diff --git a/README.md b/README.md
index 8ef1127..3d96a11 100644
--- a/README.md
+++ b/README.md
@@ -152,8 +152,8 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
 |
- STranslate |
- STranslate（Windows） is a ready-to-go translation ocr tool developed by WPF |
+ STranslate |
+ STranslate（Windows） is a ready-to-go translation ocr tool developed by WPF |
 |
@@ -164,7 +164,6 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
 |
ASP Client |
Deepseek.ASPClient is a lightweight ASP.NET wrapper for the Deepseek AI API, designed to simplify AI-driven text processing in .NET applications.. |
-
 |
@@ -188,13 +187,17 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
 |
16x Prompt |
16x Prompt is an AI coding tool with context management. It helps developers manage source code context and craft prompts for complex coding tasks on existing codebases. |
-
-
+
### AI Agent frameworks
+
+  |
+ YoMo |
+ Stateful Serverless LLM Function Calling Framework with Strongly-typed Language Support |
+
 |
SuperAgentX |
@@ -205,7 +208,7 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
Anda |
A Rust framework for AI agent development, designed to build a highly composable, autonomous, and perpetually memorizing network of AI agents. |
-
+
 |
Just-Agents |
A lightweight, straightforward library for LLM agents - no over-engineering, just simplicity! |
@@ -214,6 +217,11 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
Alice |
An autonomous AI agent on ICP, leveraging LLMs like DeepSeek for on-chain decision-making. Alice combines real-time data analysis with a playful personality to manage tokens, mine BOB, and govern ecosystems. |
+
+  |
+ Upsonic |
+ Upsonic offers a cutting-edge enterprise-ready agent framework where you can orchestrate LLM calls, agents, and computer use to complete tasks cost-effectively. |
+
### RAG frameworks
@@ -226,6 +234,16 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
+### Solana frameworks
+
+
+
+  |
+ Solana Agent Kit |
+ An open-source toolkit for connecting AI agents to Solana protocols. Now, any agent, using any Deepseek LLM, can autonomously perform 60+ Solana actions: |
+
+
+
### Synthetic data curation
@@ -251,6 +269,11 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
LangBot
（QQ, Lark, WeCom） |
LLM-based IM bots framework, supports QQ, Lark, WeCom, and more platforms. |
+
+  |
+ NoneBot
（QQ, Lark, Discord, TG, etc.） |
+ Based on NoneBot framework, provide intelligent chat and deep thinking functions, supports QQ, Lark, Discord, TG, and more platforms. |
+
### Browser Extensions
@@ -291,6 +314,11 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
Ncurator |
Knowledge Base AI Q&A Assistant - Let AI help you organize and analyze knowledge |
+
+  |
+ RssFlow |
+ An intelligent RSS reader browser extension with AI-powered RSS summarization and multi-dimensional feed views. Supports DeepSeek model configuration for enhanced content understanding. |
+
### VS Code Extensions
@@ -401,6 +429,11 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
ShellOracle |
A terminal utility for intelligent shell command generation. |
+
+  |
+ Bolna |
+ Use DeepSeek as the LLM for conversational voice AI agents |
+
 |
siri_deepseek_shortcut |
@@ -411,6 +444,11 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
n8n-nodes-deepseek |
An N8N community node that supports direct integration with the DeepSeek API into workflows. |
+
+  |
+ Portkey AI |
+ Portkey is a unified API for interacting with over 1600+ LLM models, offering advanced tools for control, visibility, and security in your DeepSeek apps. Python & Node SDK available. |
+
 |
LiteLLM |
@@ -426,6 +464,11 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
promptfoo |
Test and evaluate LLM prompts, including DeepSeek models. Compare different LLM providers, catch regressions, and evaluate responses. |
+
+ | |
+ deepseek-tokenizer |
+ An efficient and lightweight tokenization library for DeepSeek models, relying solely on the `tokenizers` library without heavy dependencies like `transformers`. |
+
 |
Langfuse |
@@ -441,4 +484,9 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
GPTLocalost |
Use DeepSeek-R1 in Microsoft Word Locally. No inference costs. |
+
+  |
+ WordPress ai助手 |
+ Docking Deepseek api for WordPress site ai conversation assistant, post generation, post summary plugin. |
+
diff --git a/README_cn.md b/README_cn.md
index 56fbe04..f92bfed 100644
--- a/README_cn.md
+++ b/README_cn.md
@@ -50,7 +50,7 @@
 |
- RSS翻译器 |
+ RSS翻译器 |
开源、简洁、可自部署的RSS翻译器 |
@@ -120,8 +120,8 @@
| |
- STranslate |
- STranslate（Windows） 是 WPF 开发的一款即用即走的翻译、OCR工具 |
+ STranslate |
+ STranslate（Windows） 是 WPF 开发的一款即用即走的翻译、OCR工具 |
| |
@@ -152,6 +152,11 @@
一个专为 AI 智能体开发设计的 Rust 语言框架，致力于构建高度可组合、自主运行且具备永久记忆能力的 AI 智能体网络。 |
+ |
+ YoMo |
+ Stateful Serverless LLM Function Calling Framework with Strongly-typed Language Support |
+
+
 |
Alice |
一个基于 ICP 的自主 AI 代理，利用 DeepSeek 等大型语言模型进行链上决策。Alice 结合实时数据分析和独特的个性，管理代币、挖掘 BOB 并参与生态系统治理。 |
@@ -168,6 +173,16 @@
+### Solana 框架
+
+
+
+ | |
+ Solana Agent Kit |
+ 一个用于连接 AI 智能体到 Solana 协议的开源工具包。现在，任何使用 Deepseek LLM 的智能体都可以自主执行 60+ 种 Solana 操作： |
+
+
+
### 即时通讯插件
### 浏览器插件
@@ -221,6 +241,11 @@
馆长 |
知识库AI问答助手 - 让AI帮助你整理与分析知识 |
+
+ | |
+ RssFlow |
+ 一款智能的RSS阅读器浏览器扩展，具有AI驱动的RSS摘要和多维度订阅视图功能。支持配置DeepSeek模型以增强内容理解能力。 |
+
### VS Code 插件
@@ -297,8 +322,17 @@
测试和评估LLM提示，包括DeepSeek模型。比较不同的LLM提供商，捕获回归，并评估响应。 |
+ | |
+ deepseek-tokenizer |
+ 一个高效的轻量级tokenization库，仅依赖`tokenizers`库，不依赖`transformers`等重量级依赖。 |
+
CR |
deepseek-review |
🚀 使用 Deepseek 进行代码审核，支持 GitHub Action 和本地 🚀 |
+
+ | |
+ WordPress ai助手 |
+ 对接Deepseek api用于WordPress站点的ai对话助手、ai文章生成、ai文章总结插件。 |
+
diff --git a/README_ja.md b/README_ja.md
index f6a06e7..c9870aa 100644
--- a/README_ja.md
+++ b/README_ja.md
@@ -160,6 +160,16 @@ DeepSeek APIを人気のソフトウェアに統合します。APIキーを取
+### Solanaフレームワーク
+
+
+
+ | |
+ Solana Agent Kit |
+ AIエージェントをSolanaプロトコルに接続するためのオープンソースツールキット。DeepSeek LLMを使用する任意のエージェントが、60以上のSolanaアクションを自律的に実行できます。 |
+
+
+
### IMアプリケーションプラグイン
@@ -173,6 +183,11 @@ DeepSeek APIを人気のソフトウェアに統合します。APIキーを取
QChatGPT
（QQ） |
高い安定性、プラグインサポート、リアルタイムネットワーキングを備えたQQチャットボット。 |
+
+ | |
+ NoneBot
（QQ, Lark, Discord, TG, etc.） |
+ NoneBotフレームワークを基に、インテリジェントな会話と深い思考機能をサポートします。QQ/飛書/Discord/Telegram等多种多様なメッセージプラットフォームに対応しています |
+
### ブラウザ拡張機能
@@ -208,6 +223,11 @@ DeepSeek APIを人気のソフトウェアに統合します。APIキーを取
FluentRead |
誰もが母国語のような読書体験を持つことができる革新的なオープンソースのブラウザ翻訳プラグイン |
+
+ | |
+ RssFlow |
+ AIを活用したRSS要約と多次元フィードビューを備えたインテリジェントなRSSリーダーブラウザ拡張機能。コンテンツ理解を強化するためのDeepSeekモデル設定をサポートしています。 |
+
### VS Code拡張機能
diff --git a/docs/solana-agent-kit/README.md b/docs/solana-agent-kit/README.md
new file mode 100644
index 0000000..07ca47c
--- /dev/null
+++ b/docs/solana-agent-kit/README.md
@@ -0,0 +1,67 @@
+# README
+
+
+
+---
+
+An open-source toolkit for connecting AI agents to Solana protocols. Now, any agent, using any model can autonomously perform 60+ Solana actions:
+
+
+## STEP1.
+
+Apply a token from [deepseek open platform](https://platform.deepseek.com/)
+
+## STEP 2
+
+Intialize the DeepSeek LLM
+
+```
+import { ChatDeepSeek } from "@langchain/deepseek";
+
+const deepseek = new ChatDeepSeek({
+ model: "deepseek-chat",
+ temperature: 0,
+});
+```
+
+## STEP 3
+
+Intialize the Solana Agent Kit with DeepSeek
+
+```typescript
+const solanaAgent = new SolanaAgentKit(
+ process.env.SOLANA_PRIVATE_KEY!,
+ process.env.RPC_URL!,
+ {
+ OPENAI_API_KEY: process.env.OPENAI_API_KEY!,
+ HELIUS_API_KEY: process.env.HELIUS_API_KEY!,
+ PERPLEXITY_API_KEY: process.env.PERPLEXITY_API_KEY!,
+ },
+);
+
+const tools = createSolanaTools(solanaAgent);
+
+const agent = createReactAgent({
+ llm: deepseek,
+ tools,
+ checkpointSaver: memory,
+ messageModifier: `
+ You are a helpful agent that can interact onchain using the Solana Agent Kit. You are
+ empowered to interact onchain using your tools. If you ever need funds, you can request them from the
+ faucet. If not, you can provide your wallet details and request funds from the user. If there is a 5XX
+ (internal) HTTP error code, ask the user to try again later. If someone asks you to do something you
+ can't do with your currently available tools, you must say so, and encourage them to implement it
+ themselves using the Solana Agent Kit, recommend they go to https://www.solanaagentkit.xyz for more information. Be
+ concise and helpful with your responses. Refrain from restating your tools' descriptions unless it is explicitly requested.
+ `,
+});
+
+const stream = await agent.stream(
+ { messages: [new HumanMessage(userInput)] },
+ config,
+);
+```
+
+More guides can be found in the [Solana Agent Kit](https://docs.solanaagentkit.xyz/v0/introduction)
+
+
\ No newline at end of file
diff --git a/docs/solana-agent-kit/assets/sendai-logo.png b/docs/solana-agent-kit/assets/sendai-logo.png
new file mode 100644
index 0000000..638b962
Binary files /dev/null and b/docs/solana-agent-kit/assets/sendai-logo.png differ
diff --git a/docs/yomo/README.md b/docs/yomo/README.md
new file mode 100644
index 0000000..1b727c1
--- /dev/null
+++ b/docs/yomo/README.md
@@ -0,0 +1,146 @@
+# YoMo Framework - Deepseek Provider
+
+YoMo is an open-source LLM Function Calling Framework for building Geo-distributed AI agents. Built atop QUIC Transport Protocol and Strongly-typed Stateful Serverless architecture, makes your AI agents low-latency, reliable, secure, and easy.
+
+## 🚀 Getting Started
+
+Let's implement a function calling serverless `sfn-get-ip-latency`:
+
+### Step 1. Install CLI
+
+```bash
+curl -fsSL https://get.yomo.run | sh
+```
+
+### Step 2. Start the server
+
+Prepare the configuration as `my-agent.yaml`
+
+```yaml
+name: ai-zipper
+host: 0.0.0.0
+port: 9000
+
+auth:
+ type: token
+ token: SECRET_TOKEN
+
+bridge:
+ ai:
+ server:
+ addr: 0.0.0.0:9000 ## Restful API endpoint
+ provider: deepseek ## LLM API Service we will use
+
+ providers:
+ deepseek:
+ api_key:
+ model: deepseek-reasoner
+```
+
+Start the server:
+
+```sh
+YOMO_LOG_LEVEL=debug yomo serve -c my-agent.yaml
+```
+
+### Step 3. Write the function
+
+First, let's define what this function do and how's the parameters required, these will be combined to prompt when invoking LLM.
+
+```golang
+type Parameter struct {
+ Domain string `json:"domain" jsonschema:"description=Domain of the website,example=example.com"`
+}
+
+func Description() string {
+ return `if user asks ip or network latency of a domain, you should return the result of the giving domain. try your best to dissect user expressions to infer the right domain names`
+}
+
+func InputSchema() any {
+ return &Parameter{}
+}
+```
+
+Create a Stateful Serverless Function to get the IP and Latency of a domain:
+
+```golang
+func Handler(ctx serverless.Context) {
+ var msg Parameter
+ ctx.ReadLLMArguments(&msg)
+
+ // get ip of the domain
+ ips, _ := net.LookupIP(msg.Domain)
+
+ // get ip[0] ping latency
+ pinger, _ := ping.NewPinger(ips[0].String())
+ pinger.Count = 3
+ pinger.Run()
+ stats := pinger.Statistics()
+
+ val := fmt.Sprintf("domain %s has ip %s with average latency %s", msg.Domain, ips[0], stats.AvgRtt)
+ ctx.WriteLLMResult(val)
+}
+
+```
+
+Finally, let's run it
+
+```bash
+$ yomo run app.go
+
+time=2025-01-29T21:43:30.583+08:00 level=INFO msg="connected to zipper" component=StreamFunction sfn_id=B0ttNSEKLSgMjXidB11K1 sfn_name=fn-get-ip-from-domain zipper_addr=localhost:9000
+time=2025-01-29T21:43:30.584+08:00 level=INFO msg="register ai function success" component=StreamFunction sfn_id=B0ttNSEKLSgMjXidB11K1 sfn_name=fn-get-ip-from-domain zipper_addr=localhost:9000 name=fn-get-ip-from-domain tag=16
+```
+
+### Done, let's have a try
+
+```sh
+$ curl -i http://127.0.0.1:9000/v1/chat/completions -H "Content-Type: application/json" -d '{
+ "messages": [
+ {
+ "role": "system",
+ "content": "You are a test assistant."
+ },
+ {
+ "role": "user",
+ "content": "Compare website speed between Nike and Puma"
+ }
+ ],
+ "stream": false
+}'
+
+HTTP/1.1 200 OK
+Content-Length: 944
+Connection: keep-alive
+Content-Type: application/json
+Date: Wed, 29 Jan 2025 13:30:14 GMT
+Keep-Alive: timeout=4
+Proxy-Connection: keep-alive
+
+{
+ "Content": "Based on the data provided for the domains nike.com and puma.com which include IP addresses and average latencies, we can infer the following about their website speeds:
+ - Nike.com has an IP address of 13.225.183.84 with an average latency of 65.568333 milliseconds.
+ - Puma.com has an IP address of 151.101.194.132 with an average latency of 54.563666 milliseconds.
+
+ Comparing these latencies, Puma.com is faster than Nike.com as it has a lower average latency.
+
+ Please be aware, however, that website speed can be influenced by many factors beyond latency, such as server processing time, content size, and delivery networks among others. To get a more comprehensive understanding of website speed, you would need to consider additional metrics and possibly conductreal-time speed tests.",
+ "FinishReason": "stop"
+}
+```
+
+### Full Example Code
+
+[Full LLM Function Calling Codes](https://github.com/yomorun/llm-function-calling-examples)
+
+## 🎯 Focuses on Geo-distributed AI Inference Infra
+
+It’s no secret that today’s users want instant AI inference, every AI
+application is more powerful when it response quickly. But, currently, when we
+talk about `distribution`, it represents **distribution in data center**. The AI model is
+far away from their users from all over the world.
+
+If an application can be deployed anywhere close to their end users, solve the
+problem, this is **Geo-distributed System Architecture**:
+
+