Enterprise AWS contracts — Use existing AWS Bedrock credits instead of direct Anthropic API
Multiple AWS accounts — Run personal and business Bedrock accounts simultaneously
OpenAI-compatible API — Works with any tool expecting OpenAI's API format
Claude Code integration — Reuse the same AWS credentials used by Claude Code CLI

Prerequisites

AWS account with Bedrock access and Claude models enabled
AWS credentials configured (either default profile or named profile)
Python 3.8+ for LiteLLM installation

Installation

1. Install LiteLLM

pip install 'litellm[proxy]'

Verify installation:

litellm --version

Basic Setup — Single AWS Account

1. Create Configuration File

Create ~/.litellm/config.yaml:

model_list:
  - model_name: bedrock-claude
    litellm_params:
      model: bedrock/us.anthropic.claude-sonnet-4-6
      aws_region_name: us-east-1
      # Uses default AWS credentials from ~/.aws/credentials

general_settings:
  master_key: sk-1234  # Any value — used for API authentication

2. Start LiteLLM Proxy

# Run in background
nohup litellm --config ~/.litellm/config.yaml --port 8000 > ~/.litellm/litellm.log 2>&1 &

# Verify it's running
ps aux | grep litellm

3. Test the Connection

curl http://localhost:8000/v1/chat/completions \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "bedrock-claude",
    "messages": [{"role": "user", "content": "Hello"}],
    "max_tokens": 50
  }'

Expected response:

{
  "id": "chatcmpl-...",
  "model": "bedrock-claude",
  "choices": [{
    "message": {
      "role": "assistant",
      "content": "Hello! How can I help you today?"
    }
  }]
}

4. Configure TFTSR

In Settings → AI Providers → Add Provider:

Field	Value
Provider Name	OpenAI
Base URL	`http://localhost:8000/v1`
API Key	`sk-1234` (or your master_key from config)
Model	`bedrock-claude`
Display Name	`Bedrock Claude`

Advanced Setup — Multiple AWS Accounts

If you have personal and business Bedrock accounts, you can run both through the same LiteLLM instance.

1. Configure AWS Profiles

Ensure you have AWS profiles set up in ~/.aws/credentials:

[default]
aws_access_key_id = AKIA...
aws_secret_access_key = ...

[ClaudeCodeLP]
aws_access_key_id = AKIA...
aws_secret_access_key = ...

Or if using credential process (like Claude Code does):

# ~/.aws/config
[profile ClaudeCodeLP]
credential_process = /Users/${USER}/claude-code-with-bedrock/credential-process --profile ClaudeCodeLP
region = us-east-1

2. Update Configuration File

Edit ~/.litellm/config.yaml:

model_list:
  - model_name: bedrock-personal
    litellm_params:
      model: bedrock/us.anthropic.claude-sonnet-4-6
      aws_region_name: us-east-1
      # Uses default AWS credentials

  - model_name: bedrock-business
    litellm_params:
      model: bedrock/us.anthropic.claude-sonnet-4-5-20250929-v1:0
      aws_region_name: us-east-1
      aws_profile_name: ClaudeCodeLP  # Named profile for business account

general_settings:
  master_key: sk-1234

3. Restart LiteLLM

# Find and stop existing process
pkill -f "litellm --config"

# Start with new config
nohup litellm --config ~/.litellm/config.yaml --port 8000 > ~/.litellm/litellm.log 2>&1 &

4. Verify Both Models

# List available models
curl -s http://localhost:8000/v1/models \
  -H "Authorization: Bearer sk-1234" | python3 -m json.tool

# Test personal account
curl -s http://localhost:8000/v1/chat/completions \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{"model": "bedrock-personal", "messages": [{"role": "user", "content": "test"}]}'

# Test business account
curl -s http://localhost:8000/v1/chat/completions \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{"model": "bedrock-business", "messages": [{"role": "user", "content": "test"}]}'

5. Configure in TFTSR

Add both models as separate providers:

Provider 1 — Personal:

Provider: OpenAI
Base URL: http://localhost:8000/v1
API Key: sk-1234
Model: bedrock-personal
Display Name: Bedrock (Personal)

Provider 2 — Business:

Provider: OpenAI
Base URL: http://localhost:8000/v1
API Key: sk-1234
Model: bedrock-business
Display Name: Bedrock (Business)

Claude Code Integration

If you're using Claude Code with AWS Bedrock, you can reuse the same AWS credentials.

1. Check Claude Code Settings

Read your Claude Code configuration:

cat ~/.claude/settings.json

Look for:

AWS_PROFILE environment variable (e.g., ClaudeCodeLP)
awsAuthRefresh credential process path
AWS_REGION setting

2. Use Same Profile in LiteLLM

In ~/.litellm/config.yaml, add a model using the same profile:

model_list:
  - model_name: claude-code-bedrock
    litellm_params:
      model: bedrock/us.anthropic.claude-sonnet-4-5-20250929-v1:0
      aws_region_name: us-east-1
      aws_profile_name: ClaudeCodeLP  # Same as Claude Code

Now both Claude Code and TFTSR use the same Bedrock account without duplicate credential management.

Available Claude Models on Bedrock

Model ID	Name	Context	Best For
`us.anthropic.claude-sonnet-4-6`	Claude Sonnet 4.6	200k tokens	Most tasks, best quality
`us.anthropic.claude-sonnet-4-5-20250929-v1:0`	Claude Sonnet 4.5	200k tokens	High performance
`us.anthropic.claude-opus-4-6`	Claude Opus 4.6	200k tokens	Complex reasoning
`us.anthropic.claude-haiku-4-5-20251001`	Claude Haiku 4.5	200k tokens	Speed + cost optimization

Check your AWS Bedrock console for available models in your region.

Troubleshooting

Port Already in Use

If port 8000 is occupied:

# Find what's using the port
lsof -i :8000

# Use a different port
litellm --config ~/.litellm/config.yaml --port 8080

Update the Base URL in TFTSR to match: http://localhost:8080/v1

AWS Credentials Not Found

# Verify AWS CLI works
aws bedrock list-foundation-models --region us-east-1

# Test specific profile
aws bedrock list-foundation-models --region us-east-1 --profile ClaudeCodeLP

If AWS CLI fails, fix credentials first before debugging LiteLLM.

Model Not Available

Error: Model not found or Access denied

Check AWS Bedrock Console → Model Access
Request access to Claude models if not enabled
Verify model ID matches exactly (case-sensitive)

LiteLLM Won't Start

Check logs:

cat ~/.litellm/litellm.log

Common issues:

Missing Python dependencies: pip install 'litellm[proxy]' --upgrade
YAML syntax error: Validate with python3 -c "import yaml; yaml.safe_load(open('${HOME}/.litellm/config.yaml'))"

Auto-Start LiteLLM on Boot

macOS — LaunchAgent

Create ~/Library/LaunchAgents/com.litellm.proxy.plist:

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
    <key>Label</key>
    <string>com.litellm.proxy</string>
    <key>ProgramArguments</key>
    <array>
        <string>/opt/homebrew/bin/litellm</string>
        <string>--config</string>
        <string>/Users/${USER}/.litellm/config.yaml</string>
        <string>--port</string>
        <string>8000</string>
    </array>
    <key>RunAtLoad</key>
    <true/>
    <key>KeepAlive</key>
    <true/>
    <key>StandardOutPath</key>
    <string>/Users/${USER}/.litellm/litellm.log</string>
    <key>StandardErrorPath</key>
    <string>/Users/${USER}/.litellm/litellm-error.log</string>
</dict>
</plist>

Load it:

launchctl load ~/Library/LaunchAgents/com.litellm.proxy.plist

Linux — systemd

Create /etc/systemd/system/litellm.service:

[Unit]
Description=LiteLLM Proxy
After=network.target

[Service]
Type=simple
User=${USER}
ExecStart=/usr/local/bin/litellm --config /home/${USER}/.litellm/config.yaml --port 8000
Restart=always
RestartSec=10

[Install]
WantedBy=multi-user.target

Enable and start:

sudo systemctl enable litellm
sudo systemctl start litellm
sudo systemctl status litellm

Cost Comparison

Provider	Model	Input (per 1M tokens)	Output (per 1M tokens)
Anthropic Direct	Claude Sonnet 4	$3.00	$15.00
AWS Bedrock	Claude Sonnet 4	$3.00	$15.00

Pricing is identical, but Bedrock provides:

AWS consolidated billing
AWS Credits applicability
Integration with AWS services (S3, Lambda, etc.)
Enterprise support contracts

Security Notes

Master Key — The master_key in config is required but doesn't need to be complex since LiteLLM runs locally
AWS Credentials — Never commit .aws/credentials or credential process scripts to git
Local Only — LiteLLM proxy should only bind to 127.0.0.1 (localhost) — never expose to network
Audit Logs — TFTSR logs all AI requests with SHA-256 hashes in the audit table

LiteLLM + AWS Bedrock Setup

Why LiteLLM + Bedrock?