cc-haha/docs/en/guide/third-party-models.md

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.

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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

pip install 'litellm[proxy]'

2. Create Configuration File

Create litellm_config.yaml:

Using OpenAI Models

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

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

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)

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

# 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

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

{
  "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

./bin/claude-haha

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

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Option 2: Direct Connection to Anthropic-Compatible Services

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

OpenRouter

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)

MiniMax provides an Anthropic-compatible API endpoint and can be connected directly without any proxy. Available models:

Model	Description
MiniMax-M2.7	Default recommended, excellent overall performance
MiniMax-M2.7-highspeed	Faster responses, suitable for latency-sensitive use cases

ANTHROPIC_AUTH_TOKEN=your_minimax_api_key_here
# International users: api.minimax.io; China users may use api.minimaxi.com
ANTHROPIC_BASE_URL=https://api.minimax.io/anthropic
ANTHROPIC_MODEL=MiniMax-M2.7
ANTHROPIC_DEFAULT_SONNET_MODEL=MiniMax-M2.7
ANTHROPIC_DEFAULT_HAIKU_MODEL=MiniMax-M2.7-highspeed
ANTHROPIC_DEFAULT_OPUS_MODEL=MiniMax-M2.7
API_TIMEOUT_MS=3000000
DISABLE_TELEMETRY=1
CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1

Get API Key: Visit MiniMax Open Platform to register and obtain an API key.

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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

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FAQ

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

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

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.