Merge pull request #18 from IMvision12/zai

Add Zai models

Author: IMvision12

README.md

@@ -51,9 +51,9 @@ No port forwarding. No VPN. Just message and code.
 
 Connect via **6 platforms** : WhatsApp, Telegram, Discord, Slack, Microsoft Teams, and Signal.
 
-### 9 AI Providers
+### 10 AI Providers
 
-Anthropic, OpenAI, Google Gemini, Mistral, Moonshot, MiniMax, xAI Grok, HuggingFace, and OpenRouter. Instantly switch providers with `/switch` directly from your messaging app.
+Anthropic, OpenAI, Google Gemini, Mistral, Moonshot, MiniMax, xAI Grok, Z.ai (Zhipu), HuggingFace, and OpenRouter. Instantly switch providers with `/switch` directly from your messaging app.
 
 ### Hot-Switching
 
@@ -141,7 +141,7 @@ docker run -it \
 
 ## 🤖 AI Providers
 
-txtcode supports **9 LLM providers** for chat mode. Configure one or more during setup and hot-switch with `/switch`.
+txtcode supports **10 LLM providers** for chat mode. Configure one or more during setup and hot-switch with `/switch`.
 
 | Provider            | Example Models                             | Notes                       |
 | :------------------ | :----------------------------------------- | :-------------------------- |
@@ -152,6 +152,7 @@ txtcode supports **9 LLM providers** for chat mode. Configure one or more during
 | **Moonshot (Kimi)** | `kimi-k2.5`, `moonshot-v1-128k`            | Long-context models         |
 | **MiniMax**         | `MiniMax-M2.5`, `MiniMax-M2.1`             | MiniMax family              |
 | **xAI (Grok)**      | `grok-4`, `grok-3-fast`                    | Grok family                 |
+| **Z.ai (Zhipu)**    | `glm-5`, `glm-4.7`, `glm-4.6`              | GLM family                  |
 | **HuggingFace**     | _Discovered at runtime_                    | Inference Providers API     |
 | **OpenRouter**      | _Discovered at runtime_                    | Unified API for 100+ models |
 

src/core/router.ts

@@ -14,6 +14,7 @@ import { processWithMoonshot } from "../providers/moonshot";
 import { processWithOpenAI } from "../providers/openai";
 import { processWithOpenRouter } from "../providers/openrouter";
 import { processWithXAI } from "../providers/xai";
+import { processWithZAI } from "../providers/zai";
 import { logger } from "../shared/logger";
 import { IDEAdapter, ModelInfo } from "../shared/types";
 import { ContextManager } from "./context-manager";
@@ -146,6 +147,8 @@ export class Router {
         return await processWithMistral(instruction, this.apiKey, this.model);
       case "xai":
         return await processWithXAI(instruction, this.apiKey, this.model);
+      case "zai":
+        return await processWithZAI(instruction, this.apiKey, this.model);
       default:
         return `[ERROR] Unsupported AI provider: ${this.provider}. Run: txtcode config`;
     }

src/data/zai_models.json

@@ -0,0 +1,21 @@
+{
+  "name": "Z.ai",
+  "models": [
+    {
+      "id": "glm-5",
+      "name": "GLM-5",
+      "description": "Flagship foundation model for agentic engineering",
+      "recommended": true
+    },
+    {
+      "id": "glm-4.7",
+      "name": "GLM-4.7",
+      "description": "High-performance general-purpose model"
+    },
+    {
+      "id": "glm-4.6",
+      "name": "GLM-4.6",
+      "description": "Balanced model for chat and reasoning tasks"
+    }
+  ]
+}

src/providers/zai.ts

@@ -0,0 +1,44 @@
+import OpenAI from "openai";
+import { logger } from "../shared/logger";
+
+const SYSTEM_PROMPT =
+  "You are TxtCode AI — a helpful, knowledgeable coding assistant accessible via messaging. Be concise, use markdown for clarity, and suggest /code mode for deep coding work.";
+
+export async function processWithZAI(
+  instruction: string,
+  apiKey: string,
+  model: string,
+): Promise<string> {
+  const startTime = Date.now();
+  logger.debug(`[ZAI] Request → model=${model}, prompt=${instruction.length} chars`);
+
+  try {
+    const client = new OpenAI({
+      apiKey,
+      baseURL: "https://api.z.ai/api/paas/v4",
+    });
+
+    const completion = await client.chat.completions.create({
+      model,
+      max_tokens: 4096,
+      messages: [
+        { role: "system", content: SYSTEM_PROMPT },
+        { role: "user", content: instruction },
+      ],
+    });
+
+    const choice = completion.choices[0];
+
+    logger.debug(
+      `[ZAI] Done in ${Date.now() - startTime}ms, ` +
+        `tokens=${completion.usage?.prompt_tokens ?? "?"}in/${completion.usage?.completion_tokens ?? "?"}out`,
+    );
+
+    return choice.message.content || "No response from Z.ai";
+  } catch (error: unknown) {
+    logger.error(`[ZAI] API error after ${Date.now() - startTime}ms`, error);
+    throw new Error(`Z.ai API error: ${error instanceof Error ? error.message : "Unknown error"}`, {
+      cause: error,
+    });
+  }
+}

test/unit/router.test.ts

@@ -181,6 +181,12 @@ describe("Router", () => {
       expect(result).toContain("[ERROR]");
       expect(result).toContain("Unsupported");
     });
+
+    it("routes to zai provider without throwing", async () => {
+      router.updateProvider("zai", "test-key", "glm-5");
+      expect(router.getProviderName()).toBe("zai");
+      expect(router.getCurrentModel()).toBe("glm-5");
+    });
   });
 
   describe("abortCurrentCommand", () => {

test/unit/zai-provider.test.ts

@@ -0,0 +1,43 @@
+import { describe, it, expect, beforeEach } from "vitest";
+import { loadModelsCatalog, clearCatalogCache } from "../../src/utils/models-catalog-loader";
+
+describe("Z.ai provider", () => {
+  beforeEach(() => {
+    clearCatalogCache();
+  });
+
+  describe("model catalog", () => {
+    it("is discovered by the catalog loader", () => {
+      const catalog = loadModelsCatalog();
+      expect(catalog.providers.zai).toBeDefined();
+    });
+
+    it("has correct provider name", () => {
+      const catalog = loadModelsCatalog();
+      expect(catalog.providers.zai.name).toBe("Z.ai");
+    });
+
+    it("includes all expected models", () => {
+      const catalog = loadModelsCatalog();
+      const ids = catalog.providers.zai.models.map((m) => m.id);
+      expect(ids).toContain("glm-5");
+      expect(ids).toContain("glm-4.7");
+      expect(ids).toContain("glm-4.6");
+    });
+
+    it("has glm-5 marked as recommended", () => {
+      const catalog = loadModelsCatalog();
+      const glm5 = catalog.providers.zai.models.find((m) => m.id === "glm-5");
+      expect(glm5).toBeDefined();
+      expect(glm5!.recommended).toBe(true);
+    });
+
+    it("every model has a description", () => {
+      const catalog = loadModelsCatalog();
+      for (const model of catalog.providers.zai.models) {
+        expect(model.description).toBeDefined();
+        expect(model.description.length).toBeGreaterThan(0);
+      }
+    });
+  });
+});