fix: 0.6.4 — Docker/ollama compatibility & better error messages

- demo: read OLLAMA_BASE_URL env for Docker detection
- MCP: compose_workflow reads AO_PROVIDER/AO_MODEL from env
- ollama: friendly error on ECONNREFUSED (hint Docker config)
- ollama: detect "model not found" and suggest `ollama pull`

Author: jnMetaCode

package-lock.json

@@ -1,6 +1,6 @@
 {
   "name": "agency-orchestrator",
-  "version": "0.6.3",
+  "version": "0.6.4",
   "description": "Multi-agent YAML workflow engine — 211 AI roles, auto DAG parallelism, zero code. One sentence → multiple AI roles collaborate → complete plan in minutes. 10 LLM providers, 7 need no API key.",
   "keywords": [
     "multi-agent",

package.json

@@ -167,7 +167,8 @@ export async function detectAvailableLLMs(): Promise<DetectedLLM[]> {
   try {
     const controller = new AbortController();
     const timeout = setTimeout(() => controller.abort(), 2000);
-    const res = await fetch('http://localhost:11434/api/tags', {
+    const ollamaUrl = process.env.OLLAMA_BASE_URL || 'http://localhost:11434';
+    const res = await fetch(`${ollamaUrl.replace(/\/+$/, '')}/api/tags`, {
       signal: controller.signal,
     });
     clearTimeout(timeout);

src/cli/demo.ts

@@ -12,24 +12,36 @@ export class OllamaConnector implements LLMConnector {
   }
 
   async chat(systemPrompt: string, userMessage: string, config: LLMConfig): Promise<LLMResult> {
-    const response = await fetch(`${this.baseUrl}/api/chat`, {
-      method: 'POST',
-      headers: { 'Content-Type': 'application/json' },
-      body: JSON.stringify({
-        model: config.model || 'llama3.1',
-        messages: [
-          { role: 'system', content: systemPrompt },
-          { role: 'user', content: userMessage },
-        ],
-        stream: false,
-        options: {
-          num_predict: config.max_tokens || 2048,
-        },
-      }),
-    });
+    let response: Response;
+    try {
+      response = await fetch(`${this.baseUrl}/api/chat`, {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({
+          model: config.model || 'llama3.1',
+          messages: [
+            { role: 'system', content: systemPrompt },
+            { role: 'user', content: userMessage },
+          ],
+          stream: false,
+          options: {
+            num_predict: config.max_tokens || 2048,
+          },
+        }),
+      });
+    } catch (err: any) {
+      if (err?.cause?.code === 'ECONNREFUSED' || err?.message?.includes('ECONNREFUSED')) {
+        throw new Error(`无法连接 Ollama (${this.baseUrl})，请确认 ollama 已启动。Docker 环境请设置 OLLAMA_BASE_URL=http://host.docker.internal:11434`);
+      }
+      throw err;
+    }
 
     if (!response.ok) {
       const text = await response.text();
+      if (response.status === 404 && text.includes('not found')) {
+        const model = config.model || 'llama3.1';
+        throw new Error(`Ollama 模型 "${model}" 未找到，请先运行: ollama pull ${model}`);
+      }
       throw new Error(`Ollama error ${response.status}: ${text}`);
     }
 

src/connectors/ollama.ts

@@ -269,14 +269,14 @@ export async function startServer(verbose = false): Promise<void> {
     async ({ description, provider, model }) => {
       try {
         const agentsDir = findAgentsDir();
-        const llmProvider = provider || 'deepseek';
+        const llmProvider = provider || process.env.AO_PROVIDER as any || 'deepseek';
         const defaultModels: Record<string, string> = {
           deepseek: 'deepseek-chat',
           claude: 'claude-sonnet-4-20250514',
           openai: 'gpt-4o',
           ollama: 'llama3',
         };
-        const llmModel = model || defaultModels[llmProvider] || 'gpt-4o';
+        const llmModel = model || process.env.AO_MODEL || defaultModels[llmProvider] || 'gpt-4o';
 
         const result = await silentCall(() =>
           composeWorkflow({