python后端调用Deep Seek API
python后端调用Deep Seek API
需要依次下载
●Ollama
●Deepseek R1 LLM模型
●嵌入模型nomic-embed-text / bge-m3
●AnythingLLM
参考教程：
Deepseek R1打造本地化RAG知识库:安装部署使用详细教程
手把手教你：deepseek R1基于 AnythingLLM API 调用本地知识库
python调用anythingllm的API
import requests
# import jsondef
def ask_anythingllm(question, workspace_name, api_key):url = f"http://localhost:3001/api/v1/workspace/{workspace_name}/chat"headers = {"Authorization": f"Bearer {api_key}","Content-Type": "application/json","accept": "application/json"}data = {"message": question,"mode": "query" # 可选chat/query模式}response = requests.post(url, headers=headers, json=data)if response.status_code == 200:result = response.json()# 提取有效回答（去除思考过程）answer = result['textResponse'].split('</think>')[-1].strip()sources = result.get('sources', [])return answer, sourceselse:return f"Error: {response.text}", []# 示例调用
workspace = "" # 填入workspace 名字，注意要全小写
api_key = "" # api_key
question = "你是谁？"
print(question)
answer, sources = ask_anythingllm(question, workspace, api_key)
print("回答:", answer)
print("来源:", [src['title'] for src in sources])注意workspace_name与anythingllm平台上的显示有所出入，要全部小写，且空格要改成连字符，比如说
MY Workspaces要写成my-workspaces
DeepSeek要写成deepseek
结果：
