import edward

llm/local/ollama.py

@@ -0,0 +1,56 @@
+import requests
+
+
+class Ollama:
+    def __init__(self, model="qwen2.5:14b", server_url="http://192.168.1.200:11434"):
+        self.model = model
+        self.server_url = server_url
+
+    def is_service_running(self):
+        """检查 Ollama 服务是否正在运行"""
+        try:
+            url = f"{self.server_url}/api/generate"
+            headers = {"Content-Type": "application/json"}
+            payload = {
+                "model": self.model,
+                "prompt": "ping",  # 使用轻量级的 prompt 测试
+                "stream": False
+            }
+            output = requests.post(url, headers=headers, json=payload, timeout=60)
+            if output.status_code == 200:
+                return True
+            else:
+                return False
+        except requests.exceptions.RequestException:
+            return False
+
+    def generate_text(self, input_message: str):
+        url = f"{self.server_url}/api/generate"
+        headers = {"Content-Type": "application/json"}
+        payload = {
+            "model": self.model,
+            "prompt": input_message,
+            "stream": False,  # 关闭流式传输
+            "options": {
+                "temperature": 0.7,
+                "top_p": 0.9,
+                "num_ctx": 20480
+            }
+        }
+        try:
+            output = requests.post(url, headers=headers, json=payload)
+            output.raise_for_status()  # 检查HTTP请求是否成功
+            result = output.json()
+            return result.get("response", "No response from model.")
+        except requests.exceptions.RequestException as e:
+            return f"Error calling Ollama API: {e}"
+
+
+if __name__ == "__main__":
+    # 示例提示文本
+    ollama = Ollama()
+    print("Ollama 服务是否正在运行：", ollama.is_service_running())
+    prompt = "请用中文描述机器学习的基本概念。"
+    response = ollama.generate_text(prompt)
+    print("模型生成的文本：")
+    print(response)