ragflow

docker-compose-with-pgsql.yml

@@ -1,7 +1,7 @@
 version: "3.8"
 
 services:
-  postgres:
+  postgres-agent:
     image: pgvector/pgvector:pg16
     container_name: qwen-agent-postgres
     environment:
@@ -29,20 +29,19 @@ services:
       - "8001:8001"
     environment:
       # 应用配置
-      - BACKEND_HOST=http://api-dev.gbase.ai
       - MAX_CONTEXT_TOKENS=262144
       - DEFAULT_THINKING_ENABLE=true
       - PROFILE=low_memory
-      - RAGFLOW_API_URL=http://172.26.31.232:1080
+      - RAGFLOW_API_URL=http://ragflow-cpu
       - RAGFLOW_API_KEY=ragflow-0vldzYY_SfQLnjBIGOBDDgvdgWemdK4gmH1L7kgenQ0
       # PostgreSQL 配置
-      - CHECKPOINT_DB_URL=postgresql://postgres:E5ACJo6zJub4QS@postgres:5432/agent_db
+      - CHECKPOINT_DB_URL=postgresql://postgres:E5ACJo6zJub4QS@postgres-agent:5432/agent_db
     volumes:
       # 挂载项目数据目录
       - ./projects:/app/projects
       - ./models:/app/models
     depends_on:
-      postgres:
+      postgres-agent:
         condition: service_healthy
     restart: unless-stopped
     healthcheck:
@@ -51,5 +50,12 @@ services:
       timeout: 10s
       retries: 3
       start_period: 40s
+    networks:
+        - default
+        - ragflow
 volumes:
    postgres_data:
+networks:
+   ragflow:
+      name: docker_ragflow
+      external: true

skills/ragflow-loader/.claude-plugin/plugin.json

@@ -12,9 +12,9 @@
   "mcpServers": {
     "rag_retrieve": {
       "transport": "http",
-      "url": "http://host.docker.internal:9382/mcp/",
+      "url": "http://ragflow-cpu:9382/mcp/",
       "headers": {
-        "api_key": "ragflow-MRqxnDnYZ1yp5kklDMIlKH4f1qezvXIngSMGPhu1AG8",
+        "api_key": "ragflow-0vldzYY_SfQLnjBIGOBDDgvdgWemdK4gmH1L7kgenQ0",
         "X-Dataset-Ids": "{dataset_ids}"
       }
     }