Merge pull request #1092 from mykonos-ibiza/add-gemini-api

add support for Google Gemini API integration

backend/.env.example

@@ -28,6 +28,7 @@ AWS_REGION_NAME=
 
 GROQ_API_KEY=
 OPENROUTER_API_KEY=
+GEMINI_API_KEY=
 MORPH_API_KEY=
 
 # DATA APIS

backend/README.md

@@ -86,6 +86,7 @@ RABBITMQ_PORT=5672
 ANTHROPIC_API_KEY=your-anthropic-key
 OPENAI_API_KEY=your-openai-key
 OPENROUTER_API_KEY=your-openrouter-key
+GEMINI_API_KEY=your-gemini-api-key
 MODEL_TO_USE=anthropic/claude-sonnet-4-20250514
 
 # Search and Web Scraping

backend/services/billing.py

@@ -1197,9 +1197,14 @@ async def get_available_models(
                     if '/' in model:
                         models_to_try.append(model.split('/', 1)[1])
                     
-                    # Special handling for Google models accessed via OpenRouter
+                    # Special handling for Google models accessed via Google API
-                    if model.startswith('openrouter/google/'):
+                    if model.startswith('gemini/'):
-                        google_model_name = model.replace('openrouter/', '')
+                        google_model_name = model.replace('gemini/', '')
+                        models_to_try.append(google_model_name)
+                    
+                    # Special handling for Google models accessed via Google API
+                    if model.startswith('gemini/'):
+                        google_model_name = model.replace('gemini/', '')
                         models_to_try.append(google_model_name)
                     
                     # Try each model name variation until we find one that works

backend/services/llm.py

@@ -38,7 +38,7 @@ class LLMRetryError(LLMError):
 
 def setup_api_keys() -> None:
     """Set up API keys from environment variables."""
-    providers = ['OPENAI', 'ANTHROPIC', 'GROQ', 'OPENROUTER', 'XAI', 'MORPH']
+    providers = ['OPENAI', 'ANTHROPIC', 'GROQ', 'OPENROUTER', 'XAI', 'MORPH', 'GEMINI']
     for provider in providers:
         key = getattr(config, f'{provider}_API_KEY')
         if key:
@@ -76,6 +76,7 @@ def get_openrouter_fallback(model_name: str) -> Optional[str]:
         "anthropic/claude-3-7-sonnet-latest": "openrouter/anthropic/claude-3.7-sonnet",
         "anthropic/claude-sonnet-4-20250514": "openrouter/anthropic/claude-sonnet-4",
         "xai/grok-4": "openrouter/x-ai/grok-4",
+        "gemini/gemini-2.5-pro": "openrouter/google/gemini-2.5-pro",
     }
     
     # Check for exact match first

backend/utils/config.py

@@ -176,6 +176,7 @@ class Configuration:
     OPENROUTER_API_KEY: Optional[str] = None
     XAI_API_KEY: Optional[str] = None
     MORPH_API_KEY: Optional[str] = None
+    GEMINI_API_KEY: Optional[str] = None
     OPENROUTER_API_BASE: Optional[str] = "https://openrouter.ai/api/v1"
     OR_SITE_URL: Optional[str] = "https://kortix.ai"
     OR_APP_NAME: Optional[str] = "Kortix AI"    

backend/utils/constants.py

@@ -60,7 +60,7 @@ MODELS = {
     },
     
     # Paid tier only models
-    "openrouter/google/gemini-2.5-pro": {
+    "gemini/gemini-2.5-pro": {
         "aliases": ["google/gemini-2.5-pro"],
         "pricing": {
             "input_cost_per_million_tokens": 1.25,
@@ -145,8 +145,8 @@ def _generate_model_structures():
         elif model_name.startswith("openrouter/qwen/"):
             legacy_name = model_name.replace("openrouter/", "")
             pricing[legacy_name] = config["pricing"]
-        elif model_name.startswith("openrouter/google/"):
+        elif model_name.startswith("gemini/"):
-            legacy_name = model_name.replace("openrouter/", "")
+            legacy_name = model_name.replace("gemini/", "")
             pricing[legacy_name] = config["pricing"]
         elif model_name.startswith("anthropic/"):
             # Add anthropic/claude-sonnet-4 alias for claude-sonnet-4-20250514

docs/SELF-HOSTING.md

@@ -172,6 +172,7 @@ RABBITMQ_PORT=5672
 ANTHROPIC_API_KEY=your-anthropic-key
 OPENAI_API_KEY=your-openai-key
 OPENROUTER_API_KEY=your-openrouter-key
+GEMINI_API_KEY=your-gemini-api-key
 MORPH_API_KEY=
 MODEL_TO_USE=anthropic/claude-sonnet-4-20250514
 

setup.py

@@ -130,6 +130,7 @@ def load_existing_env_vars():
             "ANTHROPIC_API_KEY": backend_env.get("ANTHROPIC_API_KEY", ""),
             "OPENROUTER_API_KEY": backend_env.get("OPENROUTER_API_KEY", ""),
             "MORPH_API_KEY": backend_env.get("MORPH_API_KEY", ""),
+            "GEMINI_API_KEY": backend_env.get("GEMINI_API_KEY", ""),
             "MODEL_TO_USE": backend_env.get("MODEL_TO_USE", ""),
         },
         "search": {
@@ -685,7 +686,7 @@ class SetupWizard:
             )
         else:
             print_info(
-                "Suna requires at least one LLM provider. Supported: OpenAI, Anthropic, OpenRouter."
+                "Suna requires at least one LLM provider. Supported: OpenAI, Anthropic, Google Gemini, OpenRouter."
             )
 
         # Don't clear existing keys if we're updating
@@ -700,7 +701,8 @@ class SetupWizard:
             providers = {
                 "1": ("OpenAI", "OPENAI_API_KEY"),
                 "2": ("Anthropic", "ANTHROPIC_API_KEY"),
-                "3": ("OpenRouter", "OPENROUTER_API_KEY"),
+                "3": ("Google Gemini", "GEMINI_API_KEY"),
+                "4": ("OpenRouter", "OPENROUTER_API_KEY"),
             }
             print(
                 f"\n{Colors.CYAN}Select LLM providers to configure (e.g., 1,3):{Colors.ENDC}"
@@ -748,10 +750,14 @@ class SetupWizard:
                 self.env_vars["llm"][
                     "MODEL_TO_USE"
                 ] = "anthropic/claude-sonnet-4-20250514"
+            elif self.env_vars["llm"].get("GEMINI_API_KEY"):
+                self.env_vars["llm"][
+                    "MODEL_TO_USE"
+                ] = "gemini/gemini-2.5-pro"
             elif self.env_vars["llm"].get("OPENROUTER_API_KEY"):
                 self.env_vars["llm"][
                     "MODEL_TO_USE"
-                ] = "openrouter/google/gemini-flash-1.5"
+                ] = "openrouter/google/gemini-2.5-pro"
 
         print_success(
             f"LLM keys saved. Default model: {self.env_vars['llm'].get('MODEL_TO_USE', 'Not set')}"