The /gemini-pc
command enables you to access Google Gemini AI models through PinkConnect Proxy. Perfect for:
- Text generation and creative writing
- Image analysis and description
- Multi-turn conversations
- Code generation and analysis
- Function calling capabilities
- Multimodal AI interactions
Basic Usage
Use the command to interact with Gemini models:
/gemini-pc generate a short story about space exploration
/gemini-pc analyze this image and describe what you see
/gemini-pc help me write a Python function for data processing
Key Features
Text Generation
- Creative writing
- Content creation
- Code generation
- Technical documentation
- Conversational AI
Multimodal Capabilities
- Image understanding
- Video analysis
- Audio processing
- Visual reasoning
- Cross-modal tasks
Advanced Features
- Function calling
- Tool integration
- JSON mode support
- Multi-turn conversations
- Structured outputs
Example Commands
Creative Writing
/gemini-pc write a poem about artificial intelligence
Code Generation
/gemini-pc create a Python class for managing user accounts
Image Analysis
/gemini-pc describe the contents of this uploaded image
Conversation
/gemini-pc start a conversation about machine learning concepts
Function Calling
/gemini-pc get weather information for San Francisco using available tools
Available Models
Latest Generation
- gemini-2.0-flash: Next-generation features, speed, and thinking
- gemini-2.0-flash-lite: Cost-efficient with low latency
- gemini-2.5-flash: Fast and versatile for general tasks
- gemini-2.5-pro: Advanced reasoning and coding capabilities
Established Models
- gemini-1.5-pro: High intelligence for complex tasks
- gemini-1.5-flash: Fast and versatile performance
Text Generation
Basic Request
{
"contents": [
{
"parts": [
{
"text": "Write a short story about a robot learning to paint"
}
]
}
],
"generationConfig": {
"temperature": 0.7,
"topK": 40,
"topP": 0.95,
"maxOutputTokens": 1024
}
}
Configuration Options
- temperature: Creativity level (0.0-1.0)
- topK: Token selection diversity
- topP: Nucleus sampling threshold
- maxOutputTokens: Response length limit
Image Analysis
{
"contents": [
{
"parts": [
{
"text": "Describe what you see in this image"
},
{
"inline_data": {
"mime_type": "image/jpeg",
"data": "base64_encoded_image_data"
}
}
]
}
]
}
- JPEG images
- PNG images
- WebP images
- Base64 encoding
- Inline data format
Multi-turn Conversations
{
"contents": [
{
"role": "user",
"parts": [{"text": "Hello! Can you help me with coding?"}]
},
{
"role": "model",
"parts": [{"text": "Hello! I'd be happy to help you with coding..."}]
},
{
"role": "user",
"parts": [{"text": "I need help with Python functions"}]
}
]
}
Conversation Flow
- Maintain context across turns
- Use role-based messaging
- Build on previous responses
- Handle conversation history
Function Calling
Function Declaration
{
"tools": [
{
"function_declarations": [
{
"name": "get_weather",
"description": "Get the current weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
}
},
"required": ["location"]
}
}
]
}
]
}
- Define custom functions
- Structured parameter schemas
- Automatic function calling
- Result integration
Response Structure
Standard Response
{
"candidates": [
{
"content": {
"parts": [
{
"text": "Generated response text..."
}
],
"role": "model"
},
"finishReason": "STOP",
"safetyRatings": [...]
}
],
"usageMetadata": {
"promptTokenCount": 12,
"candidatesTokenCount": 150,
"totalTokenCount": 162
}
}
Response Elements
- candidates: Generated responses
- finishReason: Completion status
- safetyRatings: Content safety scores
- usageMetadata: Token usage information
Best Practices
-
Model Selection
- Choose appropriate model for task
- Consider speed vs. capability trade-offs
- Use flash models for quick responses
- Use pro models for complex reasoning
-
Prompt Engineering
- Be specific and clear
- Provide context and examples
- Use structured formatting
- Test different approaches
-
Configuration Tuning
- Adjust temperature for creativity
- Set appropriate token limits
- Use sampling parameters wisely
- Monitor response quality
-
Multimodal Usage
- Combine text and images effectively
- Use appropriate mime types
- Optimize image sizes
- Provide clear instructions
Common Use Cases
Content Creation
/gemini-pc create marketing copy for a new product launch
Code Analysis
/gemini-pc review this code and suggest improvements
Data Processing
/gemini-pc analyze this dataset and provide insights
Creative Tasks
/gemini-pc generate ideas for a mobile app interface
Error Handling
Common Issues
- Invalid API keys
- Model not found
- Rate limiting
- Content safety blocks
Response Codes
- 200: Success
- 400: Bad request
- 401: Unauthorized
- 429: Rate limited
- 500: Server error
Safety Features
Content Filtering
- Automatic safety checks
- Harmful content detection
- Bias mitigation
- Responsible AI practices
Safety Categories
- Sexually explicit content
- Hate speech
- Harassment
- Dangerous content
Speed Considerations
- Use flash models for quick responses
- Optimize prompt length
- Batch similar requests
- Cache common responses
Cost Management
- Monitor token usage
- Use appropriate models
- Optimize request frequency
- Track usage metrics
Tips
- Choose the right model for your specific task requirements
- Use multimodal capabilities by combining text with images
- Leverage function calling for structured interactions
- Adjust temperature settings based on desired creativity level
- Monitor token usage to optimize costs
- Test different prompt strategies for best results