Initial TEI deployment for Clawdbot memory search
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README.md
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README.md
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# TEI - Text Embeddings Inference
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Lightweight embedding service for Clawdbot memory search.
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## Overview
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Runs [HuggingFace Text Embeddings Inference](https://github.com/huggingface/text-embeddings-inference) (TEI) on CPU to provide OpenAI-compatible embeddings for semantic memory search.
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- **Model:** `sentence-transformers/all-MiniLM-L6-v2` (~90MB, 384 dimensions)
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- **Endpoint:** `http://text-embeddings:8080/v1/embeddings`
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- **No GPU required**
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## Deploy
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```bash
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oc new-project tei
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oc apply -f deployment.yaml
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```
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## Clawdbot Config
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Add to `~/.clawdbot/clawdbot.json`:
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```json5
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{
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"agents": {
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"defaults": {
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"memorySearch": {
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"enabled": true,
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"provider": "openai",
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"model": "sentence-transformers/all-MiniLM-L6-v2",
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"remote": {
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"baseUrl": "http://text-embeddings.tei.svc.cluster.local:8080/v1/",
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"apiKey": "not-needed"
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}
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}
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}
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}
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}
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```
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## Resources
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- **Memory:** 512Mi request, 1Gi limit
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- **CPU:** 250m request, 1000m limit
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- **Storage:** 1Gi PVC for model cache
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## Test
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```bash
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curl -X POST http://text-embeddings:8080/v1/embeddings \
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-H "Content-Type: application/json" \
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-d '{"input": "Hello world", "model": "sentence-transformers/all-MiniLM-L6-v2"}'
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```
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deployment.yaml
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deployment.yaml
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---
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apiVersion: v1
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kind: PersistentVolumeClaim
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metadata:
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name: tei-model-cache
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spec:
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accessModes:
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- ReadWriteOnce
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resources:
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requests:
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storage: 1Gi
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---
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: text-embeddings
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labels:
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app: text-embeddings
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spec:
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replicas: 1
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selector:
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matchLabels:
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app: text-embeddings
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template:
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metadata:
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labels:
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app: text-embeddings
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spec:
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containers:
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- name: tei
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image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
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args:
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- --model-id
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- sentence-transformers/all-MiniLM-L6-v2
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- --port
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- "8080"
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ports:
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- containerPort: 8080
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resources:
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requests:
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memory: "512Mi"
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cpu: "250m"
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limits:
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memory: "1Gi"
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cpu: "1000m"
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volumeMounts:
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- name: model-cache
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mountPath: /data
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env:
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- name: HF_HOME
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value: /data
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readinessProbe:
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httpGet:
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path: /health
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port: 8080
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initialDelaySeconds: 30
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periodSeconds: 10
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livenessProbe:
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httpGet:
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path: /health
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port: 8080
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initialDelaySeconds: 60
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periodSeconds: 30
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volumes:
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- name: model-cache
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persistentVolumeClaim:
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claimName: tei-model-cache
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---
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apiVersion: v1
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kind: Service
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metadata:
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name: text-embeddings
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spec:
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selector:
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app: text-embeddings
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ports:
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- port: 8080
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targetPort: 8080
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kustomization.yaml
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kustomization.yaml
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apiVersion: kustomize.config.k8s.io/v1beta1
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kind: Kustomization
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namespace: tei
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resources:
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- deployment.yaml
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