Add AI section with FedLLM service documentation

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content/en/users/ai/_index.md

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+---
+title: Artificial Intelligence
+linkTitle: Artificial Intelligence 
+type: docs
+weight: 80
+description: Artificial Intelligence (AI) services in the EGI Infrastructure 
+---
+
+## Overview
+
+AI is becoming an important component in supporting data-driven science
+across disciplines. In this context, EGI is evolving its service offering
+towards an **AI-ready compute–data continuum**, where computing, data, and AI
+capabilities are integrated and accessible across federated providers.
+
+The following AI service is currently available:
+
+- [FedLLM](./fedllm/) providing access to LLM inference capabilities via a web interface and an OpenAI-compatible API
+
+Its dedicated section offers a detailed description of both access methods.

content/en/users/ai/fedllm/_index.md

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+---
+title: FedLLM
+linkTitle: FedLLM
+type: docs
+weight: 10
+aliases:
+  - /users/fedllm
+description: Federated LLM inference service
+---
+
+## Overview
+
+FedLLM is an EGI service that provides access to Large Language Models (LLMs) through:
+
+- A web-based chat interface: [chat.ai.egi.eu](https://chat.ai.egi.eu/)
+- An OpenAI-compatible API: [llm.ai.egi.eu](https://llm.ai.egi.eu/)
+
+The service enables users to generate and analyse text,
+run retrieval-augmented generation (RAG) workflows,
+and integrate AI capabilities into scientific applications.
+
+## Access and Authentication
+
+Access is managed through EGI Check-in:
+
+1. Create an [EGI account](../../aai/check-in/signup)
+2. Enrol in a supported Virtual Organisation (VO) such as
+[vo.fedllm.egi.eu](https://aai-demo.egi.eu/auth/realms/id/account/#/enroll?groupPath=/vo.fedllm.egi.eu)
+3. Access the service via [chat.ai.egi.eu](https://chat.ai.egi.eu/)
+4. To use the API, generate an API key from the web interface (Account settings → Create a new secret key)
+5. Use the API key to access the [llm.ai.egi.eu](https://llm.ai.egi.eu/) API endpoints
+
+## Using AI Models
+
+### Web Interface
+
+After logging into the web interface:
+
+- Select a model from the dropdown menu
+- Enter your prompt in the input field
+- Submit the request to receive a response
+
+![FedLLM Web Interface](./fedllm_ui.png)
+
+### API Usage
+
+You can retrieve a list of available models:
+
+```shell
+curl https://llm.ai.egi.eu/v1/models \
+  -H "Authorization: Bearer $API_KEY" | jq .
+```
+
+You can then send a request using one of the available models:
+
+ ```shell
+curl https://llm.ai.egi.eu/v1/chat/completions \
+  -H "Authorization: Bearer $API_KEY" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "gpt-oss-120b",
+    "messages": [
+      { "role": "user", "content": "Hello!" }
+    ]
+  }' | jq .
+```
+
+For detailed API specifications, refer to the
+[API reference](https://developers.openai.com/api/reference/overview).
+Note that not all endpoints are supported.
+
+For client access and development, refer to the [LiteLLM SDK](https://docs.litellm.ai/docs/#litellm-python-sdk)
+or the [OpenAI Client Libraries](https://developers.openai.com/api/docs/libraries/).
+
+<!--
+## Service options
+
+### LLMs for Researchers
+
+- Shared service access
+- Standard quotas (requests per minute, tokens per minute)
+
+### LLMs for Communities
+
+- Dedicated deployments
+- Custom models and quotas
+- Integration with community services
+
+### On-premises LLMs
+
+- Deployment on community-owned infrastructure
+- Full control over models and data
+-->
+## High-level Service architecture
+
+The FedLLM service is composed of the following components:
+
+- **Web interface** (Open WebUI): user interaction and API key management
+- **API gateway** (LiteLLM): OpenAI-compatible interface and routing
+- **Inference backend** (e.g. vLLM): execution of LLM workloads on GPU resources
+
+User data is processed only for service delivery and is not retained or reused for training.
+
+## Usage considerations
+
+- Available models may vary depending on your VO
+- Usage may be subject to quotas and rate limits