From 24b5477e4fdf85dada7e0af5a91b1f332e7f3a5c Mon Sep 17 00:00:00 2001
From: Blog Creator <ridgway.infrastructure@gmail.com>
Date: Fri, 27 Jun 2025 06:22:56 +0000
Subject: [PATCH] 'LLM Matrix bot integration deployed'

---
 .../matrix_ai_integrations_with_baibot.md     | 107 ++++++++++++++++++
 1 file changed, 107 insertions(+)
 create mode 100644 src/content/matrix_ai_integrations_with_baibot.md

diff --git a/src/content/matrix_ai_integrations_with_baibot.md b/src/content/matrix_ai_integrations_with_baibot.md
new file mode 100644
index 0000000..f3c90bd
--- /dev/null
+++ b/src/content/matrix_ai_integrations_with_baibot.md
@@ -0,0 +1,107 @@
+# Matrix AI Integrations with baibot
+
+I've been experimenting with **baibot** (<https://github.com/etkecc/baibot>), a locally deployable bot for integrating Large Language Models (LLMs) into Matrix chatrooms. This setup allows me to interact with LLMs directly within my own Matrix server, enhancing both personal and community communication.
+
+### Key Setup Steps
+
+1. **Configuration**:
+   - Use the sample provider config (e.g., <https://github.com/etkecc/baibot/blob/main/docs/sample-provider-configs/ollama.yml>) to define LLM models, prompts, temperatures, and token limits.
+2. **Kubernetes Deployment**:
+   - Deploy using a custom `Deployment.yaml` and PersistentVolumeClaim (PVC) for storage persistence.
+   - Example `Deployment.yaml`:
+
+```yaml
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  ...
+spec:
+  template:
+    spec:
+      containers:
+        - env:
+            - name: BAIBOT_PERSISTENCE_DATA_DIR_PATH
+              value: /data
+          image: ghcr.io/etkecc/baibot:v1.7.4
+          volumeMounts:
+            - mountPath: /app/config.yml
+              subPath: config.yml
+            - mountPath: /data
+              subPath: data
+```
+
+   - PVC setup (`pvc-ridgway-bot.yaml`):
+
+```yaml
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: ridgway-bot-storage
+spec:
+  storageClassName: longhorn
+  accessModes:
+    - ReadWriteMany
+  resources:
+    requests:
+      storage: 500Mi
+```
+
+3. **Kubernetes Deployment Script**:
+
+```sh
+kubectl delete namespace ridgway-bot
+kubectl create namespace ridgway-bot
+kubectl -n ridgway-bot create cm ridgway-bot --from-file=config.yml=./config.yml
+kubectl apply -f pvc-ridgway-bot.yaml
+kubectl apply -f Deployment.yaml
+sleep 90 && kubectl cp data/* $(kubectl get pods -o custom-columns=":metadata.name" -n ridgway_bot | head -n1):/data
+```
+
+4. **Post-Deployment**:
+   - Connect the bot to Matrix rooms via Element’s admin interface.
+   - Fine-tune configurations (e.g., temperature, prompts) for specific rooms.
+
+### Example Configurations
+
+#### Ollama Integration:
+
+```yaml
+base_url: http://192.168.178.45:11434/v1
+text_generation:
+  model_id: gemma3:latest
+  prompt: 'You are a lighthearted bot...'
+  temperature: 0.9
+  max_response_tokens: 4096
+  max_context_tokens: 128000
+```
+
+#### Openwebui Integration (RAG):
+
+```yaml
+base_url: https://ai.aridgwayweb.com/api/
+api_key: <my-openwebui-api-key>
+text_generation:
+  model_id: andrew-knowledge-base
+  prompt: 'Your name is Rodergast...'
+  temperature: 0.7
+  max_response_tokens: 4096
+  max_context_tokens: 128000
+```
+
+### Benefits of Local Deployment
+
+- **Full Control**: Data privacy and compliance without third-party dependencies.
+- **Scalability**: Kubernetes enables easy scaling as needed.
+- **Flexibility**: Combine with services like openwebui for rich contextual responses.
+
+### Future Plans
+
+Next, I aim to integrate baibot with Home Assistant for alarm notifications. However, current hardware limitations (a 10-year-old PC) may necessitate a more powerful setup in the future.
+
+Stay tuned for updates!
+
+# Conclusion
+
+baibot enhances Matrix interactions by enabling direct LLM integration, offering seamless control over room-specific behaviors. Combining local deployment with RAG capabilities via openwebui demonstrates DIY tech stack potential.
+
+Explore further and share your experiences! 🚀🤖