Anannas: a single API gateway for free access to 500+ AI models

Anannas AI is a unified API gateway. It gives users access to over 500 large-scale language models through a single API. These models come from different providers like OpenAI, Anthropic, Mistral, Gemini and DeepSeek.The platform provides fail-safe routing capabilities. It controls costs and gives instant usage insights. Users can see spend, token usage and API request data on the dashboard.Anannas AI supports integration with Langfuse for two-tier observability. It tracks gateway metrics while Langfuse captures application tracing and debugging processes. The platform has sub-millisecond overhead for production environments.Anannas AI was developed by a small company with 2 to 10 employees. The focus is on IT custom software development. It helps developers avoid using multiple SDKs and APIs. the platform was recently launched and has processed more than 2 billion tokens. anannas AI participates in events, such as Nouscon, to support open source research.

Function List

• Single API access: connect to more than 500 LLM models via a single API, including models from providers such as OpenAI, Anthropic, Mistral, Gemini, DeepSeek, and Nebius.
• Fail-safe routing: Automatically routes requests to the best model or provider, ensuring uninterrupted service.
• Cost Control: Monitor and limit spending to help users manage their budgets and avoid unexpected costs.
• Instant usage insights: dashboards showing spend, token usage, API requests and recent activity, with data by day and month.
• Two-tier observability: integrated Langfuse, tracking gateway metrics and application tracing to provide a full view from model selection to production execution.
• Sub-millisecond overhead: low latency processing ensures fast response for real-time applications.
• Integration support: Integrate with tools such as Pipecat and Langfuse to extend functionality.
• Production environment-ready: designed to scale and support high-traffic requests, such as the 2 billion tokens recently processed.

Using Help

Anannas AI does not require a complicated installation process. It is a cloud-based platform that users can sign up for and use via a webpage. First, visit https://anannas.ai/. Click on the "Sign Up" button and enter your email and password to create an account. After verifying the email, login to the dashboard. The dashboard is the main interface where your usage data is displayed.

To start using the Single API Access feature, first obtain an API key. On the dashboard, find the "API Keys" section. Click on "Generate New Key" and a key will be generated. Copy this key and use it in your application code.Anannas AI is compatible with OpenAI's SDK, so you can call it as if you were using the OpenAI API. But it can route to other models.

For example, install the OpenAI library in Python: pip install openai. Then, import the library and set up the client: from openai import OpenAI. client = OpenAI(api_key="your Anannas API key ", base_url="https://api.anannas.ai/v1″). Now you can call the model. For example, complete the chat: response = client.chat.completions.create(model="gpt-4o", messages=[{"role". "user", "content": "Hello"}]). Here, the model can be any supported model, such as "claude-3-opus" or "gemini-pro".

Fail-safe routing is the featured function. Set up routing rules in the dashboard. Go to the "Routing" section and add rules. For example, select the preferred model and if it is not available, switch to the alternate model. The rules are based on cost, speed or availability. Once saved, the rules will be automatically applied by the API call. Test Routing: Enter a prompt on the playground page, select a model, and view the response and routing path.

Cost control features are set up in the "Billing" section. Add a budget limit, such as a monthly cap. The system monitors spending and sends alerts if the limit is approached. View detailed reports: Click on "Usage Insights" to see graphs showing token input/output, number of requests and cost. Data is updated in real-time to help optimize usage.

Instant usage insights on the dashboard home page. "Recent Activity" lists the latest API calls, including time, model and status. Click on an entry to see detailed logs such as input prompts and output text. This helps with debugging.

To integrate Langfuse, first register an account with Langfuse. Get Langfuse public and private keys. In Anannas dashboard, go to "Integrations" and select Langfuse. enter Langfuse key and enable integration. Now your invocations are sent to Langfuse traces. the Langfuse dashboard displays application traces, such as hint chains and errors. anannas traces gateway-level metrics, such as latency and routing decisions. The two-tier view is visible end-to-end from the model to the application.

Sub-millisecond overhead is automatic. No configuration is required and the platform optimizes the infrastructure. Ideal for high load scenarios such as the 2 billion tokens recently processed.

Integration with Pipecat for specific applications such as speech processing. Use Anannas as the LLM provider in the Pipecat code. Install the pipecat-anannas package: pip install pipecat-anannas. then, configure the Anannas client in the code.

Production environment use: securing API keys. Use environment variables to store keys. Monitor quotas and contact support for upgrade plans if traffic is high.Anannas supports free trials with paid tiers based on usage.

If you run into problems, go to the documentation page. The documentation link is at the top of the dashboard. There is an API reference, sample code, and FAQs. The support team responds via email or Discord.

Overall operation process: registration → generate API key → configure routing and integration → call API in code → monitor dashboard. The platform is simple to get started with and is suitable for developers to build AI applications without obsessing over multiple providers.

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application scenario

1. AI application development
   Developers build chatbots with Anannas switching models to test performance without changing code. Routing ensures that the best model is available, keeping costs under budget.
2. Production environment deployment
   Company runs large-scale AI services and handles high-traffic requests with Anannas. Integration with Langfuse debugs issues and insights help optimize spend.
3. model experiment
   The researcher tests different LLMs such as switching from OpenAI to Mistral. dashboards show comparative data and support fast iteration.
4. Integration of third-party tools
   Building Speech AI in conjunction with Pipecat.Anannas provides unified access to simplify multi-model support.
5. Cost optimization
   Startup teams manage AI expenses. Maintaining quality of service with budget alerts and routing to select cheap models.

QA

1. What is Anannas AI?
   It is an API gateway that gives users access to more than 500 AI models through a single interface.
2. How do I get an API key?
   Log into the dashboard, go to the API Keys section and generate a new key.
3. What models are supported?
   Includes models from providers such as OpenAI, Anthropic, Mistral, Gemini, DeepSeek, and others.
4. How do I set up routing?
   Add rules to the Routing section to select models based on cost or availability.
5. How does integrating Langfuse work?
   Enter the Langfuse key at Integrations to enable automatic tracking.
6. Is there a free plan?
   Yes, there is a trial, support for basic use, paid based on traffic.
7. How do I monitor usage?
   The dashboard displays spend, token and request data, updated in real time.
8. For which users?
   developers, researchers, and companies for AI integration and optimization.