Update Ollama Setup

Ollama-Setup.md

@@ -17,10 +17,6 @@ Set up local AI models with Ollama for offline inference. Ollama runs on your ho
   - [Step 1: Install Ollama (Clean Install)](#step-1-install-ollama-clean-install)
   - [Step 2: Pull Models](#step-2-pull-models)
   - [Step 3: Add Model to GT AI OS](#step-3-add-model-to-gt-ai-os)
-- [macOS (Apple Silicon M1+)](#macos-apple-silicon-m1)
-  - [Step 1: Install Ollama](#step-1-install-ollama-2)
-  - [Step 2: Pull a Model](#step-2-pull-a-model)
-  - [Step 3: Add Model to GT AI OS](#step-3-add-model-to-gt-ai-os-1)
 - [Verify Ollama is Working](#verify-ollama-is-working)
 
 ---
@@ -39,7 +35,6 @@ Set up local AI models with Ollama for offline inference. Ollama runs on your ho
 |----------|-------------------|
 | Ubuntu Linux 24.04 (x86_64) | `http://ollama-host:11434/v1/chat/completions` |
 | NVIDIA DGX OS 7 | `http://ollama-host:11434/v1/chat/completions` |
-| macOS (Apple Silicon M1+) | `http://host.docker.internal:11434/v1/chat/completions` |
 
 ---
 
@@ -352,65 +347,13 @@ ollama pull gemma3:27b
 
 ---
 
-## macOS (Apple Silicon M1+)
-
-### Step 1: Install Ollama
-
-Download from https://ollama.com/download or run:
-
-```bash
-curl -fsSL https://ollama.com/install.sh | sh
-```
-
-### Step 2: Pull a Model
-
-```bash
-ollama pull llama3.1:8b
-```
-
-### Step 3: Add Model to GT AI OS
-
-1. Open Control Panel: http://localhost:3001
-2. Log in with `gtadmin@test.com` / `Test@123`
-3. Go to **Models** → **Add Model**
-4. Fill in:
-   - **Model ID:** `llama3.1:8b` (must match exactly what you pulled)
-   - **Provider:** `Local Ollama (macOS Apple Silicon)`
-   - **Endpoint URL:** `http://host.docker.internal:11434/v1/chat/completions`
-   - **Model Type:** `LLM` (Language Model - this is the most common type for AI agents)
-   - **Context Length:** Based on your Mac's unified memory (see table below)
-   - **Max Tokens:** `4096`
-5. Click **Save**
-6. Go to **Tenant Access** → **Assign Model to Tenant**
-7. Select your model, tenant, and rate limit
-
-**Context Length by Mac Memory:**
-
-| Unified Memory | Context Length |
-|----------------|----------------|
-| 8GB | `8192` |
-| 16GB | `32768` |
-| 32GB | `65536` |
-| 64GB+ | `131072` |
-
-> ⚠️ **Critical: Model ID Must Match Exactly**
->
-> The **Model ID** in GT AI OS must match the Ollama model name **exactly** - character for character. Run `ollama list` to see the exact model names. Common mistakes:
-> - Extra spaces before or after the ID
-> - Missing version tags (e.g., `qwen3-coder` vs `qwen3-coder:30b`)
-> - Typos in the model name
->
-> **Example:** If `ollama list` shows `llama3.1:8b`, use `llama3.1:8b` exactly as shown.
-
----
-
 ## Verify Ollama is Working
 
 After completing the setup for your platform, follow these verification steps to ensure Ollama is properly configured and accessible by GT AI OS.
 
 ### Step 1: Verify Ollama Service is Running
 
-**All Platforms (Ubuntu, DGX, macOS):**
+**All Platforms (Ubuntu and DGX):**
 
 Run these commands on your host machine (not inside Docker) to confirm Ollama is running and responding:
 
@@ -426,7 +369,7 @@ This tests the Ollama API. You should see a JSON response with version informati
 
 ### Step 2: Verify GPU Acceleration
 
-**Ubuntu x86 and DGX Only** (skip this step on macOS):
+**Ubuntu x86 and DGX Only**:
 
 While a model is running, check that your NVIDIA GPU is being utilized:
 
@@ -440,17 +383,11 @@ nvidia-smi
 
 You should see `ollama` or `ollama_llama_server` processes using GPU memory. If you only see CPU usage, revisit Step 1 (NVIDIA driver installation) in your platform's setup.
 
-**macOS:** Apple Silicon Macs automatically use the GPU via Metal. No verification needed.
 
 ### Step 3: Verify GT AI OS Can Reach Ollama
 
 This step confirms that the Docker containers running GT AI OS can communicate with Ollama on your host machine.
 
-**macOS (Apple Silicon M1+):**
-```bash
-docker exec gentwo-resource-cluster curl http://host.docker.internal:11434/api/version
-```
-
 **Ubuntu x86 and DGX:**
 ```bash
 docker exec gentwo-resource-cluster curl http://ollama-host:11434/api/version