Using Third-Party Models (OpenAI / DeepSeek / Local Models)

This project communicates with LLMs via the Anthropic protocol. By using a protocol translation proxy, you can use any model including OpenAI, DeepSeek, Ollama, etc.

How It Works

claude-code-haha ──Anthropic protocol──▶ LiteLLM Proxy ──OpenAI protocol──▶ Target Model API
                                          (translation)

This project sends Anthropic Messages API requests. The LiteLLM proxy automatically translates them to OpenAI Chat Completions API format and forwards them to the target model.

Option 1: LiteLLM Proxy (Recommended)

LiteLLM is a unified proxy gateway supporting 100+ LLMs (41k+ GitHub Stars), with native support for receiving Anthropic protocol requests.

1. Install LiteLLM

bash

pip install 'litellm[proxy]'

2. Create Configuration File

Create litellm_config.yaml:

Using OpenAI Models

yaml

model_list:
  - model_name: gpt-4o
    litellm_params:
      model: openai/gpt-4o
      api_key: os.environ/OPENAI_API_KEY

litellm_settings:
  drop_params: true  # Drop Anthropic-specific params (thinking, etc.)

Using DeepSeek Models

yaml

model_list:
  - model_name: deepseek-chat
    litellm_params:
      model: deepseek/deepseek-chat
      api_key: os.environ/DEEPSEEK_API_KEY
      api_base: https://api.deepseek.com

litellm_settings:
  drop_params: true

Using Ollama Local Models

yaml

model_list:
  - model_name: llama3
    litellm_params:
      model: ollama/llama3
      api_base: http://localhost:11434

litellm_settings:
  drop_params: true

Using Multiple Models (switchable after startup)

yaml

model_list:
  - model_name: gpt-4o
    litellm_params:
      model: openai/gpt-4o
      api_key: os.environ/OPENAI_API_KEY

  - model_name: deepseek-chat
    litellm_params:
      model: deepseek/deepseek-chat
      api_key: os.environ/DEEPSEEK_API_KEY
      api_base: https://api.deepseek.com

  - model_name: llama3
    litellm_params:
      model: ollama/llama3
      api_base: http://localhost:11434

litellm_settings:
  drop_params: true

3. Start the Proxy

bash

# Set your target model's API key
export OPENAI_API_KEY=sk-xxx
# or
export DEEPSEEK_API_KEY=sk-xxx

# Start the proxy
litellm --config litellm_config.yaml --port 4000

The proxy will listen on http://localhost:4000 and expose an Anthropic-compatible /v1/messages endpoint.

4. Configure This Project

Choose one of two configuration methods:

Method A: Via `.env` File

env

ANTHROPIC_AUTH_TOKEN=sk-anything
ANTHROPIC_BASE_URL=http://localhost:4000
ANTHROPIC_MODEL=gpt-4o
ANTHROPIC_DEFAULT_SONNET_MODEL=gpt-4o
ANTHROPIC_DEFAULT_HAIKU_MODEL=gpt-4o
ANTHROPIC_DEFAULT_OPUS_MODEL=gpt-4o
API_TIMEOUT_MS=3000000
DISABLE_TELEMETRY=1
CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1

Method B: Via `~/.claude/settings.json`

json

{
  "env": {
    "ANTHROPIC_AUTH_TOKEN": "sk-anything",
    "ANTHROPIC_BASE_URL": "http://localhost:4000",
    "ANTHROPIC_MODEL": "gpt-4o",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "gpt-4o",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "gpt-4o",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "gpt-4o",
    "API_TIMEOUT_MS": "3000000",
    "DISABLE_TELEMETRY": "1",
    "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1"
  }
}

Note: The ANTHROPIC_AUTH_TOKEN value can be any string when using the LiteLLM proxy (LiteLLM uses its own configured key for forwarding), unless you've set a master_key on the LiteLLM side.

5. Start and Verify

bash

./bin/claude-haha

If everything is configured correctly, you should see the normal chat interface, with your configured target model handling the requests.

Option 2: Direct Connection to Anthropic-Compatible Services

Some third-party services directly support the Anthropic Messages API, no proxy needed:

OpenRouter

env

ANTHROPIC_AUTH_TOKEN=sk-or-v1-xxx
ANTHROPIC_BASE_URL=https://openrouter.ai/api/v1
ANTHROPIC_MODEL=openai/gpt-4o
ANTHROPIC_DEFAULT_SONNET_MODEL=openai/gpt-4o
ANTHROPIC_DEFAULT_HAIKU_MODEL=openai/gpt-4o-mini
ANTHROPIC_DEFAULT_OPUS_MODEL=openai/gpt-4o
DISABLE_TELEMETRY=1
CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1

MiniMax (pre-configured in .env.example)

env

ANTHROPIC_AUTH_TOKEN=your_token_here
ANTHROPIC_BASE_URL=https://api.minimaxi.com/anthropic
ANTHROPIC_MODEL=MiniMax-M2.7-highspeed
ANTHROPIC_DEFAULT_SONNET_MODEL=MiniMax-M2.7-highspeed
ANTHROPIC_DEFAULT_HAIKU_MODEL=MiniMax-M2.7-highspeed
ANTHROPIC_DEFAULT_OPUS_MODEL=MiniMax-M2.7-highspeed
API_TIMEOUT_MS=3000000
DISABLE_TELEMETRY=1
CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1

Option 3: Other Proxy Tools

The community has built several proxy tools specifically for Claude Code:

Tool	Description	Link
a2o	Anthropic → OpenAI single binary, zero dependencies	Twitter
Empero Proxy	Full Anthropic Messages API to OpenAI translation	Twitter
Alma	Client with built-in OpenAI → Anthropic proxy	Twitter
Chutes	Docker container supporting 60+ open-source models	Twitter

Known Limitations

1. `drop_params: true` Is Essential

This project sends Anthropic-specific parameters (e.g., thinking, cache_control) that don't exist in the OpenAI API. You must set drop_params: true in the LiteLLM config, otherwise requests will fail.

2. Extended Thinking Unavailable

Anthropic's Extended Thinking is a proprietary feature not supported by other models. It is automatically disabled when using third-party models.

3. Prompt Caching Unavailable

cache_control is an Anthropic-specific feature. Prompt caching won't work with third-party models (but won't cause errors — it's silently ignored by drop_params).

4. Tool Calling Compatibility

This project heavily uses tool calling (tool_use). LiteLLM automatically translates Anthropic's tool_use format to OpenAI's function_calling format. This works in most cases, but some complex tool calls may have compatibility issues. If you encounter problems, try using a more capable model (e.g., GPT-4o).

5. Telemetry and Non-Essential Requests

Configure these environment variables to avoid unnecessary network requests:

DISABLE_TELEMETRY=1
CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1

FAQ

Q: LiteLLM proxy returns `/v1/responses` not found?

Some OpenAI-compatible services only support /v1/chat/completions. Add this to your LiteLLM config:

yaml

litellm_settings:
  use_chat_completions_url_for_anthropic_messages: true

Q: What's the difference between `ANTHROPIC_API_KEY` and `ANTHROPIC_AUTH_TOKEN`?

ANTHROPIC_API_KEY → Sent via x-api-key header
ANTHROPIC_AUTH_TOKEN → Sent via Authorization: Bearer header

LiteLLM proxy accepts Bearer Token format by default, so ANTHROPIC_AUTH_TOKEN is recommended.

Q: Can I configure multiple models?

Yes. Define multiple model_name entries in litellm_config.yaml, then switch by changing the ANTHROPIC_MODEL value.

Q: Local Ollama models don't work well?

This project's system prompts and tool calls require strong model capabilities. Use larger models (e.g., Llama 3 70B+, Qwen 72B+). Smaller models may fail to handle tool calling correctly.

Using Third-Party Models (OpenAI / DeepSeek / Local Models) ​

How It Works ​

Option 1: LiteLLM Proxy (Recommended) ​

1. Install LiteLLM ​

2. Create Configuration File ​

Using OpenAI Models ​

Using DeepSeek Models ​

Using Ollama Local Models ​

Using Multiple Models (switchable after startup) ​

3. Start the Proxy ​

4. Configure This Project ​

Method A: Via .env File ​

Method B: Via ~/.claude/settings.json ​

5. Start and Verify ​

Option 2: Direct Connection to Anthropic-Compatible Services ​

OpenRouter ​

MiniMax (pre-configured in .env.example) ​

Option 3: Other Proxy Tools ​

Known Limitations ​

1. drop_params: true Is Essential ​

2. Extended Thinking Unavailable ​

3. Prompt Caching Unavailable ​

4. Tool Calling Compatibility ​

5. Telemetry and Non-Essential Requests ​

FAQ ​

Q: LiteLLM proxy returns /v1/responses not found? ​

Q: What's the difference between ANTHROPIC_API_KEY and ANTHROPIC_AUTH_TOKEN? ​

Q: Can I configure multiple models? ​

Q: Local Ollama models don't work well? ​

Using Third-Party Models (OpenAI / DeepSeek / Local Models)

How It Works

Option 1: LiteLLM Proxy (Recommended)

1. Install LiteLLM

2. Create Configuration File

Using OpenAI Models

Using DeepSeek Models

Using Ollama Local Models

Using Multiple Models (switchable after startup)

3. Start the Proxy

4. Configure This Project

Method A: Via `.env` File

Method B: Via `~/.claude/settings.json`

5. Start and Verify

Option 2: Direct Connection to Anthropic-Compatible Services

OpenRouter

MiniMax (pre-configured in .env.example)

Option 3: Other Proxy Tools

Known Limitations

1. `drop_params: true` Is Essential

2. Extended Thinking Unavailable

3. Prompt Caching Unavailable

4. Tool Calling Compatibility

5. Telemetry and Non-Essential Requests

FAQ

Q: LiteLLM proxy returns `/v1/responses` not found?

Q: What's the difference between `ANTHROPIC_API_KEY` and `ANTHROPIC_AUTH_TOKEN`?

Q: Can I configure multiple models?

Q: Local Ollama models don't work well?