Skip to main content

Available Models

Model: gemini-pro

Gemini Pro Vision

Model: gemini-pro-vision

Setup

Step 1: Get API Key

  1. Go to Google AI Studio
  2. Click “Create API Key”
  3. Select your GCP project
  4. Copy the API key

Step 2: Enable Gemini API

In Google Cloud Console:
  1. Go to Google Cloud Console
  2. Search for “Generative Language API”
  3. Click “Enable”
  4. Wait for API to activate (usually instant)

Step 3: Add to CallIntel

For Super Admins:
  1. Go to Settings → Developer Settings
  2. Click “API Keys”
  3. Select “Google Gemini” from provider list
  4. Paste API key
  5. Click “Test Connection”
  6. Save
For Organization Admins:
  1. Go to Settings → AI Models
  2. Click “Add Google Gemini”
  3. Paste API key
  4. Select which models to enable
  5. Save

Step 4: Configure Agent

  1. Create or Edit an Agent
  2. Under “Language Model”, select:
    • gemini-pro or
    • gemini-pro-vision
  3. Configure settings:
    • Temperature: 0.7 (default)
    • Max Tokens: 200
  4. Save agent

Step 5: Test

Make a test call:
  1. Use Web Call feature
  2. Speak with agent
  3. Verify responses
  4. Check logs

Model Selection

Gemini vs OpenAI

When to Use Gemini

Advantages:
  • Slightly cheaper than GPT-3.5
  • Faster responses
  • Native vision support
  • Great for document analysis
  • Excellent multilingual support
Best Use Cases:
  • High-volume customer service
  • Document verification
  • Multilingual agents
  • Vision-based tasks
  • Cost-sensitive operations

Configuration

Temperature

Controls response variability (0-2):

Top P

Controls diversity (0-1):

Top K

Controls output (1-40):

Cost Comparison

Monthly Costs (1000 calls)

Gemini Vision Costs

Advanced Features

Image Analysis

Process images with Gemini Pro Vision:
Cost Note: Image processing is more expensive per call.

Function Calling

Enable agents to interact with external systems:

Streaming Responses

Get responses progressively:

Optimization

1. Use Gemini for High Volume

2. Optimize Prompts

Keep system prompts concise:

3. Reduce Token Usage

Monitoring

API Usage

Check Gemini API usage:
  1. Go to Google AI Studio
  2. View usage statistics
  3. Check spending rate
  4. Monitor quota limits

Call Metrics

Track in CallIntel dashboard:

Best Practices

1. Start with Gemini Pro

2. Use Vision Sparingly

3. Monitor Response Quality

4. Test Before Deploying

Troubleshooting

Verify key format is correct, API is enabled in Google Cloud Console, and key is for Gemini API.
Gemini is typically fast, but check network latency. Try reducing max_tokens.
Ensure image format is supported (JPEG, PNG, GIF). Check file size isn’t too large.
Check if using vision model. Vision requests cost 2-3x more. Switch to Gemini Pro for text-only.

See Also

AI Models Overview

Compare all AI providers

OpenAI Models

Using OpenAI models

Agent Setup

Create and configure agents

Support

Contact Support