> ## Documentation Index > Fetch the complete documentation index at: https://docs-model.skyengine.com.cn/llms.txt > Use this file to discover all available pages before exploring further. # Gemini 工具调用示例 > 使用Gemini API进行Function Calling工具调用的完整示例代码 # Gemini 工具调用示例 以下示例展示如何使用Gemini的Function Calling功能，让AI能够调用外部工具来获取信息或执行操作。 ## 快速开始 只需要替换 `` 为你的实际API密钥即可运行。 ```bash cURL theme={null} curl -X POST "https://model-api.skyengine.com.cn/v1beta/models/gemini-2.5-flash:generateContent" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer " \ -d '{ "contents": [ { "role": "user", "parts": [ { "text": "计算一下 (25 + 15) * 3 - 20 等于多少？" } ] } ], "tools": [{ "functionDeclarations": [ { "name": "calculate_math", "description": "执行数学计算，支持基本的四则运算和括号", "parameters": { "type": "object", "properties": { "expression": { "type": "string", "description": "要计算的数学表达式，如 '2+3*4' 或 '(10+5)/3'" } }, "required": [ "expression" ] } } ] }] }' ``` ```python Python theme={null} import requests # 配置API密钥和基础URL API_KEY = "" BASE_URL = "https://model-api.skyengine.com.cn/v1beta" # 定义计算器工具函数 def calculate_math(expression): """执行安全的数学计算""" try: # 安全检查，只允许基本的数学操作 allowed_chars = set('0123456789+-*/.() ') if not all(c in allowed_chars for c in expression): return {"error": "表达式包含不允许的字符", "status": "error"} # 禁止一些危险的函数调用 dangerous_words = ['import', 'exec', 'eval', '__'] if any(word in expression.lower() for word in dangerous_words): return {"error": "表达式包含不安全的内容", "status": "error"} result = eval(expression) return { "expression": expression, "result": result, "formatted": f"{expression} = {result}", "status": "success" } except Exception as e: return {"error": f"计算出错: {str(e)}", "status": "error"} # 工具函数映射 AVAILABLE_FUNCTIONS = { "calculate_math": calculate_math } def gemini_function_calling(user_message): """使用Gemini进行函数调用对话""" url = f"{BASE_URL}/models/gemini-2.5-flash:generateContent" headers = { "Content-Type": "application/json", "Authorization": f"Bearer {API_KEY}" } # 定义可用的工具 tools = [ { "functionDeclarations": [ { "name": "calculate_math", "description": "执行数学计算，支持基本的四则运算和括号", "parameters": { "type": "object", "properties": { "expression": { "type": "string", "description": "要计算的数学表达式，如 '2+3*4' 或 '(10+5)/3'" } }, "required": ["expression"] } } ] } ] messages = [ { "role": "user", "parts": [ { "text": user_message } ] } ] data = { "contents": messages, "tools": tools } try: response = requests.post(url, headers=headers, json=data) if response.status_code != 200: return f"API错误: {response.status_code} - {response.text}" result = response.json() # 处理Gemini的响应 if 'candidates' in result and len(result['candidates']) > 0: candidate = result['candidates'][0] content = candidate.get('content', {}) parts = content.get('parts', []) # 检查是否有函数调用（注意：API返回的是 functionCall 而不是 function_call） function_calls = [part for part in parts if 'functionCall' in part] if function_calls: print("检测到函数调用请求:") # 处理函数调用并收集结果 function_responses = [] for part in parts: if 'functionCall' in part: function_call = part['functionCall'] function_name = function_call['name'] function_args = function_call.get('args', {}) print(f"- 调用函数: {function_name}") print(f"- 参数: {function_args}") # 执行函数调用 if function_name in AVAILABLE_FUNCTIONS: try: function_result = AVAILABLE_FUNCTIONS[function_name](**function_args) print(f"- 结果: {function_result}") function_responses.append({ "functionResponse": { "name": function_name, "response": function_result } }) except Exception as e: error_result = {"error": f"函数执行失败: {str(e)}", "status": "error"} function_responses.append({ "functionResponse": { "name": function_name, "response": error_result } }) else: error_result = {"error": f"未知的函数: {function_name}", "status": "error"} function_responses.append({ "functionResponse": { "name": function_name, "response": error_result } }) # 将函数结果发送回Gemini生成最终回复 # 模型的函数调用响应需要指定 role: "model" messages.append({ "role": "model", "parts": parts }) # 函数执行结果需要指定 role: "user" messages.append({ "role": "user", "parts": function_responses }) data["contents"] = messages final_response = requests.post(url, headers=headers, json=data) if final_response.status_code == 200: final_result = final_response.json() if 'candidates' in final_result and len(final_result['candidates']) > 0: final_content = final_result['candidates'][0]['content'] final_parts = final_content.get('parts', []) # 提取文本内容 text_parts = [part.get('text', '') for part in final_parts if 'text' in part] return '\n'.join(text_parts) else: return "无法获取最终回复" else: return f"获取最终回复失败: {final_response.status_code} - {final_response.text}" else: # 没有函数调用，直接返回文本回复 text_parts = [part.get('text', '') for part in parts if 'text' in part] return '\n'.join(text_parts) else: return "没有获得有效回复" except Exception as e: return f"请求处理出错: {str(e)}" # 使用示例 if __name__ == "__main__": print("=== Gemini计算器工具调用示例 ===\n") query = "计算一下 (25 + 15) * 3 - 20 等于多少？" print(f"用户问题: {query}") print("AI回复:") response = gemini_function_calling(query) print(response) ``` ## Gemini工具调用的特点 ### 1. 工具定义格式 Gemini使用 `functionDeclarations` 数组来定义工具： ```json theme={null} { "tools": [{ "functionDeclarations": [ { "name": "function_name", "description": "函数描述", "parameters": { "type": "object", "properties": { "param": { "type": "string", "description": "参数描述" } }, "required": ["param"] } } ] }] } ``` ### 2. 响应结构 Gemini的工具调用响应格式： ```json theme={null} { "candidates": [ { "content": { "parts": [ { "functionCall": { "name": "function_name", "args": { "param": "value" } } } ] } } ] } ``` ### 3. 工作流程 1. 用户发送带有工具定义的消息 2. Gemini分析是否需要使用工具 3. Gemini返回包含 `functionCall` 的响应 4. 客户端执行对应的函数 5. 客户端将结果作为 `functionResponse` 发送回Gemini 6. Gemini基于工具结果生成最终回复 ## 结果示例 ```json 200 theme={null} { "candidates": [ { "content": { "parts": [ { "functionCall": { "name": "calculate_math", "args": { "expression": "(25 + 15) * 3 - 20" } } } ], "role": "model" }, "finishReason": "STOP", "index": 0 } ], "usageMetadata": { "promptTokenCount": 150, "candidatesTokenCount": 50, "totalTokenCount": 200 } } ``` ## Google Search 工具 Gemini 支持内置的 Google Search 工具，可以让模型搜索实时信息来回答问题。与自定义函数调用不同，Google Search 是由 Gemini 自动执行的，无需客户端处理搜索逻辑。 ```bash cURL theme={null} curl -X POST "https://model-api.skyengine.com.cn/v1beta/models/gemini-2.5-flash:generateContent" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer " \ -d '{ "contents": [ { "parts": [ {"text": "2024年欧洲杯冠军是谁？"} ] } ], "tools": [ { "googleSearch": {} } ] }' ``` ```python Python theme={null} import requests API_KEY = "" BASE_URL = "https://model-api.skyengine.com.cn/v1beta" def gemini_google_search(query): """使用 Gemini 的 Google Search 工具进行搜索""" url = f"{BASE_URL}/models/gemini-2.5-flash:generateContent" headers = { "Content-Type": "application/json", "Authorization": f"Bearer {API_KEY}" } data = { "contents": [ { "parts": [ {"text": query} ] } ], "tools": [ { "googleSearch": {} } ] } response = requests.post(url, headers=headers, json=data) if response.status_code == 200: result = response.json() if 'candidates' in result and len(result['candidates']) > 0: parts = result['candidates'][0]['content'].get('parts', []) text_parts = [part.get('text', '') for part in parts if 'text' in part] return '\n'.join(text_parts) return f"错误: {response.status_code} - {response.text}" # 使用示例 if __name__ == "__main__": query = "2024年欧洲杯冠军是谁？" print(f"问题: {query}") print("回答:") print(gemini_google_search(query)) ``` ### Google Search 工具特点 * **自动执行**: 模型会自动调用 Google Search 获取信息，无需客户端处理 * **实时信息**: 可以获取最新的新闻、事件、数据等实时信息 * **简单配置**: 只需在 `tools` 中添加 `{"googleSearch": {}}` 即可启用 ## 注意事项 1. **消息角色**: 多轮对话时，所有消息都需要指定 `role` 字段（`user` 或 `model`） 2. **字段命名**: API 使用 camelCase 命名（`functionCall`、`functionResponse`），而不是 snake\_case 3. **函数响应**: 函数执行结果需要以 `role: "user"` 的消息发送回模型 4. **错误处理**: 建议在函数执行中添加完善的错误处理机制