Spaces:
Running
Running
File size: 10,430 Bytes
d12a6b6 cb01b8b d12a6b6 cfdf66d d12a6b6 d239855 d12a6b6 d239855 d12a6b6 8472bc0 d12a6b6 d239855 d12a6b6 d9e170e cfdf66d d9e170e d12a6b6 d239855 d12a6b6 cfdf66d 0185608 105831b cfdf66d 0185608 cfdf66d 0185608 cfdf66d 0185608 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 |
"""
Configuration constants for the Geminicli2api proxy server.
Centralizes all configuration to avoid duplication across modules.
"""
import os
# API Endpoints
CODE_ASSIST_ENDPOINT = "https://cloudcode-pa.googleapis.com"
# Client Configuration
CLI_VERSION = "0.1.5" # Match current gemini-cli version
# OAuth Configuration
CLIENT_ID = "681255809395-oo8ft2oprdrnp9e3aqf6av3hmdib135j.apps.googleusercontent.com"
CLIENT_SECRET = "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"
SCOPES = [
"https://www.googleapis.com/auth/cloud-platform",
"https://www.googleapis.com/auth/userinfo.email",
"https://www.googleapis.com/auth/userinfo.profile",
]
# File Paths
SCRIPT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
CREDENTIAL_FILE = os.path.join(SCRIPT_DIR, os.getenv("GOOGLE_APPLICATION_CREDENTIALS", "oauth_creds.json"))
# Authentication
GEMINI_AUTH_PASSWORD = os.getenv("GEMINI_AUTH_PASSWORD", "123456")
# Default Safety Settings for Google API
DEFAULT_SAFETY_SETTINGS = [
{"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
{"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"},
{"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"},
{"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"},
{"category": "HARM_CATEGORY_CIVIC_INTEGRITY", "threshold": "BLOCK_NONE"}
]
# Base Models (without search variants)
BASE_MODELS = [
{
"name": "models/gemini-2.5-pro-preview-05-06",
"version": "001",
"displayName": "Gemini 2.5 Pro Preview 05-06",
"description": "Preview version of Gemini 2.5 Pro from May 6th",
"inputTokenLimit": 1048576,
"outputTokenLimit": 65535,
"supportedGenerationMethods": ["generateContent", "streamGenerateContent"],
"temperature": 1.0,
"maxTemperature": 2.0,
"topP": 0.95,
"topK": 64
},
{
"name": "models/gemini-2.5-pro-preview-06-05",
"version": "001",
"displayName": "Gemini 2.5 Pro Preview 06-05",
"description": "Preview version of Gemini 2.5 Pro from June 5th",
"inputTokenLimit": 1048576,
"outputTokenLimit": 65535,
"supportedGenerationMethods": ["generateContent", "streamGenerateContent"],
"temperature": 1.0,
"maxTemperature": 2.0,
"topP": 0.95,
"topK": 64
},
{
"name": "models/gemini-2.5-pro",
"version": "001",
"displayName": "Gemini 2.5 Pro",
"description": "Advanced multimodal model with enhanced capabilities",
"inputTokenLimit": 1048576,
"outputTokenLimit": 65535,
"supportedGenerationMethods": ["generateContent", "streamGenerateContent"],
"temperature": 1.0,
"maxTemperature": 2.0,
"topP": 0.95,
"topK": 64
},
{
"name": "models/gemini-2.5-flash-preview-05-20",
"version": "001",
"displayName": "Gemini 2.5 Flash Preview 05-20",
"description": "Preview version of Gemini 2.5 Flash from May 20th",
"inputTokenLimit": 1048576,
"outputTokenLimit": 65535,
"supportedGenerationMethods": ["generateContent", "streamGenerateContent"],
"temperature": 1.0,
"maxTemperature": 2.0,
"topP": 0.95,
"topK": 64
},
{
"name": "models/gemini-2.5-flash-preview-04-17",
"version": "001",
"displayName": "Gemini 2.5 Flash Preview 04-17",
"description": "Preview version of Gemini 2.5 Flash from April 17th",
"inputTokenLimit": 1048576,
"outputTokenLimit": 65535,
"supportedGenerationMethods": ["generateContent", "streamGenerateContent"],
"temperature": 1.0,
"maxTemperature": 2.0,
"topP": 0.95,
"topK": 64
},
{
"name": "models/gemini-2.5-flash",
"version": "001",
"displayName": "Gemini 2.5 Flash",
"description": "Fast and efficient multimodal model with latest improvements",
"inputTokenLimit": 1048576,
"outputTokenLimit": 65535,
"supportedGenerationMethods": ["generateContent", "streamGenerateContent"],
"temperature": 1.0,
"maxTemperature": 2.0,
"topP": 0.95,
"topK": 64
}
]
# Generate search variants for applicable models
def _generate_search_variants():
"""Generate search variants for models that support content generation."""
search_models = []
for model in BASE_MODELS:
# Only add search variants for models that support content generation
if "generateContent" in model["supportedGenerationMethods"]:
search_variant = model.copy()
search_variant["name"] = model["name"] + "-search"
search_variant["displayName"] = model["displayName"] + " with Google Search"
search_variant["description"] = model["description"] + " (includes Google Search grounding)"
search_models.append(search_variant)
return search_models
# Generate thinking variants for applicable models
def _generate_thinking_variants():
"""Generate nothinking and maxthinking variants for models that support thinking."""
thinking_models = []
for model in BASE_MODELS:
# Only add thinking variants for models that support content generation
# and contain "gemini-2.5-flash" or "gemini-2.5-pro" in their name
if ("generateContent" in model["supportedGenerationMethods"] and
("gemini-2.5-flash" in model["name"] or "gemini-2.5-pro" in model["name"])):
# Add -nothinking variant
nothinking_variant = model.copy()
nothinking_variant["name"] = model["name"] + "-nothinking"
nothinking_variant["displayName"] = model["displayName"] + " (No Thinking)"
nothinking_variant["description"] = model["description"] + " (thinking disabled)"
thinking_models.append(nothinking_variant)
# Add -maxthinking variant
maxthinking_variant = model.copy()
maxthinking_variant["name"] = model["name"] + "-maxthinking"
maxthinking_variant["displayName"] = model["displayName"] + " (Max Thinking)"
maxthinking_variant["description"] = model["description"] + " (maximum thinking budget)"
thinking_models.append(maxthinking_variant)
return thinking_models
# Generate combined variants (search + thinking combinations)
def _generate_combined_variants():
"""Generate combined search and thinking variants."""
combined_models = []
for model in BASE_MODELS:
# Only add combined variants for models that support content generation
# and contain "gemini-2.5-flash" or "gemini-2.5-pro" in their name
if ("generateContent" in model["supportedGenerationMethods"] and
("gemini-2.5-flash" in model["name"] or "gemini-2.5-pro" in model["name"])):
# search + nothinking
search_nothinking = model.copy()
search_nothinking["name"] = model["name"] + "-search-nothinking"
search_nothinking["displayName"] = model["displayName"] + " with Google Search (No Thinking)"
search_nothinking["description"] = model["description"] + " (includes Google Search grounding, thinking disabled)"
combined_models.append(search_nothinking)
# search + maxthinking
search_maxthinking = model.copy()
search_maxthinking["name"] = model["name"] + "-search-maxthinking"
search_maxthinking["displayName"] = model["displayName"] + " with Google Search (Max Thinking)"
search_maxthinking["description"] = model["description"] + " (includes Google Search grounding, maximum thinking budget)"
combined_models.append(search_maxthinking)
return combined_models
# Supported Models (includes base models, search variants, and thinking variants)
# Combine all models and then sort them by name to group variants together
all_models = BASE_MODELS + _generate_search_variants() + _generate_thinking_variants()
SUPPORTED_MODELS = sorted(all_models, key=lambda x: x['name'])
# Helper function to get base model name from any variant
def get_base_model_name(model_name):
"""Convert variant model name to base model name."""
# Remove all possible suffixes in order
suffixes = ["-maxthinking", "-nothinking", "-search"]
for suffix in suffixes:
if model_name.endswith(suffix):
return model_name[:-len(suffix)]
return model_name
# Helper function to check if model uses search grounding
def is_search_model(model_name):
"""Check if model name indicates search grounding should be enabled."""
return "-search" in model_name
# Helper function to check if model uses no thinking
def is_nothinking_model(model_name):
"""Check if model name indicates thinking should be disabled."""
return "-nothinking" in model_name
# Helper function to check if model uses max thinking
def is_maxthinking_model(model_name):
"""Check if model name indicates maximum thinking budget should be used."""
return "-maxthinking" in model_name
# Helper function to get thinking budget for a model
def get_thinking_budget(model_name):
"""Get the appropriate thinking budget for a model based on its name and variant."""
base_model = get_base_model_name(model_name)
if is_nothinking_model(model_name):
if "gemini-2.5-flash" in base_model:
return 0 # No thinking for flash
elif "gemini-2.5-pro" in base_model:
return 128 # Limited thinking for pro
elif is_maxthinking_model(model_name):
if "gemini-2.5-flash" in base_model:
return 24576
elif "gemini-2.5-pro" in base_model:
return 32768
else:
# Default thinking budget for regular models
return -1 # Default for all models
# Helper function to check if thinking should be included in output
def should_include_thoughts(model_name):
"""Check if thoughts should be included in the response."""
if is_nothinking_model(model_name):
# For nothinking mode, still include thoughts if it's a pro model
base_model = get_base_model_name(model_name)
return "gemini-2.5-pro" in base_model
else:
# For all other modes, include thoughts
return True |