update model list

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
init
2026-07-20 17:03:42 +08:00 · 2026-07-14 16:44:33 +08:00 · 2026-07-14 15:45:51 +08:00 · 2026-07-13 19:43:35 +08:00 · 2026-07-13 18:38:55 +08:00 · 2026-06-22 19:00:46 +08:00
4 changed files with 583 additions and 121 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1,2 @@
+.DS_Store
+__pycache__/
--- a/1
+++ b/1
@@ -2,6 +2,7 @@ FROM modelhubxc-4pd.tencentcloudcr.com/xc_agent_platform/python:3.11-slim

 ENV PYTHONUNBUFFERED=1 
    
+
 WORKDIR /app

 COPY requirements.txt .
--- a/README.md
+++ b/README.md
@@ -1,22 +1,24 @@
-# xc_validation_strategy
+# xc_validation_strategy_gguf

-批量向 ModelHub XC 平台提交模型验证任务的策略服务，之后保持 HTTP 服务存活供平台探活。
+GGUF 模型下载 + 验证任务提交流水线策略服务：批量创建 GGUF 模型下载任务（最大并发 8），
+每个模型下载成功后立即提交 hygon / bi150 两个验证任务，之后保持 HTTP 服务存活供平台探活。

 ## 功能

- 自动登录 ModelHub 获取 Token
- 批量提交模型验证任务（vLLM 框架，Cambricon MLU-370-x8）
- 提交结果写入 `submitted_validation_tasks.txt`
+- 自动登录 ModelHub 获取 Token（失败时回退到预设 Token）
+- 按流水线批量创建 GGUF 模型下载任务（HuggingFace 源，最大并发 8）
+- 每个模型下载成功后，立即提交 hygon_k100-ai 与 Iluvatar_bi-150 两个验证任务（llamacpp 框架）
+- 下载成功的模型 ID 写入 `downloaded_success_models.txt`
 - 暴露 `/health` 和 `/status` 接口满足平台运行时契约

 ## 项目结构

 ```
 .
-├── main.py            # 主入口：HTTP 服务 + 提交逻辑
+├── main.py            # 主入口：HTTP 服务 + 下载/提交流水线
 ├── Dockerfile         # 平台镜像构建配置
 ├── requirements.txt   # Python 依赖
-└── submitted_validation_tasks.txt   # 运行后自动生成，记录提交结果
+└── downloaded_success_models.txt   # 运行后自动生成，记录下载成功的模型
 ```

 ## 平台契约说明
--- a/main.py
+++ b/main.py
@@ -1,34 +1,48 @@
 """
-xc_validation_strategy — 主入口
+xc_validation_strategy_gguf — 主入口

-启动后执行一次模型验证任务批量提交，之后保持 HTTP 服务存活。
+GGUF 模型下载 + 验证任务提交流水线（部署框架与 xc_validation_strategy 一致）。
+
+启动后运行流水线：批量创建 GGUF 模型下载任务（最大并发 8），
+每个模型下载成功后立即提交 hygon / bi150 两个验证任务；
 同时暴露 /health（K8s 探活）和 /status（运行状态）。
 """

 import json
 import os
+import re
 import signal
 import threading
 from datetime import datetime
 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
-from typing import List, Tuple
+from typing import Set

 import requests

 # ══════════════════════════════════════════════════════════
-#  配置（全部从环境变量读取，不硬编码敏感信息）
+#  配置
 # ══════════════════════════════════════════════════════════
 BASE_URL                      = os.environ.get("BASE_URL", "https://modelhub.org.cn")
-SUBMIT_ENDPOINT    = "/adminApi/async/task/create-contest-task"
+LOGIN_ENDPOINT                = "/adminApi/user/login"
+CREATE_DOWNLOAD_TASK_ENDPOINT = "/adminApi/async/task/model-download-task"
+SUBMIT_TEST_TASK_ENDPOINT     = "/adminApi/async/task/create-contest-task"
+
+# 登录账号：启动时优先用账号密码换取新 token（流水线运行时间长，预设 token 可能过期）
+USER_ACCOUNT  = "zhoushasha@4paradigm.com"
+USER_PASSWORD = "ganshenme0"
+
+# 通过 curl -X POST https://modelhub.org.cn/adminApi/user/login 获取后填入（登录失败时的回退）
+AUTH_TOKEN = "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ1c2VyQWNjb3VudCI6Inpob3VzaGFzaGEiLCJpZCI6MTQsInVzZXJSb2xlIjoibGVhZGVyYm9hcmQiLCJleHAiOjE3ODQ1NDc1NDYsImlhdCI6MTc4Mzk0Mjc0Nn0.ZcOqcrfI22LPi4mGMnt164nZGhi61ZxtJGYsoO7fZdM"

-# 通过 curl -X POST https://modelhub.org.cn/adminApi/user/login 获取后填入
-AUTH_TOKEN        = "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJ1c2VyQWNjb3VudCI6Inpob3VzaGFzaGEiLCJpZCI6MTQsInVzZXJSb2xlIjoibGVhZGVyYm9hcmQiLCJleHAiOjE3ODE4NTE0NzcsImlhdCI6MTc4MTI0NjY3N30.p3uvCpG50aLNifNVVXxvzmWJahbLM5K1671FVCtj8E8"
 CONTEST_API_TOKEN = "ef1ef82f3c9efee413d602345fbe224d"
+HF_TOKEN          = "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"
 CONTRIBUTORS      = "zhoushasha"
-GPU_TYPE          = "Cambricon_mlu-370-x8"
 TASK_TYPE         = "text-generation"
 STRATEGY_ID       = os.environ.get("STRATEGY_ID", "")  # 平台自动注入，无需修改

+MAX_CONCURRENT_DOWNLOADS = 8    # 同时下载的模型数上限
+CHECK_INTERVAL_SECONDS   = 10   # 下载状态轮询间隔（秒）
+
 HTTP_HOST = "0.0.0.0"
 HTTP_PORT = 8080

@@ -36,45 +50,255 @@ HTTP_PORT = 8080
 #  模型列表
 # ══════════════════════════════════════════════════════════
 ALL_MODEL_IDS = [
-    "NovaSky-AI/Sky-T1-7B",
-    "prithivMLmods/TESS-QwenRe-Fact-0.5B",
-    "Magpie-Align/Llama-3.1-8B-Magpie-Align-v0.1",
-    "Magpie-Align/Llama-3-8B-Magpie-Align-SFT-v0.1",
-    "Magpie-Align/Llama-3.1-8B-Magpie-Align-SFT-v0.2",
-    "LLM-Research/layerskip-llama2-7B",
-    "PowerInfer/SmallThinker-3B-Preview",
-    "HuggingFaceTB/SmolLM2-360M",
-    "ModelCloud.AI/Llama3.2-1B-Instruct",
-    "NousResearch/DeepHermes-3-Llama-3-8B-Preview",
-    "PAI/DistilQwen2.5-DS3-0324-14B",
-    "OpenBMB/MiniCPM-1B-sft-bf16",
-    "OpenBMB/MiniCPM4-8B-marlin-vLLM",
-    "OpenBMB/MiniCPM-2B-sft-fp32",
-    "unsloth/gemma-3-1b-it",
-    "LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct",
-    "Magpie-Align/Llama-3-8B-WildChat",
-    "allenai/tulu-2-7b",
-    "argilla/distilabeled-OpenHermes-2.5-Mistral-7B",
-    "Fengshenbang/Ziya2-13B-Chat",
-    "AI-ModelScope/starcoder2-15b",
-    "AI-ModelScope/phi-2",
-    "KoboldAI/OPT-13B-Erebus",
-    "NousResearch/OLMo-Bitnet-1B",
-    "AI-ModelScope/merlinite-7b",
-    "IndexTeam/Index-1.9B-Chat",
-    "AI-ModelScope/gpt2",
-    "togethercomputer/GPT-JT-6B-v1",
+
+    
+    
+    "mradermacher/Llama-3.2-3B-Della-GGUF",
+    "mradermacher/Aspire_V2_ALT-8B-Model_Stock-GGUF",
+    "mradermacher/Aspire_V2_ALT_ROW-8B-Model_Stock-GGUF",
+    "mradermacher/OTG1.6-Instruct-sft-dpo-7B-rc-2025-01-20-GGUF",
+    "mradermacher/llama-3.2-3b-it-Ehealthcare-ChatBot-v3-GGUF",
+    "mradermacher/nsfw_plz_gguf_me-GGUF",
+    "mradermacher/mistral-7b-sci-arc_reasoning_v2-GGUF",
+    "mradermacher/Jaja-small-GGUF",
+    "mradermacher/euclid-3B-GGUF",
+    "mradermacher/Llama-3.2-3B-Blend-GGUF",
+    "mradermacher/Llama-3.1-8B-KG-Extraction-v2-GGUF",
+    "mradermacher/Minerva-8b-GGUF",
+    "mradermacher/RTLCoder-Deepseek_OB25-GGUF",
+    "mradermacher/RTLCoder-Deepseek_OB50-GGUF",
+    "mradermacher/MedGPT_Finetuned-GGUF",
+    "mradermacher/mistral-irl-iter2-iterative-dpo-GGUF",
+    "mradermacher/Llama-3.2-Taiwan-3B-Instruct-GGUF",
+    "mradermacher/llama3-8b-breadcrumbs-ties-v4-GGUF",
+    "mradermacher/llama3-8b-della-v2-GGUF",
+    "mradermacher/hermes-GGUF",
+    "mradermacher/Orpo-oman-ar-stablelm-2-chat-GGUF",
+    "mradermacher/cocoruta-8b-llama3.1-GGUF",
+    "mradermacher/FalconSlerp6-7B-GGUF",
+    "mradermacher/mistral-7b-arc_reasoning-GGUF",
+    "mradermacher/Llama3.1-8B-relu-stage-1-dolma-v1_7-50B-4096-GGUF",
+    "mradermacher/mistral-7b-CoT-GGUF",
+    "mradermacher/llama3-8b-dare-ties-v3-GGUF",
+    "mradermacher/hopefully_humanish-rp-nsfw-test-v1-GGUF",
+    "mradermacher/mistral-7b-lima_v2-GGUF",
+    "mradermacher/Mistral-AFT-Off-Policy-GGUF",
+    "mradermacher/Mistral-AFT-On-Policy-GGUF",
+    "mradermacher/Llama-AFT-Off-Policy-GGUF",
+    "mradermacher/Llama-AFT-On-Policy-GGUF",
+    "mradermacher/OrangeJ-8B-Model_Stock-GGUF",
+    "mradermacher/Llama3-8b-alpaca-GGUF",
+    "mradermacher/hitchens-3-1-GGUF",
+    "mradermacher/Yearn-8B-Model_Stock-GGUF",
+    "mradermacher/DavidAU-Dark-Planet-of-Davids-8B-64k-GGUF",
+    "mradermacher/Qwen-2.5-3B-Tiny-Story-GGUF",
+    "mradermacher/CodeLlama-7b-Instruct-hf-SAP-RAP-GGUF",
+    "mradermacher/R1-ImpishMind-8B-GGUF",
+    "mradermacher/llama3-8b-slerp-v2-GGUF",
+    "mradermacher/layer-skip-vanill-3.2-1b-GGUF",
+    "mradermacher/AlexeyRyzhikov-Mistral-7b-TXT_to_JSON-V5.2-GGUF",
+    "mradermacher/SJT-2.5B-GGUF",
+    "mradermacher/liujx-78k-GGUF",
+    "mradermacher/Vangelus-Secundus-GGUF",
+    "mradermacher/bloomz-7b1-p3-GGUF",
+    "mradermacher/Llama-3.1-8B-price-GGUF",
+    "mradermacher/asm2asm-deepseek-1.3b-500k-mac-x86-O0-arm-2-GGUF",
+    "mradermacher/SJT-2.3B-GGUF",
+    "mradermacher/Llama-3-ELYZA-JP-8B-ojousama-chosen-after-SFTboth-GGUF",
+    "mradermacher/LLaMA-3-8B-SFR-SFT-R-GGUF",
+    "mradermacher/ELN-Llama-1B-base-GGUF",
+    "mradermacher/Qwen0.5b-RagSemanticChunker-GGUF",
+    "mradermacher/Llama-3-ELYZA-JP-8B-normal-chosen-after-SFTboth-GGUF",
+    "mradermacher/LLaMA-3-8B-SFR-Iterative-DPO-Concise-R-GGUF",
+    "mradermacher/Qwen2.7-7B-Instruct-QwQ-PRIME-1k-GGUF",
+    "mradermacher/flora-v1-GGUF",
+    "mradermacher/exaone-3.5-2.4b-instruct-dacon-llm2-GGUF",
+    "mradermacher/RPMash-8B-Model_Stock-GGUF",
+    "mradermacher/qwen2.5-0.5B_ichikara_4802-GGUF",
+    "mradermacher/payroll-teacher-model-2-GGUF",
+    "mradermacher/Phi-3.5-mini-instruct-3x-v1-GGUF",
+    "mradermacher/ImmyV2.7-GGUF",
+    "mradermacher/Qwen2.5-3B-Renoia-GGUF",
+    "mradermacher/ImmyV2.5-GGUF",
+    "mradermacher/mistral-7b-CoT_v2-GGUF",
+    "mradermacher/gpt2_individuated_zero_chaos-GGUF",
+    "mradermacher/ImmyV2.6-GGUF",
+    "mradermacher/gpt2_trickster-GGUF",
+    "mradermacher/Phi-3.5-mini-instruct-2x-v1-GGUF",
+    "mradermacher/llama-3.1-8b-dacon-GGUF",
+    "mradermacher/Llama3.1-8B-relu-stage-2-dolma-v1_7-50B-4096-GGUF",
+    "mradermacher/QwQ-LCoT1-Merged-GGUF",
+    "mradermacher/Magdala-9B-GGUF",
+    "mradermacher/fireblossom-32K-7B-GGUF",
+    "mradermacher/RPMash_V2-8B-Model_Stock-GGUF",
+    "mradermacher/Qwen2-7B-FullBirdnTiger-SmallDB-GGUF",
+    "mradermacher/Llama-8B-Distill-CoT-GGUF",
+    "mradermacher/Vangelus-Poetic-9B-GGUF",
+    "mradermacher/Unbound-Llama3-8B-GGUF",
+    "mradermacher/DeepSolana-GPT2-GGUF",
+    "mradermacher/layerskip-llama2-7b-topv1-v1-GGUF",
+    "mradermacher/QwQ-R1-Distill-7B-CoT-GGUF",
+    "mradermacher/DeepSeek-R1-MFANN-TIES-unretrained-7b-GGUF",
+    "mradermacher/mergekit-model_stock-zengbax-GGUF",
+    "mradermacher/Llama-2-7b-sft-SPIN-Llama-2-70b-Instruct-rm-GGUF",
+    "mradermacher/ZEUS-8B-V24-GGUF",
+    "mradermacher/YamshadowInex12_ShadowExperiment24-GGUF",
+    "mradermacher/SJT-4B-v1.1-GGUF",
+    "mradermacher/Qwen1.5-0.4B-Chat-GGUF",
+    "mradermacher/CogitoDistil-GGUF",
+    "mradermacher/MeliodasPercival_01_AlloyingotneoyInex12-GGUF",
+    "mradermacher/Experiment26Neuralsirkrishna_Experiment29Experiment24-GGUF",
+    "mradermacher/Llama-3.1-SISaAI-Ko-merge-8B-Instruct-GGUF",
+    "mradermacher/asm2asm-deepseek-1.3b-500k-mac-x86-O3-arm-GGUF",
+    "mradermacher/Soaring-3B-V2-GGUF",
+    "mradermacher/SJT-2.4B-GGUF",
+    "mradermacher/Qwen2-7B-sft-SPIN-gpt4o-rm-GGUF",
+    "mradermacher/Qwen2.5-DeepSeek-R1-MFANN-Slerp-7b-GGUF",
+    "mradermacher/sara_finetuned-GGUF",
+    "mradermacher/mistral-7b-v0.1-social_iqa-GGUF",
+    "mradermacher/Qwen2-7B-sft-SPIN-Qwen2.5-72B-Instruct-rm-GGUF",
+    "mradermacher/LlamaUz-3.1-8b-ct-GGUF",
+    "mradermacher/qwen2vl-model-2b-instruct-spatial-information-v1-GGUF",
+    "mradermacher/qwen2vl-model-2b-instruct-spatial-information-v2-GGUF",
+    "mradermacher/Aspire_V4-8B-Model_Stock-GGUF",
+    "mradermacher/kyutech5-jp-GGUF",
+    "mradermacher/Aspire_V4_ALT-8B-Model_Stock-GGUF",
+    "mradermacher/SRole_3181-GGUF",
+    "mradermacher/Bespoke-Stratos-17k-GGUF",
+    "mradermacher/SineAgentRL-vog-GGUF",
+    "mradermacher/LLAMA3-ReasoningCOT-GGUF",
+    "mradermacher/Intelligence-R1-Distill-7B-GGUF",
+    "mradermacher/Bitnet-M7-resized-GGUF",
+    "mradermacher/NeuralsirkrishnaShadow_PasticheInex12-GGUF",
+    "mradermacher/SineAgentRL-v0.2-GGUF",
+    "mradermacher/LonAI_20250122-GGUF",
+    "mradermacher/Experiment28M7_Experiment29Experiment24-GGUF",
+    "mradermacher/Mergerix-7b-v0.1-GGUF",
+    "mradermacher/Llama-3-8B-Instruct-v0.5-GGUF",
+    "mradermacher/Experiment26Yam_Multi_verse_modelM7-GGUF",
+    "mradermacher/Experiment28T3q_OgnoShadow-GGUF",
+    "mradermacher/Llama-2-7b-chat-hf_fictional_chinese_v2-GGUF",
+    "mradermacher/M7T3qm7xp_T3qm7xpStrangemerges_32-GGUF",
+    "mradermacher/Mistral-7B-v0.1-sft-SPIN-gpt4o-rm-GGUF",
+    "mradermacher/MeliodasPercival_01_Experiment28Experiment29-GGUF",
+    "mradermacher/Llama-2-7b-sft-SPIN-gpt4o-rm-GGUF",
+    "mradermacher/Experiment28M7_Strangemerges_32Ogno-GGUF",
+    "mradermacher/M7Yamshadowexperiment28_Strangemerges_32Strangemerges_30-GGUF",
+    "mradermacher/YamshadowStrangemerges_32_Inex12Yam-GGUF",
+    "mradermacher/Commonsense-QA-Mistral-7B-GGUF",
+    "mradermacher/NeuralsirkrishnaShadow_NeuralExperiment26-GGUF",
+    "mradermacher/llama2-7b-dpo-full-wo-healthsearch_qa-ep3-GGUF",
+    "mradermacher/Meta-Llama-3-8B-Instruct_fictional_arc_French_v2-GGUF",
+    "mradermacher/M7Yamshadowexperiment28_Experiment26Strangemerges_30-GGUF",
+    "mradermacher/CalmexperimentT3q-7B-GGUF",
+    "mradermacher/granite-8b-rpgle-GGUF",
+    "mradermacher/llama3-8b-tofutune-GGUF",
+    "mradermacher/Bart-finetuned-QA-GGUF",
+    "mradermacher/TinyLlama-1.1B-Chat-v1.0-mt-GGUF",
+    "mradermacher/h2o-dpo-merge2-GGUF",
+    "mradermacher/MKLLM-7B-Instruct-GGUF",
+    "mradermacher/T3Q-LLM3-Llama3-sft1.0-dpo1.0-GGUF",
+    "mradermacher/numfalm-3b-GGUF",
+    "mradermacher/NeuralsirkrishnaShadow_Experiment26Experiment24-GGUF",
+    "mradermacher/M7Yamshadowexperiment28_Strangemerges_32T3qm7xp-GGUF",
+    "mradermacher/SparrowMind-8B-GGUF",
+    "mradermacher/SmolLM-360M-TigerMath-Evaluated-SFT-GGUF",
+    "mradermacher/BreakingBadLlama-3-8B-GGUF",
+    "mradermacher/YamshadowInex12_Strangemerges_32Alloyingotneoy-GGUF",
+    "mradermacher/flammen17-py-DPO-v1-7B-GGUF",
+    "mradermacher/MetaAligner-HH-RLHF-1.1B-GGUF",
+    "mradermacher/Experiment26Yam_YamYam-GGUF",
+    "mradermacher/SmartQwen1.5-1.8B-orpo-v1-GGUF",
+    "mradermacher/TinyLlama-1.1B-chat-ties-v1-GGUF",
+    "mradermacher/al-baka-llama3-8b-experimental-GGUF",
+    "mradermacher/Mistral-7B-Instruct-v0.3-pruned-GGUF",
+    "mradermacher/Apollo2-3.8B-GGUF",
+    "mradermacher/Llama-3-DARE-v1-8B-GGUF",
+    "mradermacher/Experiment28T3q_Experiment27Inex12-GGUF",
+    "mradermacher/coder-2b-v0.1-hfrl-GGUF",
+    "mradermacher/myalee-v3-L31-8B-GGUF",
+    "mradermacher/TinyMoE-DopeykarasuMoe-xdareties2-GGUF",
+    "mradermacher/llama-3-bophades-v1-8B-GGUF",
+    "mradermacher/NeuralMonarchCoderPearlBeagle-GGUF",
+    "mradermacher/An4-7Bv2.3-GGUF",
+    "mradermacher/bruphin-lambda-GGUF",
+    "mradermacher/Qwen-2.5-7B-R1-Stock-GGUF",
+    "mradermacher/Llama-3.1-8B-sft-SPIN-gpt4o-rm-GGUF",
+    "mradermacher/LunarPass-1-GGUF",
+    "mradermacher/Llama-3.1-8B-sft-SPIN-Llama-3.1-70B-Instruct-rm-GGUF",
+    "mradermacher/game-play-point25-50-GGUF",
+    "mradermacher/woollie-7b-GGUF",
+    "mradermacher/Bespoke-Stratos-17k-v2-GGUF",
+    "mradermacher/DeepSeek-R1-Distill-Llama-UK-Legislation-8B-GGUF",
+    "mradermacher/Taiwan-tinyllama-v1.1-base-GGUF",
+    "mradermacher/M7Yamshadowexperiment28_YamExperiment26-GGUF",
+    "mradermacher/latin_english_translation_model-GGUF",
+    "mradermacher/K2S3-Mistral-7b-v1.3-GGUF",
+    "mradermacher/zephyr-7b-beta-ExPO-GGUF",
+    "mradermacher/mine-3B-GGUF",
+    "mradermacher/Ice0.64-24.01-RP-GGUF",
+    "mradermacher/Mistral-7B-v0.1-sft-SPIN-Mistral-8x7B-Instruct-v0.1-rm-GGUF",
+    "mradermacher/Mistral-7B-v0.3-sft-SPIN-gpt4o-rm-GGUF",
+    "mradermacher/Oolel-Small-v0.1-GGUF",
+    "mradermacher/Deepseek-qwen-modelstock-7B-GGUF",
+    "mradermacher/ZEUS-8B-V25-GGUF",
+    "mradermacher/MathSageFR-DeepSeek-R1-Distill-Qwen-1.5B-GGUF",
+    "mradermacher/LunarPass-2-GGUF",
+    "mradermacher/SJT-2.4B-Alpha-GGUF",
+    "mradermacher/Ice0.62.1-24.01-RP-GGUF",
+    "mradermacher/Trendyol-Turkcell-7b-mixture-GGUF",
+    "mradermacher/DeepSeek-R1-Distill-Qwen-MFANN-Slerp-7b-GGUF",
+    "mradermacher/Artifact_1-GGUF",
+    "mradermacher/gemma-2-9b-HangulFixer-GGUF",
+    "mradermacher/mistral-7b-v0.3-instruct-norobots-GGUF",
+    "mradermacher/Mistral7B-ASQA-GGUF",
+    "mradermacher/EEVE-Ko-8B-Instruct-hr_250124_ver1-GGUF",
+    "mradermacher/salamandra-2B-instruct-ultrachat-GGUF",
+    "mradermacher/salamandra-2B-instruct-smoltalk-GGUF",
+    "mradermacher/SJTpass-1-GGUF",
+    "mradermacher/QwenPass-4-GGUF",
+    "mradermacher/Llama-3.2-3B-Instruct-MedicalQA-GGUF",
+    "mradermacher/SJTPass-2-GGUF",
+    "mradermacher/Qwen2.5-7B-R1-Bespoke-Stock-GGUF",
+    "mradermacher/QwenTies-3-GGUF",
+    "mradermacher/Ice0.64.1-24.01-RP-GGUF",
+    "mradermacher/Qwen2.5-7B-R1-Bespoke-Task-GGUF",
+    "mradermacher/albert-spp-8b-GGUF",
+    "mradermacher/QwenLinear-1-GGUF",
+    "mradermacher/Llama-3.2-3B-Math-Oct-GGUF",
+    
+    
+    
+    
+    
+    
 ]

+
+# 去重（保持原有顺序）
+_seen = set()
+_deduplicated = []
+for _mid in ALL_MODEL_IDS:
+    if _mid not in _seen:
+        _deduplicated.append(_mid)
+        _seen.add(_mid)
+ALL_MODEL_IDS = _deduplicated
+print(f"[INFO] 去重后模型数量: {len(ALL_MODEL_IDS)}", flush=True)
+
+HEADERS = {"Content-Type": "application/json"}
+
 # ══════════════════════════════════════════════════════════
 #  全局状态（供 /status 展示）
 # ══════════════════════════════════════════════════════════
 _state = {
    "strategy_id":       STRATEGY_ID,
-    "phase":         "starting",   # starting | submitting | done | error
+    "phase":             "starting",   # starting | running | done | error
    "total":             len(ALL_MODEL_IDS),
-    "submitted":     0,
-    "failed":        0,
+    "downloading":       [],           # 当前正在下载的模型
+    "download_success":  0,
+    "download_failed":   0,
+    "submitted":         0,            # 成功提交的验证任务数（hygon + bi150）
+    "submit_failed":     0,
    "started_at":        None,
    "finished_at":       None,
 }
@@ -114,103 +338,336 @@ def _run_http():
    print("[http] 已关闭", flush=True)

 # ══════════════════════════════════════════════════════════
-#  业务逻辑
+#  工具函数：生成模型文件名
 # ══════════════════════════════════════════════════════════
-def _submit_task(token: str, model_id: str) -> Tuple[bool, str]:
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": f"Bearer {token}",
+def get_model_filename(model_id: str) -> str:
+    """
+    从 model_id 生成标准 GGUF 模型文件名。
+
+    规则：
+    - 移除组织名（/ 前部分）
+    - 处理 '_-_' 分割（保留原有逻辑）
+    - 移除末尾 '-GGUF'（不区分大小写）
+    - 若移除后以 -i1, -i2, ..., -i99 结尾：
+        → 替换为 .i1, .i2, ... 并添加 '-Q4_0.gguf'
+      否则：
+        → 直接添加 '.f16.gguf'
+
+    示例：
+      'mradermacher/Qwen3-8B-makisu-v2.0.1-i1-GGUF'
+        → 'Qwen3-8B-makisu-v2.0.1.i1-Q4_0.gguf'
+
+      'QuantFactory/Apollo2-9B-GGUF'
+        → 'Apollo2-9B.f16.gguf'
+    """
+    # 1. 提取模型名部分（/ 后）
+    base_name = model_id.split("/")[-1]
+
+    # 2. 处理 '_-_' 分割
+    if '_-_' in base_name:
+        base_name = base_name.split('_-_')[-1]
+
+    # 3. 移除末尾的 -GGUF（不区分大小写）
+    if base_name.lower().endswith("-gguf"):
+        base_name = base_name[:-5]
+
+    # 4. 检查是否以 -i<数字> 结尾（支持 i1～i99 等）
+    match = re.search(r'-i(\d+)$', base_name)
+    if match:
+        number = match.group(1)
+        base_name = base_name[:match.start()] + f".i{number}-Q4_0.gguf"
+    else:
+        base_name = base_name + ".f16.gguf"
+
+    return base_name
+
+# ══════════════════════════════════════════════════════════
+#  登录获取 token（失败时回退到预设 AUTH_TOKEN）
+# ══════════════════════════════════════════════════════════
+def login() -> str:
+    payload = {"userAccount": USER_ACCOUNT, "userPassword": USER_PASSWORD}
+    print("[login] 正在登录...", flush=True)
+    try:
+        resp = requests.post(BASE_URL + LOGIN_ENDPOINT, headers=HEADERS, json=payload, timeout=15)
+        data = resp.json()
+        if resp.status_code == 200 and data.get("code") == 0:
+            print("[login] 登录成功", flush=True)
+            return data["data"]["token"]
+        print(f"[login] 登录失败: {data.get('message')}，回退使用预设 Token", flush=True)
+    except Exception as e:
+        print(f"[login] 登录异常: {e}，回退使用预设 Token", flush=True)
+    return AUTH_TOKEN
+
+# ══════════════════════════════════════════════════════════
+#  创建单个模型的下载任务
+# ══════════════════════════════════════════════════════════
+def create_download_task(token: str, model_id: str) -> bool:
+    filename = get_model_filename(model_id)
+    auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
+    payload = {
+        "allowPatterns": [filename],
+        "hfToken": HF_TOKEN,
+        "modelId": model_id,
+        "source": "HUGGING_FACE",
+        "stillDownloadAlreadySuccessDownloadedModel": False
    }
-    config_content = f"""docker_image: harbor.4pd.io/hardcore-tech/cambricon-mlu370-pytorch:v25.01-torch2.5.0-torchmlu1.24.1-ubuntu22.04-py310
-nv_docker_image: harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0
-framework: vllm
+    print(f"📥 创建下载任务: {model_id} → {filename}", flush=True)
+    try:
+        resp = requests.post(BASE_URL + CREATE_DOWNLOAD_TASK_ENDPOINT, headers=auth_headers, json=payload, timeout=15)
+        if resp.status_code == 200:
+            data = resp.json()
+            if data.get("code") == 0:
+                print(f"✅ 下载任务已提交: {model_id}", flush=True)
+                return True
+            else:
+                print(f"⚠️ 下载任务业务失败 ({model_id}): {data.get('message')}", flush=True)
+                return False
+        else:
+            print(f"❌ HTTP 错误 ({model_id}): {resp.status_code} - {resp.text}", flush=True)
+            return False
+    except Exception as e:
+        print(f"💥 创建下载任务异常 ({model_id}): {e}", flush=True)
+        return False
+
+# ══════════════════════════════════════════════════════════
+#  查询单个模型的最新下载任务状态
+# ══════════════════════════════════════════════════════════
+def check_model_status(token: str, model_id: str) -> str:
+    """
+    返回状态: 'WAITING', 'RUNNING', 'SUCCESS', 'FAILED', 'UNKNOWN'
+    """
+    url = BASE_URL + CREATE_DOWNLOAD_TASK_ENDPOINT
+    auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
+    params = {"modelId": model_id, "current": 1, "pageSize": 1}
+    try:
+        resp = requests.get(url, headers=auth_headers, params=params, timeout=10)
+        if resp.status_code != 200:
+            return "UNKNOWN"
+        data = resp.json()
+        if data.get("code") != 0:
+            return "UNKNOWN"
+        records = data.get("data", {}).get("records", [])
+        if not records:
+            return "UNKNOWN"
+        status = records[0].get("status", "UNKNOWN").upper()
+        return status
+    except Exception as e:
+        print(f"⚠️ 查询状态异常 ({model_id}): {e}", flush=True)
+        return "UNKNOWN"
+
+# ══════════════════════════════════════════════════════════
+#  提交单个模型的测试任务 hygon
+# ══════════════════════════════════════════════════════════
+def submit_test_task(token: str, model_id: str) -> bool:
+    auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
+    model_filename = get_model_filename(model_id)
+    gpu_type = "hygon_k100-ai"
+    config_content = f"""docker_image: git.modelhub.org.cn:9443/enginex-hygon/hygon-llama.cpp:b7516
+nv_docker_image: harbor-contest.4pd.io/luxinlong02/llama-cpp:b7003-cuda-full-12.3
+framework: llamacpp
 storage: gpfs
 modelhub_options:
  srcRelativePath: leaderboard/modelHubXC/{model_id}
  mountPoint: /model
+api: completion
+temperature: 0
+repetition_penalty: 1.1
+top_p: 0.9
+max_model_len: 4096
 sut_config:
-  values:
  gpu_num: 1
-    env:
-      - name: MAX_MODEL_LEN
-        value: 8192
-    command: ["vllm", "serve", "/model", "--port", "8000", "--served-model-name", "llm", "--max-model-len", "8192", "--trust-remote-code", "--dtype", "float16"]
+  values:
+    command: ['/app/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20','--n-gpu-layers', '999', '--prio', '3', '--min_p', '0.01', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off']
 ref_config:
-  values:
-    cpu_num: 2
  gpu_num: 1
-    env:
-      - name: MAX_MODEL_LEN
-        value: 8192
-    command: ["vllm", "serve", "/model", "--port", "80", "--served-model-name", "llm", "--max-model-len", "8192", "--trust-remote-code", "--dtype", "float16"]
+  values:
+    command: ['/workspace/llama.cpp/build/bin/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20', '--n-gpu-layers', '999', '--prio', '3', '--min_p', '0.01', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off']
 """
-    payload = {
+    task_data = {
        "contestApiToken": CONTEST_API_TOKEN,
        "contributors": CONTRIBUTORS,
-        "gpuTypes":        [GPU_TYPE],
+        "gpuTypes": [gpu_type],
        "taskType": TASK_TYPE,
        "modelId": model_id,
-        "framework":       "vllm",
        "strategyId": STRATEGY_ID,   # 平台要求
        "submissionConfig": [{
            "config": config_content,
-            "gpuType":  GPU_TYPE,
-            "taskType": TASK_TYPE,
-        }],
+            "gpuType": gpu_type,
+            "taskType": TASK_TYPE
+        }]
    }
+    print(f"📤 提交测试任务 (hygon): {model_id}", flush=True)
    try:
-        resp = requests.post(
-            BASE_URL + SUBMIT_ENDPOINT,
-            headers=headers,
-            json=payload,
-            timeout=15,
-        )
+        resp = requests.post(BASE_URL + SUBMIT_TEST_TASK_ENDPOINT, json=task_data, headers=auth_headers, timeout=15)
+        if resp.status_code == 200:
            result = resp.json()
            if result.get("code") == 0:
-            task_id = result.get("data", {}).get("id", "")
-            print(f"[worker] OK  {model_id}  task_id={task_id}", flush=True)
-            return True, task_id
+                task_id = result.get("data", {}).get("taskId")
+                print(f"✅ 测试任务提交成功! Task ID: {task_id}", flush=True)
+                return True
            else:
-            print(f"[worker] FAIL {model_id}: {result.get('message')}", flush=True)
-            return False, ""
+                print(f"❌ 测试任务业务错误: {result.get('message')}", flush=True)
+                return False
+        else:
+            print(f"❌ 测试任务 HTTP 错误: {resp.status_code} - {resp.text}", flush=True)
+            return False
    except Exception as e:
-        print(f"[worker] ERROR {model_id}: {e}", flush=True)
-        return False, ""
+        print(f"💥 提交测试任务异常 ({model_id}): {e}", flush=True)
+        return False

+# ══════════════════════════════════════════════════════════
+#  提交单个模型的测试任务 bi150
+# ══════════════════════════════════════════════════════════
+def submit_test_task_bi150(token: str, model_id: str) -> bool:
+    auth_headers = {**HEADERS, "Authorization": f"Bearer {token}"}
+    model_filename = get_model_filename(model_id)
+    gpu_type = "Iluvatar_bi-150"
+    config_content = f"""docker_image: git.modelhub.org.cn:9443/enginex-iluvatar/iluvatar-llama.cpp:b7516-bi150
+nv_docker_image: harbor-contest.4pd.io/luxinlong02/llama-cpp:b7003-cuda-full-12.3
+framework: llamacpp
+storage: gpfs
+modelhub_options:
+  srcRelativePath: leaderboard/modelHubXC/{model_id}
+  mountPoint: /model
+max_model_len: 4096
+sut_config:
+  gpu_num: 1
+  values:
+    command: ['/app/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20','--n-gpu-layers','128', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off', '--no-mmap', '--sync-to-temp']
+ref_config:
+  gpu_num: 1
+  values:
+    command: ['/workspace/llama.cpp/build/bin/llama-server','--model', '/model/{model_filename}', '--alias', 'llm', '--threads', '20','--n-gpu-layers','128', '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000', '--jinja', '--flash-attn', 'off']
+"""
+    task_data = {
+        "contestApiToken": CONTEST_API_TOKEN,
+        "contributors": CONTRIBUTORS,
+        "gpuTypes": [gpu_type],
+        "taskType": TASK_TYPE,
+        "modelId": model_id,
+        "strategyId": STRATEGY_ID,   # 平台要求
+        "submissionConfig": [{
+            "config": config_content,
+            "gpuType": gpu_type,
+            "taskType": TASK_TYPE
+        }]
+    }
+    print(f"📤 提交测试任务 (bi150): {model_id}", flush=True)
+    try:
+        resp = requests.post(BASE_URL + SUBMIT_TEST_TASK_ENDPOINT, json=task_data, headers=auth_headers, timeout=15)
+        if resp.status_code == 200:
+            result = resp.json()
+            if result.get("code") == 0:
+                task_id = result.get("data", {}).get("taskId")
+                print(f"✅ 测试任务提交成功! Task ID: {task_id}", flush=True)
+                return True
+            else:
+                print(f"❌ 测试任务业务错误: {result.get('message')}", flush=True)
+                return False
+        else:
+            print(f"❌ 测试任务 HTTP 错误: {resp.status_code} - {resp.text}", flush=True)
+            return False
+    except Exception as e:
+        print(f"💥 提交测试任务异常 ({model_id}): {e}", flush=True)
+        return False

+# ══════════════════════════════════════════════════════════
+#  业务逻辑：动态流水线（下载 → 提交验证任务）
+# ══════════════════════════════════════════════════════════
 def _run_worker():
    _state["started_at"] = datetime.utcnow().isoformat()
-    _state["phase"] = "submitting"
+    _state["phase"] = "running"

-    successful: List[Tuple[str, str]] = []
-    token = AUTH_TOKEN
-    print("[worker] 使用预设 Token，跳过登录", flush=True)
+    try:
+        token = login()
+    except Exception as e:
+        print(f"[worker] 登录失败: {e}", flush=True)
+        _state["phase"] = "error"
+        return

-    for model_id in ALL_MODEL_IDS:
+    pending_models = list(ALL_MODEL_IDS)   # 尚未开始下载的模型
+    active_models: Set[str] = set()        # 当前正在下载的模型
+    completed_results = {}                 # model_id -> status
+
+    print(f"🚀 总共 {len(pending_models)} 个模型待下载。最大并发数: {MAX_CONCURRENT_DOWNLOADS}\n", flush=True)
+
+    while (pending_models or active_models) and not _shutdown.is_set():
+        # 1. 检查活跃任务状态
+        for model_id in list(active_models):
            if _shutdown.is_set():
                break
-        ok, task_id = _submit_task(token, model_id)
-        if ok:
+            status = check_model_status(token, model_id)
+            if status in ("SUCCESS", "FAILED"):
+                completed_results[model_id] = status
+                active_models.remove(model_id)
+                print(f"⏹️  {model_id} 完成，状态: {status}", flush=True)
+                if status == "SUCCESS":
+                    _state["download_success"] += 1
+                    # 下载成功后立即提交该模型的验证任务
+                    if submit_test_task(token, model_id):
                        _state["submitted"] += 1
-            successful.append((task_id, model_id))
+                        print(f"🧪 已为 {model_id} 提交 hygon 验证任务", flush=True)
                    else:
-            _state["failed"] += 1
+                        _state["submit_failed"] += 1
+                        print(f"⚠️ {model_id} hygon 验证任务提交失败", flush=True)

-    # 写入结果文件
+                    if submit_test_task_bi150(token, model_id):
+                        _state["submitted"] += 1
+                        print(f"🧪 已为 {model_id} 提交 bi150 验证任务", flush=True)
+                    else:
+                        _state["submit_failed"] += 1
+                        print(f"⚠️ {model_id} bi150 验证任务提交失败", flush=True)
+                else:
+                    _state["download_failed"] += 1
+
+        # 2. 补充新任务（最多补到 MAX_CONCURRENT_DOWNLOADS 个）
+        while len(active_models) < MAX_CONCURRENT_DOWNLOADS and pending_models and not _shutdown.is_set():
+            next_model = pending_models.pop(0)
+            if create_download_task(token, next_model):
+                active_models.add(next_model)
+                print(f"▶️  启动下载: {next_model} (当前活跃: {len(active_models)})", flush=True)
+            else:
+                # 创建失败也视为完成（避免卡住）
+                completed_results[next_model] = "CREATE_FAILED"
+                _state["download_failed"] += 1
+                print(f"❌ 创建失败: {next_model}", flush=True)
+
+        _state["downloading"] = sorted(active_models)
+
+        # 3. 稍作等待，避免频繁查询（可被 shutdown 信号打断）
+        if active_models or pending_models:
+            _shutdown.wait(CHECK_INTERVAL_SECONDS)
+
+    print("\n✅ 所有模型处理完毕！\n", flush=True)
+
+    # 4. 收集所有成功下载的模型ID并写入结果文件
+    success_models = [
+        mid for mid, status in completed_results.items()
+        if status == "SUCCESS"
+    ]
    try:
-        with open("submitted_validation_tasks.txt", "w", encoding="utf-8") as f:
-            for tid, mid in successful:
-                f.write(f"{tid}\t{mid}\n")
+        with open("downloaded_success_models.txt", "w", encoding="utf-8") as f:
+            for mid in success_models:
+                f.write(f"{mid}\n")
    except Exception:
        pass

+    print("🎉 下载成功的模型ID列表：", flush=True)
+    print("[", flush=True)
+    for mid in success_models:
+        print(f'    "{mid}",', flush=True)
+    print("]", flush=True)
+
+    _state["downloading"] = []
    _state["finished_at"] = datetime.utcnow().isoformat()
    _state["phase"] = "done"
    print(
-        f"[worker] 完成  submitted={_state['submitted']}  failed={_state['failed']}",
+        f"[worker] 完成  download_success={_state['download_success']}  "
+        f"download_failed={_state['download_failed']}  "
+        f"submitted={_state['submitted']}  submit_failed={_state['submit_failed']}",
        flush=True,
    )
-    # 提交完成后继续保持进程存活，等待平台停止
+    # 流水线完成后继续保持进程存活，等待平台停止

 # ══════════════════════════════════════════════════════════
 #  入口
@@ -228,7 +685,7 @@ def main():
    http_thread = threading.Thread(target=_run_http, daemon=False)
    http_thread.start()

-    # 提交任务线程
+    # 流水线线程
    worker_thread = threading.Thread(target=_run_worker, daemon=True)
    worker_thread.start()
Author	SHA1	Message	Date
zhousha	a9fe1f6393	update model list Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>	2026-07-20 17:03:42 +08:00
zhousha	9aba1595db	init	2026-07-14 16:44:33 +08:00
zhousha	85f41bba58	Replace main.py with GGUF download + validation submit pipeline Port logic from continuous_pipeline_download_gguf_zhoushasha_and_submit.py into the strategy-deployable framework (health/status HTTP server, STRATEGY_ID env, SIGTERM handling). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>	2026-07-14 15:45:51 +08:00
zhousha	d6b0e416db	update ppu	2026-07-13 19:43:35 +08:00
zhousha	4dcfed6b6d	update ppu	2026-07-13 18:38:55 +08:00
zhousha	1e8cfacd8e	uodate	2026-06-22 19:00:46 +08:00
zhousha	d6cca90496	update main.py	2026-06-22 18:44:42 +08:00
zhousha	031e0dc7a8	update main.py	2026-06-19 01:48:50 +08:00
zhousha	af6f501a5a	update main.py	2026-06-18 15:22:29 +08:00