Add vector logging for tabby-server events. (#25)

* Switch to dagu for init job

* Add processed logging

deployment/.env

@@ -1,2 +1,6 @@
 MODEL_NAME=TabbyML/J-350M
+
+# Volumes
 HF_VOLUME="../data/hf_cache:/root/.cache/huggingface"
+
+LOGS_VOLUME="../data/logs:/logs"

deployment/config/vector.toml

@@ -0,0 +1,19 @@
+[api]
+enabled = true
+address = "0.0.0.0:8686"
+
+[sources.tabby_server_logs]
+type = "file"
+include = ["/logs/tabby-server/events.*.log"]
+
+[transforms.process_tabby_server_logs]
+type = "remap"
+inputs = [ "tabby_server_logs" ]
+source = ". = parse_json!(parse_json!(.message).record.message)"
+
+[sinks.write_tabby_server_logs]
+type = "file"
+inputs = [ "process_tabby_server_logs" ]
+encoding = { codec = "json" }
+framing = { method = "newline_delimited" }
+path = "/logs/tabby-server/events.%Y-%m-%d.json"

deployment/docker-compose.yml

@@ -4,7 +4,7 @@ services:
   init:
     image: tabbyml/tabby
     container_name: tabby-init
-    command: python -m tabby.tools.model_preload --repo_id ${MODEL_NAME}
+    command: dagu start --params=MODEL_NAME=${MODEL_NAME} ./tabby/tasks/init.yaml
     volumes:
       - ${HF_VOLUME}
 
@@ -15,10 +15,12 @@ services:
     environment:
       MODEL_NAME: ${MODEL_NAME}
       MODEL_BACKEND: triton
+      EVENTS_LOG_DIR: /logs/tabby-server
     ports:
       - "5000:5000"
     volumes:
       - ${HF_VOLUME}
+      - ${LOGS_VOLUME}
     depends_on:
       init:
         condition: service_completed_successfully
@@ -57,3 +59,10 @@ services:
       interval: 2s
       timeout: 2s
       start_period: 120s
+
+  vector:
+    image: timberio/vector:0.28.1-alpine
+    container_name: tabby-vector
+    volumes:
+      - ./config/vector.toml:/etc/vector/vector.toml:ro
+      - ${LOGS_VOLUME}

tabby/tasks/init.yaml

@@ -0,0 +1,8 @@
+params: MODEL_NAME
+env:
+  - PATH: "/opt/conda/bin:$PATH"
+  - APP_DIR: /app
+steps:
+  - name: Download models
+    dir: $APP_DIR
+    command: python -m tabby.tools.download_models --repo_id=$MODEL_NAME