.getsize(file_path), - 'modified': datetime.fromtimestamp(os.path.getmtime(file_path)).isoformat() + items = [] + # List only immediate contents of current directory + for entry in os.scandir(folder_path): + if entry.name.startswith('.'): + continue + + if entry.is_dir(): + items.append({ + 'type': 'directory', + 'name': entry.name, + 'modified': datetime.fromtimestamp(entry.stat().st_mtime).isoformat() + }) + else: + items.append({ + 'type': 'file', + 'name': entry.name, + 'size': entry.stat().st_size, + 'modified': datetime.fromtimestamp(entry.stat().st_mtime).isoformat() }) - return web.json_response({'files': files}) + return web.json_response({'items': items}) + + + async def health_check(self, request): + """健康检查端点""" + return web.Response(text='OK', status=200) async def run(self, host: str = "0.0.0.0", port: int = 52525): runner = web.AppRunner(self.app) diff --git a/exo/localmodel/lh_helpers.py b/exo/localmodel/lh_helpers.py index 103efc210..c85621235 100644 --- a/exo/localmodel/lh_helpers.py +++ b/exo/localmodel/lh_helpers.py @@ -19,16 +19,15 @@ import aiofiles from aiofiles import os as aios +import exo.main as exo +# remove function : resolve_revision_to_commit_hash + T = TypeVar("T") # Ori: get_local_snapshot_dir -async def get_local_model_dir(repo_id: str, revision: str = "main") -> Optional[Path]: - refs_dir = get_repo_root(repo_id)/"refs" - refs_file = refs_dir/revision - if await aios.path.exists(refs_file): - async with aiofiles.open(refs_file, 'r') as f: - commit_hash = (await f.read()).strip() - snapshot_dir = get_repo_root(repo_id)/"snapshots"/commit_hash - return snapshot_dir +async def get_local_model_dir(repo_id: str) -> Optional[Path]: + refs_dir = get_repo_root(repo_id) + if os.path.exists(refs_dir): + return refs_dir return None @@ -73,10 +72,10 @@ def _add_wildcard_to_directories(pattern: str) -> str: return pattern + "*" return pattern - -def get_hf_endpoint() -> str: - #need http ip address - return os.environ.get('HF_ENDPOINT', "http://huggingface.co") +# Ori: get_hf_endpoint +def get_lh_endpoint() -> str: + # http://:52525 + return exo.local_model_api_endpoints[0] def get_exo_home() -> Path: # Ori: get_hf_home @@ -98,7 +97,7 @@ async def get_lh_token(): # Ori: get_hf_token async def get_auth_headers(): """Get/Custom authentication headers if a token is available.""" - token = await get_hf_token() + token = await get_lh_token() if token: # custom auth header return {"Authorization": f"Bearer {token}"} @@ -107,8 +106,8 @@ async def get_auth_headers(): def get_repo_root(model_id: str) -> Path: """Get the model directory for a given model ID.""" - sanitized_model_id = str(model_id).split("/")[-1] - return get_exo_home()/f"{sanitized_repo_id}" + sanitized_model_name = str(model_id).split("/")[-1] + return get_exo_home()/f"{sanitized_model_name}" async def move_models_to_exo(seed_dir: Union[str, Path]): # Ori: move_models_to_hf """Move model in resources folder of app to .cache/exo/""" @@ -125,26 +124,35 @@ async def move_models_to_exo(seed_dir: Union[str, Path]): # Ori: move_models_to_ print("Done Move") -async def fetch_file_list(session, repo_id, revision, path=""): - api_url = f"{get_hf_endpoint()}/api/models/{repo_id}/tree/{revision}" - url = f"{api_url}/{path}" if path else api_url - +# Ori: fetch_file_list +@retry( + stop=stop_after_attempt(5), wait=wait_exponential(multiplier=1, min=4, max=60) +) +async def fetch_lh_file_list(session, repo_id, path=""): + model_name = repo_id.split("/")[-1] + if path : + url = f"{get_lh_endpoint()}/models/{model_name}/{path}/list" + else: + url = f"{get_lh_endpoint()}/models/{model_name}/list" + headers = await get_auth_headers() - async with session.get(url, headers=headers) as response: + + async with session.get(url, headers=headers, timeout=10) as response: if response.status == 200: data = await response.json() + model_datas = data['items'] files = [] - for item in data: + for item in model_datas: if item["type"] == "file": - files.append({"path": item["path"], "size": item["size"]}) + files.append({"path": item["name"], "size": item.get("size", "Unknow")}) elif item["type"] == "directory": - subfiles = await fetch_file_list(session, repo_id, revision, item["path"]) + subfolders_path = f'{path}/{item["name"]}' + subfiles = await fetch_lh_file_list(session, repo_id, subfolders_path) files.extend(subfiles) return files else: raise Exception(f"Failed to fetch file list: {response.status}") - - + @retry( stop=stop_after_attempt(5), wait=wait_exponential(multiplier=1, min=4, max=60), retry=retry_if_exception_type((aiohttp.ClientError, asyncio.TimeoutError, aiohttp.ClientResponseError)), reraise=True ) @@ -226,62 +234,24 @@ async def download_file( await progress_callback(RepoFileProgressEvent(repo_id, revision, file_path, downloaded_size, downloaded_this_session, total_size, speed, eta, status)) if DEBUG >= 2: print(f"Downloaded: {file_path}") - -async def resolve_revision_to_commit_hash(repo_id: str, revision: str) -> str: - repo_root = get_repo_root(repo_id) - refs_dir = repo_root/"refs" - refs_file = refs_dir/revision - - # Check if we have a cached commit hash - if await aios.path.exists(refs_file): - async with aiofiles.open(refs_file, 'r') as f: - commit_hash = (await f.read()).strip() - if DEBUG >= 2: print(f"Commit hash is already cached at {refs_file}: {commit_hash}") - return commit_hash - - # Fetch the commit hash for the given revision - async with aiohttp.ClientSession() as session: - api_url = f"{get_hf_endpoint()}/api/models/{repo_id}/revision/{revision}" - headers = await get_auth_headers() - async with session.get(api_url, headers=headers) as response: - if response.status != 200: - raise Exception(f"Failed to fetch revision info from {api_url}: {response.status}") - revision_info = await response.json() - commit_hash = revision_info['sha'] - - # Cache the commit hash - await aios.makedirs(refs_dir, exist_ok=True) - async with aiofiles.open(refs_file, 'w') as f: - await f.write(commit_hash) - - return commit_hash - - -async def download_repo_files( +# Ori: download_repo_files +async def download_model_dir( repo_id: str, - revision: str = "main", + revision: str = "Local", progress_callback: Optional[RepoProgressCallback] = None, allow_patterns: Optional[Union[List[str], str]] = None, ignore_patterns: Optional[Union[List[str], str]] = None, max_parallel_downloads: int = 4 ) -> Path: repo_root = get_repo_root(repo_id) - snapshots_dir = repo_root/"snapshots" cachedreqs_dir = repo_root/"cachedreqs" # Ensure directories exist - await aios.makedirs(snapshots_dir, exist_ok=True) + await aios.makedirs(repo_root, exist_ok=True) await aios.makedirs(cachedreqs_dir, exist_ok=True) - # Resolve revision to commit hash - commit_hash = await resolve_revision_to_commit_hash(repo_id, revision) - - # Set up the snapshot directory - snapshot_dir = snapshots_dir/commit_hash - await aios.makedirs(snapshot_dir, exist_ok=True) - # Set up the cached file list directory - cached_file_list_dir = cachedreqs_dir/commit_hash + cached_file_list_dir = cachedreqs_dir await aios.makedirs(cached_file_list_dir, exist_ok=True) cached_file_list_path = cached_file_list_dir/"fetch_file_list.json" @@ -292,23 +262,24 @@ async def download_repo_files( file_list = json.loads(await f.read()) if DEBUG >= 2: print(f"Using cached file list from {cached_file_list_path}") else: - file_list = await fetch_file_list(session, repo_id, revision) + file_list = await fetch_lh_file_list(session, repo_id) # Cache the file list async with aiofiles.open(cached_file_list_path, 'w') as f: await f.write(json.dumps(file_list)) if DEBUG >= 2: print(f"Cached file list at {cached_file_list_path}") - - filtered_file_list = list(filter_repo_objects(file_list, allow_patterns=allow_patterns, ignore_patterns=ignore_patterns, key=lambda x: x["path"])) - total_files = len(filtered_file_list) - total_bytes = sum(file["size"] for file in filtered_file_list) + + #filtered_file_list = list(filter_repo_objects(file_list, allow_patterns=allow_patterns, ignore_patterns=ignore_patterns, key=lambda x: x["path"])) + + total_files = len(file_list) + total_bytes = sum(file["size"] for file in file_list) file_progress: Dict[str, RepoFileProgressEvent] = { file["path"]: RepoFileProgressEvent(repo_id, revision, file["path"], 0, 0, file["size"], 0, timedelta(0), "not_started") - for file in filtered_file_list + for file in file_list } start_time = datetime.now() async def download_with_progress(file_info, progress_state): - local_path = snapshot_dir/file_info["path"] + local_path = repo_root/file_info["path"] if await aios.path.exists(local_path) and (await aios.stat(local_path)).st_size == file_info["size"]: if DEBUG >= 2: print(f"File already fully downloaded: {file_info['path']}") progress_state['completed_files'] += 1 @@ -371,13 +342,13 @@ async def download_with_semaphore(file_info): async with semaphore: await download_with_progress(file_info, progress_state) - tasks = [asyncio.create_task(download_with_semaphore(file_info)) for file_info in filtered_file_list] + tasks = [asyncio.create_task(download_with_semaphore(file_info)) for file_info in file_list] await asyncio.gather(*tasks) - return snapshot_dir - + return repo_root -async def get_weight_map(repo_id: str, revision: str = "main") -> Optional[Dict[str, str]]: +# Ori: get_weight_map +async def get_lh_weight_map(repo_id: str) -> Optional[Dict[str, str]]: """ Retrieve the weight map from the model.safetensors.index.json file. @@ -390,16 +361,14 @@ async def get_weight_map(repo_id: str, revision: str = "main") -> Optional[Dict[ """ # Download the index file - await download_repo_files(repo_id=repo_id, revision=revision, allow_patterns="model.safetensors.index.json") + await download_model_dir(repo_id=repo_id, allow_patterns="model.safetensors.index.json") # Check if the file exists repo_root = get_repo_root(repo_id) - commit_hash = await resolve_revision_to_commit_hash(repo_id, revision) - snapshot_dir = repo_root/"snapshots"/commit_hash - index_file = next((f for f in await aios.listdir(snapshot_dir) if f.endswith("model.safetensors.index.json")), None) + index_file = next((f for f in await aios.listdir(repo_root) if f.endswith("model.safetensors.index.json")), None) if index_file: - index_file_path = snapshot_dir/index_file + index_file_path = repo_root/index_file if await aios.path.exists(index_file_path): async with aiofiles.open(index_file_path, 'r') as f: index_data = json.loads(await f.read()) diff --git a/exo/main.py b/exo/main.py index fc0ac3d0c..1181036cc 100644 --- a/exo/main.py +++ b/exo/main.py @@ -95,14 +95,13 @@ exo_home = get_exo_home() for folder_path in Path(exo_home).iterdir(): if folder_path.is_dir(): - model_path = f"http://{args.node_host}:{args.local_model_api_port}/models/{folder_path.name}" model_name = folder_path.name config_file_path = Path(folder_path/'config.json') if config_file_path.is_file(): with open(config_file_path, 'r') as file: config = json.load(file) config_n_layers = config['num_hidden_layers'] - build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, int(config_n_layers)) + build_local_model_card(model_name, None, inference_engine.__class__.__name__, int(config_n_layers)) print(f"Add Local Model Complete!!") if args.node_port is None: @@ -193,8 +192,11 @@ def preemptively_start_download(request_id: str, opaque_status: str): if status.get("type") == "node_status" and status.get("status") == "start_process_prompt": current_shard = node.get_current_shard(Shard.from_dict(status.get("shard"))) - if "Local" in current_shard.model_id or os.path.isdir(current_shard.model_id): + if os.path.isdir(current_shard.model_id): print("Local model detected, skip download") + pass + elif "Local" in current_shard.model_id: + print("Local model detected, http download to other node") # borcast download model #asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) pass @@ -229,15 +231,17 @@ def throttled_broadcast(shard: Shard, event: RepoProgressEvent): async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name_or_path: str, prompt: str): if model_cards.get(model_name_or_path): inference_class = inference_engine.__class__.__name__ + print(f'model_card = {get_repo(model_name_or_path, inference_class)}') shard = build_base_shard(model_name_or_path, inference_class) if not shard: print(f"Error: exo Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") return + print(f'model_id = {get_repo(shard.model_id, inference_class)}') tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) elif os.path.isdir(model_name_or_path): model_path = model_name_or_path.rstrip('/') - model_config_path = Path(model_path)/'config.json' model_name = str(model_path.split('/')[-1]) + model_config_path = Path(model_path)/'config.json' if os.path.isfile(model_config_path): with open(model_config_path, 'r') as file: diff --git a/exo/models.py b/exo/models.py index 156d88163..27eea31b2 100644 --- a/exo/models.py +++ b/exo/models.py @@ -133,13 +133,18 @@ def build_base_shard(model_id: str, inference_engine_classname: str) -> Optional return None return Shard(model_id, 0, 0, n_layers) -def build_local_model_card(model_name: str, model_path: str, inference_engine: str, config_n_layers: int) -> None: +def build_local_model_card(model_name: str, model_path: str|None, inference_engine: str, config_n_layers: int) -> None: short_model_name = f"Local/{model_name}" pretty_model_name = f"{model_name} (Local)".replace('-', ' ') + if model_path is None: + model_repo = short_model_name + else: + model_repo = model_path + model_cards[short_model_name] = { "layers": config_n_layers, "repo": { - inference_engine: model_path + inference_engine: model_repo }, } pretty_name[short_model_name]=pretty_model_name From aca7eba395da488ad7c8b44a65c4bb4fbfc2332e Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Tue, 17 Dec 2024 09:53:37 +0800 Subject: [PATCH 19/26] filter: add args setting sotre model ip and port --- exo/localmodel/http/http_server.py | 16 +++++++++++++++- exo/localmodel/lh_helpers.py | 5 +++-- exo/main.py | 16 +++++++++++----- 3 files changed, 29 insertions(+), 8 deletions(-) diff --git a/exo/localmodel/http/http_server.py b/exo/localmodel/http/http_server.py index eeb58f894..3b78b523a 100644 --- a/exo/localmodel/http/http_server.py +++ b/exo/localmodel/http/http_server.py @@ -29,7 +29,8 @@ def __init__(self): ('GET', '/files', self.handle_list_files), ('GET', '/models', self.handle_list_models), ('GET', '/models/{foldername:.*}/list', self.handle_list_model_items), - ('GET', '/models/{model_name}/download', self.handle_model_download) + ('GET', '/models/{model_name}/download', self.handle_model_download), + ('GET', '/models/{model_name}/download/{filename:.*}', self.model_file_download) ] for method, path, handler in routes: @@ -166,7 +167,20 @@ async def handle_list_model_items(self, request): }) return web.json_response({'items': items}) + + async def model_file_download(self, request): + model_name = request.match_info['model_name'] + filename = request.match_info['filename'] + + full_path = os.path.join(self.cache_dir, model_name, filename) # Corrected to use 'filename' + + if not os.path.exists(full_path): + return web.json_response({"error": "File not found"}, status=404) + + if not os.path.isfile(full_path): + return web.json_response({"error": "Not a valid file"}, status=400) + return web.FileResponse(full_path) async def health_check(self, request): """健康检查端点""" diff --git a/exo/localmodel/lh_helpers.py b/exo/localmodel/lh_helpers.py index c85621235..79c0f4753 100644 --- a/exo/localmodel/lh_helpers.py +++ b/exo/localmodel/lh_helpers.py @@ -159,7 +159,8 @@ async def fetch_lh_file_list(session, repo_id, path=""): async def download_file( session: aiohttp.ClientSession, repo_id: str, revision: str, file_path: str, save_directory: str, progress_callback: Optional[RepoFileProgressCallback] = None, use_range_request: bool = True ): - base_url = f"{get_hf_endpoint()}/{repo_id}/resolve/{revision}/" + #base_url = f"{get_hf_endpoint()}/{repo_id}/resolve/{revision}/" + base_url = f'{get_lh_endpoint()}/models/{repo_id}/download/' url = urljoin(base_url, file_path) local_path = os.path.join(save_directory, file_path) @@ -316,7 +317,7 @@ async def file_progress_callback(event: RepoFileProgressEvent): ) ) - await download_file(session, repo_id, revision, file_info["path"], snapshot_dir, file_progress_callback) + await download_file(session, repo_id, revision, file_info["path"], repo_root, file_progress_callback) progress_state['completed_files'] += 1 file_progress[ file_info["path"] diff --git a/exo/main.py b/exo/main.py index 1181036cc..eabf9dbd2 100644 --- a/exo/main.py +++ b/exo/main.py @@ -74,7 +74,8 @@ parser.add_argument("--tailscale-api-key", type=str, default=None, help="Tailscale API key") parser.add_argument("--tailnet-name", type=str, default=None, help="Tailnet name") parser.add_argument("--node-id-filter", type=str, default=None, help="Comma separated list of allowed node IDs (only for UDP and Tailscale discovery)") -parser.add_argument("--local-model-api-port", type=int, default=52525, help="Local Model API port") +parser.add_argument("--stored-model-ip", type=str, default="0.0.0.0", help="Stored Local Model IP") +parser.add_argument("--stored-model-port", type=int, default=52525, help="Local Model API port") args = parser.parse_args() print(f"Selected inference engine: {args.inference_engine}") @@ -92,6 +93,7 @@ inference_engine = get_inference_engine(inference_engine_name, shard_downloader) print(f"Using inference engine: {inference_engine.__class__.__name__} with shard downloader: {shard_downloader.__class__.__name__}") +print(f"Add Local Model To Model Card：") exo_home = get_exo_home() for folder_path in Path(exo_home).iterdir(): if folder_path.is_dir(): @@ -102,7 +104,7 @@ config = json.load(file) config_n_layers = config['num_hidden_layers'] build_local_model_card(model_name, None, inference_engine.__class__.__name__, int(config_n_layers)) -print(f"Add Local Model Complete!!") + print(f"- Local/{model_name}") if args.node_port is None: args.node_port = find_available_port(args.node_host) @@ -113,13 +115,16 @@ if args.node_host == "0.0.0.0": chatgpt_api_endpoints = [f"http://{ip}:{args.chatgpt_api_port}/v1/chat/completions" for ip, _ in get_all_ip_addresses_and_interfaces()] - local_model_api_endpoints = [f"http://{ip}:{args.local_model_api_port}" for ip, _ in get_all_ip_addresses_and_interfaces()] web_chat_urls = [f"http://{ip}:{args.chatgpt_api_port}" for ip, _ in get_all_ip_addresses_and_interfaces()] else: chatgpt_api_endpoints = [f"http://{args.node_host}:{args.chatgpt_api_port}/v1/chat/completions"] - local_model_api_endpoints = [f"http://{args.node_host}:{args.local_model_api_port}"] web_chat_urls = [f"http://{args.node_host}:{args.chatgpt_api_port}"] +if args.stored_model_ip == "0.0.0.0": + local_model_api_endpoints = [f"http://{ip}:{args.stored_model_port}" for ip, _ in get_all_ip_addresses_and_interfaces()] +else: + local_model_api_endpoints = [f"http://{args.stored_model_ip}:{args.stored_model_port}"] + if DEBUG >= 0: print("Chat interface started:") for web_chat_url in web_chat_urls: @@ -408,7 +413,8 @@ def handle_exit(): else: asyncio.create_task(chatgpt_api.run(host=args.node_host, port=args.chatgpt_api_port)) # Start the API server as a non-blocking task - asyncio.create_task(local_model_api.run(host=args.node_host, port=args.local_model_api_port)) # Start the local model server as a non-blocking task + if any(ip == args.stored_model_ip for ip, _ in get_all_ip_addresses_and_interfaces()): + asyncio.create_task(local_model_api.run(host=args.stored_model_ip, port=args.stored_model_port)) # Start the local model server as a non-blocking task await asyncio.Event().wait() if args.wait_for_peers > 0: From ef60ff3c1c716d866606dc22fb87e7817bac0b51 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Wed, 18 Dec 2024 16:49:08 +0800 Subject: [PATCH 20/26] future:add other node update local model to model_crads --- exo/download/hf/hf_shard_download.py | 5 +-- exo/helpers.py | 35 +++++++++++++++++ exo/inference/tokenizers.py | 5 +-- exo/localmodel/http/http_server.py | 57 +--------------------------- exo/main.py | 30 ++++++++++----- 5 files changed, 60 insertions(+), 72 deletions(-) diff --git a/exo/download/hf/hf_shard_download.py b/exo/download/hf/hf_shard_download.py index 4553fa200..919fe481e 100644 --- a/exo/download/hf/hf_shard_download.py +++ b/exo/download/hf/hf_shard_download.py @@ -132,9 +132,8 @@ async def get_shard_download_status(self) -> Optional[Dict[str, Union[float, int total_bytes = 0 downloaded_bytes = 0 - conn = aiohttp.TCPConnector(limit=100) - async with aiohttp.ClientSession(connector=conn) as session: - if self.current_repo_id.startswith("Local"): + async with aiohttp.ClientSession() as session: + if self.current_repo_id.startswith("Local"): # 看要不要換 check_agent file_list = await fetch_lh_file_list(session, self.current_repo_id) else: file_list = await fetch_file_list(session, self.current_repo_id, self.revision) diff --git a/exo/helpers.py b/exo/helpers.py index 5552524e8..4498299eb 100644 --- a/exo/helpers.py +++ b/exo/helpers.py @@ -14,6 +14,8 @@ import json from concurrent.futures import ThreadPoolExecutor +import aiohttp + DEBUG = int(os.getenv("DEBUG", default="0")) DEBUG_DISCOVERY = int(os.getenv("DEBUG_DISCOVERY", default="0")) VERSION = "0.0.1" @@ -308,6 +310,39 @@ async def get_interface_priority_and_type(ifname: str) -> Tuple[int, str]: # Other physical interfaces return (2, "Other") +async def get_stored_models(stored_ip: str, stored_port: int): + url = f"http://{stored_ip}:{stored_port}/models" + try: + async with aiohttp.ClientSession() as session: + async with session.get(url) as response: + if response.status == 200: + return await response.json() + else: + return [] + except Exception as e: + print(f"Error getting models from store: {e}") + return [] + +async def get_stored_model_config(stored_ip: str, stored_port: int, model_name: str): + url = f"http://{stored_ip}:{stored_port}/models/{model_name}/download/config.json" + try: + async with aiohttp.ClientSession() as session: + async with session.get(url) as response: + if response.status == 200: + return await response.json() + else: + return None + except Exception as e: + print(f"Error getting models from store: {e}") + return None + +def check_agent(store_ip: str) -> str: + for ip, _ in get_all_ip_addresses_and_interfaces(): + if (store_ip == ip) or (store_ip == "0.0.0.0"): + return "master" + else: + return "client" + async def shutdown(signal, loop, server): """Gracefully shutdown the server and close the asyncio loop.""" print(f"Received exit signal {signal.name}...") diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index a8cd6212f..823dbdc2d 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -31,15 +31,14 @@ async def resolve_tokenizer(model_id: str): if model_id == "dummy": return DummyTokenizer() - if os.path.isdir(model_id): # local model - # model_path = model_id ex: ~/.cach/exo/llama-3.3-70b + if os.path.isdir(model_id): # local path model local_path = str(model_id).rstrip('/') model_id = 'Local/'+str(local_path.split('/')[-1]) elif "Local" in model_id: local_path = await get_local_model_dir(model_id) else: local_path = await get_local_snapshot_dir(model_id) - + print(f'local_path = {local_path}') if DEBUG >= 2: print(f"Checking if local path exists to load tokenizer from local {local_path=}") try: if local_path and await aios.path.exists(local_path): diff --git a/exo/localmodel/http/http_server.py b/exo/localmodel/http/http_server.py index 3b78b523a..5b263e2b0 100644 --- a/exo/localmodel/http/http_server.py +++ b/exo/localmodel/http/http_server.py @@ -27,9 +27,8 @@ def __init__(self): ('GET', '/health', self.health_check), ('GET', '/files/{filename}', self.handle_download_file), ('GET', '/files', self.handle_list_files), - ('GET', '/models', self.handle_list_models), + ('GET', '/models', self.handle_list_models), # models list ('GET', '/models/{foldername:.*}/list', self.handle_list_model_items), - ('GET', '/models/{model_name}/download', self.handle_model_download), ('GET', '/models/{model_name}/download/{filename:.*}', self.model_file_download) ] @@ -67,60 +66,6 @@ async def handle_list_files(self, request): }) return web.json_response({'files': files}) - async def handle_model_download(self, request): - model_name = request.match_info['model_name'] - chunk_size = 32768 # 32KB chunks for better performance - model_path = os.path.join(self.cache_dir, model_name) - - if not os.path.exists(model_path): - return web.json_response({"error": "Model not found"}, status=404) - - if not os.path.isdir(model_path): - return web.json_response({"error": "Not a valid model directory"}, status=400) - - # Setup streaming response - response = web.StreamResponse( - status=200, - reason='OK', - headers={ - 'Content-Type': 'application/octet-stream' - } - ) - await response.prepare(request) - - # Walk through directory and stream files - for root, _, files in os.walk(model_path): - for filename in files: - if filename.startswith('.'): - continue - - file_path = os.path.join(root, filename) - rel_path = os.path.relpath(file_path, model_path) - - if DEBUG >= 2: - print(f"Streaming file: {rel_path}") - - # Send file metadata - metadata = { - 'filename': rel_path, - 'size': os.path.getsize(file_path) - } - await response.write(json.dumps(metadata).encode() + b'\n') - - # Stream file content in chunks - with open(file_path, 'rb') as f: - while True: - chunk = f.read(chunk_size) - if not chunk: - break - await response.write(chunk) - - # Send end of file marker - await response.write(b'EOF\n') - - await response.write_eof() - return response - async def handle_list_models(self, request): folders = [] for entry in os.scandir(self.cache_dir): diff --git a/exo/main.py b/exo/main.py index eabf9dbd2..7e102c0ee 100644 --- a/exo/main.py +++ b/exo/main.py @@ -38,6 +38,7 @@ from exo.localmodel.http.http_server import LocalModelAPI from exo.localmodel.lh_helpers import has_exo_home_read_access, has_exo_home_write_access, get_exo_home +from exo.helpers import check_agent, get_stored_models, get_stored_model_config # parse args parser = argparse.ArgumentParser(description="Initialize GRPC Discovery") @@ -93,6 +94,7 @@ inference_engine = get_inference_engine(inference_engine_name, shard_downloader) print(f"Using inference engine: {inference_engine.__class__.__name__} with shard downloader: {shard_downloader.__class__.__name__}") +# (Host) Local Model Card print(f"Add Local Model To Model Card：") exo_home = get_exo_home() for folder_path in Path(exo_home).iterdir(): @@ -196,15 +198,13 @@ def preemptively_start_download(request_id: str, opaque_status: str): status = json.loads(opaque_status) if status.get("type") == "node_status" and status.get("status") == "start_process_prompt": current_shard = node.get_current_shard(Shard.from_dict(status.get("shard"))) - if os.path.isdir(current_shard.model_id): print("Local model detected, skip download") pass elif "Local" in current_shard.model_id: print("Local model detected, http download to other node") # borcast download model - #asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) - pass + asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) else: if DEBUG >= 2: print(f"Preemptively starting download for {current_shard}") asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) @@ -234,14 +234,12 @@ def throttled_broadcast(shard: Shard, event: RepoProgressEvent): shard_downloader.on_progress.register("broadcast").on_next(throttled_broadcast) async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name_or_path: str, prompt: str): + inference_class = inference_engine.__class__.__name__ if model_cards.get(model_name_or_path): - inference_class = inference_engine.__class__.__name__ - print(f'model_card = {get_repo(model_name_or_path, inference_class)}') shard = build_base_shard(model_name_or_path, inference_class) if not shard: print(f"Error: exo Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") return - print(f'model_id = {get_repo(shard.model_id, inference_class)}') tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) elif os.path.isdir(model_name_or_path): model_path = model_name_or_path.rstrip('/') @@ -252,16 +250,19 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam with open(model_config_path, 'r') as file: config = json.load(file) config_n_layers = config['num_hidden_layers'] - build_local_model_card(model_name, model_path, inference_engine.__class__.__name__, config_n_layers) + build_local_model_card(model_name, model_path, inference_class, config_n_layers) shard = Shard(model_id=model_path, start_layer=0, end_layer=0, n_layers=config_n_layers) tokenizer = await resolve_tokenizer(model_path) else: - print(f"Error: Not Find Local model '{model_name}' for inference engine {inference_engine.__class__.__name__}") + print(f"Error: Not Find Local model '{model_name}' for inference engine {inference_class}") return else: print(f"Error: Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") return + print(f'model_card = {get_repo(model_name_or_path, inference_class)}') + print(f'model_id = {get_repo(shard.model_id, inference_class)}') + request_id = str(uuid.uuid4()) callback_id = f"cli-wait-response-{request_id}" callback = node.on_token.register(callback_id) @@ -388,6 +389,17 @@ def handle_exit(): for s in [signal.SIGINT, signal.SIGTERM]: loop.add_signal_handler(s, handle_exit) + if check_agent(args.stored_model_ip) == "master": # Local model server + asyncio.create_task(local_model_api.run(host=args.stored_model_ip, port=args.stored_model_port)) + elif check_agent(args.stored_model_ip) == "client": # get local models from master + stored_models_data = await get_stored_models(args.stored_model_ip, args.stored_model_port) + for model in stored_models_data.get("models"): + model_name = model.get('name') + model_config_data = await get_stored_model_config(args.stored_model_ip, args.stored_model_port, model_name) + if model_config_data is not None: + model_layer = model_config_data.get('num_hidden_layers') + build_local_model_card(model_name, None, inference_engine.__class__.__name__, int(model_layer)) + await node.start(wait_for_peers=args.wait_for_peers) if args.command == "run" or args.run_model: @@ -413,8 +425,6 @@ def handle_exit(): else: asyncio.create_task(chatgpt_api.run(host=args.node_host, port=args.chatgpt_api_port)) # Start the API server as a non-blocking task - if any(ip == args.stored_model_ip for ip, _ in get_all_ip_addresses_and_interfaces()): - asyncio.create_task(local_model_api.run(host=args.stored_model_ip, port=args.stored_model_port)) # Start the local model server as a non-blocking task await asyncio.Event().wait() if args.wait_for_peers > 0: From 22b4484c1993753c1511043e78f85d5f76a08229 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Thu, 19 Dec 2024 15:49:52 +0800 Subject: [PATCH 21/26] filter: _resolve_tokenizer find error --- exo/main.py | 31 ++++++++++++++++++++----------- 1 file changed, 20 insertions(+), 11 deletions(-) diff --git a/exo/main.py b/exo/main.py index 30fb1d32f..7b4bb229f 100644 --- a/exo/main.py +++ b/exo/main.py @@ -207,18 +207,18 @@ def throttled_broadcast(shard: Shard, event: RepoProgressEvent): shard_downloader.on_progress.register("broadcast").on_next(throttled_broadcast) async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name_or_path: str, prompt: str): - if model_cards.get(model_name_or_path): - inference_class = inference_engine.__class__.__name__ - shard = build_base_shard(model_name_or_path, inference_class) - if not shard: - print(f"Error: exo Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") - return - tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) - elif os.path.isdir(model_name_or_path): - model_path = model_name_or_path.rstrip('/') - model_config_path = Path(model_path)/'config.json' - model_name = str(model_path.split('/')[-1]) + + if os.path.isdir(model_name_or_path) or model_name_or_path.startswith("Local/"): + if os.path.isdir(model_name_or_path): + model_path = model_name_or_path.rstrip('/') + model_name = str(model_path.split('/')[-1]) + else: + model_name = model_name_or_path.split("/")[-1] + exo_path = Path(Path.home()/".cache"/"exo") + model_path = f'{exo_path}/{model_name}' + model_config_path = Path(model_path)/'config.json' + print(model_config_path) if os.path.isfile(model_config_path): with open(model_config_path, 'r') as file: config = json.load(file) @@ -229,6 +229,15 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam else: print(f"Error: Not Find Local model '{model_name}' for inference engine {inference_engine.__class__.__name__}") return + + elif model_cards.get(model_name_or_path): + inference_class = inference_engine.__class__.__name__ + shard = build_base_shard(model_name_or_path, inference_class) + if not shard: + print(f"Error: exo Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") + return + tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) + else: print(f"Error: Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") return From 8c3a600abbabb8e263e507b8650086cbcbebaebc Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Thu, 19 Dec 2024 16:59:14 +0800 Subject: [PATCH 22/26] future: local mode auto download prototype --- exo/helpers.py | 2 +- exo/localmodel/lh_helpers.py | 5 +++- exo/main.py | 47 +++++++++++++++++++++--------------- 3 files changed, 32 insertions(+), 22 deletions(-) diff --git a/exo/helpers.py b/exo/helpers.py index 4498299eb..3d7225e70 100644 --- a/exo/helpers.py +++ b/exo/helpers.py @@ -339,7 +339,7 @@ async def get_stored_model_config(stored_ip: str, stored_port: int, model_name: def check_agent(store_ip: str) -> str: for ip, _ in get_all_ip_addresses_and_interfaces(): if (store_ip == ip) or (store_ip == "0.0.0.0"): - return "master" + return "stored" else: return "client" diff --git a/exo/localmodel/lh_helpers.py b/exo/localmodel/lh_helpers.py index 79c0f4753..db969d7a9 100644 --- a/exo/localmodel/lh_helpers.py +++ b/exo/localmodel/lh_helpers.py @@ -160,6 +160,7 @@ async def download_file( session: aiohttp.ClientSession, repo_id: str, revision: str, file_path: str, save_directory: str, progress_callback: Optional[RepoFileProgressCallback] = None, use_range_request: bool = True ): #base_url = f"{get_hf_endpoint()}/{repo_id}/resolve/{revision}/" + repo_id = repo_id.split("/")[-1] base_url = f'{get_lh_endpoint()}/models/{repo_id}/download/' url = urljoin(base_url, file_path) local_path = os.path.join(save_directory, file_path) @@ -245,7 +246,7 @@ async def download_model_dir( max_parallel_downloads: int = 4 ) -> Path: repo_root = get_repo_root(repo_id) - cachedreqs_dir = repo_root/"cachedreqs" + cachedreqs_dir = get_exo_home()/"cachedreqs"/repo_root # Ensure directories exist await aios.makedirs(repo_root, exist_ok=True) @@ -415,3 +416,5 @@ async def has_exo_home_write_access() -> bool: # Ori: has_hf_home_write_access try: return await aios.access(lh_home, os.W_OK) except OSError: return False +async def downlaod_tokenizer_config(repo_id: str): + await download_model_dir(repo_id=repo_id, allow_patterns="tokenizer_config.json") diff --git a/exo/main.py b/exo/main.py index 7e102c0ee..d47def994 100644 --- a/exo/main.py +++ b/exo/main.py @@ -37,7 +37,7 @@ from exo.download.hf.hf_helpers import has_hf_home_read_access, has_hf_home_write_access, get_hf_home, move_models_to_hf from exo.localmodel.http.http_server import LocalModelAPI -from exo.localmodel.lh_helpers import has_exo_home_read_access, has_exo_home_write_access, get_exo_home +from exo.localmodel.lh_helpers import has_exo_home_read_access, has_exo_home_write_access, get_exo_home, downlaod_tokenizer_config from exo.helpers import check_agent, get_stored_models, get_stored_model_config # parse args @@ -85,6 +85,9 @@ system_info = get_system_info() print(f"Detected system: {system_info}") +node_agent = check_agent(args.stored_model_ip) +print(f"Node Agent: {node_agent}") + inference_engine_name = args.inference_engine or ("mlx" if system_info == "Apple Silicon Mac" else "tinygrad") print(f"Inference engine name after selection: {inference_engine_name}") @@ -199,12 +202,13 @@ def preemptively_start_download(request_id: str, opaque_status: str): if status.get("type") == "node_status" and status.get("status") == "start_process_prompt": current_shard = node.get_current_shard(Shard.from_dict(status.get("shard"))) if os.path.isdir(current_shard.model_id): - print("Local model detected, skip download") + if DEBUG >= 2: print("Local model detected, skip download") pass elif "Local" in current_shard.model_id: - print("Local model detected, http download to other node") + if DEBUG >= 2: print("Local model detected, http download to other node") # borcast download model - asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) + if node_agent == "client": + asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) else: if DEBUG >= 2: print(f"Preemptively starting download for {current_shard}") asyncio.create_task(shard_downloader.ensure_shard(current_shard, inference_engine.__class__.__name__)) @@ -230,7 +234,6 @@ def throttled_broadcast(shard: Shard, event: RepoProgressEvent): last_broadcast_time = current_time asyncio.create_task(node.broadcast_opaque_status("", json.dumps({"type": "download_progress", "node_id": node.id, "progress": event.to_dict()}))) - shard_downloader.on_progress.register("broadcast").on_next(throttled_broadcast) async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_name_or_path: str, prompt: str): @@ -240,6 +243,8 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam if not shard: print(f"Error: exo Unsupported model '{model_name_or_path}' for inference engine {inference_engine.__class__.__name__}") return + if "Local" in model_name_or_path: + await downlaod_tokenizer_config(model_name_or_path) tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) elif os.path.isdir(model_name_or_path): model_path = model_name_or_path.rstrip('/') @@ -252,7 +257,7 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam config_n_layers = config['num_hidden_layers'] build_local_model_card(model_name, model_path, inference_class, config_n_layers) shard = Shard(model_id=model_path, start_layer=0, end_layer=0, n_layers=config_n_layers) - tokenizer = await resolve_tokenizer(model_path) + tokenizer = await resolve_tokenizer(model_path) # transformer tokenizer else: print(f"Error: Not Find Local model '{model_name}' for inference engine {inference_class}") return @@ -269,21 +274,22 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam if topology_viz: topology_viz.update_prompt(request_id, prompt) prompt = tokenizer.apply_chat_template([{"role": "user", "content": prompt}], tokenize=False, add_generation_prompt=True) - + try: print(f"Processing prompt: {prompt}") - await node.process_prompt(shard, prompt, request_id=request_id) - + await node.process_prompt(shard, prompt, request_id=request_id) # download model entry + _, tokens, _ = await callback.wait(lambda _request_id, tokens, is_finished: _request_id == request_id and is_finished, timeout=300) print("\nGenerated response:") print(tokenizer.decode(tokens)) + except Exception as e: print(f"Error processing prompt: {str(e)}") traceback.print_exc() finally: node.on_token.deregister(callback_id) - + def clean_path(path): """Clean and resolve path""" if path.startswith("Optional("): @@ -346,7 +352,7 @@ async def main(): # Check HuggingFace directory permissions hf_home, has_read, has_write = get_hf_home(), await has_hf_home_read_access(), await has_hf_home_write_access() - if DEBUG >= 1: print(f"Model storage directory: {hf_home}") + if DEBUG >= 1: print(f"HF Model storage directory: {hf_home}") print(f"{has_read=}, {has_write=}") if not has_read or not has_write: print(f""" @@ -357,7 +363,7 @@ async def main(): """) # Check exo directory permissions exo_home, has_read, has_write = get_exo_home(), await has_exo_home_read_access(), await has_exo_home_write_access() - if DEBUG >= 1: print(f"Model storage directory: {exo_home}") + if DEBUG >= 1: print(f"Local Model storage directory: {exo_home}") print(f"{has_read=}, {has_write=}") if not has_read or not has_write: print(f""" @@ -389,16 +395,17 @@ def handle_exit(): for s in [signal.SIGINT, signal.SIGTERM]: loop.add_signal_handler(s, handle_exit) - if check_agent(args.stored_model_ip) == "master": # Local model server + if node_agent == "stored": # Local model server asyncio.create_task(local_model_api.run(host=args.stored_model_ip, port=args.stored_model_port)) - elif check_agent(args.stored_model_ip) == "client": # get local models from master + elif node_agent == "client": # get local models from master stored_models_data = await get_stored_models(args.stored_model_ip, args.stored_model_port) - for model in stored_models_data.get("models"): - model_name = model.get('name') - model_config_data = await get_stored_model_config(args.stored_model_ip, args.stored_model_port, model_name) - if model_config_data is not None: - model_layer = model_config_data.get('num_hidden_layers') - build_local_model_card(model_name, None, inference_engine.__class__.__name__, int(model_layer)) + if stored_models_data != []: + for model in stored_models_data.get("models"): + model_name = model.get('name') + model_config_data = await get_stored_model_config(args.stored_model_ip, args.stored_model_port, model_name) + if model_config_data is not None: + model_layer = model_config_data.get('num_hidden_layers') + build_local_model_card(model_name, None, inference_engine.__class__.__name__, int(model_layer)) await node.start(wait_for_peers=args.wait_for_peers) From f0e18773eab9b4309a201e857444d311ba641f2a Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Fri, 20 Dec 2024 14:16:33 +0800 Subject: [PATCH 23/26] =?UTF-8?q?filter=EF=BC=9Adownload=20file=20path?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- exo/inference/tokenizers.py | 1 - exo/localmodel/lh_helpers.py | 13 +++---------- 2 files changed, 3 insertions(+), 11 deletions(-) diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index 823dbdc2d..381627e80 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -38,7 +38,6 @@ async def resolve_tokenizer(model_id: str): local_path = await get_local_model_dir(model_id) else: local_path = await get_local_snapshot_dir(model_id) - print(f'local_path = {local_path}') if DEBUG >= 2: print(f"Checking if local path exists to load tokenizer from local {local_path=}") try: if local_path and await aios.path.exists(local_path): diff --git a/exo/localmodel/lh_helpers.py b/exo/localmodel/lh_helpers.py index db969d7a9..c5da1fe82 100644 --- a/exo/localmodel/lh_helpers.py +++ b/exo/localmodel/lh_helpers.py @@ -159,7 +159,6 @@ async def fetch_lh_file_list(session, repo_id, path=""): async def download_file( session: aiohttp.ClientSession, repo_id: str, revision: str, file_path: str, save_directory: str, progress_callback: Optional[RepoFileProgressCallback] = None, use_range_request: bool = True ): - #base_url = f"{get_hf_endpoint()}/{repo_id}/resolve/{revision}/" repo_id = repo_id.split("/")[-1] base_url = f'{get_lh_endpoint()}/models/{repo_id}/download/' url = urljoin(base_url, file_path) @@ -246,17 +245,11 @@ async def download_model_dir( max_parallel_downloads: int = 4 ) -> Path: repo_root = get_repo_root(repo_id) - cachedreqs_dir = get_exo_home()/"cachedreqs"/repo_root - - # Ensure directories exist + cachedreqs_model_dir = Path(get_exo_home()) / "cachedreqs" / repo_root await aios.makedirs(repo_root, exist_ok=True) - await aios.makedirs(cachedreqs_dir, exist_ok=True) - - # Set up the cached file list directory - cached_file_list_dir = cachedreqs_dir - await aios.makedirs(cached_file_list_dir, exist_ok=True) - cached_file_list_path = cached_file_list_dir/"fetch_file_list.json" + await aios.makedirs(cachedreqs_model_dir, exist_ok=True) + cached_file_list_path = cachedreqs_model_dir / "fetch_file_list.json" async with aiohttp.ClientSession() as session: # Check if we have a cached file list if await aios.path.exists(cached_file_list_path): From 5eef335ef8d9c53795f4d8b63ab8dd5cc78797d1 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Fri, 20 Dec 2024 14:44:34 +0800 Subject: [PATCH 24/26] filter: stored_model dir path and http class name --- exo/download/hf/hf_shard_download.py | 2 +- .../storedhost}/http/http_helpers.py | 0 exo/{localmodel => download/storedhost}/http/http_server.py | 2 +- .../lh_helpers.py => download/storedhost/sh_helpers.py} | 0 exo/inference/tokenizers.py | 2 +- exo/main.py | 6 +++--- 6 files changed, 6 insertions(+), 6 deletions(-) rename exo/{localmodel => download/storedhost}/http/http_helpers.py (100%) rename exo/{localmodel => download/storedhost}/http/http_server.py (99%) rename exo/{localmodel/lh_helpers.py => download/storedhost/sh_helpers.py} (100%) diff --git a/exo/download/hf/hf_shard_download.py b/exo/download/hf/hf_shard_download.py index 919fe481e..64e682534 100644 --- a/exo/download/hf/hf_shard_download.py +++ b/exo/download/hf/hf_shard_download.py @@ -16,7 +16,7 @@ import aiohttp from aiofiles import os as aios -from exo.localmodel.lh_helpers import ( +from exo.download.storedhost.sh_helpers import ( get_exo_home, get_lh_weight_map, fetch_lh_file_list, download_model_dir ) diff --git a/exo/localmodel/http/http_helpers.py b/exo/download/storedhost/http/http_helpers.py similarity index 100% rename from exo/localmodel/http/http_helpers.py rename to exo/download/storedhost/http/http_helpers.py diff --git a/exo/localmodel/http/http_server.py b/exo/download/storedhost/http/http_server.py similarity index 99% rename from exo/localmodel/http/http_server.py rename to exo/download/storedhost/http/http_server.py index 5b263e2b0..29eca8f15 100644 --- a/exo/localmodel/http/http_server.py +++ b/exo/download/storedhost/http/http_server.py @@ -7,7 +7,7 @@ from typing import Dict from exo import DEBUG -class LocalModelAPI: +class StoredModelAPI: def __init__(self): self.app = web.Application() self.cache_dir = os.path.expanduser('~/.cache/exo') diff --git a/exo/localmodel/lh_helpers.py b/exo/download/storedhost/sh_helpers.py similarity index 100% rename from exo/localmodel/lh_helpers.py rename to exo/download/storedhost/sh_helpers.py diff --git a/exo/inference/tokenizers.py b/exo/inference/tokenizers.py index 381627e80..600c9f6a3 100644 --- a/exo/inference/tokenizers.py +++ b/exo/inference/tokenizers.py @@ -9,7 +9,7 @@ from exo.download.hf.hf_helpers import get_local_snapshot_dir from exo.helpers import DEBUG -from exo.localmodel.lh_helpers import get_local_model_dir +from exo.download.storedhost.sh_helpers import get_local_model_dir class DummyTokenizer: diff --git a/exo/main.py b/exo/main.py index d47def994..559c0c805 100644 --- a/exo/main.py +++ b/exo/main.py @@ -36,8 +36,8 @@ from exo.viz.topology_viz import TopologyViz from exo.download.hf.hf_helpers import has_hf_home_read_access, has_hf_home_write_access, get_hf_home, move_models_to_hf -from exo.localmodel.http.http_server import LocalModelAPI -from exo.localmodel.lh_helpers import has_exo_home_read_access, has_exo_home_write_access, get_exo_home, downlaod_tokenizer_config +from exo.download.storedhost.http.http_server import StoredModelAPI +from exo.download.storedhost.sh_helpers import has_exo_home_read_access, has_exo_home_write_access, get_exo_home, downlaod_tokenizer_config from exo.helpers import check_agent, get_stored_models, get_stored_model_config # parse args @@ -191,7 +191,7 @@ on_chat_completion_request=lambda req_id, __, prompt: topology_viz.update_prompt(req_id, prompt) if topology_viz else None, default_model=args.default_model ) -local_model_api = LocalModelAPI() +local_model_api = StoredModelAPI() node.on_token.register("update_topology_viz").on_next( lambda req_id, tokens, __: topology_viz.update_prompt_output(req_id, inference_engine.tokenizer.decode(tokens)) if topology_viz and hasattr(inference_engine, "tokenizer") else None ) From c557fe89402addfd8e7243df1015d710bf3740f7 Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Tue, 24 Dec 2024 09:49:43 +0800 Subject: [PATCH 25/26] feat:chatAPI can run Local model on multi node --- exo/api/chatgpt_api.py | 87 ++++++--- exo/download/storedhost/http/http_server.py | 52 ++++- exo/download/storedhost/sh_helpers.py | 52 +++++ exo/download/storedhost/sh_shard_download.py | 188 +++++++++++++++++++ exo/main.py | 3 +- 5 files changed, 352 insertions(+), 30 deletions(-) create mode 100644 exo/download/storedhost/sh_shard_download.py diff --git a/exo/api/chatgpt_api.py b/exo/api/chatgpt_api.py index b05a78788..36403b791 100644 --- a/exo/api/chatgpt_api.py +++ b/exo/api/chatgpt_api.py @@ -22,6 +22,9 @@ from exo.download.hf.hf_helpers import get_hf_home, get_repo_root from exo.apputil import create_animation_mp4 +from exo.download.storedhost.sh_shard_download import SHShardDownloader +from exo.download.storedhost.sh_helpers import get_repo_root, downlaod_tokenizer_config + class Message: def __init__(self, role: str, content: Union[str, List[Dict[str, Union[str, Dict[str, str]]]]]): self.role = role @@ -242,18 +245,19 @@ async def handle_model_support(self, request): shard = build_base_shard(model_name, self.inference_engine_classname) if shard: if 'Local/' in model_name: - download_percentage = 100.0 - total_size = "Unknown" - total_downloaded = "Unknown" + downloader = SHShardDownloader(quick_check=True) + downloader.current_shard = shard + downloader.current_repo_id = get_repo(shard.model_id, self.inference_engine_classname) + status = await downloader.get_shard_download_status() else: downloader = HFShardDownloader(quick_check=True) downloader.current_shard = shard downloader.current_repo_id = get_repo(shard.model_id, self.inference_engine_classname) status = await downloader.get_shard_download_status() - download_percentage = status.get("overall") if status else None - total_size = status.get("total_size") if status else None - total_downloaded = status.get("total_downloaded") if status else False + download_percentage = status.get("overall") if status else None + total_size = status.get("total_size") if status else None + total_downloaded = status.get("total_downloaded") if status else False model_data = { model_name: { @@ -341,6 +345,7 @@ async def handle_post_chat_completions(self, request): if not chat_request.model or chat_request.model not in model_cards: if DEBUG >= 1: print(f"Invalid model: {chat_request.model}. Supported: {list(model_cards.keys())}. Defaulting to {self.default_model}") chat_request.model = self.default_model + shard = build_base_shard(chat_request.model, self.inference_engine_classname) if not shard: supported_models = [model for model, info in model_cards.items() if self.inference_engine_classname in info.get("repo", {})] @@ -349,10 +354,12 @@ async def handle_post_chat_completions(self, request): status=400, ) - if "Local" in shard.model_id: + if os.path.isfile(chat_request.model): model_path = model_cards.get(shard.model_id, {}).get("repo", {}).get(self.inference_engine_classname,{}) tokenizer = await resolve_tokenizer(model_path) else: + if shard.model_id.startswith("Local"): + await downlaod_tokenizer_config(shard.model_id) tokenizer = await resolve_tokenizer(get_repo(shard.model_id, self.inference_engine_classname)) if DEBUG >= 4: print(f"Resolved tokenizer: {tokenizer}") @@ -485,30 +492,54 @@ async def handle_delete_model(self, request): repo_id = get_repo(shard.model_id, self.inference_engine_classname) if DEBUG >= 2: print(f"Repo ID for model: {repo_id}") + + if repo_id.startswith("local"): + lm_dir = get_repo_root(repo_id) + print(lm_dir) + if DEBUG >= 2: print(f"Looking for model files in: {lm_dir}") + + if os.path.exists(lm_dir): + if DEBUG >= 2: print(f"Found model files at {lm_dir}, deleting...") + try: + shutil.rmtree(lm_dir) + return web.json_response({ + "status": "success", + "message": f"Model {model_name} deleted successfully", + "path": str(lm_dir) + }) + except Exception as e: + return web.json_response({ + "detail": f"Failed to delete model files: {str(e)}" + }, status=500) + else: + return web.json_response({ + "detail": f"Model files not found at {lm_dir}" + }, status=404) + + else: + # Get the HF cache directory using the helper function + hf_home = get_hf_home() + cache_dir = get_repo_root(repo_id) - # Get the HF cache directory using the helper function - hf_home = get_hf_home() - cache_dir = get_repo_root(repo_id) - - if DEBUG >= 2: print(f"Looking for model files in: {cache_dir}") + if DEBUG >= 2: print(f"Looking for model files in: {cache_dir}") - if os.path.exists(cache_dir): - if DEBUG >= 2: print(f"Found model files at {cache_dir}, deleting...") - try: - shutil.rmtree(cache_dir) - return web.json_response({ - "status": "success", - "message": f"Model {model_name} deleted successfully", - "path": str(cache_dir) - }) - except Exception as e: + if os.path.exists(cache_dir): + if DEBUG >= 2: print(f"Found model files at {cache_dir}, deleting...") + try: + shutil.rmtree(cache_dir) + return web.json_response({ + "status": "success", + "message": f"Model {model_name} deleted successfully", + "path": str(cache_dir) + }) + except Exception as e: + return web.json_response({ + "detail": f"Failed to delete model files: {str(e)}" + }, status=500) + else: return web.json_response({ - "detail": f"Failed to delete model files: {str(e)}" - }, status=500) - else: - return web.json_response({ - "detail": f"Model files not found at {cache_dir}" - }, status=404) + "detail": f"Model files not found at {cache_dir}" + }, status=404) except Exception as e: print(f"Error in handle_delete_model: {str(e)}") diff --git a/exo/download/storedhost/http/http_server.py b/exo/download/storedhost/http/http_server.py index 29eca8f15..05c5835b6 100644 --- a/exo/download/storedhost/http/http_server.py +++ b/exo/download/storedhost/http/http_server.py @@ -29,7 +29,8 @@ def __init__(self): ('GET', '/files', self.handle_list_files), ('GET', '/models', self.handle_list_models), # models list ('GET', '/models/{foldername:.*}/list', self.handle_list_model_items), - ('GET', '/models/{model_name}/download/{filename:.*}', self.model_file_download) + ('GET', '/models/{model_name}/download/{filename:.*}', self.model_file_download), + ('HEAD', '/models/{model_name}/info/{filename:.*}', self.model_file_info), ] for method, path, handler in routes: @@ -127,6 +128,55 @@ async def model_file_download(self, request): return web.FileResponse(full_path) + async def model_file_info(self, request): + try: + model_name = request.match_info['model_name'] + filename = request.match_info['filename'] + full_path = os.path.join(self.cache_dir, model_name, filename) + + if not os.path.exists(full_path): + return web.json_response({ + "error": "File not found", + "path": full_path, + "model": model_name, + "filename": filename + }, status=404) + + if not os.path.isfile(full_path): + return web.json_response({ + "error": "Not a valid file", + "path": full_path, + "type": "directory" if os.path.isdir(full_path) else "unknown" + }, status=400) + + stat = os.stat(full_path) + file_info = { + 'name': filename, + 'model': model_name, + 'path': full_path, + 'size': stat.st_size, + 'content_length': stat.st_size, + 'modified': datetime.fromtimestamp(stat.st_mtime).isoformat(), + 'created': datetime.fromtimestamp(stat.st_ctime).isoformat(), + 'permissions': oct(stat.st_mode)[-3:], + 'is_file': True, + 'mime_type': self._get_mime_type(full_path), + 'status': 'available' + } + + return web.json_response(file_info) + + except Exception as e: + return web.json_response({ + "error": str(e), + "status": "error" + }, status=500) + + def _get_mime_type(self, file_path): + import mimetypes + mime_type, _ = mimetypes.guess_type(file_path) + return mime_type or 'application/octet-stream' + async def health_check(self, request): """健康检查端点""" return web.Response(text='OK', status=200) diff --git a/exo/download/storedhost/sh_helpers.py b/exo/download/storedhost/sh_helpers.py index c5da1fe82..4e465a6d7 100644 --- a/exo/download/storedhost/sh_helpers.py +++ b/exo/download/storedhost/sh_helpers.py @@ -399,6 +399,58 @@ def get_allow_patterns(weight_map: Dict[str, str], shard: Shard) -> List[str]: if DEBUG >= 2: print(f"get_allow_patterns {weight_map=} {shard=} {shard_specific_patterns=}") return list(default_patterns | shard_specific_patterns) +async def get_sh_model_file_download_percentage( # Ori: get_file_download_percentage + session: aiohttp.ClientSession, + repo_id: str, + file_path: str, + snapshot_dir: Path, +) -> float: + """ + Calculate the download percentage for a file by comparing local and remote sizes. + """ + try: + local_path = snapshot_dir / file_path + if not await aios.path.exists(local_path): + return 0 + + # Get local file size first + local_size = await aios.path.getsize(local_path) + if local_size == 0: + return 0 + + # Check remote size + # Change to SH endpoint get file size + model_name = repo_id.split("/")[-1] + base_url = f"{get_lh_endpoint()}/models/{model_name}/info/" + url = urljoin(base_url, file_path) + headers = await get_auth_headers() + + # Use HEAD request with redirect following for all files + async with session.head(url, headers=headers, allow_redirects=True) as response: + if response.status != 200: + if DEBUG >= 2: + print(f"Failed to get remote file info for {file_path}: {response.status}") + return 0 + + remote_size = int(response.headers.get('Content-Length', 0)) + print(f'file_path: {file_path} remote_size: {remote_size} local_size: {local_size}') + if remote_size == 0: + if DEBUG >= 2: + print(f"Remote size is 0 for {file_path}") + return 0 + + # Only return 100% if sizes match exactly + if local_size == remote_size: + return 100.0 + + # Calculate percentage based on sizes + return (local_size / remote_size) * 100 if remote_size > 0 else 0 + + except Exception as e: + if DEBUG >= 2: + print(f"Error checking file download status for {file_path}: {e}") + return 0 + async def has_exo_home_read_access() -> bool: # Ori: has_hf_home_read_access lh_home = get_exo_home() try: return await aios.access(lh_home, os.R_OK) diff --git a/exo/download/storedhost/sh_shard_download.py b/exo/download/storedhost/sh_shard_download.py new file mode 100644 index 000000000..fbe1710eb --- /dev/null +++ b/exo/download/storedhost/sh_shard_download.py @@ -0,0 +1,188 @@ +import asyncio +import traceback +from pathlib import Path +from typing import Dict, List, Tuple, Optional, Union +from exo.inference.shard import Shard +from exo.download.shard_download import ShardDownloader +from exo.download.download_progress import RepoProgressEvent +from exo.download.hf.hf_helpers import ( + download_repo_files, RepoProgressEvent, get_weight_map, + get_allow_patterns, get_repo_root, fetch_file_list, + get_local_snapshot_dir, get_file_download_percentage, + filter_repo_objects +) +from exo.helpers import AsyncCallbackSystem, DEBUG +from exo.models import model_cards, get_repo +import aiohttp +from aiofiles import os as aios + +from exo.download.storedhost.sh_helpers import ( + get_exo_home, get_lh_weight_map, fetch_lh_file_list, download_model_dir +) +from exo.download.storedhost.sh_helpers import ( + download_model_dir, RepoProgressEvent, get_lh_weight_map, + get_allow_patterns, get_repo_root, fetch_lh_file_list, + get_local_model_dir, get_sh_model_file_download_percentage +) + +class SHShardDownloader(ShardDownloader): + def __init__(self, quick_check: bool = False, max_parallel_downloads: int = 4): + self.quick_check = quick_check + self.max_parallel_downloads = max_parallel_downloads + self.active_downloads: Dict[Shard, asyncio.Task] = {} + self.completed_downloads: Dict[Shard, Path] = {} + self._on_progress = AsyncCallbackSystem[str, Tuple[Shard, RepoProgressEvent]]() + self.current_shard: Optional[Shard] = None + self.current_repo_id: Optional[str] = None + self.revision: str = "main" + + async def ensure_shard(self, shard: Shard, inference_engine_name: str) -> Path: + self.current_shard = shard + self.current_repo_id = get_repo(shard.model_id, inference_engine_name) + repo_name = get_repo(shard.model_id, inference_engine_name) + if shard in self.completed_downloads: + return self.completed_downloads[shard] + if self.quick_check: + repo_root = get_repo_root(repo_name) + if 'Local' in shard.model_id: + model_name = shard.model_id.split('/')[1] + snapshots_dir = Path(get_exo_home()/model_name) + else: # HF model + snapshots_dir = repo_root/"snapshots" + + if snapshots_dir.exists(): + visible_dirs = [d for d in snapshots_dir.iterdir() if not d.name.startswith('.')] + if visible_dirs: + most_recent_dir = max(visible_dirs, key=lambda x: x.stat().st_mtime) + return most_recent_dir + + # If a download on this shard is already in progress, keep that one + for active_shard in self.active_downloads: + if active_shard == shard: + if DEBUG >= 2: print(f"Download already in progress for {shard}. Keeping that one.") + return await self.active_downloads[shard] + + # Cancel any downloads for this model_id on a different shard + existing_active_shards = [active_shard for active_shard in self.active_downloads.keys() if active_shard.model_id == shard.model_id] + for active_shard in existing_active_shards: + if DEBUG >= 2: print(f"Cancelling download for {active_shard} (replacing with {shard})") + task = self.active_downloads[active_shard] + task.cancel() + try: + await task + except asyncio.CancelledError: + pass # This is expected when cancelling a task + except Exception as e: + if DEBUG >= 2: print(f"Error in cancelling download {active_shard}: {e}") + traceback.print_exc() + self.active_downloads = {active_shard: task for active_shard, task in self.active_downloads.items() if active_shard.model_id != shard.model_id} + + # Start new download + download_task = asyncio.create_task(self._download_shard(shard, repo_name)) + self.active_downloads[shard] = download_task + try: + path = await download_task + self.completed_downloads[shard] = path + return path + finally: + # Ensure the task is removed even if an exception occurs + print(f"Removing download task for {shard}: {shard in self.active_downloads}") + if shard in self.active_downloads: + self.active_downloads.pop(shard) + + async def _download_shard(self, shard: Shard, repo_name: str) -> Path: + async def wrapped_progress_callback(event: RepoProgressEvent): + self._on_progress.trigger_all(shard, event) + + if 'Local' in repo_name: + weight_map = await get_lh_weight_map(repo_name) + allow_patterns = get_allow_patterns(weight_map, shard) + return await download_model_dir(repo_name, progress_callback=wrapped_progress_callback, allow_patterns=allow_patterns, max_parallel_downloads=self.max_parallel_downloads) + else: # HF + weight_map = await get_weight_map(repo_name) + allow_patterns = get_allow_patterns(weight_map, shard) + return await download_repo_files(repo_name, progress_callback=wrapped_progress_callback, allow_patterns=allow_patterns, max_parallel_downloads=self.max_parallel_downloads) + + + @property + def on_progress(self) -> AsyncCallbackSystem[str, Tuple[Shard, RepoProgressEvent]]: + return self._on_progress + + async def get_shard_download_status(self) -> Optional[Dict[str, Union[float, int]]]: + if not self.current_shard or not self.current_repo_id: + if DEBUG >= 2: + print(f"No current shard or repo_id set: {self.current_shard=} {self.current_repo_id=}") + return None + + try: + # If no snapshot directory exists, return None - no need to check remote files + snapshot_dir = await get_local_model_dir(self.current_repo_id) + if not snapshot_dir: + if DEBUG >= 2: + print(f"No snapshot directory found for {self.current_repo_id}") + return None + + # Get the weight map to know what files we need + weight_map = await get_lh_weight_map(self.current_repo_id) + if not weight_map: + if DEBUG >= 2: + print(f"No weight map found for {self.current_repo_id}") + return None + + # Get all files needed for this shard + patterns = get_allow_patterns(weight_map, self.current_shard) + + # Check download status for all relevant files + status = {} + total_bytes = 0 + downloaded_bytes = 0 + + async with aiohttp.ClientSession() as session: + if self.current_repo_id.startswith("Local"): # 看要不要換 check_agent + file_list = await fetch_lh_file_list(session, self.current_repo_id) + else: + file_list = await fetch_file_list(session, self.current_repo_id, self.revision) + + relevant_files = list( + filter_repo_objects( + file_list, allow_patterns=patterns, key=lambda x: x["path"])) + + for file in relevant_files: + file_size = file["size"] + total_bytes += file_size + + percentage = await get_sh_model_file_download_percentage( + session, + self.current_repo_id, + file["path"], + snapshot_dir, + ) + status[file["path"]] = percentage + downloaded_bytes += (file_size * (percentage / 100)) + + # Add overall progress weighted by file size + if total_bytes > 0: + status["overall"] = (downloaded_bytes / total_bytes) * 100 + else: + status["overall"] = 0 + + # Add total size in bytes + status["total_size"] = total_bytes + if status["overall"] != 100: + status["total_downloaded"] = downloaded_bytes + + + if DEBUG >= 2: + print(f"Download calculation for {self.current_repo_id}:") + print(f"Total bytes: {total_bytes}") + print(f"Downloaded bytes: {downloaded_bytes}") + for file in relevant_files: + print(f"File {file['path']}: size={file['size']}, percentage={status[file['path']]}") + + return status + + except Exception as e: + if DEBUG >= 2: + print(f"Error getting shard download status: {e}") + traceback.print_exc() + return None diff --git a/exo/main.py b/exo/main.py index 559c0c805..7f9a1e229 100644 --- a/exo/main.py +++ b/exo/main.py @@ -246,7 +246,8 @@ async def run_model_cli(node: Node, inference_engine: InferenceEngine, model_nam if "Local" in model_name_or_path: await downlaod_tokenizer_config(model_name_or_path) tokenizer = await resolve_tokenizer(get_repo(shard.model_id, inference_class)) - elif os.path.isdir(model_name_or_path): + elif os.path.isdir(os.path.expanduser(model_name_or_path)): + model_name_or_path = os.path.expanduser(model_name_or_path) model_path = model_name_or_path.rstrip('/') model_name = str(model_path.split('/')[-1]) model_config_path = Path(model_path)/'config.json' From 322b36cb72e3487c2e90a705cde8000f8b75efce Mon Sep 17 00:00:00 2001 From: "OKHand.ziyu" Date: Tue, 24 Dec 2024 11:03:13 +0800 Subject: [PATCH 26/26] docs: Update the README.md to add instructions for using local models and automatic download steps. --- README.md | 41 ++++++++++++++++++++++++++++------------- 1 file changed, 28 insertions(+), 13 deletions(-) diff --git a/README.md b/README.md index 4871775fd..5eec24982 100644 --- a/README.md +++ b/README.md @@ -210,35 +210,50 @@ exo run llama-3.2-3b --prompt "What is the meaning of exo?" ### Example Usage on a single device with Local Model - Step1. Download the model from huggingface -- Step2. - ```shell - exo --add-local-model - ``` +- Step2. Put it in the exo folder(~/.cache/exo) - Step3. ```shell - exo --inference-engine mlx --run-model + exo --inference-engine mlx --run-model <~/.cache/exo/'model_name'> or - exo --inference-engine mlx --run-model + exo --inference-engine mlx --run-model ``` ### Example Usage on Multiple Devices with Local Model -#### Both devices are on MacOS: -- Step1. Download the model from huggingface and put it in the exo folder(/.cache/exo) +#### Manual Put Local Model: +- Step1. Download the Hugging Face model and place it in the exo folder (~/.cache/exo) of each node. - Step2. ```shell - exo --add-local-model + # Every node runs the following command + exo --inference-engine mlx ``` -#### Choose one device to run the following command: -```shell -curl http://localhost:52415/v1/chat/completions \ +- Step3. + ```shell + curl http://localhost:52415/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "Local/", "messages": [{"role": "user", "content": "What is the meaning of exo?"}], "temperature": 0.7 }' -``` + ``` +#### Auto Download Local Model: +- Step1. Download the Hugging Face model and place it in the exo folder (~/.cache/exo) of one node. +- Step2. + ```shell + # Every node runs the following command + exo --stored-model-ip --inference-engine mlx + ``` +- Step3. + ```shell + curl http://localhost:52415/v1/chat/completions \ + -H "Content-Type: application/json" \ + -d '{ + "model": "Local/", + "messages": [{"role": "user", "content": "What is the meaning of exo?"}], + "temperature": 0.7 + }' + ``` ### Model Storage Models by default are stored in `~/.cache/huggingface/hub`.