DonaldFang 方士碩
a6af297623
變更內容： - 所有資料表加上 HR_position_ 前綴 - 整理完整欄位顯示名稱與 ID 對照表 - 模組化 JS 檔案 (admin.js, ai.js, csv.js 等) - 專案結構優化 (docs/, scripts/, tests/ 等) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
451 lines
16 KiB
Python
451 lines
16 KiB
Python
"""
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LLM API Configuration Module
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Supports Gemini, DeepSeek, and OpenAI APIs with connection testing
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"""
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import os
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import requests
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from dotenv import load_dotenv
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from typing import Dict, List, Tuple
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import urllib3
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# Disable SSL warnings for Ollama endpoint
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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# Load environment variables
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load_dotenv()
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class LLMConfig:
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"""LLM API configuration and management"""
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def __init__(self):
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self.apis = {
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'gemini': {
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'name': 'Google Gemini',
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'api_key': os.getenv('GEMINI_API_KEY', ''),
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'endpoint': 'https://generativelanguage.googleapis.com/v1/models',
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'enabled': bool(os.getenv('GEMINI_API_KEY'))
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},
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'deepseek': {
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'name': 'DeepSeek',
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'api_key': os.getenv('DEEPSEEK_API_KEY', ''),
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'endpoint': os.getenv('DEEPSEEK_API_URL', 'https://api.deepseek.com/v1'),
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'enabled': bool(os.getenv('DEEPSEEK_API_KEY'))
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},
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'openai': {
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'name': 'OpenAI',
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'api_key': os.getenv('OPENAI_API_KEY', ''),
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'endpoint': os.getenv('OPENAI_API_URL', 'https://api.openai.com/v1'),
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'enabled': bool(os.getenv('OPENAI_API_KEY'))
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},
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'ollama': {
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'name': 'Ollama',
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'api_key': '', # Ollama 不需要 API Key
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'endpoint': os.getenv('OLLAMA_API_URL', 'https://ollama_pjapi.theaken.com'),
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'model': os.getenv('OLLAMA_MODEL', 'qwen2.5:3b'),
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'enabled': True # Ollama 預設啟用
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},
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'gptoss': {
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'name': 'GPT-OSS',
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'api_key': '', # GPT-OSS 不需要 API Key (使用 Ollama 介面)
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'endpoint': os.getenv('GPTOSS_API_URL', 'https://ollama_pjapi.theaken.com'),
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'model': os.getenv('GPTOSS_MODEL', 'gpt-oss:120b'),
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'enabled': True # GPT-OSS 預設啟用
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}
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}
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def get_enabled_apis(self) -> List[str]:
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"""Get list of enabled APIs"""
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return [key for key, config in self.apis.items() if config['enabled']]
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def get_api_config(self, api_name: str) -> Dict:
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"""Get configuration for specific API"""
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return self.apis.get(api_name, {})
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def test_gemini_connection(self) -> Tuple[bool, str]:
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"""Test Gemini API connection"""
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try:
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api_key = self.apis['gemini']['api_key']
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if not api_key:
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return False, "API Key 未設定"
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# Test endpoint - list models
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url = f"https://generativelanguage.googleapis.com/v1beta/models?key={api_key}"
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response = requests.get(url, timeout=10)
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if response.status_code == 200:
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data = response.json()
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models = data.get('models', [])
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model_count = len(models)
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return True, f"連線成功！找到 {model_count} 個可用模型"
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elif response.status_code == 400:
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return False, "API Key 格式錯誤"
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elif response.status_code == 403:
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return False, "API Key 無效或權限不足"
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else:
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return False, f"連線失敗 (HTTP {response.status_code})"
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except requests.exceptions.Timeout:
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return False, "連線逾時"
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except requests.exceptions.ConnectionError:
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return False, "無法連接到伺服器"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def test_deepseek_connection(self) -> Tuple[bool, str]:
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"""Test DeepSeek API connection"""
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try:
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api_key = self.apis['deepseek']['api_key']
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endpoint = self.apis['deepseek']['endpoint']
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if not api_key:
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return False, "API Key 未設定"
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# Test endpoint - list models
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url = f"{endpoint}/models"
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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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response = requests.get(url, headers=headers, timeout=10)
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if response.status_code == 200:
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data = response.json()
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models = data.get('data', [])
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if models:
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model_count = len(models)
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return True, f"連線成功！找到 {model_count} 個可用模型"
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else:
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return True, "連線成功！"
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elif response.status_code == 401:
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return False, "API Key 無效"
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elif response.status_code == 403:
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return False, "權限不足"
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else:
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return False, f"連線失敗 (HTTP {response.status_code})"
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except requests.exceptions.Timeout:
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return False, "連線逾時"
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except requests.exceptions.ConnectionError:
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return False, "無法連接到伺服器"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def test_openai_connection(self) -> Tuple[bool, str]:
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"""Test OpenAI API connection"""
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try:
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api_key = self.apis['openai']['api_key']
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endpoint = self.apis['openai']['endpoint']
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if not api_key:
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return False, "API Key 未設定"
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# Test endpoint - list models
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url = f"{endpoint}/models"
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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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response = requests.get(url, headers=headers, timeout=10)
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if response.status_code == 200:
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data = response.json()
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models = data.get('data', [])
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model_count = len(models)
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return True, f"連線成功！找到 {model_count} 個可用模型"
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elif response.status_code == 401:
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return False, "API Key 無效"
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elif response.status_code == 403:
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return False, "權限不足"
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else:
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return False, f"連線失敗 (HTTP {response.status_code})"
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except requests.exceptions.Timeout:
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return False, "連線逾時"
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except requests.exceptions.ConnectionError:
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return False, "無法連接到伺服器"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def test_ollama_connection(self) -> Tuple[bool, str]:
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"""Test Ollama API connection"""
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try:
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endpoint = self.apis['ollama']['endpoint']
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# Test endpoint - list models
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url = f"{endpoint}/v1/models"
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response = requests.get(url, timeout=10, verify=False)
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if response.status_code == 200:
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data = response.json()
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models = data.get('data', [])
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if models:
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model_count = len(models)
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model_names = [m.get('id', '') for m in models[:3]]
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return True, f"連線成功！找到 {model_count} 個可用模型 (例如: {', '.join(model_names)})"
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else:
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return True, "連線成功！"
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else:
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return False, f"連線失敗 (HTTP {response.status_code})"
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except requests.exceptions.Timeout:
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return False, "連線逾時"
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except requests.exceptions.ConnectionError:
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return False, "無法連接到伺服器"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def test_all_connections(self) -> Dict[str, Tuple[bool, str]]:
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"""Test all configured API connections"""
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results = {}
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if self.apis['gemini']['enabled']:
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results['gemini'] = self.test_gemini_connection()
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if self.apis['deepseek']['enabled']:
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results['deepseek'] = self.test_deepseek_connection()
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if self.apis['openai']['enabled']:
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results['openai'] = self.test_openai_connection()
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if self.apis['ollama']['enabled']:
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results['ollama'] = self.test_ollama_connection()
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return results
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def generate_text_gemini(self, prompt: str, max_tokens: int = 2000) -> Tuple[bool, str]:
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"""Generate text using Gemini API"""
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try:
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api_key = self.apis['gemini']['api_key']
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if not api_key:
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return False, "API Key 未設定"
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# 從環境變數讀取模型名稱，默認使用 gemini-1.5-flash
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model_name = os.getenv('GEMINI_MODEL', 'gemini-1.5-flash')
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url = f"https://generativelanguage.googleapis.com/v1beta/models/{model_name}:generateContent?key={api_key}"
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data = {
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"contents": [
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{
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"parts": [
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{"text": prompt}
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]
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}
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],
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"generationConfig": {
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"maxOutputTokens": max_tokens,
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"temperature": 0.7
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}
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}
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response = requests.post(url, json=data, timeout=30)
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if response.status_code == 200:
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result = response.json()
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text = result['candidates'][0]['content']['parts'][0]['text']
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return True, text
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else:
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return False, f"生成失敗 (HTTP {response.status_code}): {response.text}"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def generate_text_deepseek(self, prompt: str, max_tokens: int = 2000) -> Tuple[bool, str]:
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"""Generate text using DeepSeek API"""
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try:
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api_key = self.apis['deepseek']['api_key']
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endpoint = self.apis['deepseek']['endpoint']
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if not api_key:
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return False, "API Key 未設定"
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url = f"{endpoint}/chat/completions"
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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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data = {
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"model": "deepseek-chat",
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"messages": [
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{"role": "user", "content": prompt}
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],
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"max_tokens": max_tokens,
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"temperature": 0.7
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}
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response = requests.post(url, json=data, headers=headers, timeout=30)
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if response.status_code == 200:
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result = response.json()
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text = result['choices'][0]['message']['content']
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return True, text
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else:
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return False, f"生成失敗 (HTTP {response.status_code}): {response.text}"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def generate_text_openai(self, prompt: str, model: str = "gpt-3.5-turbo", max_tokens: int = 2000) -> Tuple[bool, str]:
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"""Generate text using OpenAI API"""
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try:
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api_key = self.apis['openai']['api_key']
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endpoint = self.apis['openai']['endpoint']
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if not api_key:
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return False, "API Key 未設定"
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url = f"{endpoint}/chat/completions"
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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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data = {
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"model": model,
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"messages": [
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{"role": "user", "content": prompt}
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],
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"max_tokens": max_tokens,
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"temperature": 0.7
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}
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response = requests.post(url, json=data, headers=headers, timeout=30)
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if response.status_code == 200:
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result = response.json()
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text = result['choices'][0]['message']['content']
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return True, text
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else:
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return False, f"生成失敗 (HTTP {response.status_code}): {response.text}"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def generate_text_ollama(self, prompt: str, max_tokens: int = 2000, model: str = None) -> Tuple[bool, str]:
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"""Generate text using Ollama API
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Args:
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prompt: The prompt text
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max_tokens: Maximum tokens to generate (not used by Ollama but kept for compatibility)
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model: The model to use. If None, uses the default from config.
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"""
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try:
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endpoint = self.apis['ollama']['endpoint']
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# 使用傳入的 model 參數，如果沒有則使用設定檔中的預設值
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if model is None:
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model = self.apis['ollama']['model']
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url = f"{endpoint}/v1/chat/completions"
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headers = {
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'Content-Type': 'application/json'
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}
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data = {
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"model": model,
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"messages": [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": prompt}
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],
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"temperature": 0.7
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}
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# 增加逾時時間到 180 秒，處理大模型較慢的情況
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response = requests.post(url, json=data, headers=headers, timeout=180, verify=False)
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if response.status_code == 200:
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result = response.json()
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text = result['choices'][0]['message']['content']
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return True, text
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else:
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return False, f"生成失敗 (HTTP {response.status_code}): {response.text}"
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except requests.exceptions.Timeout:
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return False, f"連線逾時 (180秒)，伺服器可能過載或網路不穩定。建議：1) 稍後重試 2) 使用本地 Ollama (localhost:11434) 3) 切換到 Gemini API"
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except requests.exceptions.ConnectionError:
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return False, "無法連接到 Ollama 伺服器，請確認伺服器地址正確且服務已啟動"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def generate_text_gptoss(self, prompt: str, max_tokens: int = 2000, model: str = None) -> Tuple[bool, str]:
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"""Generate text using GPT-OSS API (120B model via Ollama interface)
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Args:
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prompt: The prompt text
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max_tokens: Maximum tokens to generate (not used by Ollama but kept for compatibility)
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model: The model to use. If None, uses the default from config.
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"""
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try:
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endpoint = self.apis['gptoss']['endpoint']
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# 使用傳入的 model 參數，如果沒有則使用設定檔中的預設值
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if model is None:
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model = self.apis['gptoss']['model']
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url = f"{endpoint}/v1/chat/completions"
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headers = {
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'Content-Type': 'application/json'
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}
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data = {
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"model": model,
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"messages": [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": prompt}
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],
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"temperature": 0.7
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}
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# 增加逾時時間到 180 秒
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response = requests.post(url, json=data, headers=headers, timeout=180, verify=False)
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if response.status_code == 200:
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result = response.json()
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text = result['choices'][0]['message']['content']
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return True, text
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else:
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return False, f"生成失敗 (HTTP {response.status_code}): {response.text}"
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except requests.exceptions.Timeout:
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return False, f"連線逾時 (180秒)，伺服器可能過載或網路不穩定。建議：1) 稍後重試 2) 使用本地 Ollama (localhost:11434) 3) 切換到 Gemini API"
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except requests.exceptions.ConnectionError:
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return False, "無法連接到 GPT-OSS 伺服器，請確認伺服器地址正確且服務已啟動"
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except Exception as e:
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return False, f"錯誤: {str(e)}"
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def main():
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"""Test script"""
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print("=" * 60)
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print("LLM API Configuration Test")
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print("=" * 60)
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print()
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config = LLMConfig()
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# Show enabled APIs
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enabled = config.get_enabled_apis()
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print(f"已啟用的 API: {', '.join(enabled) if enabled else '無'}")
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print()
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# Test all connections
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print("測試 API 連線:")
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print("-" * 60)
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results = config.test_all_connections()
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for api_name, (success, message) in results.items():
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status = "✓" if success else "✗"
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api_display_name = config.apis[api_name]['name']
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print(f"{status} {api_display_name}: {message}")
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print()
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if __name__ == '__main__':
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main()
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