menopause
    menopause
    • Auth
      • Register a new user
        POST
      • Login with email & password
        POST
    • test
      GET
    • 未命名接口
      POST
    • 数据模型
      • Schemas
        • ApiResponseUserTokens
        • ErrorResponse
        • AuthRegisterRequest
        • AuthLoginRequest
        • User
        • Tokens

      未命名接口

      开发中
      POST
      http://localhost:8000/api/v1/sred/generate
      责任人:未设置

      请求参数

      Body 参数application/json

      示例
         "files": [
              {
                  "fileId": "test-001",
                  "filename": "project.txt", 
                  "text": "SR&ED project: Machine learning algorithm optimization. Technical problem: Existing algorithms have an accuracy of 70%. Work performed: Tested 5 different algorithms, conducted 20 experiments. Results: New algorithm achieved an accuracy of 85%."
              },
              {
                  "fileId": "test-002",
                  "filename": "project.txt", 
                  "text": "Development of a novel machine learning algorithm that can achieve 95% accuracy on sparse datasets while reducing computational requirements by 40% compared to existing solutions."
              }
          ],
          "model": "gpt-4o",
          "include": {
              "evidenceBlurb": True,
              "ieee": True,
              "misc": True,
              "l242": True,
              "l244": True,
              "l246": True
          }

      请求示例代码

      Shell
      JavaScript
      Java
      Swift
      Go
      PHP
      Python
      HTTP
      C
      C#
      Objective-C
      Ruby
      OCaml
      Dart
      R
      请求示例请求示例
      Shell
      JavaScript
      Java
      Swift
      curl --location --request POST 'http://localhost:8000/api/v1/sred/generate' \
      --header 'Content-Type: application/json' \
      --data-raw '"files": [
              {
                  "fileId": "test-001",
                  "filename": "project.txt", 
                  "text": "SR&ED project: Machine learning algorithm optimization. Technical problem: Existing algorithms have an accuracy of 70%. Work performed: Tested 5 different algorithms, conducted 20 experiments. Results: New algorithm achieved an accuracy of 85%."
              },
              {
                  "fileId": "test-002",
                  "filename": "project.txt", 
                  "text": "Development of a novel machine learning algorithm that can achieve 95% accuracy on sparse datasets while reducing computational requirements by 40% compared to existing solutions."
              }
          ],
          "model": "gpt-4o",
          "include": {
              "evidenceBlurb": True,
              "ieee": True,
              "misc": True,
              "l242": True,
              "l244": True,
              "l246": True
          }'

      返回响应

      🟢200成功
      application/json
      Body

      示例
      {}
      修改于 2025-09-30 02:30:56
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