feat(config.ini): update

config.ini

@@ -1,3 +1,7 @@
+
+
+
+
 [feature_store]
 reject_throttle = 767.0
 # text2vec model path, support local relative path and huggingface model format
@@ -11,6 +15,7 @@ domain_partial_order = ["openai.com", "pytorch.org", "readthedocs.io", "nvidia.c
 save_dir = "logs/web_search_result"
 
 [llm]
+# enable local/remote LLM or not
 enable_local = 1
 enable_remote = 0
 # hybrid llm service address
@@ -25,7 +30,7 @@ local_llm_max_text_length = 16000
 # remote LLM service configuration
 # support any python3 openai interface, such as "gpt", "kimi" and so on
 remote_type = "kimi"
-remote_api_key = ""
+remote_api_key = "Y2tpMG41dDB0YzExbjRqYW5nN2c6bXNrLTFzVlB2NGJRaDExeWdnNTlZY3dYMm5mcVRpWng="
 # max text length for remote LLM. for example, use 128000 for kimi, 192000 for gpt
 remote_llm_max_text_length = 128000
 # openai model type. use "moonshot-v1-128k" for kimi, "gpt-4" for gpt
@@ -45,6 +50,15 @@ has_weekday = 1
 binary_src_path = "/usr/local/bin/src"
 src_access_token = "sgp_636f79ad2075640f_3ef2a135579615403e29b88d4402f1e6183ad347"
 
+# add your repo here, we just take opencompass and lmdeploy as example
+[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]
 # chat group type, support "lark" and "none"
 # check https://open.feishu.cn/document/client-docs/bot-v3/add-custom-bot to add bot