Schéma JSON : extraire un CV

JSON Schema pour extraire un CV avec un LLM : expériences, compétences, langues et formation, prêt pour les sorties structurées.

Extrais les informations du CV. N'invente rien : si une information manque, laisse le champ vide. Ne déduis ni l'âge, ni la situation familiale, ni l'origine.

JSON Schema

{
  "type": "object",
  "required": [
    "nom",
    "experiences",
    "competences"
  ],
  "properties": {
    "nom": {
      "type": "string"
    },
    "titre": {
      "type": "string",
      "description": "Intitulé du poste recherché ou actuel"
    },
    "langues": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "langue": {
            "type": "string"
          },
          "niveau": {
            "type": "string"
          }
        }
      }
    },
    "formation": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "annee": {
            "type": "string"
          },
          "diplome": {
            "type": "string"
          },
          "etablissement": {
            "type": "string"
          }
        }
      }
    },
    "competences": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "experiences": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "poste",
          "entreprise"
        ],
        "properties": {
          "fin": {
            "type": "string"
          },
          "debut": {
            "type": "string"
          },
          "poste": {
            "type": "string"
          },
          "entreprise": {
            "type": "string"
          }
        }
      }
    },
    "annees_experience": {
      "type": "number"
    }
  }
}

Estimated cost

Input tokens per call : ≈ 578

Input cost only, excluding the model's answer. Providers' public standard prices (Mistral AI, DeepSeek, OpenAI, Anthropic) converted from USD to euros at the ECB rate of September 29, 2026. Estimate: 1 token ≈ 3.6 characters.

Identifier

contextetech--extraire-un-cv

Type

Output schemas

File

extraire-un-cv.schema.json

Format

JSON (application/json)

Size

1,479 bytes (1.4 KB)

Encoding

UTF-8

Estimated tokens

≈ 410

Language

French

License

MIT

Commercial use

Allowed

Personal data

None

Version

1.0

Published on

October 1, 2026 at 6:55 PM

Updated on

October 1, 2026 at 6:55 PM

Storage

in database

Uses

0

Likes

0

extraire-un-cv.schema.json

{
  "type": "object",
  "required": [
    "nom",
    "experiences",
    "competences"
  ],
  "properties": {
    "nom": {
      "type": "string"
    },
    "titre": {
      "type": "string",
      "description": "Intitulé du poste recherché ou actuel"
    },
    "langues": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "langue": {
            "type": "string"
          },
          "niveau": {
            "type": "string"
          }
        }
      }
    },
    "formation": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "annee": {
            "type": "string"
          },
          "diplome": {
            "type": "string"
          },
          "etablissement": {
            "type": "string"
          }
        }
      }
    },
    "competences": {
      "type": "array",
      "items": {
        "type": "string"
      }
    },
    "experiences": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "poste",
          "entreprise"
        ],
        "properties": {
          "fin": {
            "type": "string"
          },
          "debut": {
            "type": "string"
          },
          "poste": {
            "type": "string"
          },
          "entreprise": {
            "type": "string"
          }
        }
      }
    },
    "annees_experience": {
      "type": "number"
    }
  }
}

Anthropic API (Python)

import json, anthropic

schema = json.load(open("extraire-un-cv.schema.json"))
client = anthropic.Anthropic()
resp = client.messages.create(model="claude-sonnet-5", max_tokens=1024,
    tools=[{"name": "extraire", "description": "Renvoie les données extraites", "input_schema": schema}],
    tool_choice={"type": "tool", "name": "extraire"},
    messages=[{"role": "user", "content": "your input here"}])
print(resp.content[0].input)

OpenAI format (response_format)

{
  "type": "json_schema",
  "json_schema": {
    "name": "extraire-un-cv",
    "schema": {
      "type": "object",
      "required": [
        "nom",
        "experiences",
        "competences"
      ],
      "properties": {
        "nom": {
          "type": "string"
        },
        "titre": {
          "type": "string",
          "description": "Intitulé du poste recherché ou actuel"
        },
        "langues": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "langue": {
                "type": "string"
              },
              "niveau": {
                "type": "string"
              }
            }
          }
        },
        "formation": {
          "type": "array",
          "items": {
            "type": "object",
            "properties": {
              "annee": {
                "type": "string"
              },
              "diplome": {
                "type": "string"
              },
              "etablissement": {
                "type": "string"
              }
            }
          }
        },
        "competences": {
          "type": "array",
          "items": {
            "type": "string"
          }
        },
        "experiences": {
          "type": "array",
          "items": {
            "type": "object",
            "required": [
              "poste",
              "entreprise"
            ],
            "properties": {
              "fin": {
                "type": "string"
              },
              "debut": {
                "type": "string"
              },
              "poste": {
                "type": "string"
              },
              "entreprise": {
                "type": "string"
              }
            }
          }
        },
        "annees_experience": {
          "type": "number"
        }
      }
    },
    "strict": true
  }
}