Configuring LLM Providers

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sfp (community)

Availability

✅

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From

October 25

December 25

Features

PR Linter, Reports, Error Analysis

Reports Only

This guide covers the setup and configuration of Large Language Model (LLM) providers for AI-powered features in sfp:

AI-Powered PR Linter - sfp-pro only
AI Assisted Insight Reports - Available in both sfp-pro and community (alpha)
AI-Assisted Error Analysis - Intelligent validation error analysis

These features require OpenCode CLI and an authenticated LLM provider.

OpenCode is currently only supported on OSX or Linux runtimes. It's not supported for Windows platforms.

For sfp (community) users: These AI features are available in alpha. You can use npm install -g @flxbl-io/sfp@ai to access them.

Prerequisites

OpenCode CLI Installation

OpenCode CLI is the underlying engine that manages AI interactions for sfp's AI-powered features. It handles provider authentication, model selection, and secure API communication.

Installation Methods

Global Installation (Recommended)

# Install OpenCode CLI globally via npm
npm install -g opencode-ai

# Verify installation
opencode --version

Alternative Installation Methods

# Using yarn
yarn global add opencode-ai

# Using pnpm
pnpm add -g opencode-ai

# Using Homebrew (macOS/Linux)
brew install opencode-ai

For more installation options and troubleshooting, see the OpenCode documentation.

Supported LLM Providers

sfp currently supports the following LLM providers through OpenCode:

Provider

Status

Recommended

Best For

Anthropic (Claude)

✅ Fully Supported

⭐ Yes

Best overall performance, Flxbl framework understanding

OpenAI

✅ Fully Supported

Yes

Wide model selection, good performance

Amazon Bedrock

✅ Fully Supported

Yes

Enterprise environments with AWS infrastructure

Provider Configuration

Anthropic (Claude) - Recommended

Anthropic's Claude models provide the best understanding of Salesforce and Flxbl framework patterns. The default model used is claude-4-sonnet-xxxxx which offers optimal balance between performance and cost.

Setup Methods

Method 1: Interactive Authentication (Recommended)

# Authenticate with Anthropic
sfp ai auth --provider anthropic --auth

# This will prompt for your API key and store it securely

Method 2: Environment Variable

# Add to your shell profile (.bashrc, .zshrc, etc.)
export ANTHROPIC_API_KEY="sk-ant-xxxxxxxxxxxxx"

Method 3: Configuration File Create or edit config/ai-architecture.yaml:

enabled: true
provider: anthropic
# Model is optional - uses claude-sonnet-4-20250514 by default

Getting an Anthropic API Key

Visit console.anthropic.com
Sign up or log in to your account
Navigate to API Keys section
Create a new API key for sfp usage
Copy the key (starts with sk-ant-)

Claude Models Available:

claude-4-sonnet-xxxxx - Recommended, best balance (default)
claude-4-opus-xxxxx - Most capable, higher cost

OpenAI

OpenAI provides access to GPT models with good code analysis capabilities.

Setup Methods

Method 1: Interactive Authentication

sfp ai auth --provider openai --auth

Method 2: Environment Variable

export OPENAI_API_KEY="sk-xxxxxxxxxxxxx"

Method 3: Configuration File

# In config/ai-assist.yaml
enabled: true
provider: openai
# Model is optional - uses gpt-5 by default

Getting an OpenAI API Key

Visit platform.openai.com
Sign up or log in
Go to API Keys section
Create a new secret key
Copy the key (starts with sk-)

Amazon Bedrock

Amazon Bedrock is ideal for enterprise environments already using AWS infrastructure. It provides access to Claude models through AWS.

Setup Methods

Method 1: AWS Profile

# Set both required environment variables
export AWS_BEARER_TOKEN_BEDROCK="your-bearer-token"
export AWS_REGION="us-east-1"

# Both variables must be set for authentication to work

Method 2: AWS Credentials

# Authenticate with Amazon Bedrock
sfp ai auth --provider amazon-bedrock --auth

# This will prompt for both Bearer Token and Region

Method 3: Configuration File

# In config/ai-assist.yaml
enabled: true
provider: amazon-bedrock
model: anthropic.claude-sonnet-4-20250514-v1:0  # Default model

Important: AWS Bedrock requires both AWS_BEARER_TOKEN_BEDROCK and AWS_REGION environment variables to be set. Authentication will fail if either is missing.

Bedrock Model Access: Ensure your AWS account has access to the Claude models in Bedrock. You may need to request access through the AWS Console under Bedrock > Model access.

Regional Considerations

Bedrock automatically handles model prefixes based on your AWS region:

US Regions: Models may require us. prefix
EU Regions: Models may require eu. prefix
AP Regions: Models may require apac. prefix

The OpenCode SDK handles this automatically based on your AWS_REGION.

GitHub Copilot

GitHub Copilot can be used if you have an active subscription with model access enabled.

Setup

# Authenticate with GitHub Copilot
sfp ai auth --provider github-copilot --auth

# Ensure models are enabled in GitHub Settings:
# https://github.com/settings/copilot/features

GitHub Copilot requires the corresponding models to be activated in your GitHub Copilot Settings. Visit GitHub Copilot Features to enable model access.

Configuration File Reference

The AI features are configured through config/ai-assist.yaml in your project root:

# Enable/disable AI features
enabled: true

# Provider Configuration
provider: anthropic  # anthropic, openai, amazon-bedrock, github-copilot

# Model Configuration (Optional - uses provider defaults if not specified)
# Default models:
# - anthropic: claude-sonnet-4-20250514
# - github-copilot: claude-sonnet-4
# - openai: gpt-5
# - amazon-bedrock: anthropic.claude-sonnet-4-20250514-v1:0
model: claude-sonnet-4-20250514  # Override default model

# Architectural Patterns to Check (for PR Linter)
patterns:
  - singleton
  - factory
  - repository
  - service-layer

# Architecture Principles
principles:
  - separation-of-concerns
  - single-responsibility
  - dependency-inversion

# Focus Areas for Analysis
focusAreas:
  - security
  - performance
  - maintainability
  - testability

# Additional Context Files
contextFiles:
  - ARCHITECTURE.md
  - docs/patterns.md
  - docs/coding-standards.md

Authentication Management

Checking Authentication Status

# Check all providers
sfp ai auth

# Check specific provider
sfp ai auth --provider anthropic

# List all supported providers
sfp ai auth --list

Testing Provider Inference

After configuring authentication, you can verify that providers are working correctly using the ai check command:

# Test all configured providers
sfp ai check

# Test specific provider with default model
sfp ai check --provider anthropic

# Test Amazon Bedrock (uses default: anthropic.claude-sonnet-4-20250514-v1:0)
sfp ai check --provider amazon-bedrock

# Test GitHub Copilot (uses default: claude-sonnet-4)
sfp ai check --provider github-copilot

This command performs a simple inference test to verify:

Authentication is configured correctly
The provider is accessible
Model inference is working
Response time and performance

Authentication Storage

Credentials are stored securely in ~/.sfp/ai-auth.json with appropriate file permissions. This file is created automatically when you authenticate.

Rotating API Keys

# Re-authenticate to update stored credentials
sfp ai auth --provider anthropic --auth

# Or update environment variable
export ANTHROPIC_API_KEY="sk-ant-new-key-xxxxx"

Usage Priority

When multiple authentication methods are available, sfp uses the following priority:

Environment Variables - Highest priority, useful for CI/CD
Stored Credentials - From ~/.sfp/ai-auth.json
Configuration File - From config/ai-assist.yaml

Troubleshooting

OpenCode CLI Not Found

# Verify installation
which opencode

# If not found, reinstall
npm install -g opencode-ai

# Check npm global bin path is in PATH
npm bin -g

Provider Not Available

# Check authentication
sfp ai auth --provider anthropic

# Verify environment variables
echo $ANTHROPIC_API_KEY

# For AWS Bedrock - check both required variables
echo $AWS_BEARER_TOKEN_BEDROCK
echo $AWS_REGION

# Check stored credentials exist
ls -la ~/.sfp/ai-auth.json

# Test provider inference
sfp ai check --provider <provider-name>

AWS Bedrock Specific Issues

Both Environment Variables Required

# This will NOT work (missing region)
export AWS_BEARER_TOKEN_BEDROCK="token"

# This will work (both variables set)
export AWS_BEARER_TOKEN_BEDROCK="token"
export AWS_REGION="us-east-1"

Authentication Failed

Verify both AWS_BEARER_TOKEN_BEDROCK and AWS_REGION are set
Check that your bearer token is valid and not expired
Ensure your AWS account has access to Claude models in Bedrock

API Rate Limits

If you encounter rate limits:

Anthropic: Check your usage at console.anthropic.com
OpenAI: Monitor at platform.openai.com/usage
Bedrock: Check AWS CloudWatch metrics

Model Not Found

Ensure you're using the correct model identifier:

# Correct
model: claude-4-sonnet-xxxxx

Last updated 6 days ago