Spaces:
Sleeping
Sleeping
[feature_store] | |
reject_throttle = 0 | |
embedding_model_path = "/root/models/bce-embedding-base_v1" | |
reranker_model_path = "/root/models/bce-reranker-base_v1" | |
repo_dir = "repodir" | |
work_dir = "workdir" | |
n_clusters = [20, 50] | |
chunk_size = 1024 | |
[web_search] | |
x_api_key = "${YOUR-API-KEY}" | |
domain_partial_order = ["openai.com", "pytorch.org", "readthedocs.io", "nvidia.com", "stackoverflow.com", "juejin.cn", "zhuanlan.zhihu.com", "www.cnblogs.com"] | |
save_dir = "logs/web_search_result" | |
[llm] | |
enable_local = 1 | |
enable_remote = 1 | |
client_url = "http://127.0.0.1:8888/inference" | |
[llm.server] | |
local_llm_path = "/root/models/Qwen1.5-7B-Chat" | |
local_llm_max_text_length = 32000 | |
local_llm_bind_port = 8888 | |
remote_type = "" | |
remote_api_key = "" | |
remote_llm_max_text_length = 32000 | |
remote_llm_model = "" | |
rpm = 500 | |
[worker] | |
enable_sg_search = 0 | |
save_path = "logs/work.txt" | |
[worker.time] | |
start = "00:00:00" | |
end = "23:59:59" | |
has_weekday = 1 | |
[sg_search] | |
binary_src_path = "/usr/local/bin/src" | |
src_access_token = "${YOUR-SRC-ACCESS-TOKEN}" | |
[sg_search.opencompass] | |
github_repo_id = "open-compass/opencompass" | |
introduction = "用于评测大型语言模型(LLM). 它提供了完整的开源可复现的评测框架,支持大语言模型、多模态模型的一站式评测,基于分布式技术,对大参数量模型亦能实现高效评测。评测方向汇总为知识、语言、理解、推理、考试五大能力维度,整合集纳了超过70个评测数据集,合计提供了超过40万个模型评测问题,并提供长文本、安全、代码3类大模型特色技术能力评测。" | |
[sg_search.lmdeploy] | |
github_repo_id = "internlm/lmdeploy" | |
introduction = "lmdeploy 是一个用于压缩、部署和服务 LLM(Large Language Model)的工具包。是一个服务端场景下,transformer 结构 LLM 部署工具,支持 GPU 服务端部署,速度有保障,支持 Tensor Parallel,多并发优化,功能全面,包括模型转换、缓存历史会话的 cache feature 等. 它还提供了 WebUI、命令行和 gRPC 客户端接入。" | |
[frontend] | |
type = "none" | |
webhook_url = "https://open.feishu.cn/open-apis/bot/v2/hook/xxxxxxxxxxxxxxx" | |
message_process_policy = "immediate" | |
[frontend.lark_group] | |
app_id = "cli_a53a34dcb778500e" | |
app_secret = "2ajhg1ixSvlNm1bJkH4tJhPfTCsGGHT1" | |
encrypt_key = "abc" | |
verification_token = "def" | |
[frontend.wechat_personal] | |
bind_port = 9527 | |