Merge branch 'main' into main

docs/Geneplore AI/README.md

@@ -0,0 +1,17 @@
+# [Geneplore AI](https://geneplore.com/bot)
+
+## Geneplore AI is building the world's easiest way to use AI - Use 50+ models, all on Discord
+
+Chat with the all-new Deepseek v3, GPT-4o, Claude 3 Opus, LLaMA 3, Gemini Pro, FLUX.1, and ChatGPT with **one bot**. Generate videos with Stable Diffusion Video, and images with the newest and most popular models available.
+
+Don't like how the bot responds? Simply change the model in *seconds* and continue chatting like normal, without adding another bot to your server. No more fiddling with API keys and webhooks - every model is completely integrated into the bot.
+
+**NEW:** Try the most powerful open AI model, Deepseek v3, for free with our bot. Simply type /chat and select Deepseek in the model list.
+
+![image](https://github.com/user-attachments/assets/14db7e3c-c2c7-46d7-9fe1-5a5d1e3fc856)
+
+Use the bot trusted by over 60,000 servers and hundreds of paying subscribers, without the hassle of multiple $20/month subscriptions and complicated programming.
+
+https://geneplore.com
+
+© 2025 Geneplore AI, All Rights Reserved.

docs/Ncurator/README.md

@@ -0,0 +1,12 @@
+<img src="./assets/logo.png" width="64" height="auto" />
+
+# [Ncurator](https://www.ncurator.com)
+
+Knowledge Base AI Q&A Assistant -
+Let AI help you organize and analyze knowledge
+
+## UI
+<img src="./assets/screenshot3.png" width="360" height="auto" />
+
+## Integrate with Deepseek API
+<img src="./assets/screenshot2.png" width="360" height="auto" />

docs/Ncurator/README_cn.md

@@ -0,0 +1,11 @@
+<img src="./assets/logo.png" width="64" height="auto" />
+
+# [Ncurator](https://www.ncurator.com)
+
+知识库AI问答助手-让AI帮助你整理与分析知识
+
+## UI
+<img src="./assets/screenshot1.png" width="360" height="auto" />
+
+## 配置 Deepseek API
+<img src="./assets/screenshot2.png" width="360" height="auto" />

docs/avante.nvim/README.md

@@ -25,16 +25,14 @@ return {
     lazy = false,
     version = false, -- set this if you want to always pull the latest change
     opts = {
-      provider = "openai",
-      auto_suggestions_provider = "openai", -- Since auto-suggestions are a high-frequency operation and therefore expensive, it is recommended to specify an inexpensive provider or even a free provider: copilot
-      openai = {
-        endpoint = "https://api.deepseek.com/v1",
-        model = "deepseek-chat",
-        timeout = 30000, -- Timeout in milliseconds
-        temperature = 0,
-        max_tokens = 4096,
-        -- optional
-        api_key_name = "OPENAI_API_KEY",  -- default OPENAI_API_KEY if not set
+      provider = "deepseek",
+      vendors = {
+        deepseek = {
+          __inherited_from = "openai",
+          api_key_name = "DEEPSEEK_API_KEY",
+          endpoint = "https://api.deepseek.com",
+          model = "deepseek-coder",
+        },
       },
     },
     -- if you want to build from source then do `make BUILD_FROM_SOURCE=true`

docs/avante.nvim/README_cn.md

@@ -25,16 +25,14 @@ return {
     lazy = false,
     version = false, -- set this if you want to always pull the latest change
     opts = {
-      provider = "openai",
-      auto_suggestions_provider = "openai", -- Since auto-suggestions are a high-frequency operation and therefore expensive, it is recommended to specify an inexpensive provider or even a free provider: copilot
-      openai = {
-        endpoint = "https://api.deepseek.com/v1",
-        model = "deepseek-chat",
-        timeout = 30000, -- Timeout in milliseconds
-        temperature = 0,
-        max_tokens = 4096,
-        -- optional
-        api_key_name = "OPENAI_API_KEY",  -- default OPENAI_API_KEY if not set
+      provider = "deepseek",
+      vendors = {
+        deepseek = {
+          __inherited_from = "openai",
+          api_key_name = "DEEPSEEK_API_KEY",
+          endpoint = "https://api.deepseek.com",
+          model = "deepseek-coder",
+        },
       },
     },
     -- if you want to build from source then do `make BUILD_FROM_SOURCE=true`

docs/codecompanion.nvim/README.md

@@ -34,9 +34,8 @@ return {
     require("codecompanion").setup({
       adapters = {
         deepseek = function()
-          return require("codecompanion.adapters").extend("openai_compatible", {
+          return require("codecompanion.adapters").extend("deepseek", {
             env = {
-              url = "https://api.deepseek.com",
               api_key = "YOUR_API_KEY",
             },
           })
@@ -71,9 +70,8 @@ later(function()
   require("codecompanion").setup({
     adapters = {
       deepseek = function()
-        return require("codecompanion.adapters").extend("openai_compatible", {
+        return require("codecompanion.adapters").extend("deepseek", {
           env = {
-            url = "https://api.deepseek.com",
               api_key = "YOUR_API_KEY",
           },
         })

docs/codecompanion.nvim/README_cn.md

@@ -34,9 +34,8 @@ return {
     require("codecompanion").setup({
       adapters = {
         deepseek = function()
-          return require("codecompanion.adapters").extend("openai_compatible", {
+          return require("codecompanion.adapters").extend("deepseek", {
             env = {
-              url = "https://api.deepseek.com",
               api_key = "YOUR_API_KEY",
             },
           })
@@ -71,9 +70,8 @@ later(function()
   require("codecompanion").setup({
     adapters = {
       deepseek = function()
-        return require("codecompanion.adapters").extend("openai_compatible", {
+        return require("codecompanion.adapters").extend("deepseek", {
           env = {
-            url = "https://api.deepseek.com",
               api_key = "YOUR_API_KEY",
           },
         })

docs/continue/README.md

@@ -1,4 +1,4 @@
-<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/59196087/e4d082de-6f64-44b9-beaa-0de55d70cfab" width="64" height="auto" /> 
+<img src="https://github.com/continuedev/continue/blob/main/docs/static/img/logo.png?raw=true" width="64" height="auto" />
 
 # [Continue](https://continue.dev/)
 

docs/continue/README_cn.md

@@ -1,4 +1,4 @@
-<img src="https://github.com/deepseek-ai/awesome-deepseek-integration/assets/59196087/e4d082de-6f64-44b9-beaa-0de55d70cfab" width="64" height="auto" /> 
+<img src="https://github.com/continuedev/continue/blob/main/docs/static/img/logo.png?raw=true" width="64" height="auto" />
 
 # [Continue](https://continue.dev/)
 

docs/curator/README.md

@@ -0,0 +1,30 @@
+
+![image](https://raw.githubusercontent.com/bespokelabsai/curator/main/docs/Bespoke-Labs-Logomark-Red-crop.png)
+
+
+# [Curator](https://github.com/bespokelabsai/curator)
+
+
+Curator is an open-source tool to curate large scale datasets for post-training LLMs. 
+
+Curator was used to curate [Bespoke-Stratos-17k](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k), a reasoning dataset to train a fully open reasoning model [Bespoke-Stratos](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation).
+
+
+### Curator supports:
+
+- Calling Deepseek API for scalable synthetic data curation
+- Easy structured data extraction
+- Caching and automatic recovery
+- Dataset visualization
+- Saving $$$ using batch mode
+
+### Call Deepseek API with Curator easily:
+
+![image](https://pbs.twimg.com/media/GiLHb-xasAAbs4m?format=jpg&name=4096x4096)
+
+# Get Started here
+
+- [Colab Example](https://colab.research.google.com/drive/1Z78ciwHIl_ytACzcrslNrZP2iwK05eIF?usp=sharing)
+- [Github Repo](https://github.com/bespokelabsai/curator)
+- [Documentation](https://docs.bespokelabs.ai/)
+- [Discord](https://discord.com/invite/KqpXvpzVBS)

docs/curator/README_cn.md

@@ -0,0 +1,29 @@
+![image](https://raw.githubusercontent.com/bespokelabsai/curator/main/docs/Bespoke-Labs-Logomark-Red-crop.png)
+
+
+# [Curator](https://github.com/bespokelabsai/curator)
+
+
+Curator 是一个用于后训练大型语言模型 (LLMs) 和结构化数据提取的制作与管理可扩展的数据集的开源工具。
+
+Curator 被用来制作 [Bespoke-Stratos-17k](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k)，这是一个用于训练完全开源的推理模型 [Bespoke-Stratos](https://www.bespokelabs.ai/blog/bespoke-stratos-the-unreasonable-effectiveness-of-reasoning-distillation) 的推理数据集。
+
+
+### Curator 支持：
+
+- 调用 Deepseek API 进行可扩展的合成数据管理
+- 简便的结构化数据提取
+- 缓存和自动恢复
+- 数据集可视化
+- 使用批处理模式节省费用
+
+### 轻松使用 Curator 调用 Deepseek API：
+
+![image](https://pbs.twimg.com/media/GiLHb-xasAAbs4m?format=jpg&name=4096x4096)
+
+# 从这里开始
+
+- [Colab 示例](https://colab.research.google.com/drive/1Z78ciwHIl_ytACzcrslNrZP2iwK05eIF?usp=sharing)
+- [Github 仓库](https://github.com/bespokelabsai/curator)
+- [文档](https://docs.bespokelabs.ai/)
+- [Discord](https://discord.com/invite/KqpXvpzVBS)

docs/superagentx/README.md

@@ -0,0 +1,33 @@
+# `SuperAgentX`
+
+> 🤖 SuperAgentX: A lightweight autonomous true multi-agent framework with AGI capabilities.
+
+**SuperAgentX Source Code**: [https://github.com/superagentxai/superagentx](https://github.com/superagentxai/superagentx)
+
+**DeepSeek AI Agent Example**: [https://github.com/superagentxai/superagentx/blob/master/tests/llm/test_deepseek_client.py](https://github.com/superagentxai/superagentx/blob/master/tests/llm/test_deepseek_client.py)
+
+**Documentation** : [https://docs.superagentx.ai/](https://docs.superagentx.ai/)
+
+The SuperAgentX framework integrates DeepSeek as its LLM service provider, enhancing the multi-agent's reasoning and decision-making capabilities.
+
+## 🤖 Introduction
+
+`SuperAgentX` SuperAgentX is an advanced agentic AI framework designed to accelerate the development of Artificial General Intelligence (AGI). It provides a powerful, modular, and flexible platform for building autonomous AI agents capable of executing complex tasks with minimal human intervention.
+
+![SuperAgentX Diagram](https://raw.githubusercontent.com/superagentxai/superagentX/refs/heads/master/docs/images/architecture.png)
+
+### ✨ Key Features
+
+🚀 Open-Source Framework: A lightweight, open-source AI framework built for multi-agent applications with Artificial General Intelligence (AGI) capabilities.
+
+🎯 Goal-Oriented Multi-Agents: This technology enables the creation of agents with retry mechanisms to achieve set goals. Communication between agents is Parallel, Sequential, or hybrid.
+
+🏖️ Easy Deployment: Offers WebSocket, RESTful API, and IO console interfaces for rapid setup of agent-based AI solutions.
+
+♨️ Streamlined Architecture: Enterprise-ready scalable and pluggable architecture. No major dependencies; built independently!
+
+📚 Contextual Memory: Uses SQL + Vector databases to store and retrieve user-specific context effectively.
+
+🧠 Flexible LLM Configuration: Supports simple configuration options of various Gen AI models.
+
+🤝🏻 Extendable Handlers: Allows integration with diverse APIs, databases, data warehouses, data lakes, IoT streams, and more, making them accessible for function-calling features.