AnyAI-2-Open-API 🚀

Enhanced fork with Warp protocol support, Ollama protocol converter, model prefix system, and parallel fetching. A powerful proxy that unifies various AI model APIs (Gemini CLI, Qwen CLI, Kiro Claude, Warp) into OpenAI-compatible interfaces. Includes Ollama protocol converter to access cloud AI models via Ollama clients.

中文 | English | 日本語 | 📚 Complete Documentation

AnyAI-2-Open-API is an enhanced fork of AIClient2API. This fork adds Warp protocol integration, Ollama protocol converter (OpenAI ↔ Ollama translation), model prefix routing system, and parallel model fetching. Built on Node.js, it supports intelligent conversion between multiple protocols (OpenAI, Claude, Gemini, Warp, Ollama). The project adopts a modular architecture based on strategy and adapter patterns.

🌟 Enhanced Features in This Fork

• 🔥 Warp Protocol Support: Full Warp API integration with Protocol Buffers support (11 proto definitions)
  • Complete Warp module ecosystem (10 specialized handlers: auth, config, core, models, packet-builder, protobuf-utils, reorder, response, strategy, utils)
  • WarpApiService adapter with full streaming support
  • Protobuf-based packet building for Warp communication
• 🦙 Ollama Protocol Converter: Bidirectional translation (OpenAI ↔ Ollama)
  • Native Ollama protocol converter with complete API support
  • Ollama-specific endpoints: /api/tags, /api/show, /api/chat, /api/generate, /api/version
  • ⚠️ Important: To use Ollama endpoints, either run this server on Ollama's default port (11434) or manually configure the Ollama port in your client
  • ⚠️ Note: Close the official Ollama client before using this proxy, otherwise requests will be intercepted by the official client and models won't be visible
• 🏷️ Model Prefix System: Intelligent model-based provider routing (auto-detects Warp models like 'gpt-5')
  • Model-to-provider mapper for automatic routing
• ⚡ Parallel Model Fetching: Concurrent model information retrieval for improved performance
• 🎯 Enhanced Converter Architecture:
  • Extended GeminiConverter with tool call support
  • Enhanced OpenAIConverter with function call handling
  • OllamaConverter strategy for protocol translation

Note

🎉 Fork Enhancements

This is an enhanced fork of the original AIClient-2-API project with additional enterprise features.

📅 Fork Update Log

• 2025.11.14 - Added model prefix system and parallel model fetching
• 2025.11.14 - Added enterprise-grade Warp and Ollama protocol support with advanced routing

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💡 Core Advantages

🎯 Unified Access, One-Stop Management

• Multi-Model Unified Interface: Through standard OpenAI-compatible protocol, configure once to access mainstream large models including Gemini, Claude, GPT, Qwen Code, Warp, Kimi K2, GLM-4.6
• Flexible Switching Mechanism: Support dynamic model switching via startup parameters, Path routing, model prefixes, or environment variables to meet different scenario requirements
• Zero-Cost Migration: Fully compatible with OpenAI API specifications
• Multi-Protocol Intelligent Conversion: Support intelligent conversion between OpenAI, Claude, Gemini, Warp, and Ollama protocols for cross-protocol model invocation
  • Call Claude models using OpenAI protocol: Use claude-custom or claude-kiro-oauth providers
  • Call Gemini models using OpenAI protocol: Use gemini-cli-oauth provider
  • Call Gemini models using Claude protocol: Use gemini-cli-oauth provider
  • Call OpenAI models using Claude protocol: Use openai-custom or openai-qwen-oauth providers
  • Call Warp models using OpenAI protocol: Use warp provider with model prefix routing
  • Access cloud AI models via Ollama protocol: Ollama protocol converter translates Ollama API requests to OpenAI format, then routes to configured cloud providers (Gemini, Claude, GPT, etc.)

🚀 Break Through Limitations, Improve Efficiency

• Bypass Official Restrictions: Utilize OAuth authorization mechanism to effectively break through rate and quota limits of free APIs like Gemini
• Free Advanced Models: Use Claude Sonnet 4.5 for free via Kiro API mode, use Qwen3 Coder Plus via Qwen OAuth mode, reducing usage costs
• Intelligent Account Pool Scheduling: Support multi-account polling, automatic failover, and configuration degradation, ensuring 99.9% service availability

🛡️ Secure and Controllable, Data Transparent

• Full-Chain Log Recording: Capture all request and response data, supporting auditing and debugging
• Private Dataset Construction: Quickly build proprietary training datasets based on log data
• System Prompt Management: Support override and append modes, achieving perfect combination of unified base instructions and personalized extensions

🔧 Developer-Friendly, Easy to Extend

• Modular Architecture: Based on strategy and adapter patterns, adding new model providers requires only 3 steps
• Enhanced Converter System: Refactored protocol converters with improved maintainability and extensibility
• Model Prefix Routing: Intelligent model selection based on prefix patterns for flexible deployment
• Parallel Processing: Concurrent model fetching and request handling for optimal performance
• Complete Test Coverage: Integration and unit test coverage 90%+, ensuring code quality
• Containerized Deployment: Provides Docker support, one-click deployment, cross-platform operation
• MCP Protocol Support: Perfectly compatible with Model Context Protocol, easily extend functionality
• Warp & Ollama Integration: Enterprise-grade protocol support for advanced AI workflows

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📑 Quick Navigation

• 🐳 Docker Deployment
• 🎨 Model Protocol and Provider Relationship Diagram
• 🔧 Usage Instructions
• 🚀 Project Startup Parameters
• 📄 Open Source License
• 🙏 Acknowledgements
• ⚠️ Disclaimer

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🎨 Model Protocol and Provider Relationship Diagram

This project supports multiple model providers through different protocols. The following is an overview of their relationships:

• OpenAI Protocol (P_OPENAI): Implemented by openai-custom, gemini-cli-oauth, claude-custom, claude-kiro-oauth, openai-qwen-oauth, openaiResponses-custom, and warp model providers.
• Claude Protocol (P_CLAUDE): Implemented by claude-custom, claude-kiro-oauth, gemini-cli-oauth, openai-custom, openai-qwen-oauth, and openaiResponses-custom model providers.
• Gemini Protocol (P_GEMINI): Implemented by gemini-cli-oauth model provider.
• Warp Protocol (P_WARP): Implemented by warp model provider with enterprise-grade features.
• Ollama Protocol (P_OLLAMA): Protocol converter that translates Ollama API requests to OpenAI format, enabling Ollama clients to access cloud AI models through this proxy.

Detailed relationship diagram:

 
 graph TD
     subgraph Core_Protocols["Core Protocols"]
         P_OPENAI[OpenAI Protocol]
         P_GEMINI[Gemini Protocol]
         P_CLAUDE[Claude Protocol]
     end
 
     subgraph Supported_Model_Providers["Supported Model Providers"]
         MP_OPENAI[openai-custom]
         MP_GEMINI[gemini-cli-oauth]
         MP_CLAUDE_C[claude-custom]
         MP_CLAUDE_K[claude-kiro-oauth]
         MP_QWEN[openai-qwen-oauth]
         MP_OPENAI_RESP[openaiResponses-custom]
     end
 
     P_OPENAI ---|Support| MP_OPENAI
     P_OPENAI ---|Support| MP_QWEN
     P_OPENAI ---|Support| MP_GEMINI
     P_OPENAI ---|Support| MP_CLAUDE_C
     P_OPENAI ---|Support| MP_CLAUDE_K
     P_OPENAI ---|Support| MP_OPENAI_RESP
 
     P_GEMINI ---|Support| MP_GEMINI
 
     P_CLAUDE ---|Support| MP_CLAUDE_C
     P_CLAUDE ---|Support| MP_CLAUDE_K
     P_CLAUDE ---|Support| MP_GEMINI
     P_CLAUDE ---|Support| MP_OPENAI
     P_CLAUDE ---|Support| MP_QWEN
     P_CLAUDE ---|Support| MP_OPENAI_RESP
 
     style P_OPENAI fill:#f9f,stroke:#333,stroke-width:2px
     style P_GEMINI fill:#ccf,stroke:#333,stroke-width:2px
     style P_CLAUDE fill:#cfc,stroke:#333,stroke-width:2px

Loading

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🔧 Usage Instructions

🚀 Quick Start with install-and-run Script

The easiest way to get started with AIClient-2-API is to use our automated installation and startup scripts. We provide both Linux/macOS and Windows versions:

For Linux/macOS Users

# Make the script executable and run it
chmod +x install-and-run.sh
./install-and-run.sh

For Windows Users

# Run the batch file
install-and-run.bat

What the Script Does

The install-and-run script automatically:

1. Checks Node.js Installation: Verifies Node.js is installed and provides download link if missing
2. Dependency Management: Automatically installs npm dependencies if node_modules doesn't exist
3. File Validation: Ensures all required project files are present
4. Server Startup: Launches the API server on http://localhost:3000
5. Web UI Access: Provides direct access to the management console

Script Output Example

========================================
  AI Client 2 API Quick Install Script
========================================

[Check] Checking if Node.js is installed...
✅ Node.js is installed, version: v20.10.0
✅ Found package.json file
✅ node_modules directory already exists
✅ Project file check completed

========================================
  Starting AI Client 2 API Server...
========================================

🌐 Server will start on http://localhost:3000
📖 Visit http://localhost:3000 to view management interface
⏹️  Press Ctrl+C to stop server

💡 Tip: The script will automatically install dependencies and start the server. If you encounter any issues, the script provides clear error messages and suggested solutions.

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📋 Core Features

Web UI Management Console

A comprehensive web-based management interface offering:

📊 Dashboard: System overview, interactive routing examples, and client configuration guides

⚙️ Configuration: Real-time parameter modification for all providers (Gemini, OpenAI, Claude, Kiro, Qwen) with advanced settings and file upload support

🔗 Provider Pools: Monitor active connections, provider health statistics, and enable/disable providers

📁 Config Files: Centralized OAuth credential management with search, filtering, and file operations

📜 Logs: Real-time system and request logs with management controls

🔐 Login: Authentication required (default: admin123, modify via pwd file)

Access: http://localhost:3000 → Login → Sidebar navigation → Immediate effect changes

MCP Protocol Support

This project is fully compatible with Model Context Protocol (MCP), enabling seamless integration with MCP-supporting clients for powerful functional extensions.

Multimodal Input Capabilities

Supports various input types including images and documents, providing richer interactive experiences and more powerful application scenarios.

Latest Model Support

Seamlessly supports the following latest large models, simply configure the corresponding OpenAI or Claude compatible interface in config.json:

• Kimi K2 - Moonshot AI's latest flagship model
• GLM-4.5 - Zhipu AI's latest version
• Qwen Code - Alibaba Tongyi Qianwen code-specific model
• Gemini 3 - Google's latest preview model
• Claude Sonnet 4.5 - Anthropic's latest flagship model

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🔐 Authorization Configuration Guide

Gemini CLI OAuth Configuration

1. Obtain OAuth Credentials: Visit Google Cloud Console to create a project and enable Gemini API
2. First Authorization: After using Gemini service, the command line will print Google authorization page, copy the page to browser for authorization, then return to command line
3. Credential Storage: After successful authorization, oauth_creds.json file will be automatically generated and saved to ~/.gemini directory
4. Project Configuration: Need to provide a valid Google Cloud project ID, can be specified via startup parameter --project-id

Qwen Code OAuth Configuration

1. First Authorization: After starting the service, the system will automatically open the authorization page in the browser
2. Credential Storage: After successful authorization, oauth_creds.json file will be automatically generated and saved to ~/.qwen directory
3. Recommended Parameters: Use official default parameters for best results

   {
     "temperature": 0,
     "top_p": 1
   }

Kiro API Configuration

1. Environment Preparation: Download and install Kiro client
2. Complete Authorization: Log in to your account in the client to generate kiro-auth-token.json credential file
3. Best Practice: Recommended to use with Claude Code for optimal experience
4. Important Notice: Kiro service usage policy has been updated, please visit the official website for the latest usage restrictions and terms

Warp API Configuration

1. Access Warp Website: Visit Warp AI website and sign in to your account
2. Open Browser Console: After successful login, press F12 or Ctrl+Shift+I (Windows/Linux) / Cmd+Option+I (Mac) to open Developer Tools
3. Extract Refresh Token: In the Console tab, paste and execute the following code:

   (async () => {
     const request = indexedDB.open("firebaseLocalStorageDb");
   
     request.onsuccess = function (event) {
       const db = event.target.result;
       const tx = db.transaction("firebaseLocalStorage", "readonly");
       const store = tx.objectStore("firebaseLocalStorage");
   
       const getAllReq = store.getAll();
   
       getAllReq.onsuccess = function () {
         const results = getAllReq.result;
         const firstValue = results[0]?.value;
         
         console.log("Your account data:");
         console.log(JSON.stringify(firstValue, null, 2));
         
         const valueString = JSON.stringify(firstValue, null, 2);
         navigator.clipboard.writeText(valueString).then(() => {
           alert("Account data copied to clipboard!");
         });
       };
     };
   })();

4. Extract Refresh Token: From the copied JSON data, find the stsTokenManager.refreshToken field
5. Configure in config.json:
   • Set MODEL_PROVIDER to warp
   • Copy the refresh token value to WARP_REFRESH_TOKEN field in config.json
   • Example:

     {
       "MODEL_PROVIDER": "warp",
       "WARP_REFRESH_TOKEN": "AMf-vBxSRmdhveGGBYM69p05kDhIn1i7wscALEmC9fYdRpHzjER9dL7kk...",
       "WARP_REFRESH_URL": "https://app.warp.dev/proxy/token?key=AIzaSyBdy3O3S9hrdayLJxJ7mriBR4qgUaUygAs"
     }

6. Important Notes:
   • The system automatically refreshes JWT tokens using the refresh token
   • Keep your refresh token secure and never share it publicly
   • If refresh token expires, repeat steps 1-5 to get a new one

OpenAI Responses API

• Application Scenario: Suitable for scenarios requiring structured dialogue using OpenAI Responses API, such as Codex
• Configuration Method:
  • Method 1: Set MODEL_PROVIDER to openaiResponses-custom in config.json
  • Method 2: Use startup parameter --model-provider openaiResponses-custom
  • Method 3: Use path routing /openaiResponses-custom
• Required Parameters: Provide valid API key and base URL

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🔄 Model Provider Switching

This project provides two flexible model switching methods to meet different usage scenario requirements.

Achieve instant switching by specifying provider identifier in API request path:

Route Path	Description	Use Case
/claude-custom	Use Claude API from config file	Official Claude API calls
/claude-kiro-oauth	Access Claude via Kiro OAuth	Free use of Claude Sonnet 4.5
/openai-custom	Use OpenAI provider to handle requests	Standard OpenAI API calls
/gemini-cli-oauth	Access via Gemini CLI OAuth	Break through Gemini free limits
/openai-qwen-oauth	Access via Qwen OAuth	Use Qwen Code Plus
/openaiResponses-custom	OpenAI Responses API	Structured dialogue scenarios

Usage Examples:

# Configure in programming agents like Cline, Kilo
API_ENDPOINT=http://localhost:3000/claude-kiro-oauth

# Direct API call
curl http://localhost:3000/gemini-cli-oauth/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"gemini-2.0-flash-exp","messages":[...]}'

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📁 Authorization File Storage Paths

Default storage locations for authorization credential files of each service:

Service	Default Path	Description
Gemini	~/.gemini/oauth_creds.json	OAuth authentication credentials
Kiro	~/.aws/sso/cache/kiro-auth-token.json	Kiro authentication token
Qwen	~/.qwen/oauth_creds.json	Qwen OAuth credentials

Note: ~ represents the user home directory (Windows: C:\Users\username, Linux/macOS: /home/username or /Users/username)

Custom Path: Can specify custom storage location via relevant parameters in configuration file or environment variables

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🚀 Project Startup Parameters

This project supports rich command-line parameter configuration, allowing flexible adjustment of service behavior as needed. The following is a detailed explanation of all startup parameters, displayed in functional groups:

🔧 Server Configuration Parameters

Parameter	Type	Default Value	Description
--host	string	localhost	Server listening address
--port	number	3000	Server listening port
--api-key	string	123456	API key for authentication

🤖 Model Provider Configuration Parameters

Parameter	Type	Default Value	Description
--model-provider	string	gemini-cli-oauth	AI model provider, optional values: openai-custom, claude-custom, gemini-cli-oauth, claude-kiro-oauth, openai-qwen-oauth, openaiResponses-custom

🧠 OpenAI Compatible Provider Parameters

Parameter	Type	Default Value	Description
--openai-api-key	string	null	OpenAI API key (required when model-provider is openai-custom)
--openai-base-url	string	null	OpenAI API base URL (required when model-provider is openai-custom)

🖥️ Claude Compatible Provider Parameters

Parameter	Type	Default Value	Description
--claude-api-key	string	null	Claude API key (required when model-provider is claude-custom)
--claude-base-url	string	null	Claude API base URL (required when model-provider is claude-custom)

🔐 Gemini OAuth Authentication Parameters

Parameter	Type	Default Value	Description
--gemini-oauth-creds-base64	string	null	Base64 string of Gemini OAuth credentials (optional when model-provider is gemini-cli-oauth, choose one with --gemini-oauth-creds-file)
--gemini-oauth-creds-file	string	null	Gemini OAuth credentials JSON file path (optional when model-provider is gemini-cli-oauth, choose one with --gemini-oauth-creds-base64)
--project-id	string	null	Google Cloud project ID (required when model-provider is gemini-cli-oauth)

🎮 Kiro OAuth Authentication Parameters

Parameter	Type	Default Value	Description
--kiro-oauth-creds-base64	string	null	Base64 string of Kiro OAuth credentials (optional when model-provider is claude-kiro-oauth, choose one with --kiro-oauth-creds-file)
--kiro-oauth-creds-file	string	null	Kiro OAuth credentials JSON file path (optional when model-provider is claude-kiro-oauth, choose one with --kiro-oauth-creds-base64)

🐼 Qwen OAuth Authentication Parameters

Parameter	Type	Default Value	Description
--qwen-oauth-creds-file	string	null	Qwen OAuth credentials JSON file path (required when model-provider is openai-qwen-oauth)

🔄 OpenAI Responses API Parameters

Parameter	Type	Default Value	Description
--model-provider	string	openaiResponses-custom	Model provider, set to openaiResponses-custom when using OpenAI Responses API
--openai-api-key	string	null	OpenAI API key (required when model-provider is openaiResponses-custom)
--openai-base-url	string	null	OpenAI API base URL (required when model-provider is openaiResponses-custom)

📝 System Prompt Configuration Parameters

Parameter	Type	Default Value	Description
--system-prompt-file	string	input_system_prompt.txt	System prompt file path
--system-prompt-mode	string	overwrite	System prompt mode, optional values: overwrite (override), append (append)

📊 Log Configuration Parameters

Parameter	Type	Default Value	Description
--log-prompts	string	none	Prompt log mode, optional values: console (console), file (file), none (none)
--prompt-log-base-name	string	prompt_log	Prompt log file base name

🔄 Retry Mechanism Parameters

Parameter	Type	Default Value	Description
--request-max-retries	number	3	Maximum number of automatic retries when API requests fail
--request-base-delay	number	1000	Base delay time (milliseconds) between automatic retries, delay increases after each retry

⏰ Scheduled Task Parameters

Parameter	Type	Default Value	Description
--cron-near-minutes	number	15	Interval time (minutes) for OAuth token refresh task schedule
--cron-refresh-token	boolean	true	Whether to enable automatic OAuth token refresh task

🎯 Account Pool Configuration Parameters

Parameter	Type	Default Value	Description
--provider-pools-file	string	null	Provider account pool configuration file path

Usage Examples

# Basic usage
node src/api-server.js

# Specify port and API key
node src/api-server.js --port 8080 --api-key my-secret-key

# Use OpenAI provider
node src/api-server.js --model-provider openai-custom --openai-api-key sk-xxx --openai-base-url https://api.openai.com/v1

# Use Claude provider
node src/api-server.js --model-provider claude-custom --claude-api-key sk-ant-xxx --claude-base-url https://api.anthropic.com

# Use OpenAI Responses API provider
node src/api-server.js --model-provider openaiResponses-custom --openai-api-key sk-xxx --openai-base-url https://api.openai.com/v1

# Use Gemini provider (Base64 credentials)
node src/api-server.js --model-provider gemini-cli-oauth --gemini-oauth-creds-base64 eyJ0eXBlIjoi... --project-id your-project-id

# Use Gemini provider (credentials file)
node src/api-server.js --model-provider gemini-cli-oauth --gemini-oauth-creds-file /path/to/credentials.json --project-id your-project-id

# Configure system prompt
node src/api-server.js --system-prompt-file custom-prompt.txt --system-prompt-mode append

# Configure logging
node src/api-server.js --log-prompts console
node src/api-server.js --log-prompts file --prompt-log-base-name my-logs

# Complete example
node src/api-server.js \
  --host 0.0.0.0 \
  --port 3000 \
  --api-key my-secret-key \
  --model-provider gemini-cli-oauth \
  --project-id my-gcp-project \
  --gemini-oauth-creds-file ./credentials.json \
  --system-prompt-file ./custom-system-prompt.txt \
  --system-prompt-mode overwrite \
  --log-prompts file \
  --prompt-log-base-name api-logs

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📄 Open Source License

This project operates under the GNU General Public License v3 (GPLv3). For complete details, please refer to the LICENSE file located in the root directory.

🙏 Acknowledgements

The development of this project was significantly inspired by the official Google Gemini CLI and incorporated some code implementations from Cline 3.18.0's gemini-cli.ts. We extend our sincere gratitude to the official Google team and the Cline development team for their exceptional work!

🌟 Star History

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⚠️ Disclaimer

Usage Risk Warning

This project (AIClient-2-API) is for learning and research purposes only. Users assume all risks when using this project. The author is not responsible for any direct, indirect, or consequential losses resulting from the use of this project.

Third-Party Service Responsibility Statement

This project is an API proxy tool and does not provide any AI model services. All AI model services are provided by their respective third-party providers (such as Google, OpenAI, Anthropic, etc.). Users should comply with the terms of service and policies of each third-party service when accessing them through this project. The author is not responsible for the availability, quality, security, or legality of third-party services.

Data Privacy Statement

This project runs locally and does not collect or upload any user data. However, users should protect their API keys and other sensitive information when using this project. It is recommended that users regularly check and update their API keys and avoid using this project in insecure network environments.

Legal Compliance Reminder

Users should comply with the laws and regulations of their country/region when using this project. It is strictly prohibited to use this project for any illegal purposes. Any consequences resulting from users' violation of laws and regulations shall be borne by the users themselves.