Update providers/ollama.mdx

Co-Authored-By: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>

Author: Gerome-Elassaad

providers/ollama.mdx

@@ -1,79 +1,46 @@
 ---
 title: "Ollama"
-description: "Set up Ollama to run AI models locally with CodinIT for enhanced privacy, offline access, and complete control over your development."
+description: "Run AI models locally with Ollama for privacy and offline access."
 ---
 
-CodinIT supports running models locally using Ollama. This approach offers privacy, offline access, and potentially reduced costs. It requires some initial setup and a sufficiently powerful computer. Because of the present state of consumer hardware, it's not recommended to use Ollama with CodinIT as performance will likely be poor for average hardware configurations.
+Run models locally using Ollama for privacy, offline access, and control. Requires initial setup and sufficient hardware.
 
 **Website:** [https://ollama.com/](https://ollama.com/)
 
-### Setting up Ollama
+## Setup
 
-1.  **Download and Install Ollama:**
-    Obtain the Ollama installer for your operating system from the [Ollama website](https://ollama.com/) and follow their installation guide. Ensure Ollama is running. You can typically start it with:
+1. **Install Ollama:** Download from [ollama.com](https://ollama.com/) and install
+2. **Start Ollama:** Run `ollama serve` in terminal
+3. **Download a model:**
+   ```bash
+   ollama pull qwen2.5-coder:32b
+   ```
+4. **Configure context window:**
+   ```bash
+   ollama run qwen2.5-coder:32b
+   /set parameter num_ctx 32768
+   /save your_custom_model_name
+   ```
 
-    ```bash
-    ollama serve
-    ```
+## Configuration in CodinIT
 
-2.  **Download a Model:**
-    Ollama supports a wide variety of models. A list of available models can be found on the [Ollama model library](https://ollama.com/library). Some models recommended for coding tasks include:
+1. Click the settings icon (⚙️) in CodinIT
+2. Select "ollama" as the API Provider
+3. Enter your saved model name
+4. (Optional) Set base URL if not using default `http://localhost:11434`
 
-    -   `codellama:7b-code` (a good, smaller starting point)
-    -   `codellama:13b-code` (offers better quality, larger size)
-    -   `codellama:34b-code` (provides even higher quality, very large)
-    -   `qwen2.5-coder:32b`
-    -   `mistralai/Mistral-7B-Instruct-v0.1` (a solid general-purpose model)
-    -   `deepseek-coder:6.7b-base` (effective for coding)
-    -   `llama3:8b-instruct-q5_1` (suitable for general tasks)
+## Recommended Models
 
-    To download a model, open your terminal and execute:
+- `qwen2.5-coder:32b` - Excellent for coding
+- `codellama:34b-code` - High quality, large size
+- `deepseek-coder:6.7b-base` - Effective for coding
+- `llama3:8b-instruct-q5_1` - General tasks
 
-    ```bash
-    ollama pull <model_name>
-    ```
+See [Ollama model library](https://ollama.com/library) for full list.
 
-    For instance:
+## Notes
 
-    ```bash
-    ollama pull qwen2.5-coder:32b
-    ```
-
-3.  **Configure the Model's Context Window:**
-    By default, Ollama models often use a context window of 2048 tokens, which can be insufficient for many CodinIT requests. A minimum of 12,000 tokens is advisable for decent results, with 32,000 tokens being ideal. To adjust this, you'll modify the model's parameters and save it as a new version.
-
-    First, load the model (using `qwen2.5-coder:32b` as an example):
-
-    ```bash
-    ollama run qwen2.5-coder:32b
-    ```
-
-    Once the model is loaded within the Ollama interactive session, set the context size parameter:
-
-    ```
-    /set parameter num_ctx 32768
-    ```
-
-    Then, save this configured model with a new name:
-
-    ```
-    /save your_custom_model_name
-    ```
-
-    (Replace `your_custom_model_name` with a name of your choice.)
-
-4.  **Configure CodinIT:**
-    -   Open the CodinIT sidebar (usually indicated by the CodinIT icon).
-    -   Click the settings gear icon (⚙️).
-    -   Select "ollama" as the API Provider.
-    -   Enter the Model name you saved in the previous step (e.g., `your_custom_model_name`).
-    -   (Optional) Adjust the base URL if Ollama is running on a different machine or port. The default is `http://localhost:11434`.
-    -   (Optional) Configure the Model context size in CodinIT's Advanced settings. This helps CodinIT manage its context window effectively with your customized Ollama model.
-
-### Tips and Notes
-
--   **Resource Demands:** Running large language models locally can be demanding on system resources. Ensure your computer meets the requirements for your chosen model.
--   **Model Choice:** Experiment with various models to discover which best fits your specific tasks and preferences.
--   **Offline Capability:** After downloading a model, you can use CodinIT with that model even without an internet connection.
--   **Token Usage Tracking:** CodinIT tracks token usage for models accessed via Ollama, allowing you to monitor consumption.
--   **Ollama's Own Documentation:** For more detailed information, consult the official [Ollama documentation](https://ollama.com/docs).
+- **Context window:** Minimum 12,000 tokens recommended, 32,000 ideal
+- **Resource demands:** Large models require significant system resources
+- **Offline capability:** Works without internet after model download
+- **Performance:** May be slow on average hardware