### Credily API - Make Predictions from External Data Sources
### Use with VS Code REST Client, Insomnia, or Postman

@baseUrl = http://localhost:8000
@model_path = C:/credily/models/credit_model.pkl

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### 1. PREDICT FROM PostgreSQL DATABASE
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POST {{baseUrl}}/api/predict-from-source
Content-Type: application/json

{
  "data_source": {
    "source_type": "database",
    "database_type": "postgres",
    "connection_string": "postgresql://user:password@localhost:5432/credit_db",
    "query": "SELECT age, income, credit_score, loan_amount, debt_to_income FROM new_loan_applications WHERE processed = false"
  },
  "model_path": "{{model_path}}",
  "include_proba": true,
  "save_results": true
}

###############################################################################
### 2. PREDICT FROM REST API
###############################################################################

POST {{baseUrl}}/api/predict-from-source
Content-Type: application/json

{
  "data_source": {
    "source_type": "api",
    "url": "https://api.example.com/v1/pending-applications",
    "method": "GET",
    "headers": {
      "Accept": "application/json"
    },
    "auth": {
      "type": "bearer",
      "token": "your-api-token"
    },
    "json_path": "data.applications"
  },
  "model_path": "{{model_path}}",
  "threshold": 0.45,
  "include_proba": true,
  "save_results": true
}

###############################################################################
### 3. PREDICT FROM GraphQL ENDPOINT
###############################################################################

POST {{baseUrl}}/api/predict-from-source
Content-Type: application/json

{
  "data_source": {
    "source_type": "graphql",
    "url": "https://api.example.com/graphql",
    "graphql_query": "query GetPendingApplications($status: String!) { loanApplications(status: $status) { id age income creditScore loanAmount } }",
    "graphql_variables": {
      "status": "pending_review"
    },
    "headers": {
      "Authorization": "Bearer your-token"
    },
    "json_path": "data.loanApplications"
  },
  "model_path": "{{model_path}}",
  "include_proba": true
}

###############################################################################
### 4. PREDICT FROM MongoDB
###############################################################################

POST {{baseUrl}}/api/predict-from-source
Content-Type: application/json

{
  "data_source": {
    "source_type": "database",
    "database_type": "mongodb",
    "connection_string": "mongodb://user:password@localhost:27017/",
    "query": "{\"database\": \"credit_db\", \"collection\": \"pending_applications\", \"query\": {\"status\": \"pending\"}}"
  },
  "model_path": "{{model_path}}",
  "save_results": true
}

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### 5. PREDICT FROM CSV FILE URL
###############################################################################

POST {{baseUrl}}/api/predict-from-source
Content-Type: application/json

{
  "data_source": {
    "source_type": "url",
    "url": "https://storage.example.com/predictions/pending_loans.csv",
    "format": "csv"
  },
  "model_path": "{{model_path}}",
  "threshold": 0.5,
  "include_proba": true,
  "save_results": true
}

###############################################################################
### 6. PREDICT WITH CUSTOM THRESHOLD
###############################################################################

POST {{baseUrl}}/api/predict-from-source
Content-Type: application/json

{
  "data_source": {
    "source_type": "api",
    "url": "https://api.example.com/v1/applications-to-score",
    "auth": {
      "type": "bearer",
      "token": "token"
    },
    "json_path": "data"
  },
  "model_path": "{{model_path}}",
  "threshold": 0.35,
  "include_proba": true,
  "save_results": true
}