From a76f73d1e00b89be3a5a953a67a232ba64715b1e Mon Sep 17 00:00:00 2001
From: guanjihuan <guanjihuan@163.com>
Date: Wed, 5 Nov 2025 16:09:31 +0800
Subject: [PATCH] update

---
 2025.11.02_langchain/langchain_example.py     |  4 +-
 .../langchain_example_with_Ollama.py          | 38 +++++++++++++++++++
 2 files changed, 40 insertions(+), 2 deletions(-)
 create mode 100644 2025.11.02_langchain/langchain_example_with_Ollama.py

diff --git a/2025.11.02_langchain/langchain_example.py b/2025.11.02_langchain/langchain_example.py
index e8171f8..95b48a1 100644
--- a/2025.11.02_langchain/langchain_example.py
+++ b/2025.11.02_langchain/langchain_example.py
@@ -3,7 +3,7 @@ This code is supported by the website: https://www.guanjihuan.com
 The newest version of this code is on the web page: https://www.guanjihuan.com/archives/47909
 """
 
-import langchain_openai
+from langchain_openai import ChatOpenAI
 from langchain_core.prompts import ChatPromptTemplate
 import dotenv
 import os
@@ -12,7 +12,7 @@ import os
 dotenv.load_dotenv()
 
 # 创建聊天模型
-llm = langchain_openai.ChatOpenAI(
+llm = ChatOpenAI(
     api_key=os.getenv("OPENAI_API_KEY"),  # 从环境变量获取 API 密钥
     base_url=os.getenv("DASHSCOPE_BASE_URL"),  # 指定 API 端点
     model="qwen-plus",  # 使用通义千问 Plus 模型
diff --git a/2025.11.02_langchain/langchain_example_with_Ollama.py b/2025.11.02_langchain/langchain_example_with_Ollama.py
new file mode 100644
index 0000000..06832dc
--- /dev/null
+++ b/2025.11.02_langchain/langchain_example_with_Ollama.py
@@ -0,0 +1,38 @@
+"""
+This code is supported by the website: https://www.guanjihuan.com
+The newest version of this code is on the web page: https://www.guanjihuan.com/archives/47909
+"""
+
+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import ChatPromptTemplate
+import dotenv
+
+# 加载环境变量（包含API密钥）
+dotenv.load_dotenv()
+
+# 创建聊天模型 - 修改为调用 Ollama
+llm = ChatOpenAI(
+    api_key="ollama",  # 对于 Ollama，API key 可以设为任意值或 "ollama"
+    base_url="http://localhost:11434/v1",  # Ollama 的本地 API 地址
+    model="qwen2.5:3b",  # 替换为你本地安装的模型名称，如 qwen2.5 等
+    temperature=0.7,  # 控制回复的随机性（0-1，越高越有创意）
+    streaming=True,  # 启用流式模式
+)
+
+# 创建简单的提示词模板
+prompt = ChatPromptTemplate.from_messages([
+    ("system", "你是一个友好的聊天助手。"),  # 系统角色设定
+    ("human", "{question}")   # 用户输入占位符
+])
+
+# 创建处理链
+chain = prompt | llm  # 使用管道操作符连接组件
+
+# 使用 stream() 实现流式输出
+for chunk in chain.stream({"question": "你好"}):
+    print(chunk.content, end="", flush=True)
+print()  # 换行
+
+# # 非流式输出
+# response = chain.invoke({"question": "你好"})
+# print(response.content)
\ No newline at end of file