ask-gemini

ask-gemini-flash.md

Ask Gemini Flash Command

Ask Gemini Flash this question and get a quick, balanced response: $ARGUMENTS

Expected Output:

• Provide clear, concise answers (limit ~500 tokens)
• Use creative but accurate tone
• For complex code tasks, suggest using ask-gemini-pro instead
• If unable to answer, explain why clearly

Code Example:

from dotenv import load_dotenv
load_dotenv('/home/graham/workspace/experiments/llm_call/.env')
import os
from litellm import completion

model = os.getenv('SLASHCMD_ASK_GEMINI_FLASH_MODEL')  # Gets configured Gemini Flash model
response = completion(
    model=model,
    messages=[{"role": "user", "content": "YOUR_QUERY"}],
    temperature=0.7,  # Balanced creativity
    max_tokens=500    # Reasonable response length
)
print(response.choices[0].message.content)

Model Information:

• vertex_ai/gemini-1.5-flash: Fast, cost-efficient version of Gemini 1.5
• Good for: Code generation, analysis, general questions, quick responses
• Features: Multi-modal support, function calling, safety settings

Environment Requirements:

• GOOGLE_APPLICATION_CREDENTIALS: Path to service account JSON file
• VERTEX_PROJECT: Google Cloud project ID (optional, can be in credentials)
• VERTEX_LOCATION: Region like 'us-central1' (optional)

Helpful Documentation:

• Vertex AI Setup: https://docs.litellm.ai/docs/providers/vertex
• Gemini Models: https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/gemini
• Authentication: https://cloud.google.com/docs/authentication/getting-started

Usage Examples:

• /user:ask-gemini-flash Write a Python function to calculate fibonacci
• /user:ask-gemini-flash Explain quantum computing in simple terms
• /user:ask-gemini-flash Debug this code: [paste code]

Notes:

• Ensure Google Cloud credentials are properly configured
• Flash model is optimized for speed and cost-efficiency
• For complex reasoning tasks, consider using gemini-1.5-pro instead