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+# One Endpoint, Many AI Clients: Turning ABP Workspaces into OpenAI-Compatible Models
+
+ABP's AI Management module already makes it easy to define and manage AI workspaces (provider, model, API key/base URL, system prompt, permissions, MCP tools, RAG settings, and more).
+With **ABP v10.2**, there is a major addition: you can now expose those workspaces through **OpenAI-compatible endpoints** under `/v1`.
+
+That changes the integration story in a practical way. Instead of wiring every external tool directly to a provider, you can point those tools to ABP and keep runtime decisions centralized in one place.
+
+In this post, we will walk through a practical setup with **AnythingLLM** and show why this pattern is useful in real projects.
+
+## Why This Is a Big Deal
+
+Many teams end up with AI configuration spread across multiple clients and services. Updating providers, rotating keys, or changing model behavior can become operationally messy.
+
+With ABP in front of your AI traffic:
+
+- Clients keep speaking the familiar OpenAI contract.
+- ABP resolves the requested `model` to a workspace.
+- The workspace decides which provider/model settings are actually used.
+
+This gives you a clean split: standardized client integration outside, governed AI configuration inside.
+
+## Key Concept: Workspace = Model
+
+OpenAI-compatible clients send a `model` value.
+In ABP AI Management, that `model` maps to a **workspace name**.
+
+**For example:**
+
+- Workspace name: `SupportAgent`
+- Client request model: `SupportAgent`
+
+When the client calls `/v1/chat/completions` with `"model": "SupportAgent"`, ABP routes the request to that workspace and applies that workspace's provider and model configuration.
+
+This is the main mental model to keep in mind while integrating any OpenAI-compatible tool with ABP.
+
+## Endpoints Exposed by ABP v10.2
+
+The AI Management module exposes OpenAI-compatible REST endpoints at `/v1`.
+
+| Endpoint                     | Method | Description                                    |
+| ---------------------------- | ------ | ---------------------------------------------- |
+| `/v1/chat/completions`       | POST   | Chat completions (streaming and non-streaming) |
+| `/v1/completions`            | POST   | Legacy text completions                        |
+| `/v1/models`                 | GET    | List available models (workspaces)             |
+| `/v1/models/{modelId}`       | GET    | Get a single model (workspace)                 |
+| `/v1/embeddings`             | POST   | Generate embeddings                            |
+| `/v1/files`                  | GET    | List files                                     |
+| `/v1/files`                  | POST   | Upload a file                                  |
+| `/v1/files/{fileId}`         | GET    | Get file metadata                              |
+| `/v1/files/{fileId}`         | DELETE | Delete a file                                  |
+| `/v1/files/{fileId}/content` | GET    | Download file content                          |
+
+All endpoints require `Authorization: Bearer <token>`.
+
+## Quick Setup with AnythingLLM
+
+Before configuration, ensure:
+
+1. AI Management is installed and running in your ABP app.
+2. At least one workspace is created and **active**.
+3. You have a valid bearer token for your ABP application.
+
+### 1) Get an access token
+
+Use any valid token accepted by your app. In a demo-style setup, token retrieval can look like this:
+
+```bash
+curl -X POST http://localhost:44337/connect/token \
+  -d "grant_type=password&username=admin&password=1q2w3E*&client_id=DemoApp_API&client_secret=1q2w3e*&scope=DemoApp"
+```
+
+Use the returned `access_token` as the API key value in your OpenAI-compatible client.
+
+### 2) Configure AnythingLLM as Generic OpenAI
+
+In **AnythingLLM -> Settings -> LLM Preference**, select **Generic OpenAI** and set:
+
+| Setting              | Value                       |
+| -------------------- | --------------------------- |
+| Base URL             | `http://localhost:44337/v1` |
+| API Key              | `<access_token>`            |
+| Chat Model Selection | Select an active workspace  |
+
+In most OpenAI-compatible UIs, the app adds `Bearer` automatically, so the API key field should contain only the raw token string.
+
+### 3) Optional: configure embeddings
+
+If you want RAG flows through ABP, go to **Settings -> Embedding Preference** and use the same Base URL/API key values.
+Then select a workspace that has embedder settings configured.
+
+## Validate the Flow
+
+### List models (workspaces)
+
+```bash
+curl http://localhost:44337/v1/models \
+  -H "Authorization: Bearer <your-token>"
+```
+
+### Chat completion
+
+```bash
+curl -X POST http://localhost:44337/v1/chat/completions \
+  -H "Authorization: Bearer <your-token>" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "MyWorkspace",
+    "messages": [
+      { "role": "user", "content": "Hello from ABP OpenAI-compatible endpoint!" }
+    ]
+  }'
+```
+
+### Optional SDK check (Python)
+
+```python
+from openai import OpenAI
+
+client = OpenAI(
+    base_url="http://localhost:44337/v1",
+    api_key="<your-token>"
+)
+
+response = client.chat.completions.create(
+    model="MyWorkspace",
+    messages=[{"role": "user", "content": "Hello!"}]
+)
+
+print(response.choices[0].message.content)
+```
+
+## Where This Fits in Real Projects
+
+This approach is a strong fit when you want to:
+
+- Keep ABP as the central control plane for AI workspaces.
+- Let client tools integrate through a standard OpenAI contract.
+- Switch providers or model settings without rewriting client-side integration.
+
+If your team uses multiple AI clients, this pattern keeps integration simple while preserving control where it matters.
+
+## See It in Action: AnythingLLM + ABP
+
+The demo below shows the full flow: connecting an OpenAI-compatible client to ABP, selecting a workspace-backed model, and sending a successful chat request through `/v1`.
+
+![ABP AI Management OpenAI-compatible endpoints demo](./openai-compatible-endpoints-demo.gif)
+
+## Learn More
+
+- [ABP AI Management Documentation](https://abp.io/docs/10.2/modules/ai-management)