unity調用本地部署deepseek全流程
deepseek本地部署
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安裝Ollama
搜索并打開Ollama官網[Ollama](https://ollama.com/download)
點擊Download下載對應版本
下載后點擊直接安裝
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安裝deepseek大語言模型
官網選擇Models
選擇deepseek-r1，選擇對應的模型，復制對應的命令
打開cmd，輸入命名啟動下載。下載完后便可以簡單進行聊天了。
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啟動Ollama服務
cmd輸入ollama serve命令啟動服務
如果無法啟動，可以嘗試退出ollama后重啟
常用的Ollama命令
命令 說明 ollama run <模型名> # 例如：ollama run llama2 下載并運行模型 ollama pull <模型名> # 例如：ollama pull mistral 僅下載模型不運行 ollama list 查看已安裝的模型列表 ollama rm <模型名> # 例如：ollama rm llama2 刪除本地模型 ollama cp <原模型名> <新模型名> 復制模型 ollama create <自定義模型名> -f ./Modelfile 自定義模型執行構建命令 ollama push <自定義模型名> 推送自定義模型到倉庫 ollama serve 啟動 Ollama 服務器 按 Ctrl+C終止進程，或結束相關后臺服務。停止服務器
unity調用
調用地址默認為：http://127.0.0.1:11434/api/chat
核心代碼
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>/// 緩存對話/// </summary>[SerializeField] public List<SendData> m_DataList = new List<SendData>();/// <summary>/// api key/// </summary>[SerializeField] private string api_key;/// <summary>/// AI設定/// </summary>public string m_SystemSetting = string.Empty;/// <summary>/// 模型名稱/// </summary>public string m_ModelName = "deepseek-r1:7b";//使用本地安裝的模型private void Start(){//運行時，添加AI設定m_DataList.Add(new SendData("system", m_SystemSetting));}/ <summary>/ 發送消息/ </summary>/ <returns></returns>public void PostMsg(string _msg, Action<string> _callback){//緩存發送的信息列表m_DataList.Add(new SendData("user", _msg));StartCoroutine(Request(_callback));}/// <summary>/// 調用接口/// </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;// 使用正則表達式提取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 數據包[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
}
