unity调用本地部署deepseek全流程

unity调用本地部署deepseek全流程

deepseek本地部署

• 安装Ollama
  搜索并打开Ollama官网[Ollama](https://ollama.com/download)

  

  点击Download下载对应版本

  

  下载后点击直接安装

• 安装deepseek大语言模型

  官网选择Models

  

  选择deepseek-r1，选择对应的模型，复制对应的命令

  

  打开cmd，输入命名启动下载。下载完后便可以简单进行聊天了。

  

  

• 启动Ollama服务

  cmd输入ollama serve命令启动服务

  

  如果无法启动，可以尝试退出ollama后重启

  常用的Ollama命令

  命令	说明
  ollama run <模型名> # 例如：ollama run llama2	下载并运行模型
  ollama pull <模型名> # 例如：ollama pull mistral	仅下载模型不运行
  ollama list	查看已安装的模型列表
  ollama rm <模型名> # 例如：ollama rm llama2	删除本地模型
  ollama cp <原模型名> <新模型名>	复制模型
  ollama create <自定义模型名> -f ./Modelfile	自定义模型执行构建命令
  ollama push <自定义模型名>	推送自定义模型到仓库
  ollama serve	启动 Ollama 服务器
  按 Ctrl+C 终止进程，或结束相关后台服务。	停止服务器

unity调用

调用地址默认为：http://127.0.0.1:11434/api/chat

核心代码

using System;
using System.Collections;
using System.Collections.Generic;
using System.Text.RegularExpressions;
using UnityEngine;
using UnityEngine.Networking;public class LocalDeepSeek : MonoBehaviour
{string  url = "http://127.0.0.1:11434/api/chat";/// <summary>/// 缓存对话/// </summary>[SerializeField] public List<SendData> m_DataList = new List<SendData>();/// <summary>/// api key/// </summary>[SerializeField] private string api_key;/// <summary>/// AI设定/// </summary>public string m_SystemSetting = string.Empty;/// <summary>/// 模型名称/// </summary>public string m_ModelName = "deepseek-r1:7b";//使用本地安装的模型private void Start(){//运行时，添加AI设定m_DataList.Add(new SendData("system", m_SystemSetting));}/ <summary>/ 发送消息/ </summary>/ <returns></returns>public void PostMsg(string _msg, Action<string> _callback){//缓存发送的信息列表m_DataList.Add(new SendData("user", _msg));StartCoroutine(Request(_callback));}/// <summary>/// 调用接口/// </summary>/// <param name="_postWord"></param>/// <param name="_callback"></param>/// <returns></returns>public  IEnumerator Request(System.Action<string> _callback){using (UnityWebRequest request = new UnityWebRequest(url, "POST")){Debug.Log("url:" + url);Debug.Log("m_ModelName:" + m_ModelName);PostData _postData = new PostData{model = m_ModelName,messages = m_DataList,stream = false};string _jsonText = JsonUtility.ToJson(_postData);byte[] data = System.Text.Encoding.UTF8.GetBytes(_jsonText);request.uploadHandler = (UploadHandler)new UploadHandlerRaw(data);request.downloadHandler = (DownloadHandler)new DownloadHandlerBuffer();request.SetRequestHeader("Content-Type", "application/json");if (!string.IsNullOrEmpty(api_key)){request.SetRequestHeader("Authorization", string.Format("Bearer {0}", api_key));}yield return request.SendWebRequest();if (request.responseCode == 200){string _msgBack = request.downloadHandler.text;Debug.Log(_msgBack);MessageBack2 _textback = JsonUtility.FromJson<MessageBack2>(_msgBack);string _backMsg = _textback.message.content;// 使用正则表达式提取Match match = Regex.Match(_backMsg, @"</think>\n\n(.*?)$", RegexOptions.Singleline);if (match.Success){string extractedText = match.Groups[1].Value.Trim();_backMsg = extractedText;}Debug.Log(_msgBack);m_DataList.Add(new SendData("assistant", _backMsg));_callback(_backMsg);//返回接收的消息}else{string _msgBack = request.downloadHandler.text;Debug.LogError(_msgBack);}}}#region 数据包[Serializable]public class PostData{public string model;public List<SendData> messages;public bool stream = false;}[Serializable]public class MessageBack{public string id;public string created;public string model;public List<MessageBody> choices;}[Serializable]public class MessageBack2{public string model;public string created;public Message message;}[Serializable]public class MessageBody{public Message message;public string finish_reason;public string index;}[Serializable]public class Message{public string role;public string content;}[Serializable]public class SendData{[SerializeField] public string role;[SerializeField] public string content;public SendData() { }public SendData(string _role, string _content){role = _role;content = _content;}}#endregion
}