Human edit and update

git commit -m "AI: Know when to use it"
```

**Explanation of the commit message:**

*   **Concise:** It's short and to the point, adhering to the common 5-word limit.
*   **Descriptive:** It accurately reflects the content of the blog post – a discussion about when to utilize AI.
*   **Action-oriented:**  Implies a need for thoughtful consideration.
'

.gitea/workflows/build_push.yml

@@ -1,42 +1,61 @@
 name: Build and Push Image
-on: [ push ]
+on:
+    push:
+        branches:
+            - master
 
 jobs:
-  build:
+    build:
-    name: Build and push image
+        name: Build and push image
-    runs-on: ubuntu-latest
+        runs-on: ubuntu-latest
-    container: catthehacker/ubuntu:act-latest
+        container: catthehacker/ubuntu:act-latest
-    if: gitea.ref == 'refs/heads/master'
+        if: gitea.ref == 'refs/heads/master'
 
-    steps:
+        steps:
-    - name: Checkout
+            - name: Checkout
-      uses: actions/checkout@v4
+              uses: actions/checkout@v4
 
-    - name: Create Kubeconfig
+            - name: Create Kubeconfig
-      run: |
+              run: |
-        mkdir $HOME/.kube
+                  mkdir $HOME/.kube
-        echo "${{ secrets.KUBEC_CONFIG_BUILDX }}" > $HOME/.kube/config        
+                  echo "${{ secrets.KUBEC_CONFIG_BUILDX }}" > $HOME/.kube/config
 
-    - name: Set up Docker Buildx
+            - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v3
+              uses: docker/setup-buildx-action@v3
-      with:
+              with:
-        driver: kubernetes
+                  driver: kubernetes
-        driver-opts: |
+                  driver-opts: |
-          namespace=gitea-runner
+                      namespace=gitea-runner
-          qemu.install=true          
+                      qemu.install=true
 
-    - name: Login to Docker Registry
+            - name: Login to Docker Registry
-      uses: docker/login-action@v3
+              uses: docker/login-action@v3
-      with:
+              with:
-        registry: git.aridgwayweb.com
+                  registry: git.aridgwayweb.com
-        username: armistace
+                  username: armistace
-        password: ${{ secrets.REG_PASSWORD }}
+                  password: ${{ secrets.REG_PASSWORD }}
 
-    - name: Build and push
+            - name: Build and push
-      uses: docker/build-push-action@v5
+              uses: docker/build-push-action@v5
-      with:
+              with:
-        context: .
+                  context: .
-        push: true
+                  push: true
-        platforms: linux/amd64,linux/arm64
+                  platforms: linux/amd64,linux/arm64
-        tags: |
+                  tags: |
-          git.aridgwayweb.com/armistace/blog:latest    
+                      git.aridgwayweb.com/armistace/blog:latest
+
+            - name: Deploy
+              run: |
+                  echo "Installing Kubectl"
+                  apt-get update
+                  apt-get install -y apt-transport-https ca-certificates curl gnupg
+                  curl -fsSL https://pkgs.k8s.io/core:/stable:/v1.33/deb/Release.key | gpg --dearmor -o /etc/apt/keyrings/kubernetes-apt-keyring.gpg
+                  chmod 644 /etc/apt/keyrings/kubernetes-apt-keyring.gpg
+                  echo 'deb [signed-by=/etc/apt/keyrings/kubernetes-apt-keyring.gpg] https://pkgs.k8s.io/core:/stable:/v1.33/deb/ /' | tee /etc/apt/sources.list.d/kubernetes.list
+                  chmod 644 /etc/apt/sources.list.d/kubernetes.list
+                  apt-get update
+                  apt-get install kubectl
+                  kubectl delete namespace blog
+                  kubectl create namespace blog
+                  kubectl create secret docker-registry regcred --docker-server=${{ vars.DOCKER_SERVER }} --docker-username=${{ vars.DOCKER_USERNAME }} --docker-password='${{ secrets.DOCKER_PASSWORD }}' --docker-email=${{ vars.DOCKER_EMAIL }} --namespace=blog
+                  kubectl apply -f kube/blog_pod.yaml && kubectl apply -f kube/blog_deployment.yaml && kubectl apply -f kube/blog_service.yaml

kube/blog_deployment.yaml

@@ -0,0 +1,24 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: blog-deployment
+  labels:
+    app: blog
+  namespace: blog
+spec:
+  replicas: 3
+  selector:
+    matchLabels:
+      app: blog
+  template:
+    metadata:
+      labels:
+        app: blog
+    spec:
+      containers:
+      - name: blog
+        image: git.aridgwayweb.com/armistace/blog:latest
+        ports:
+        - containerPort: 8000
+      imagePullSecrets:
+        - name: regcred

kube/blog_pod.yaml

@@ -0,0 +1,13 @@
+apiVersion: v1
+kind: Pod
+metadata:
+    name: blog
+    namespace: blog
+spec:
+    containers:
+        - name: blog
+          image: git.aridgwayweb.com/armistace/blog:latest
+          ports:
+              - containerPort: 8000
+    imagePullSecrets:
+        - name: regcred

kube/blog_service.yaml

@@ -0,0 +1,13 @@
+apiVersion: v1
+kind: Service
+metadata:
+  name: blog-service
+  namespace: blog
+spec:
+  type: NodePort
+  selector:
+    app: blog 
+  ports:
+    - port: 80
+      targetPort: 8000
+      nodePort: 30009

src/content/first_ai_blog.md

@@ -12,11 +12,11 @@ As mentioned in the last post I have been experimenting with AI content generati
 
 It's still not in the state I want it to be and isn't connecting to the actual blog repo yet (the idea being that I edit and change as part of a review process). But it is generating stuff that I thought would be worth a share just for fun. The eventual idea is the container will be something I trigger as part of a CI/CD process when the equipment is up and running but the final "production" implementation is still being fleshed out in my head (if you can call a homelab project "production")
 
-The focus to this point has been on prompt engineering and model selection. A big part of this is that it needs to be able to run completely indepdantly of any cloud services so no Chat GPT.
+The focus to this point has been on prompt engineering and model selection. A big part of this is that it needs to be able to run completely independently of any cloud services so no Chat GPT.
 
-The obvious solution is [ollama](https://ollama.com) I'm luck enough to have a modest secondary gaming rig in my living room with an nvidia 2060 in it that can act as a modest AI server so I have set it up there.
+The obvious solution is [ollama](https://ollama.com) I'm lucky enough to have a modest secondary gaming rig in my living room with an nvidia 2060 in it that can act as a modest AI server so I have set it up there.
 
-This server has allowed me to experiment almost at will with models. a few I tried included
+This server has allowed me to experiment, almost at will, with models. a few I tried included
 
 - llama3.2
 - zephyr
@@ -29,6 +29,7 @@ However I have found that mistral-nemo seems to be the strongest contender, at l
 You can see the code and what I have been working on for more details [HERE](https://git.aridgwayweb.com/armistace/blog_creator)
 
 #### The summary prompt used by mistral to generate this post
+
 _The following is what I have in trilium to generate the AI written content_
 
 Get a python file that can communicate with a local ollama instance
@@ -50,7 +51,8 @@ Send a notification to matrix that there is a new PR in and give a summary of th
 _as you can see it pretty light on content so what it generates given this lack of context I feel is pretty good_
 
 # Let the post begin (begin...begin...begin...)
-_What follows is what it generated.. yes it is hilarious but well... it was to good not to share_
+
+_What follows is what it generated.. yes it is hilarious but well... it was too good not to share_
 
 # G'day, mates! Let's make an Ollama Blog Writer!
 

src/content/when_to_use_ai.md

@@ -0,0 +1,75 @@
+Title: When to use AI 
+Date: 2025-06-05 20:00 
+Modified: 2025-06-06 08:00 
+Category: AI, Data 
+Tags: ai, python 
+Slug: when-to-use-ai 
+Authors: Andrew Ridgway 
+Summary: Should we be using AI for ALL THE THINGS!?
+
+
+# Human Introduction
+Well.. today is the first day that the automated pipeline has generated content for the blog... still a bit of work to do including
+
+1. establishing a permanent vectordb solution (chromadb? pg_vector?)
+2. Notification to Matrix that something has happened
+3. Updating Trilium so that the note is marked as blog_written=true
+
+BUT it can take a note from trilium, generate drafts with mulitple agents, and then use RAG to have an editor go over those drafts.
+
+I'm particularly proud of the randomness I've applied to temperature, top_p and top_k for the different draft agents. This means that each pass is giving me quite different "creativity" (as much as that can be applied to an algorithm that is essentially munging letters together that have a high probability of being together) It has created some really interesting variation for the editor to work with and getting some really interesting results.
+
+Anyways, without further ado, I present to you the first, pipeline written, AI content for this blog
+
+---
+
+# When to Use AI: Navigating the Right Scenarios
+
+Okay, so I've been getting this question a lot lately: "When should we use AI?" or even more frustratingly, "Why can't AI do this?" It's like asking when to use a hammer versus a screwdriver. Sometimes AI is the perfect tool, other times it's better left in the toolbox. Let me break down some scenarios where AI shines and where it might not be the best bet.
+
+## The Spreadsheet Dilemma: Where AI Fails
+
+**Scenario:** Mapping work types to categories in a spreadsheet with thousands of entries, like distinguishing between "Painting," "Repainting," "Deck Painting," or "Stucco Repainting."
+
+**Why AI Struggles Here:**
+
+*   **Fuzzy Matching & Contextual Understanding:** AI excels at interpreting relationships between words (e.g., recognizing "Deck Painting" as a subset of "Painting"). However, traditional methods with regex or string manipulation fail here because they lack the nuanced judgment needed to handle ambiguity.
+*   **Precision Over Ambiguity:** Calculations requiring exact values (e.g., average durations) are better handled by deterministic algorithms rather than AI’s probabilistic approach.
+
+**Traditional Methods Win Here:**
+
+*   **Formula-Based Logic:** Building precise formulas for workload analysis relies on clear, unambiguous rules. AI can’t replace the need for human oversight in such cases.
+
+## When AI Shines: Contextual and Unstructured Tasks
+
+**Scenario:** Automating customer support with chatbots or analyzing social media sentiment.
+
+**Why AI Works Here:**
+
+*   **Natural Language Processing (NLP):** AI understands context, tone, and intent in unstructured data, making it ideal for tasks like chatbot responses or content analysis.
+*   **Pattern Recognition:** AI identifies trends or anomalies in large datasets that humans might miss, such as predictive maintenance in industrial settings.
+
+## Hybrid Approaches: The Future of Efficiency
+
+While traditional methods remain superior for precise calculations, AI can assist in setting up initial parameters or generating insights. For example:
+
+*   **AI Proposes Formulas:** An LLM suggests a workload calculation formula based on historical data.
+*   **Human Checks Validity:** A human ensures the formula’s accuracy before deployment.
+
+## Key Takeaways
+
+1.  **Use AI** for tasks involving:
+    *   Unstructured data (e.g., text, images).
+    *   Contextual understanding and interpretation.
+    *   Pattern recognition and trend analysis.
+2.  **Stick to Traditional Methods** for:
+    *   Precise calculations with deterministic logic.
+    *   Tasks requiring error-free accuracy (e.g., financial modeling).
+
+## Conclusion
+
+AI is a powerful tool but isn’t a one-size-fits-all solution. Match the right approach to the task at hand—whether it’s interpreting natural language or crunching numbers. The key is knowing when AI complements human expertise rather than replaces it.
+
+**Final Tip:** Always consider the trade-offs between precision and context. For tasks where nuance matters, AI is your ally; for rigid logic, trust traditional methods.
+
+🚀