智能体大模型接口全面切换 + 新增视觉智能体

- 全部 AI Worker 切换到 deepseek/deepseek-v4-flash（api.deepseek.com，实测757ms/次，成本降40倍）
- 团队模板默认 provider/model 同步改为 deepseek/deepseek-v4-flash
- 新增视觉智能体「视觉分析师」：autodl/qwen3.6-plus 多模态
- llm_gateway: chat_vision 多模态调用(URL/base64) + 空content自动重试 + 聚合后端路由容错
- engine: 任务描述支持 ![图](url) 图片注入（视觉任务直接派活）
- API: POST /api/workers/<id>/vision_test；前端 Worker 页新增🖼️视觉测试按钮
- 实测: 截图结构化分析 ✅ 雪羊图片识别 ✅ 辩论模式DeepSeek 55秒完成

app.py

@@ -263,6 +263,35 @@ def worker_test(wid):
         return jsonify({'ok': False, 'error': str(e)})
 
 
+@app.route('/api/workers/<int:wid>/vision_test', methods=['POST'])
+@require_auth
+def worker_vision_test(wid):
+    """视觉智能体能力测试：传入图片（URL 或 base64）与问题，验证多模态理解"""
+    w = db.q('SELECT * FROM workers WHERE id=?', (wid,), one=True)
+    if not w:
+        return jsonify({'ok': False, 'error': '不存在'}), 404
+    d = request.get_json(force=True)
+    image_url = (d.get('image_url') or '').strip()
+    image_b64 = (d.get('image_base64') or '').strip()
+    question = (d.get('question') or '请描述这张图片的内容').strip()
+    if not image_url and not image_b64:
+        return jsonify({'ok': False, 'error': '请提供图片 URL 或 base64 数据'}), 400
+    try:
+        if image_b64:
+            r = llm_gateway.chat_vision(
+                w['provider'], w['model'], question, image_url=f'data:image/png;base64,{image_b64}',
+                temperature=0.3, max_tokens=w['max_tokens'] or 2000,
+                base_url=w['base_url'] or None, api_key=w['api_key'] or None)
+        else:
+            r = llm_gateway.chat_vision(
+                w['provider'], w['model'], question, image_url=image_url,
+                temperature=0.3, max_tokens=w['max_tokens'] or 2000,
+                base_url=w['base_url'] or None, api_key=w['api_key'] or None)
+        return jsonify({'ok': True, 'data': r})
+    except Exception as e:
+        return jsonify({'ok': False, 'error': str(e)})
+
+
 @app.route('/api/providers')
 @require_auth
 def providers():
@@ -273,7 +302,7 @@ def providers():
             'has_key': bool(v['api_key']),
             'models': [m for m in config.MODEL_PRICING.keys() if m.startswith(
                 {'doubao': 'doubao', 'deepseek': 'deepseek', 'openai': 'gpt',
-                 'qwen': 'qwen', 'vllm': ''}.get(k, '__none__'))],
+                 'qwen': 'qwen', 'vllm': '', 'autodl': 'qwen3'}.get(k, '__none__'))],
         })
     return jsonify({'ok': True, 'data': data})
 
@@ -1119,8 +1148,8 @@ def template_apply(tid):
             pid, ids = tplmod.apply_project_template(t, variables, worker_id)
             return jsonify({'ok': True, 'kind': 'project', 'id': pid, 'task_ids': ids})
         if t['type'] == 'team':
-            ids = tplmod.apply_team_template(t, variables, provider=d.get('provider', 'doubao'),
+            ids = tplmod.apply_team_template(t, variables, provider=d.get('provider', 'deepseek'),
-                                             model=d.get('model', 'doubao-seed-evolving'))
+                                             model=d.get('model', 'deepseek-v4-flash'))
             return jsonify({'ok': True, 'kind': 'team', 'ids': ids})
         return jsonify({'ok': False, 'error': '未知模板类型'}), 400
     except Exception as e:

config.py

@@ -33,8 +33,14 @@ PROVIDERS = {
     },
     'deepseek': {
         'name': 'DeepSeek',
-        'base_url': 'https://api.deepseek.com/v1',
+        'base_url': 'https://api.deepseek.com',
-        'api_key': os.environ.get('DEEPSEEK_API_KEY', ''),
+        'api_key': os.environ.get('DEEPSEEK_API_KEY', 'sk-edb9df58ff574f8c98df1cd6a425e97c'),
+        'timeout': 600,
+    },
+    'autodl': {
+        'name': 'AutoDL 多模态（视觉）',
+        'base_url': 'https://www.autodl.art/api/v1',
+        'api_key': os.environ.get('AUTODL_API_KEY', 'F9MBfolzuapqTsD4KmUf9qen720rXvUZ3Sp3IrWiCTukqonx'),
         'timeout': 600,
     },
     'openai': {
@@ -66,10 +72,12 @@ MODEL_PRICING = {
     'doubao-pro-32k':            {'input': 2.0,   'output': 8.0},
     'deepseek-chat':             {'input': 2.0,   'output': 8.0},
     'deepseek-reasoner':         {'input': 4.0,   'output': 16.0},
+    'deepseek-v4-flash':         {'input': 0.2,   'output': 0.6},
     'gpt-4o':                    {'input': 17.5,  'output': 70.0},
     'gpt-4o-mini':               {'input': 1.1,   'output': 4.4},
     'qwen-plus':                 {'input': 0.8,   'output': 2.0},
     'qwen-max':                  {'input': 4.0,   'output': 12.0},
+    'qwen3.6-plus':              {'input': 2.0,   'output': 8.0},
 }
 DEFAULT_PRICE = {'input': 2.0, 'output': 8.0}
 

engine.py

@@ -123,7 +123,9 @@ def _budget_alert(project_id):
 
 
 def _build_messages(task, worker):
-    """构造提示词：任务指令 + RAG 知识库上下文"""
+    """构造提示词：任务指令 + RAG 知识库上下文
+    支持图片注入：任务描述中的 ![说明](图片URL) 或 图片:URL 会转成多模态消息（视觉 Worker）。"""
+    import re as _re
     messages = []
     if worker['system_prompt']:
         messages.append({'role': 'system', 'content': worker['system_prompt']})
@@ -132,7 +134,20 @@ def _build_messages(task, worker):
     if ctx:
         user_text = f'{ctx}\n\n----\n\n任务指令：{user_text}'
         _log(task['id'], 'info', f'📚 RAG 知识库命中 {len(refs)} 个片段：' + '；'.join(refs[:5]))
-    messages.append({'role': 'user', 'content': user_text})
+    # 提取图片 URL（![alt](url) 或 图片:url 或 image:url）
+    img_urls = []
+    for m in _re.finditer(r'!\[[^\]]*\]\(([^)\s]+)\)', user_text):
+        img_urls.append(m.group(1))
+    for m in _re.finditer(r'(?:图片|image)\s*[:：]\s*(https?://\S+)', user_text, _re.I):
+        img_urls.append(m.group(1))
+    if img_urls:
+        content = [{'type': 'text', 'text': user_text}]
+        for u in img_urls:
+            content.append({'type': 'image_url', 'image_url': {'url': u}})
+        messages.append({'role': 'user', 'content': content})
+        _log(task['id'], 'info', f'🖼️ 检测到 {len(img_urls)} 张图片，已注入多模态消息')
+    else:
+        messages.append({'role': 'user', 'content': user_text})
     return messages
 
 

llm_gateway.py

@@ -30,7 +30,12 @@ def calc_cost(model, prompt_tokens, completion_tokens):
 
 def chat(provider, model, messages, temperature=0.7, max_tokens=None,
          base_url=None, api_key=None, timeout=None, retries=None):
-    """调用 OpenAI 兼容 chat/completions，返回 {text, usage, cost, model}"""
+    """调用 OpenAI 兼容 chat/completions，返回 {text, usage, cost, model}
+    messages 支持两种格式：
+      - 纯文本：[{'role':'user','content':'...'}]
+      - 多模态：[{'role':'user','content':[{'type':'text','text':'...'},
+                                        {'type':'image_url','image_url':{'url':'...'}}]}]
+    """
     cfg = get_provider_cfg(provider)
     url = (base_url or cfg['base_url']).rstrip('/') + '/chat/completions'
     key = api_key or cfg['api_key']
@@ -56,7 +61,14 @@ def chat(provider, model, messages, temperature=0.7, max_tokens=None,
             resp = requests.post(url, json=payload, headers=headers, timeout=timeout)
             if resp.status_code == 200:
                 data = resp.json()
-                text = data['choices'][0]['message']['content'] or ''
+                msg = data['choices'][0]['message']
+                text = msg.get('content') or ''
+                if not text:
+                    # 推理模型偶发 content 为空：用 reasoning_content 兜底
+                    text = msg.get('reasoning_content') or ''
+                if not text:
+                    last_err = LLMError('模型返回空内容，重试中…')
+                    continue
                 usage = data.get('usage', {})
                 pt = usage.get('prompt_tokens', 0)
                 ct = usage.get('completion_tokens', 0)
@@ -84,6 +96,48 @@ def chat(provider, model, messages, temperature=0.7, max_tokens=None,
     raise last_err or LLMError('未知错误')
 
 
+def chat_vision(provider, model, text, image_url=None, image_path=None,
+                temperature=0.4, max_tokens=2000, base_url=None, api_key=None,
+                retries=3):
+    """多模态视觉调用：文本 + 图片（URL 或本地路径/base64）。
+    返回与 chat() 相同结构。
+    容错：聚合 API 偶发路由到纯文本后端（不认识 image_url），自动重试。"""
+    import base64 as _b64
+    import time as _time
+    content = [{'type': 'text', 'text': text}]
+    img_url = image_url
+    if image_path:
+        with open(image_path, 'rb') as f:
+            raw = f.read()
+        mime = 'image/png'
+        if image_path.lower().endswith(('.jpg', '.jpeg')):
+            mime = 'image/jpeg'
+        elif image_path.lower().endswith('.gif'):
+            mime = 'image/gif'
+        elif image_path.lower().endswith('.webp'):
+            mime = 'image/webp'
+        img_url = f'data:{mime};base64,{_b64.b64encode(raw).decode()}'
+    if img_url:
+        content.append({'type': 'image_url', 'image_url': {'url': img_url}})
+    messages = [{'role': 'user', 'content': content}]
+    last_err = None
+    for attempt in range(max(1, retries)):
+        try:
+            return chat(provider, model, messages,
+                        temperature=temperature, max_tokens=max_tokens,
+                        base_url=base_url, api_key=api_key)
+        except LLMError as e:
+            last_err = e
+            msg = str(e)
+            # 仅对“多模态格式不被支持/图片无效”类错误重试（聚合后端路由问题）
+            if any(k in msg for k in ('image_url', 'InvalidParameter', 'invalid_parameter',
+                                      'does not appear to be valid', 'image')):
+                _time.sleep(2 * (attempt + 1))
+                continue
+            raise
+    raise last_err or LLMError('视觉调用失败')
+
+
 def test_connection(provider, model, base_url=None, api_key=None):
     """连通性测试：发一条最小请求"""
     t0 = time.time()

static/app.js

@@ -623,6 +623,7 @@ async function pageWorkers() {
         <td class="mono">${w.task_cost_limit ? '单任务 ¥' + w.task_cost_limit : '—'}<br>${w.monthly_cost_limit ? '月 ¥' + w.monthly_cost_limit : ''}</td>
         <td><span class="badge ${w.status === 'enabled' ? 'st-done' : 'st-cancelled'}">${w.status === 'enabled' ? '启用' : '停用'}</span></td>
         <td><button class="btn sm" onclick="testWorker(${w.id})">测试</button>
+            <button class="btn sm" onclick="visionTest(${w.id})">🖼️ 视觉测试</button>
             <button class="btn sm" onclick="openWorkerModal(${JSON.stringify(w).replace(/"/g,'&quot;')}, ${JSON.stringify(ps.data).replace(/"/g,'&quot;')})">编辑</button>
             <button class="btn sm danger" onclick="delWorker(${w.id})">删除</button></td>
       </tr>`).join('') || '<tr><td colspan="9" class="empty">还没有 Worker，注册第一个虚拟员工吧</td></tr>'}
@@ -636,6 +637,27 @@ async function testWorker(wid) {
   catch (e) { toast('❌ ' + e.message, 'err'); }
 }
 
+async function visionTest(wid) {
+  openModal(`
+    <h3>🖼️ 视觉能力测试</h3>
+    <div class="tab-note">多模态智能体：输入图片 URL 与问题，验证图像理解能力。示例：<br>
+    https://upload.wikimedia.org/wikipedia/commons/thumb/3/3a/Cat03.jpg/640px-Cat03.jpg</div>
+    <label>图片 URL</label><input id="vt-url" placeholder="https://...">
+    <label>问题</label><textarea id="vt-q" rows="2">请描述这张图片的内容，并给出专业分析。</textarea>
+    <button class="btn primary" id="vt-go">🚀 开始分析</button>
+    <div id="vt-out" style="margin-top:10px"></div>`);
+  $('#vt-go').addEventListener('click', async () => {
+    const url = $('#vt-url').value.trim();
+    if (!url) return toast('请填写图片 URL', 'err');
+    $('#vt-out').innerHTML = '<div class="tab-note"><span class="spin"></span> 视觉分析中（多模态调用约 10-60 秒）…</div>';
+    try {
+      const r = await api(`/api/workers/${wid}/vision_test`, {method:'POST', body: {image_url: url, question: $('#vt-q').value}});
+      $('#vt-out').innerHTML = `<pre style="white-space:pre-wrap;background:#f6f8fa;padding:10px;border-radius:8px;max-height:320px;overflow:auto">${esc(r.data.text)}</pre>
+        <div class="tab-note">tokens ${r.data.total_tokens} · 成本 ${fmtMoney(r.data.cost)} · 延迟 ${r.data.latency_ms ?? '—'}ms</div>`;
+    } catch (e) { $('#vt-out').innerHTML = `<div class="err">${esc(e.message)}</div>`; }
+  });
+}
+
 async function delWorker(wid) {
   if (!confirm('确认删除该 Worker？（历史任务将解除指派）')) return;
   await api(`/api/workers/${wid}`, {method:'DELETE'});

templates.py

@@ -180,7 +180,7 @@ def apply_project_template(tpl, variables, worker_id=None):
     return pid, created
 
 
-def apply_team_template(tpl, variables, provider='doubao', model='doubao-seed-evolving'):
+def apply_team_template(tpl, variables, provider='deepseek', model='deepseek-v4-flash'):
     """应用团队模板 → 批量注册 Worker"""
     content = render(json.loads(tpl['content']), variables)
     created = []