feat: 大模型节点新增模型参数配置-深度思考开关(enable_thinking)/温度(0-2)/最大输出字数(max_tokens)/随机种子(seed),AiChatRequest扩展透传参数,AiService新增ChatRequestAsync统一请求入口(图片+参数),前端节点面板模型参数区+帮助弹窗更新

Author: pythonHuang

Juggle.Application/Services/Flow/FlowExecutionService.cs

@@ -68,9 +68,7 @@ private async Task<string> BuildSkillsPromptAsync(List<long> ids)
     private async Task<FlowEngine> BuildEngineAsync(Dictionary<string, DataSourceInfo> dsInfos,
         Dictionary<string, string?> staticVars, Func<string, Task<string?>> flowContentLoader)
         => new FlowEngine(_httpClientFactory, dsInfos, staticVars, flowContentLoader,
-            aiChatFunc: req => req.Images.Count > 0
-                ? _aiService.ChatWithImagesAsync(req.SystemPrompt, req.UserInput, req.Images, req.ProviderId, req.Model)
-                : _aiService.ChatAsync(req.SystemPrompt, req.UserInput, req.ProviderId, modelOverride: req.Model),
+            aiChatFunc: req => _aiService.ChatRequestAsync(req),
             redisConnStrs: await GetRedisConnStrsAsync(),
             kbSearchFunc: (kbId, query, topK) => _kbService.SearchAsContextAsync(kbId, query, topK),
             skillResolver: BuildSkillsPromptAsync);

Juggle.Application/Services/Impl/AiService.cs

@@ -1,5 +1,6 @@
 using System.Text;
 using System.Text.Json;
+using Juggle.Domain.Engine.NodeExecutors;
 using Juggle.Domain.Entities;
 using Juggle.Infrastructure.Persistence;
 using Microsoft.EntityFrameworkCore;
@@ -185,6 +186,58 @@ public async Task<string> ChatMessagesAsync(List<(string Role, string Content)>
         return content?.Trim() ?? "";
     }
 
+    /// <summary>按 AI 节点请求调用大模型（统一入口：支持图片输入、温度/最大输出字数/随机种子/深度思考等模型参数）。</summary>
+    public async Task<string> ChatRequestAsync(AiChatRequest req)
+    {
+        var cfg = await ResolveConfigAsync(req.ProviderId > 0 ? req.ProviderId : null);
+        if (!string.IsNullOrEmpty(req.Model)) cfg.Model = req.Model;
+        if (string.IsNullOrEmpty(cfg.BaseUrl) || string.IsNullOrEmpty(cfg.ApiKey))
+            throw new Exception("未配置 AI 大模型：请在系统设置 → 大模型设置中添加并启用供应商");
+
+        var url = cfg.BaseUrl.TrimEnd('/');
+        if (!url.EndsWith("/chat/completions", StringComparison.OrdinalIgnoreCase))
+            url += "/chat/completions";
+
+        // 图片输入 → 多模态 content 数组
+        object userContent = req.UserInput;
+        if (req.Images is { Count: > 0 })
+        {
+            var content = new List<object>();
+            if (!string.IsNullOrWhiteSpace(req.UserInput))
+                content.Add(new { type = "text", text = req.UserInput });
+            foreach (var img in req.Images)
+                content.Add(new { type = "image_url", image_url = new { url = img } });
+            userContent = content.ToArray();
+        }
+
+        var payload = new Dictionary<string, object?>
+        {
+            ["model"] = cfg.Model,
+            ["messages"] = new object[]
+            {
+                new { role = "system", content = req.SystemPrompt },
+                new { role = "user", content = userContent }
+            },
+            ["temperature"] = req.Temperature ?? 0.2
+        };
+        if (req.MaxTokens is > 0) payload["max_tokens"] = req.MaxTokens.Value;
+        if (req.Seed.HasValue) payload["seed"] = req.Seed.Value;
+        if (req.EnableThinking) payload["enable_thinking"] = true;
+
+        var client = _httpClientFactory.CreateClient();
+        client.Timeout = TimeSpan.FromSeconds(180);
+        using var reqMsg = new HttpRequestMessage(HttpMethod.Post, url);
+        reqMsg.Headers.TryAddWithoutValidation("Authorization", $"Bearer {cfg.ApiKey}");
+        reqMsg.Content = new StringContent(JsonSerializer.Serialize(payload), Encoding.UTF8, "application/json");
+
+        using var resp = await client.SendAsync(reqMsg);
+        var body = await resp.Content.ReadAsStringAsync();
+        if (!resp.IsSuccessStatusCode)
+            throw new Exception($"AI 调用失败({(int)resp.StatusCode}): {Truncate(body, 300)}");
+        using var doc = JsonDocument.Parse(body);
+        return doc.RootElement.GetProperty("choices")[0].GetProperty("message").GetProperty("content").GetString()?.Trim() ?? "";
+    }
+
     private static string Truncate(string s, int len) => s.Length <= len ? s : s[..len] + "...";
 
     // ==================== 流程生成 ====================

Juggle.Domain/Engine/FlowModels.cs

@@ -304,6 +304,22 @@ public class AiConfig
     /// <summary>技能 ID 列表（逗号分隔，执行时技能内容拼入系统提示词）</summary>
     [JsonPropertyName("skills")]
     public string Skills { get; set; } = "";
+
+    /// <summary>是否启用深度思考（发送 enable_thinking 参数，Qwen/DeepSeek 等推理模型生效）</summary>
+    [JsonPropertyName("enableThinking")]
+    public bool EnableThinking { get; set; }
+
+    /// <summary>温度（0-2，越大越发散；空=服务默认）</summary>
+    [JsonPropertyName("temperature")]
+    public double? Temperature { get; set; }
+
+    /// <summary>最大输出字数（max_tokens，0/空=不限制）</summary>
+    [JsonPropertyName("maxTokens")]
+    public int? MaxTokens { get; set; }
+
+    /// <summary>随机种子（seed，固定后输出更稳定；空=随机）</summary>
+    [JsonPropertyName("seed")]
+    public int? Seed { get; set; }
 }
 
 /// <summary>文件解析节点配置（FILE_PARSE 节点）</summary>

Juggle.Domain/Engine/NodeExecutors/AiNodeExecutor.cs

@@ -1,7 +1,8 @@
 namespace Juggle.Domain.Engine.NodeExecutors;
 
 /// <summary>大模型调用请求（AI 节点与文件解析图片识别共用）。</summary>
-public record AiChatRequest(string SystemPrompt, string UserInput, List<string> Images, long ProviderId, string? Model);
+public record AiChatRequest(string SystemPrompt, string UserInput, List<string> Images, long ProviderId, string? Model,
+    double? Temperature = null, int? MaxTokens = null, int? Seed = null, bool EnableThinking = false);
 
 /// <summary>
 /// AI 大模型节点执行器：把输入变量内容作为用户消息、按系统提示词调用大模型，
@@ -56,7 +57,8 @@ public AiNodeExecutor(Func<AiChatRequest, Task<string>> chat, Func<List<long>, T
             }
         }
 
-        var reply = await _chat(new AiChatRequest(systemPrompt, input, images, cfg.ProviderId, string.IsNullOrWhiteSpace(cfg.Model) ? null : cfg.Model));
+        var reply = await _chat(new AiChatRequest(systemPrompt, input, images, cfg.ProviderId, string.IsNullOrWhiteSpace(cfg.Model) ? null : cfg.Model,
+            cfg.Temperature, cfg.MaxTokens, cfg.Seed, cfg.EnableThinking));
 
         if (!string.IsNullOrWhiteSpace(cfg.Output))
         {

JuggleNet6.Frontend/src/views/flow/FlowDesign.vue

@@ -328,6 +328,29 @@
               </el-select>
               <div style="font-size:11px;color:#909399;margin-top:4px">技能在 系统设置 → Skill 管理 中维护；执行时按「技能名 + 内容」拼入系统提示词。</div>
             </div>
+            <div class="prop-item">
+              <label>模型参数</label>
+              <div style="display:flex;align-items:center;gap:8px;margin-bottom:6px">
+                <span style="width:64px;font-size:12px;color:#666;flex-shrink:0">深度思考</span>
+                <el-switch v-model="selectedNode.aiConfig.enableThinking" size="small" />
+                <span style="font-size:11px;color:#909399">推理模型（deepseek-reasoner / Qwen 思考模式）生效</span>
+              </div>
+              <div style="display:flex;align-items:center;gap:8px;margin-bottom:6px">
+                <span style="width:64px;font-size:12px;color:#666;flex-shrink:0">温度</span>
+                <el-slider v-model="aiTempModel" size="small" style="flex:1" :min="0" :max="2" :step="0.1" :format-tooltip="aiTempFormat" />
+                <span style="width:36px;font-size:12px;color:#666;text-align:right;flex-shrink:0">{{ aiTempModel.toFixed(1) }}</span>
+              </div>
+              <div style="display:flex;align-items:center;gap:8px;margin-bottom:6px">
+                <span style="width:64px;font-size:12px;color:#666;flex-shrink:0">最大输出</span>
+                <el-input-number v-model="aiMaxTokensModel" size="small" style="flex:1" :min="0" :step="100" controls-position="right" />
+                <span style="font-size:11px;color:#909399;flex-shrink:0">0=不限制</span>
+              </div>
+              <div style="display:flex;align-items:center;gap:8px">
+                <span style="width:64px;font-size:12px;color:#666;flex-shrink:0">随机种子</span>
+                <el-input-number v-model="aiSeedModel" size="small" style="flex:1" :min="0" :step="1" controls-position="right" />
+                <span style="font-size:11px;color:#909399;flex-shrink:0">0=随机</span>
+              </div>
+            </div>
             <div class="prop-item">
               <label>输出目标</label>
               <div style="display:flex;gap:4px">
@@ -1980,6 +2003,21 @@ const skillIdsModel = computed({
   }
 })
 
+// AI 节点模型参数：温度（默认 0.7）/ 最大输出字数（0=不限）/ 随机种子（0=随机）
+const aiTempModel = computed<number>({
+  get: () => selectedNode.value?.aiConfig?.temperature ?? 0.7,
+  set: (v: number) => { if (selectedNode.value?.aiConfig) selectedNode.value.aiConfig.temperature = v }
+})
+const aiMaxTokensModel = computed<number>({
+  get: () => selectedNode.value?.aiConfig?.maxTokens || 0,
+  set: (v: number) => { if (selectedNode.value?.aiConfig) selectedNode.value.aiConfig.maxTokens = v > 0 ? v : null }
+})
+const aiSeedModel = computed<number>({
+  get: () => selectedNode.value?.aiConfig?.seed || 0,
+  set: (v: number) => { if (selectedNode.value?.aiConfig) selectedNode.value.aiConfig.seed = v > 0 ? v : null }
+})
+function aiTempFormat(v: number) { return v.toFixed(1) }
+
 // 按所选供应商的"支持的能力"过滤技能列表（供应商配置了 skills 时只显示其支持的）
 const aiNodeSkillOptions = computed(() => {
   const provider = aiProviders.value.find((p: any) => p.id === (selectedNode.value?.aiConfig?.providerId || 0))
@@ -2211,6 +2249,11 @@ env_delay_ms = env_retry_count * 1000 + 500` },
 输入变量:    作为用户消息发送给模型（可选流程入参/中间变量/出参）
 图片输入:    多选图片变量（data URL），配置后走视觉模型识别（多模态）
 系统提示词:  人设与任务说明（如"你是文案专家，输出简洁有力的文案"）
+模型参数:
+  深度思考:  开启后发送 enable_thinking 参数（推理模型如 deepseek-reasoner / Qwen 思考模式生效）
+  温度:      0-2 随机性（越大越发散），默认 0.7
+  最大输出:  最大输出字数（0=不限制）
+  随机种子:  固定后同输入输出更稳定（0=随机）
 输出目标:    变量 / 出参 / 入参 + 对应参数选择（模型回复写入）` },
       { title: '三、使用 demo', code: `// 场景：流程中生成商品推荐文案
 前置 ASSIGN 节点: env_product_name = "智能手表"
@@ -3327,7 +3370,7 @@ function addNode(type: string) {
     targetType: 'VARIABLE', targetCode: '', template: ''
   }
   if (type === 'AI') bNode.aiConfig = {
-    input: '', systemPrompt: '', output: ''
+    input: '', systemPrompt: '', output: '', enableThinking: false, temperature: 0.7
   }
   if (type === 'FILE_PARSE') bNode.fileParseConfig = {
     input: '', fileType: 'auto', output: ''