Coverage for src / local_deep_research / llm / providers / implementations / google.py: 46%

1"""Google/Gemini LLM provider for Local Deep Research.""" 

2 

3from loguru import logger 

4 

5from ...llm_registry import register_llm 

6from ..openai_base import OpenAICompatibleProvider 

7 

8 

9class GoogleProvider(OpenAICompatibleProvider): 

10 """Google Gemini provider using OpenAI-compatible endpoint. 

11 

12 This uses Google's OpenAI-compatible API endpoint to access Gemini models, 

13 which automatically supports all current and future Gemini models without 

14 needing to update the code. 

15 """ 

16 

17 provider_name = "Google Gemini" 

18 api_key_setting = "llm.google.api_key" 

19 default_base_url = "https://generativelanguage.googleapis.com/v1beta/openai" 

20 default_model = "gemini-1.5-flash" 

21 

22 # Metadata for auto-discovery 

23 provider_key = "GOOGLE" 

24 company_name = "Google" 

25 region = "US" 

26 country = "United States" 

27 data_location = "Worldwide" # Google has data centers worldwide 

28 is_cloud = True 

29 

30 @classmethod 

31 def requires_auth_for_models(cls): 

32 """Google requires authentication for listing models. 

33 

34 Note: Google's OpenAI-compatible /models endpoint has a bug (returns 401). 

35 The native Gemini API endpoint requires an API key. 

36 """ 

37 return True 

38 

39 @classmethod 

40 def list_models_for_api(cls, api_key=None, base_url=None): 

41 """List available models using Google's native API. 

42 

43 Args: 

44 api_key: Google API key 

45 base_url: Not used - Google uses a fixed endpoint 

46 

47 Google's OpenAI-compatible /models endpoint returns 401 (bug), 

48 so we use the native Gemini API endpoint instead. 

49 """ 

50 if not api_key: 50 ↛ 54line 50 didn't jump to line 54 because the condition on line 50 was always true

51 logger.debug("Google Gemini requires API key for listing models") 

52 return [] 

53 

54 try: 

55 from ....security import safe_get 

56 

57 # Use the native Gemini API endpoint (not OpenAI-compatible) 

58 # Note: Google's API requires the key as a query parameter, not in headers 

59 # This is their documented approach: https://ai.google.dev/api/rest 

60 url = f"https://generativelanguage.googleapis.com/v1beta/models?key={api_key}" 

61 

62 response = safe_get(url, timeout=10) 

63 

64 if response.status_code == 200: 

65 data = response.json() 

66 models = [] 

67 

68 for model in data.get("models", []): 

69 model_name = model.get("name", "") 

70 # Extract just the model ID from "models/gemini-1.5-flash" 

71 if model_name.startswith("models/"): 

72 model_id = model_name[7:] # Remove "models/" prefix 

73 else: 

74 model_id = model_name 

75 

76 # Only include generative models (not embedding models) 

77 supported_methods = model.get( 

78 "supportedGenerationMethods", [] 

79 ) 

80 if "generateContent" in supported_methods and model_id: 

81 models.append( 

82 { 

83 "value": model_id, 

84 "label": model_id, 

85 } 

86 ) 

87 

88 logger.info( 

89 f"Found {len(models)} generative models from Google Gemini API" 

90 ) 

91 return models 

92 else: 

93 logger.warning( 

94 f"Google Gemini API returned status {response.status_code}" 

95 ) 

96 return [] 

97 

98 except Exception: 

99 logger.exception("Error fetching Google Gemini models") 

100 return [] 

101 

102 

103# Keep the standalone functions for backward compatibility and registration 

104def create_google_llm(model_name=None, temperature=0.7, **kwargs): 

105 """Factory function for Google/Gemini LLMs using OpenAI-compatible endpoint. 

106 

107 Args: 

108 model_name: Name of the model to use (e.g., "gemini-1.5-flash", "gemini-2.0-flash-exp", etc.) 

109 temperature: Model temperature (0.0-1.0) 

110 **kwargs: Additional arguments including settings_snapshot 

111 

112 Returns: 

113 A configured ChatOpenAI instance pointing to Google's API 

114 

115 Raises: 

116 ValueError: If Google API key is not configured 

117 """ 

118 return GoogleProvider.create_llm(model_name, temperature, **kwargs) 

119 

120 

121def is_google_available(settings_snapshot=None): 

122 """Check if Google/Gemini is available. 

123 

124 Args: 

125 settings_snapshot: Optional settings snapshot to use 

126 

127 Returns: 

128 True if Google API key is configured, False otherwise 

129 """ 

130 return GoogleProvider.is_available(settings_snapshot) 

131 

132 

133def register_google_provider(): 

134 """Register the Google/Gemini provider with the LLM registry.""" 

135 register_llm("google", create_google_llm) 

136 logger.info("Registered Google/Gemini LLM provider")