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8 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| daccc625c3 | |||
| a2a7fd46c3 | |||
| baf5913bfb | |||
| ae08e01e55 | |||
| 9048d94e33 | |||
| 291de733a4 | |||
| 10f67a807a | |||
| d9ac2c78f6 |
@@ -1121,7 +1121,6 @@ async def websocket_endpoint(websocket: WebSocket, user_id: str):
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messages=history_with_tools,
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provider_config=agent_config['provider'],
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agent_config=agent_config['agent'],
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tool_results=tool_results,
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enable_thinking=enable_thinking
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)
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@@ -137,6 +137,9 @@ class AgentService:
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'api_key': provider.api_key if provider else None,
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'supports_thinking': provider.supports_thinking if provider else False,
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'thinking_model': provider.thinking_model if provider else None,
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'supports_vision': provider.supports_vision if provider else False,
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'vision_model': provider.vision_model if provider else None,
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'supports_function_calling': provider.supports_function_calling if provider else False,
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'default_model': provider.default_model if provider else 'auto',
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'max_tokens': provider.max_tokens if provider else 4096,
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'temperature': provider.temperature if provider else 0.7,
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@@ -514,17 +514,15 @@ class LLMService:
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messages: List[Dict],
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provider_config: dict,
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agent_config: dict,
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tool_results: List[Dict],
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enable_thinking: bool = True
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) -> Tuple[str, Optional[str]]:
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"""
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第二阶段调用:将工具执行结果返回给LLM
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第二阶段调用:使用包含工具调用和结果的完整消息历史
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Args:
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messages: 对话历史(包含工具调用和结果)
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messages: 已包含assistant tool_calls和tool结果的完整消息历史
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provider_config: LLM Provider配置
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agent_config: Agent配置
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tool_results: 工具执行结果 [{"tool_call_id": "xxx", "content": "..."}]
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Returns:
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Tuple[str, Optional[str]]: (回复内容, 思考过程)
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@@ -535,14 +533,8 @@ class LLMService:
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max_tokens = provider_config.get('max_tokens', 4096)
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temperature = agent_config.get('temperature_override') or provider_config.get('temperature', 0.7)
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# 将工具结果添加到消息历史
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# 消息历史已经包含了assistant的tool_calls和tool结果,直接使用
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final_messages = messages.copy()
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for result in tool_results:
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final_messages.append({
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"role": "tool",
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"tool_call_id": result['tool_call_id'],
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"content": result['content']
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})
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# 调用LLM生成最终回复
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url = f"{api_base.rstrip('/')}/chat/completions"
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@@ -557,14 +549,14 @@ class LLMService:
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"max_tokens": max_tokens
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}
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logger.info(f"工具结果返回LLM: url={url}, model={model}")
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logger.info(f"工具结果返回LLM: url={url}, model={model}, 消息数={len(final_messages)}")
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try:
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async with httpx.AsyncClient(timeout=60.0) as client:
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response = await client.post(url, headers=headers, json=payload)
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if response.status_code != 200:
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logger.error(f"API返回错误: status={response.status_code}")
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logger.error(f"API返回错误: status={response.status_code}, body={response.text[:500]}")
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response.raise_for_status()
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data = response.json()
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@@ -134,6 +134,23 @@
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/* 工具调用记录显示 */
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.tool-call-record { margin-top: 8px; padding: 8px 12px; background: #e8f5e9; border-radius: 8px; font-size: 12px; color: #10a37f; }
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.tool-call-record i { margin-right: 4px; }
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/* Agent信息侧边栏 */
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.agent-info-sidebar { width: 200px; background: #f8f9fa; border-right: 1px solid #e0e0e0; padding: 16px; display: flex; flex-direction: column; }
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.agent-info-header { display: flex; align-items: center; gap: 8px; margin-bottom: 12px; }
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.agent-avatar { width: 48px; height: 48px; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); border-radius: 12px; display: flex; align-items: center; justify-content: center; color: white; font-size: 24px; }
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.agent-name-area { flex: 1; }
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.agent-name-area h3 { font-size: 16px; margin: 0; color: #333; }
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.agent-name-area small { color: #999; font-size: 12px; }
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.agent-info-section { margin-top: 16px; }
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.agent-info-section h4 { font-size: 13px; color: #666; margin: 0 0 8px 0; font-weight: 500; }
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.agent-info-section p { font-size: 12px; color: #333; line-height: 1.5; margin: 0; }
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.agent-capabilities { display: flex; flex-wrap: wrap; gap: 6px; margin-top: 8px; }
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.capability-tag { padding: 4px 8px; background: #e8f5e9; border-radius: 6px; font-size: 11px; color: #10a37f; }
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.capability-tag.disabled { background: #f5f5f5; color: #999; }
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.agent-model-info { margin-top: 12px; padding: 8px; background: white; border-radius: 8px; border: 1px solid #e0e0e0; }
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.agent-model-info label { font-size: 11px; color: #999; }
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.agent-model-info span { font-size: 12px; color: #333; display: block; margin-top: 2px; }
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.add-phrase-btn { padding: 6px 10px; background: #f0f0f0; border: 1px solid #ddd; border-radius: 6px; cursor: pointer; font-size: 12px; color: #666; white-space: nowrap; flex-shrink: 0; }
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.add-phrase-btn:hover { background: #e8e8e8; }
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.phrase-list-wrapper { flex: 1; overflow-x: auto; overflow-y: hidden; scrollbar-width: thin; }
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@@ -191,8 +208,37 @@
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</div>
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</div>
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<div class="messages-container" id="messagesContainer">
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<div class="welcome"><h2>👋 开始对话</h2><p>选择Agent,开始聊天</p></div>
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<!-- 对话区域:左侧Agent信息 + 右侧消息 -->
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<div class="chat-area" style="display:flex;flex:1;overflow:hidden;">
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<!-- Agent信息侧边栏 -->
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<div class="agent-info-sidebar" id="agentInfoSidebar">
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<div class="agent-info-header">
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<div class="agent-avatar" id="agentAvatar">🤖</div>
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<div class="agent-name-area">
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<h3 id="agentDisplayName">加载中...</h3>
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<small id="agentName">agent-name</small>
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</div>
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</div>
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<div class="agent-info-section">
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<h4>简介</h4>
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<p id="agentDescription">-</p>
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</div>
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<div class="agent-info-section">
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<h4>能力</h4>
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<div class="agent-capabilities" id="agentCapabilities">
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<!-- 动态渲染 -->
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</div>
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</div>
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<div class="agent-model-info">
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<label>模型</label>
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<span id="agentModelInfo">-</span>
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</div>
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</div>
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<!-- 消息容器 -->
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<div class="messages-container" id="messagesContainer" style="flex:1;">
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<div class="welcome"><h2>👋 开始对话</h2><p>选择Agent,开始聊天</p></div>
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</div>
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</div>
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<div class="input-container">
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@@ -293,8 +339,8 @@
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const res = await fetch('/api/v2/providers');
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const data = await res.json();
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providers = data.providers || [];
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// 加载后检查工具支持(如果agents已加载)
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if (agents.length > 0) showToolWarning();
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// 加载后更新Agent信息侧边栏(如果agents已加载)
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if (agents.length > 0) renderAgentInfoSidebar();
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} catch (e) { console.error('加载Provider失败:', e); }
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}
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@@ -323,9 +369,58 @@
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const defaultAgent = agents.find(a => a.is_default) || agents[0];
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if (defaultAgent) currentAgentId = defaultAgent.id;
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renderAgentSelect();
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renderAgentInfoSidebar(); // 渲染Agent信息侧边栏
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} catch (e) { console.error('加载Agent失败:', e); }
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}
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// 渲染Agent信息侧边栏
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function renderAgentInfoSidebar() {
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const agent = agents.find(a => a.id === currentAgentId);
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if (!agent) return;
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// 更新名称
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document.getElementById('agentDisplayName').textContent = agent.display_name || agent.name;
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document.getElementById('agentName').textContent = agent.name;
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// 更新头像(用emoji或首字母)
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const avatar = document.getElementById('agentAvatar');
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avatar.textContent = agent.display_name?.charAt(0) || agent.name?.charAt(0) || '🤖';
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// 更新描述
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document.getElementById('agentDescription').textContent = agent.description || '暂无描述';
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// 更新能力标签
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const capabilitiesHtml = [];
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// 检查思考能力
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const provider = providers.find(p => p.id === agent.llm_provider_id);
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if (provider) {
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if (provider.supports_thinking) {
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capabilitiesHtml.push('<span class="capability-tag"><i class="ri-lightbulb-line"></i> 思考</span>');
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}
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if (provider.supports_vision) {
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capabilitiesHtml.push('<span class="capability-tag"><i class="ri-image-line"></i> 视觉</span>');
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}
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if (provider.supports_function_calling) {
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capabilitiesHtml.push('<span class="capability-tag"><i class="ri-tools-line"></i> 工具调用</span>');
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} else {
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capabilitiesHtml.push('<span class="capability-tag disabled"><i class="ri-tools-line"></i> 工具(手动)</span>');
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}
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// 更新模型信息
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const model = agent.model_override || provider.default_model || 'auto';
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document.getElementById('agentModelInfo').textContent = model;
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}
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// 检查工具配置
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const agentTools = agent.tools || [];
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if (agentTools.includes('search')) {
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capabilitiesHtml.push('<span class="capability-tag"><i class="ri-search-line"></i> 搜索</span>');
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}
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document.getElementById('agentCapabilities').innerHTML = capabilitiesHtml.join('') || '<span class="capability-tag disabled">基础对话</span>';
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}
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function renderAgentSelect() {
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const select = document.getElementById('agentSelect');
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select.innerHTML = agents.filter(a => a.is_active).map(a =>
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@@ -345,6 +440,7 @@
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if (ws?.readyState === WebSocket.OPEN) ws.send(JSON.stringify({ action: 'switch_agent', agent_id: currentAgentId }));
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await createNewConversation();
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showAgentSwitchNotice();
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renderAgentInfoSidebar(); // 更新侧边栏信息
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}
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}
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Reference in New Issue
Block a user