From 7f3400849d2747df8015d7d555527f1a5ce5c53c Mon Sep 17 00:00:00 2001
From: tpoisonooo <khj.application@aliyun.com>
Date: Mon, 8 Jan 2024 06:26:56 +0000
Subject: [PATCH] docs(README): update

---
 README.md    | 17 ++++++++++++-----
 README_en.md | 11 +++++++++--
 config.ini   | 26 ++++++--------------------
 3 files changed, 27 insertions(+), 27 deletions(-)

diff --git a/README.md b/README.md
index 0b55b6fe..e34ec20e 100644
--- a/README.md
+++ b/README.md
@@ -45,7 +45,7 @@ reject query: 茴香豆是怎么做的
 
 茴香豆使用了搜索引擎，点击 [serper 官网](https://serper.dev/api-key)获取限额 WEB_SEARCH_TOKEN，填入 `config.ini`
 
-```shell
+```bash
 # config.ini
 ..
 [web_search]
@@ -90,7 +90,7 @@ x_api_key = "${YOUR-X-API-KEY}"
 
 点击[创建飞书自定义机器人](https://open.feishu.cn/document/client-docs/bot-v3/add-custom-bot)，获取回调 WEBHOOK_URL，填写到 config.ini
 
-```shell
+```bash
 # config.ini
 ..
 [frontend]
@@ -99,7 +99,7 @@ webhook_url = "${YOUR-LARK-WEBHOOK-URL}"
 ```
 
 运行。结束后，技术助手的答复将发送到飞书群。
-```shell
+```bash
 python3 main.py workdir
 ```
 <img src="./resource/figures/lark-example.png" width="400">
@@ -200,5 +200,12 @@ python3 main.py workdir
 
     此时无法运行 local LLM，只能用 remote LLM 配合 text2vec 执行 pipeline。请确保 `config.ini` 只使用 remote LLM，关闭 local LLM
 
-# 📝 License
-项目使用 [GPL 3-License](./LICENSE)
+# 📝 引用
+```bash
+@misc{2024HuixiangDou,
+    title={HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance},
+    author={HuixiangDou Contributors},
+    howpublished = {\url{https://github.com/internlm/huixiangdou}},
+    year={2023}
+}
+```
diff --git a/README_en.md b/README_en.md
index 0029018c..a0302c55 100644
--- a/README_en.md
+++ b/README_en.md
@@ -198,5 +198,12 @@ In order to further improve the assistant's answering experience, the more of th
 
     In this case, you can't run local LLM, only remote LLM combined with text2vec to execute pipeline. Make sure `config.ini` only uses remote LLM, and turn off local LLM.
 
-# 📝 License
-The project uses the [GPL 3 License](./LICENSE).
+# 📝 Reference
+```bash
+@misc{2024HuixiangDou,
+    title={HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance},
+    author={HuixiangDou Contributors},
+    howpublished = {\url{https://github.com/internlm/huixiangdou}},
+    year={2023}
+}
+```
diff --git a/config.ini b/config.ini
index 09427eda..ec94f4e4 100644
--- a/config.ini
+++ b/config.ini
@@ -1,34 +1,24 @@
 [feature_store]
 reject_throttle = 767.0
-# text2vec model path, support local relative path and huggingface model format
-model_path = "shibing624/text2vec-base-chinese"
+model_path = "../models/text2vec-large-chinese"
 work_dir = "workdir"
 
 [web_search]
-# check https://serper.dev/api-key to get a free API key
-x_api_key = "${YOUR-API-KEY}"
+x_api_key = "aa3da0cd69c5a2df7c0b664dc8a4c118de532405"
 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 = 0
-# hybrid llm service address
-client_url = "http://127.0.0.1:8888/inference"
+client_url = "http://10.140.24.142:39999/inference"
 
 [llm.server]
-# local LLM configuration
-# support "internlm2-7B", "internlm2-20B" and "internlm2-70B"
 local_llm_path = "/internlm/ampere_7b_v1_7_0"
 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 = "${YOUR-API-KEY}"
-# max text length for remote LLM. for example, use 128000 for kimi, 192000 for gpt
+remote_api_key = "Y2tpMG41dDB0YzExbjRqYW5nN2c6bXNrLTFzVlB2NGJRaDExeWdnNTlZY3dYMm5mcVRpWng="
 remote_llm_max_text_length = 128000
-# openai model type. use "moonshot-v1-128k" for kimi, "gpt-4" for gpt
 remote_llm_model = "moonshot-v1-128k"
 bind_port = 8888
 
@@ -43,9 +33,8 @@ has_weekday = 1
 
 [sg_search]
 binary_src_path = "/usr/local/bin/src"
-src_access_token = "${YOUR-SRC-ACCESS-TOKEN}"
+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。"
@@ -55,8 +44,5 @@ 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 lark bot
 type = "none"
-# char group webhook url, send reply to group
-webhook_url = "https://open.feishu.cn/open-apis/bot/v2/hook/7a5d3d98-fdfd-40f8-b8de-851cb7e81e5c"
\ No newline at end of file
+webhook_url = "https://open.feishu.cn/open-apis/bot/v2/hook/7a5d3d98-fdfd-40f8-b8de-851cb7e81e5c"