Configuring LLM Providers

	sfp-pro	sfp (community)
Availability	✅	N/A
From	October 25
Features	PR Linter, Reports, Error Analysis

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

• AI-Assisted Error Analysis - Intelligent validation error analysis

Prerequisites

Installation Methods

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
GitHub Copilot	✅ Fully Supported	Yes	Teams with existing Copilot subscriptions, no extra cost

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-sonnet-4-5-20250929 which offers optimal balance between performance and cost.

Setup

Step 1: Environment Variable

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

# Verify the configuration works
sfp ai test --provider anthropic

Step 2: Configuration File Create or edit config/ai-architecture.yaml:

enabled: true
provider: anthropic
# Model is optional - uses claude-sonnet-4-5-20250929 by default

Getting an Anthropic API Key

1. Visit console.anthropic.com

2. Sign up or log in to your account

3. Navigate to API Keys section

4. Create a new API key for sfp usage

5. Copy the key (starts with sk-ant-)

Claude Models Available:

• claude-sonnet-4-5-20250929 - Recommended, best balance (default)

• claude-opus-4-0-20250514 - Most capable, higher cost

OpenAI

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

Setup

Step 1: Environment Variable

export OPENAI_API_KEY="sk-xxxxxxxxxxxxx"

# Verify the configuration works
sfp ai test --provider openai

Step 2: Configuration File

# In config/ai-assist.yaml
enabled: true
provider: openai
# Model is optional - uses gpt-4o by default

Getting an OpenAI API Key

1. Visit platform.openai.com

2. Sign up or log in

3. Go to API Keys section

4. Create a new secret key

5. 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

Step 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
# Verify the configuration works
sfp ai test --provider amazon-bedrock

STEP 3: Configuration File

# In config/ai-assist.yaml
enabled: true
provider: amazon-bedrock
model: anthropic.claude-sonnet-4-5-20250929-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

Prerequisites:

• Active GitHub Copilot subscription (Individual, Business, or Enterprise)

• Models must be enabled in your GitHub Copilot settings

• Visit GitHub Copilot Features to enable model access

Setup Methods

Method 1: Generate Token Using Script (Recommended)

sfp includes a helper script to generate Copilot tokens via the GitHub device flow:

# Run the token generator script
./scripts/get-copilot-token.sh

The script will:

1. Request a device code from GitHub

2. Display a URL and verification code

3. Open your browser automatically (on supported systems)

4. Poll for authorization completion

5. Output the OAuth token (ghu_ prefixed)

After the script completes, set the token:

# Set the token in your environment
export COPILOT_TOKEN="ghu_xxxxxxxxxxxx"

# Verify the configuration works
sfp ai test --provider github-copilot

Method 2: Environment Variable (CI/CD)

For CI/CD pipelines, set the COPILOT_TOKEN environment variable:

# Add to your shell profile or CI/CD secrets
export COPILOT_TOKEN="ghu_xxxxxxxxxxxx"

In GitHub Actions:

jobs:
  analyze:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Run AI Analysis
        env:
          COPILOT_TOKEN: ${{ secrets.COPILOT_TOKEN }}
        run: |
          sfp project:analyze --provider github-copilot

Important: Use COPILOT_TOKEN instead of GITHUB_TOKEN in CI/CD environments. The GITHUB_TOKEN is automatically set by GitHub Actions for repository operations and may conflict with Copilot authentication.

How Token Exchange Works

sfp automatically handles the OAuth token exchange process:

1. OAuth Token (ghu_ prefix): The token you obtain from device flow authentication

2. API Token Exchange: sfp automatically exchanges the OAuth token for a Copilot API token via GitHub's internal API

3. Transparent Process: This exchange happens automatically when you use --provider github-copilot

OAuth Token (ghu_xxx) → Exchange API → Copilot API Token → AI Model Access

Configuration File

# In config/ai-assist.yaml
enabled: true
provider: github-copilot
# Model is optional - uses claude-sonnet-4.5 by default for GitHub Copilot

Available Models

GitHub Copilot provides access to various models. The default is claude-sonnet-4.5:

Model	Description	Notes
claude-sonnet-4.5	Claude Sonnet 4.5	Default, recommended
gpt-4.1	GPT-4.1	Alternative option

Model Naming: GitHub Copilot uses simplified model names without date suffixes (e.g., claude-sonnet-4.5 instead of claude-sonnet-4-20250514).

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-4-5-20250929
# - openai: gpt-4o
# - github-copilot: gpt-4o
# - amazon-bedrock: anthropic.claude-sonnet-4-5-20250929-v1:0
model: claude-sonnet-4-5-20250929  # 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

Testing Provider Configuration

The test command performs a complete health check:

• Authentication: Verifies credentials are available

• Connectivity: Confirms the provider endpoint is reachable

• Response: Validates the model returns a valid response

Environment Variables Reference

# 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

Usage Priority

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

1. Environment Variables - Highest priority, recommended for CI/CD

2. Configuration File - From config/ai-assist.yaml

Troubleshooting

Provider Not Available

# Verify environment variables
echo $ANTHROPIC_API_KEY

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

# For GitHub Copilot
echo $COPILOT_TOKEN

# Test provider connectivity
sfp ai test --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 for your provider:

# Anthropic
model: claude-sonnet-4-5-20250929

# OpenAI
model: gpt-4o

# GitHub Copilot
model: gpt-4o

# Amazon Bedrock
model: anthropic.claude-sonnet-4-5-20250929-v1:0