Add docker compose section in readme.

idea.md

@@ -1,65 +0,0 @@
-
-**Video Title:**
-Run LLMs Directly in VS Code with Continue (Alternatives to Cline!)
-
-**Video Structure & Script Ideas:**
-
-*   **You:** "Hey everyone, I'm going to introduce 'Continue,' a VS Code plugin that solves a common problem with other popular solutions like Cline, and lets you run LLMs locally, directly within your coding environment."
-
-*   **You:** "Lots of people are using plugins like Cline to bring LLMs into VS Code. It’s a great concept!  However, Cline has a significant issue: the context window.  Cline sends your prompts and code to a remote server, and the size of that context window – the amount of text the LLM can consider – can be *huge*. "
-
-*   **You:** "This means running Cline often requires a powerful GPU. People with older gpu like me, find themselves forced to use smaller, less capable LLMs, like the 0.5B model, just to get it to work."
-
-*   **You:** "That’s where 'Continue' comes in. 'Continue' tackles this problem head-on by using Ollama to run the LLM *locally* on your machine."
-*   **You:** "This means you can leverage powerful LLMs without needing a cloud connection or a high-end GPU." (Emphasize the key benefit: local, powerful LLMs.)
-*   **You:**  "Critically, Continue's interface lives *inside* VS Code.  No more switching back and forth between your editor and a browser window. It's a seamless, integrated experience."
-*   **Briefly explain Ollama's role:**  "Ollama makes running LLMs locally incredibly easy.  You don't need to be an AI expert to get started."
-
-**4. Demo (2:30 - 5:00):  Show, Don't Just Tell!**
-
-*   **(Visual: Screen recording of you using "Continue" in VS Code.)**
-*   **You (Narrating):**
-    *   "Let's walk through a quick example.  I have this file open..." (Show the file in VS Code.)
-    *   "To use Continue, I just right-click, and select 'Continue Chat'." (Show the context menu.)
-    *   “You can type in a prompt, like 'Explain this code snippet' and press enter.” (Type a simple prompt and wait for the response.)
-    *   **Show the response appearing directly within VS Code.**
-    *   **Show how you can easily select a block of code and send it to the LLM for analysis or explanation.** "The real power here is the ability to easily select code and send it to the LLM."
-    *   **Show how easy it is to experiment with different LLMs through Ollama.** (If time allows - demonstrates flexibility).
-    *   **Keep it concise and focused on the core benefits (seamless integration, local LLMs).**
-
-**5.  Wrap Up & Call to Action (5:00 - 5:30)**
-
-*   **(Visual:  End screen with links and social media handles.)**
-*   **You:** "So, if you're looking for a way to bring the power of LLMs into your VS Code workflow without the limitations of Cline, 'Continue' is definitely worth checking out.”
-*   **You:** "I'm going to put a link to the plugin in the description below.  Go give it a try and let me know what you think in the comments!"
-*   **Encourage engagement:** "If you found this video helpful, please like and subscribe for more developer tools and tutorials!"
-
-**Production Tips:**
-
-*   **Screen Recording Software:** OBS Studio (free), Camtasia (paid).
-*   **Microphone:**  A decent USB microphone will significantly improve audio quality.
-*   **Lighting:** Good lighting makes you look more professional.
-*   **Edit!:** Cut out any unnecessary pauses or mistakes. Tight editing makes a big difference.
-*   **Music:** Background music can add atmosphere, but keep it subtle and non-distracting.  Use royalty-free music.
-
-
-
-**IMPORTANT CONSIDERATIONS (Read This!)**
-
-*   **Target Audience:** This video is for developers who are already familiar with VS Code and potentially have some interest in using LLMs. Don’t assume *everyone* knows what an LLM is.
-*   **SEO (Search Engine Optimization):**
-    *   **Keywords:** "VS Code", "LLM", "AI", "Local LLM", "Continue", "Cline", "Ollama" - use these naturally throughout your video title, description, and tags.
-    *   **Thumbnail:** Create a visually appealing thumbnail that clearly communicates the video's topic.  Include the "Continue" plugin icon and some text (e.g., "Local LLMs in VS Code").
-    *   **Description:** Write a detailed description that includes keywords and a summary of the video's content.
-*   **Engagement is Key:** Respond to comments and questions. Building a community around your channel is crucial for growth.
-*   **Call to Action Placement:** Put the call to action (subscribe, like) in multiple places: at the beginning, middle, and end of the video.
-*   **Monetization:**  Consider how you might monetize your channel (ads, sponsorships) once you have a decent amount of views.
-
-
-
-
-To help me refine this further, can you tell me:
-
-*   What level of developer are you targeting? (Beginner, Intermediate, Advanced?)
-*   Do you want to include a section on how to install Ollama? (It adds complexity, but might be helpful.)
-*   Are there any specific features of "Continue" that you want to highlight?

ollama37/README.md

@@ -42,6 +42,63 @@ docker run --runtime=nvidia --gpus all -p 11434:11434 dogkeeper886/ollama37
 
 This command will start Ollama and expose it on port `11434`, allowing you to interact with the service.
 
+## Ollama37 Docker Compose
+
+This `docker-compose.yml` file sets up an Ollama 3.7 container for a more streamlined and persistent environment. It utilizes volumes to persist data and ensures the container automatically restarts if it fails.
+
+### Prerequisites
+
+*   Docker
+*   Docker Compose
+
+### Usage
+
+1.  **Save the `docker-compose.yml` file:** Save the content provided below into a file named `docker-compose.yml` in a convenient directory.
+
+2.  **Run the container:** Open a terminal in the directory where you saved the file and run the following command:
+
+    ```bash
+    docker-compose up -d
+    ```
+
+    This command downloads the `dogkeeper886/ollama37` image (if not already present) and starts the Ollama container in detached mode.
+
+    ```yml
+    version: '3.8'
+
+    services:
+      ollama:
+        image: dogkeeper886/ollama37
+        container_name: ollama37
+        ports:
+          - "11434:11434"
+        volumes:
+          - ./.ollama:/root/.ollama  # Persist Ollama data
+        restart: unless-stopped  # Automatically restart the container
+        runtime: nvidia  # Utilize NVIDIA GPU runtime
+    ```
+
+    **Explanation of key `docker-compose.yml` directives:**
+
+    *   `version: '3.8'`: Specifies the Docker Compose file version.
+    *   `services.ollama.image: dogkeeper886/ollama37`: Defines the Docker image to use.
+    *   `ports: - "11434:11434"`: Maps port 11434 on the host machine to port 11434 inside the container, making Ollama accessible.
+    *   `volumes: - ./.ollama:/root/.ollama`:  **Important:**  This mounts a directory named `.ollama` in the same directory as the `docker-compose.yml` file to the `/root/.ollama` directory inside the container.  This ensures that downloaded models and Ollama configuration data are persisted even if the container is stopped or removed.  Create a `.ollama` directory if it does not already exist.
+    *   `restart: unless-stopped`:  This ensures the container automatically restarts if it crashes or is stopped (but not if you explicitly stop it with `docker-compose down`).
+    *   `runtime: nvidia`: Explicitly instructs Docker to use the NVIDIA runtime, ensuring GPU acceleration.
+
+3.  **Accessing Ollama:** After running the container, you can interact with Ollama using its API.  Refer to the Ollama documentation for usage details.
+
+### Stopping the Container
+
+To stop the container, run:
+
+```bash
+docker-compose down
+```
+
+This will stop and remove the container, but the data stored in the `.ollama` directory will be preserved.
+
 ## 📦 Version History
 
 ### v1.2.0 (2025-05-06)

ollama37/docker-compose.yml

@@ -7,7 +7,7 @@ services:
     ports:
       - "11434:11434"
     volumes:
-      - /home/jack/.ollama:/root/.ollama
+      - ./.ollama:/root/.ollama
     restart: unless-stopped
     runtime: nvidia
 #volumes: