aken1023
8a929936ad
Add Python scripts for Llama API chat clients, endpoint testing, and quick tests. Include documentation (README, CONTRIBUTING, 操作指南), license, and .gitignore. Supports multiple endpoints and models for OpenAI-compatible Llama API usage.
143 lines
4.6 KiB
Python
143 lines
4.6 KiB
Python
import requests
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import json
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import time
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API_KEY = "paVrIT+XU1NhwCAOb0X4aYi75QKogK5YNMGvQF1dCyo="
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BASE_URL = "https://llama.theaken.com/v1"
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MODELS = [
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"gpt-oss-120b",
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"deepseek-r1-671b",
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"qwen3-embedding-8b"
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]
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def test_model(model_name):
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"""測試單個模型"""
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print(f"\n[測試模型: {model_name}]")
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print("-" * 40)
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headers = {
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"Authorization": f"Bearer {API_KEY}",
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"Content-Type": "application/json"
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}
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# 測試聊天完成端點
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chat_url = f"{BASE_URL}/chat/completions"
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data = {
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"model": model_name,
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"messages": [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Say 'Hello, I am working!' if you can see this message."}
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],
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"temperature": 0.5,
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"max_tokens": 50
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}
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try:
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print(f"連接到: {chat_url}")
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response = requests.post(chat_url, headers=headers, json=data, timeout=30)
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print(f"HTTP 狀態碼: {response.status_code}")
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if response.status_code == 200:
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result = response.json()
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if 'choices' in result and len(result['choices']) > 0:
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content = result['choices'][0]['message']['content']
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print(f"[SUCCESS] AI 回應: {content}")
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return True
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else:
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print("[ERROR] 回應格式異常")
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print(f"回應內容: {json.dumps(result, indent=2)}")
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else:
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print(f"[ERROR] 錯誤回應")
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# 檢查是否是 HTML 錯誤頁面
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if response.text.startswith('<!DOCTYPE'):
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print("收到 HTML 錯誤頁面 (可能是 502 Bad Gateway)")
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else:
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print(f"回應內容: {response.text[:300]}")
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except requests.exceptions.Timeout:
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print("[TIMEOUT] 請求超時 (30秒)")
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except requests.exceptions.ConnectionError as e:
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print(f"[CONNECTION ERROR]: {str(e)[:100]}")
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except Exception as e:
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print(f"[UNEXPECTED ERROR]: {str(e)[:100]}")
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return False
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def test_api_endpoints():
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"""測試不同的 API 端點"""
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print("\n[測試 API 端點可用性]")
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print("=" * 50)
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headers = {
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"Authorization": f"Bearer {API_KEY}",
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"Content-Type": "application/json"
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}
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# 測試不同的可能端點
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endpoints = [
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f"{BASE_URL}/models",
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f"{BASE_URL}/chat/completions",
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BASE_URL
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]
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for endpoint in endpoints:
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try:
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print(f"\n測試端點: {endpoint}")
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response = requests.get(endpoint, headers=headers, timeout=10)
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print(f" 狀態碼: {response.status_code}")
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if response.status_code == 200:
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print(" [OK] 端點可訪問")
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# 如果是 JSON 回應，顯示部分內容
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try:
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data = response.json()
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print(f" 回應類型: JSON")
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if 'data' in data:
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print(f" 包含 {len(data['data'])} 項資料")
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except:
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print(f" 回應類型: {response.headers.get('content-type', 'unknown')}")
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elif response.status_code == 405:
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print(" [OK] 端點存在 (但不支援 GET 方法)")
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elif response.status_code == 502:
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print(" [ERROR] 502 Bad Gateway - 伺服器暫時無法使用")
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else:
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print(f" [ERROR] 無法訪問")
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except Exception as e:
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print(f" [ERROR]: {str(e)[:50]}")
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def main():
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print("=" * 50)
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print("Llama API 完整測試程式")
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print("=" * 50)
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print(f"API 基礎 URL: {BASE_URL}")
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print(f"API 金鑰: {API_KEY[:10]}...{API_KEY[-5:]}")
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# 首先測試端點可用性
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test_api_endpoints()
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print("\n" + "=" * 50)
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print("開始測試各個模型")
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print("=" * 50)
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success_count = 0
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for model in MODELS:
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if test_model(model):
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success_count += 1
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time.sleep(1) # 避免請求過快
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print("\n" + "=" * 50)
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print(f"測試結果: {success_count}/{len(MODELS)} 個模型成功連接")
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if success_count == 0:
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print("\n可能的問題：")
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print("1. API 伺服器暫時離線 (502 錯誤)")
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print("2. API 金鑰可能不正確")
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print("3. 網路連接問題")
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print("4. 防火牆或代理設定")
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print("\n建議稍後再試，或聯繫 API 提供者確認服務狀態。")
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if __name__ == "__main__":
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main() |