fix: 修复错误

ai-rag-app/src/main/resources/application-dev.yml

@@ -4,14 +4,14 @@ server:
 spring:
   ai:
     ollama:
-      base-url: http://117.72.202.142:11434
+      base-url: http://192.168.109.134:11434
 
 # Redis
 redis:
   sdk:
     config:
-      host: 117.72.202.142
-      port: 16379
+      host: 127.0.0.1
+      port: 6379
       pool-size: 10
       min-idle-size: 5
       idle-timeout: 30000

ai-rag-trigger/src/main/java/com/storm/dev/trigger/http/OllamaController.java

@@ -22,7 +22,7 @@ public class OllamaController implements IAiService {
     private OllamaChatClient chatClient;
 
     /**
-     * http://localhost:8090/api/v1/ollama/generate?model=deepseek-r1:1.5b&message=1+1
+     * http://localhost:8090/api/v1/ollama/generate?model=deepseek-r1:7b&message=1+1
      */
     @GetMapping("generate")
     @Override
@@ -31,7 +31,7 @@ public class OllamaController implements IAiService {
     }
 
     /**
-     * http://localhost:8090/api/v1/ollama/generate_stream?model=deepseek-r1:1.5b&message=hi
+     * http://localhost:8090/api/v1/ollama/generate_stream?model=deepseek-r1:7b&message=hi
      */
     @GetMapping("generate_stream")
     @Override

docs/docker-compose-environment-aliyun2.yml

@@ -0,0 +1,43 @@
+# docker-compose -f docker-compose-environment-aliyun.yml up -d
+version: '3'
+services:
+  # 对话模型
+  # ollama pull deepseek-r1:1.5b
+  # 运行模型
+  # ollama run deepseek-r1:1.5b
+  # 联网模型
+  # ollama pull nomic-embed-text
+  ollama:
+    image: registry.cn-hangzhou.aliyuncs.com/xfg-studio/ollama:0.5.10
+    container_name: ollama
+    restart: unless-stopped
+    ports:
+      - "11434:11434"
+  vector_db:
+    image: registry.cn-hangzhou.aliyuncs.com/xfg-studio/pgvector:v0.5.0
+    container_name: vector_db
+    restart: always
+    environment:
+      - POSTGRES_USER=postgres
+      - POSTGRES_PASSWORD=postgres
+      - POSTGRES_DB=ai-rag-knowledge
+      - PGPASSWORD=postgres
+    volumes:
+      - ./pgvector/sql/init.sql:/docker-entrypoint-initdb.d/init.sql
+    logging:
+      options:
+        max-size: 10m
+        max-file: "3"
+    ports:
+      - '15432:5432'
+    healthcheck:
+      test: "pg_isready -U postgres -d ai-rag-knowledge"
+      interval: 2s
+      timeout: 20s
+      retries: 10
+    networks:
+      - my-network
+
+networks:
+  my-network:
+    driver: bridge

docs/nginx/html/ai-case-04.html

@@ -69,7 +69,7 @@
             addMessage('<span class="animate-pulse">▍</span>');
 
             // 构建API URL
-            const apiUrl = `http://localhost:8090/api/v1/ollama/generate_stream?model=deepseek-r1:1.5b&message=${encodeURIComponent(message)}`;
+            const apiUrl = `http://localhost:8090/api/v1/ollama/generate_stream?model=deepseek-r1:7b&message=${encodeURIComponent(message)}`;
 
             // 使用EventSource接收流式响应
             const eventSource = new EventSource(apiUrl);

docs/nginx/html/index.html

@@ -56,7 +56,7 @@
 
 <script>
   const API_BASE = 'http://localhost:8090/api/v1/ollama/generate_stream';
-  const MODEL = 'deepseek-r1:1.5b';
+  const MODEL = 'deepseek-r1:7b';
   const chatContainer = document.getElementById('chatContainer');
   const messageInput = document.getElementById('messageInput');
   const sendButton = document.getElementById('sendButton');