import asyncio import json from openai import OpenAI import sys import os sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) from sci_mcp import * tools_schemas = get_domain_tool_schemas(["material",'general']) tool_map = get_domain_tools(["material",'general']) api_key="gpustack_41f8963fb74e9f39_931a02e3ab35b41b1eada85da9c40705" base_url="http://gpustack.ddwtop.team/v1-openai" client = OpenAI( api_key=api_key, base_url=base_url, ) messages = [ {"role": "user", "content": """data_Ti4V _symmetry_space_group_name_H-M Fmmm _cell_length_a 3.18353600 _cell_length_b 4.52677200 _cell_length_c 22.74397000 _cell_angle_alpha 90.00000000 _cell_angle_beta 90.00000000 _cell_angle_gamma 90.00000000 _symmetry_Int_Tables_number 69 _chemical_formula_structural Ti4V _chemical_formula_sum 'Ti16 V4' _cell_volume 327.76657340 _cell_formula_units_Z 4 loop_ _symmetry_equiv_pos_site_id _symmetry_equiv_pos_as_xyz 1 'x, y, z' 2 '-x, -y, -z' 3 '-x, -y, z' 4 'x, y, -z' 5 'x, -y, -z' 6 '-x, y, z' 7 '-x, y, -z' 8 'x, -y, z' 9 'x+1/2, y, z+1/2' 10 '-x+1/2, -y, -z+1/2' 11 '-x+1/2, -y, z+1/2' 12 'x+1/2, y, -z+1/2' 13 'x+1/2, -y, -z+1/2' 14 '-x+1/2, y, z+1/2' 15 '-x+1/2, y, -z+1/2' 16 'x+1/2, -y, z+1/2' 17 'x+1/2, y+1/2, z' 18 '-x+1/2, -y+1/2, -z' 19 '-x+1/2, -y+1/2, z' 20 'x+1/2, y+1/2, -z' 21 'x+1/2, -y+1/2, -z' 22 '-x+1/2, y+1/2, z' 23 '-x+1/2, y+1/2, -z' 24 'x+1/2, -y+1/2, z' 25 'x, y+1/2, z+1/2' 26 '-x, -y+1/2, -z+1/2' 27 '-x, -y+1/2, z+1/2' 28 'x, y+1/2, -z+1/2' 29 'x, -y+1/2, -z+1/2' 30 '-x, y+1/2, z+1/2' 31 '-x, y+1/2, -z+1/2' 32 'x, -y+1/2, z+1/2' loop_ _atom_site_type_symbol _atom_site_label _atom_site_symmetry_multiplicity _atom_site_fract_x _atom_site_fract_y _atom_site_fract_z _atom_site_occupancy Ti Ti0 8 0.00000000 0.00000000 0.19939400 1.0 Ti Ti1 8 0.00000000 0.00000000 0.40878900 1.0 V V2 4 0.00000000 0.00000000 0.00000000 1.0 ，根据上文提供的CIF文件，请你分析该晶体材料的化学式、晶体系统、空间群、密度、是否为金属、磁性和稳定性，并用JSON格式回答。"""}] def get_t1_response(messages): completion = client.chat.completions.create( model="MARS-T1", messages=messages, temperature=0.3, tools=tools_schemas, ) choice = completion.choices[0] reasoning_content = choice.message.content #print("Reasoning content:", reasoning_content) if hasattr(choice.message, 'tool_calls') and choice.message.tool_calls: tool_calls_list = [] for tool_call in choice.message.tool_calls: tool_call_dict = { "id": tool_call.id, "type": "function", "function": { "name": tool_call.function.name, "arguments": tool_call.function.arguments } } tool_calls_list.append(tool_call_dict) return reasoning_content, tool_calls_list async def execute_tool(tool_name,tool_arguments): try: tool_func = tool_map[tool_name] # 获取工具函数 arguments = {} if tool_arguments: # 检查arguments是字符串还是字典 if isinstance(tool_arguments, dict): # 如果已经是字典，直接使用 arguments = tool_arguments elif isinstance(tool_arguments, str): # 如果是字符串，尝试解析为JSON try: # 尝试直接解析为JSON对象 arguments = json.loads(tool_arguments) except json.JSONDecodeError: # 如果解析失败，可能是因为字符串中包含转义字符 # 尝试修复常见的JSON字符串问题 fixed_str = tool_arguments.replace('\\"', '"').replace('\\\\', '\\') try: arguments = json.loads(fixed_str) except json.JSONDecodeError: # 如果仍然失败，尝试将字符串作为原始字符串处理 arguments = {"raw_string": tool_arguments} # 调用工具函数 if asyncio.iscoroutinefunction(tool_func): # 如果是异步函数，使用await调用 result = await tool_func(**arguments) else: # 如果是同步函数，直接调用 result = tool_func(**arguments) # if func_name=='generate_material': # print("xxxxx",result) return result finally: # 清除LLM调用上下文标记 pass def get_all_tool_calls_results(tool_calls_list): all_results = [] for tool_call in tool_calls_list: tool_name = tool_call['function']['name'] tool_arguments = tool_call['function']['arguments'] result = asyncio.run(execute_tool(tool_name,tool_arguments)) result_str = f"[{tool_name} content begin]\n"+result+f"\n[{tool_name} content end]\n" all_results.append(result_str) return all_results def get_response_from_r1(messages): completion = client.chat.completions.create( model="MARS-R1", messages=messages, temperature=0.3, ) choice = completion.choices[0] return choice.message.content print("R1 RESPONSE:", choice.message.content) if __name__ == '__main__': reasoning_content, tool_calls_list=get_t1_response(messages) print("Reasoning content:", reasoning_content) tool_call_results=get_all_tool_calls_results(tool_calls_list) tool_call_results_str = "\n".join(tool_call_results) # for tool_call in tool_call_results: # print(tool_call) user_message = { "role": "user", "content": f"# 信息如下:{tool_call_results_str}# 问题如下 {messages[0]['content']}" } print("user_message_for_r1:", user_message) get_response_from_r1([user_message])