Add examples/: connector docs, OpenAPI for new endpoints, Hub listing copy, Stripe test script

examples/README.md

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+# RevAI — POST request examples
+
+All POST endpoints require header `Content-Type: application/json` (except
+`/v1/analyze/call*`, which is multipart). Gateway also injects auth headers.
+
+## /v1/predict/churn  (JSON)
+{"data":[{"customer_id":"C1","tenure_days":45,"days_since_last_login":18,"login_frequency_7d":1,"payment_delays_90d":2,"support_tickets_last_30d":4,"contract_type":"Month-to-Month","nps_score":3,"feature_adoption_score":45,"avg_session_minutes":8}]}
+
+## /v1/predict/lead  (JSON)
+{"data":[{"lead_id":"L1","demo_requested":1,"budget_confirmed":1,"engagement_score":80,"source":"referral"}]}
+
+## /v1/train  (JSON, >=50 rows)  -> see train_body.json
+{"data":[ ...>=50 rows, each with feature cols + a 0/1 label col... ],
+ "target_column":"churned","model_type":"churn","model_name":"my-model"}
+
+## /v1/analyze/call  (multipart/form-data, NOT json)
+Fields:
+  file           = <audio file: .mp3 .wav .m4a .mp4 .ogg .webm>
+  openai_api_key = sk-...   (caller supplies their own OpenAI key for Whisper)
+curl example:
+  curl -X POST https://revai1.p.rapidapi.com/v1/analyze/call \
+    -H "X-RapidAPI-Host: revai1.p.rapidapi.com" \
+    -H "X-RapidAPI-Key: <KEY>" \
+    -F "file=@call.mp3" \
+    -F "openai_api_key=sk-..."
+
+## /v1/predict/csv  (multipart — upload a spreadsheet, no JSON needed)
+The friction-killer. One column per signal, one row per customer/lead.
+Fields:
+  file       = your .csv export  (see sample_customers.csv)
+  model_type = churn | lead       (default churn)
+  model_id   = <optional trained model id>
+curl:
+  curl -X POST https://revai1.p.rapidapi.com/v1/predict/csv \
+    -H "X-RapidAPI-Host: revai1.p.rapidapi.com" -H "X-RapidAPI-Key: <KEY>" \
+    -F "file=@customers.csv" -F "model_type=churn"
+Blank cells are fine (we use sensible defaults). Returns the same scored
+JSON as /v1/predict/churn — score, risk level, and the reasons.
+
+NOTE: RapidAPI's gateway only forwards endpoints you've DEFINED in the API.
+Add /v1/predict/csv to the RapidAPI endpoint list or the gateway returns 404.
+
+## /v1/connect/stripe  (JSON — paste a read-only Stripe key, auto-score customers)
+No data prep at all. We pull the caller's recent Stripe customers and derive
+churn signals from billing: tenure, payment delays (90d), subscription status
+(past_due / canceled fire strong rules), contract type, monthly spend.
+The key is used in-memory and NEVER stored. RevAI pays Stripe nothing.
+Body:
+  {"stripe_key":"rk_live_...", "limit":100, "model_type":"churn", "model_id":null}
+curl:
+  curl -X POST https://revai1.p.rapidapi.com/v1/connect/stripe \
+    -H "X-RapidAPI-Host: revai1.p.rapidapi.com" -H "X-RapidAPI-Key: <KEY>" \
+    -H "Content-Type: application/json" \
+    -d '{"stripe_key":"rk_live_...","limit":100}'
+Tell customers to use a RESTRICTED key (read-only: Customers, Invoices,
+Subscriptions). Returns the same scored JSON as /v1/predict/churn.
+
+NOTE: like every endpoint, add /v1/connect/stripe to your RapidAPI endpoint
+list or the gateway returns 404.
+
+## /v1/predict/smart  (JSON — UNIVERSAL connector, send ANY column names)
+The real friction-killer. You don't need our exact field names. Send your rows
+as-is; we auto-detect columns (last_seen -> days_since_last_login, signup_date
+-> tenure_days, plan -> contract_type, ...) and even derive durations from
+dates. Response includes a `field_mapping` report (matched / missing / ignored)
+so it's fully transparent.
+Body:
+  {"data":[{"account_id":"ACME","signup_date":"2024-01-10","last_seen":"2026-05-10",
+            "plan":"Monthly","missed_payments":3,"nps":2}],
+   "model_type":"churn",
+   "mapping": {"tenure_days":"signup_date"}   // OPTIONAL explicit overrides
+  }
+Auto-derives: signup/created dates -> tenure_days; last-login dates ->
+days_since_last_login; pipeline-entry dates -> days_in_pipeline.
+This is the recommended entry point for most customers — it makes Stripe/CSV/
+HubSpot/raw exports all "just work".

examples/hub_listing_docs.md

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+# RevAI — Hub Listing copy (paste into RapidAPI description / endpoint docs)
+
+> Explainable churn prediction & lead scoring. Send your customer data — by
+> spreadsheet, raw JSON, or a one-click Stripe connect — and get a risk score
+> **with the reasons behind it**, plus optional custom models trained on your
+> own data.
+
+## Quick start (most users): /v1/predict/smart
+Send rows with **whatever column names you already have** — we auto-map them.
+All POSTs require `Content-Type: application/json`.
+
+```
+POST /v1/predict/smart
+Content-Type: application/json
+
+{"data":[
+  {"account_id":"ACME","signup_date":"2024-01-10","last_seen":"2026-05-10",
+   "plan":"Monthly","missed_payments":3,"nps":2}
+],"model_type":"churn"}
+```
+Returns each row scored (0–100), a risk level, the **reasons**, and a
+`field_mapping` report showing which of your columns mapped to which signal.
+
+## Upload a spreadsheet: /v1/predict/csv  (multipart)
+```
+POST /v1/predict/csv      (multipart/form-data)
+file=@customers.csv  model_type=churn
+```
+
+## Connect Stripe: /v1/connect/stripe
+Paste a **restricted, read-only** Stripe key; we derive churn signals from
+billing (tenure, payment delays, subscription status). Key is never stored.
+```
+POST /v1/connect/stripe
+Content-Type: application/json
+{"stripe_key":"rk_live_...","limit":100,"model_type":"churn"}
+```
+
+## Classic (exact fields): /v1/predict/churn and /v1/predict/lead
+```
+POST /v1/predict/churn
+Content-Type: application/json
+{"data":[{"customer_id":"C1","tenure_days":45,"days_since_last_login":18,
+  "login_frequency_7d":1,"payment_delays_90d":2,"support_tickets_last_30d":4,
+  "contract_type":"Month-to-Month","nps_score":3,"feature_adoption_score":45,
+  "avg_session_minutes":8}]}
+```
+```
+POST /v1/predict/lead
+Content-Type: application/json
+{"data":[{"lead_id":"L1","demo_requested":1,"budget_confirmed":1,
+  "engagement_score":80,"source":"referral"}]}
+```
+
+## Train a custom model: /v1/train  (≥50 labeled rows)
+```
+POST /v1/train
+Content-Type: application/json
+{"data":[ /* ≥50 rows, each with features + a 0/1 label */ ],
+ "target_column":"churned","model_type":"churn","model_name":"my-model"}
+```
+Then pass the returned `model_id` to any predict endpoint to use your model.
+
+## Analyze a support call: /v1/analyze/call  (multipart)
+```
+POST /v1/analyze/call   (multipart/form-data)
+file=@call.mp3   openai_api_key=sk-...    # you supply your own OpenAI key
+```
+
+---
+**Common mistake:** a POST with no body returns `422 Field required`. That's
+expected — the API needs your data. Always send the JSON body (and the
+`Content-Type: application/json` header).

examples/new_endpoints.openapi.json

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+{
+  "openapi": "3.1.0",
+  "info": {
+    "title": "RevAI API \u2014 new connector endpoints",
+    "version": "1.0.0"
+  },
+  "servers": [
+    {
+      "url": "https://shaankar39-revai-api.hf.space"
+    }
+  ],
+  "paths": {
+    "/v1/predict/smart": {
+      "post": {
+        "tags": [
+          "Prediction"
+        ],
+        "summary": "Predict Smart",
+        "description": "Universal connector \u2014 send rows with ANY column names. We auto-map them\nto RevAI's signals (and derive durations from dates), then score. The\nresponse includes a `field_mapping` report of what was matched/missed.",
+        "operationId": "predict_smart_v1_predict_smart_post",
+        "requestBody": {
+          "content": {
+            "application/json": {
+              "schema": {
+                "$ref": "#/components/schemas/SmartPredictInput"
+              }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/PredictionResponse"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/HTTPValidationError"
+                }
+              }
+            }
+          }
+        },
+        "security": [
+          {
+            "APIKeyHeader": []
+          }
+        ]
+      }
+    },
+    "/v1/predict/csv": {
+      "post": {
+        "tags": [
+          "Prediction"
+        ],
+        "summary": "Predict Csv",
+        "description": "Upload a CSV instead of hand-building JSON. One column per signal,\none row per customer/lead \u2014 we parse it and score every row.",
+        "operationId": "predict_csv_v1_predict_csv_post",
+        "requestBody": {
+          "content": {
+            "multipart/form-data": {
+              "schema": {
+                "$ref": "#/components/schemas/Body_predict_csv_v1_predict_csv_post"
+              }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/PredictionResponse"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/HTTPValidationError"
+                }
+              }
+            }
+          }
+        },
+        "security": [
+          {
+            "APIKeyHeader": []
+          }
+        ]
+      }
+    },
+    "/v1/connect/stripe": {
+      "post": {
+        "tags": [
+          "connectors"
+        ],
+        "summary": "Connect Stripe",
+        "description": "Paste a read-only Stripe key \u2192 we pull your recent customers, derive\nbilling-based churn signals (tenure, payment delays, subscription status,\ncontract type), and score them. The key is used in-memory and never stored.",
+        "operationId": "connect_stripe_v1_connect_stripe_post",
+        "requestBody": {
+          "content": {
+            "application/json": {
+              "schema": {
+                "$ref": "#/components/schemas/StripeConnectInput"
+              }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/PredictionResponse"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/HTTPValidationError"
+                }
+              }
+            }
+          }
+        },
+        "security": [
+          {
+            "APIKeyHeader": []
+          }
+        ]
+      }
+    }
+  },
+  "components": {
+    "schemas": {
+      "Body_predict_csv_v1_predict_csv_post": {
+        "properties": {
+          "file": {
+            "type": "string",
+            "contentMediaType": "application/octet-stream",
+            "title": "File",
+            "description": "CSV export of your customers/leads"
+          },
+          "model_type": {
+            "type": "string",
+            "title": "Model Type",
+            "description": "'churn' or 'lead'",
+            "default": "churn"
+          },
+          "model_id": {
+            "type": "string",
+            "title": "Model Id",
+            "description": "Optional trained model ID"
+          }
+        },
+        "type": "object",
+        "required": [
+          "file"
+        ],
+        "title": "Body_predict_csv_v1_predict_csv_post"
+      },
+      "HTTPValidationError": {
+        "properties": {
+          "detail": {
+            "items": {
+              "$ref": "#/components/schemas/ValidationError"
+            },
+            "type": "array",
+            "title": "Detail"
+          }
+        },
+        "type": "object",
+        "title": "HTTPValidationError"
+      },
+      "PredictionResponse": {
+        "properties": {
+          "predictions": {
+            "items": {
+              "$ref": "#/components/schemas/SinglePrediction"
+            },
+            "type": "array",
+            "title": "Predictions"
+          },
+          "model_used": {
+            "type": "string",
+            "title": "Model Used"
+          },
+          "usage": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Usage"
+          },
+          "benchmark": {
+            "anyOf": [
+              {
+                "additionalProperties": true,
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Benchmark"
+          },
+          "field_mapping": {
+            "anyOf": [
+              {
+                "additionalProperties": true,
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Field Mapping"
+          }
+        },
+        "type": "object",
+        "required": [
+          "predictions",
+          "model_used",
+          "usage"
+        ],
+        "title": "PredictionResponse"
+      },
+      "RiskFactor": {
+        "properties": {
+          "rule": {
+            "type": "string",
+            "title": "Rule"
+          },
+          "points": {
+            "type": "integer",
+            "title": "Points"
+          },
+          "detail": {
+            "type": "string",
+            "title": "Detail"
+          }
+        },
+        "type": "object",
+        "required": [
+          "rule",
+          "points",
+          "detail"
+        ],
+        "title": "RiskFactor"
+      },
+      "SinglePrediction": {
+        "properties": {
+          "index": {
+            "type": "integer",
+            "title": "Index"
+          },
+          "score": {
+            "type": "number",
+            "title": "Score"
+          },
+          "risk_level": {
+            "type": "string",
+            "title": "Risk Level"
+          },
+          "recommended_action": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Recommended Action"
+          },
+          "risk_factors": {
+            "items": {
+              "$ref": "#/components/schemas/RiskFactor"
+            },
+            "type": "array",
+            "title": "Risk Factors",
+            "default": []
+          },
+          "scoring_mode": {
+            "type": "string",
+            "title": "Scoring Mode"
+          },
+          "customer_id": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Customer Id"
+          },
+          "input_fields": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Input Fields",
+            "default": {}
+          }
+        },
+        "type": "object",
+        "required": [
+          "index",
+          "score",
+          "risk_level",
+          "scoring_mode"
+        ],
+        "title": "SinglePrediction"
+      },
+      "SmartPredictInput": {
+        "properties": {
+          "data": {
+            "items": {
+              "additionalProperties": true,
+              "type": "object"
+            },
+            "type": "array",
+            "maxItems": 1000,
+            "minItems": 1,
+            "title": "Data",
+            "description": "Your rows with WHATEVER column names you already have"
+          },
+          "mapping": {
+            "anyOf": [
+              {
+                "additionalProperties": {
+                  "type": "string"
+                },
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Mapping",
+            "description": "Optional {canonical_signal: your_column} overrides; auto-detected otherwise"
+          },
+          "model_type": {
+            "type": "string",
+            "title": "Model Type",
+            "description": "'churn' or 'lead'",
+            "default": "churn"
+          },
+          "model_id": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Model Id",
+            "description": "Optional trained model ID"
+          }
+        },
+        "type": "object",
+        "required": [
+          "data"
+        ],
+        "title": "SmartPredictInput"
+      },
+      "StripeConnectInput": {
+        "properties": {
+          "stripe_key": {
+            "type": "string",
+            "title": "Stripe Key",
+            "description": "Your restricted, read-only Stripe key (rk_live_\u2026 or sk_\u2026)"
+          },
+          "limit": {
+            "type": "integer",
+            "maximum": 100.0,
+            "minimum": 1.0,
+            "title": "Limit",
+            "description": "How many recent customers to score",
+            "default": 100
+          },
+          "model_type": {
+            "type": "string",
+            "title": "Model Type",
+            "description": "'churn' or 'lead'",
+            "default": "churn"
+          },
+          "model_id": {
+            "anyOf": [
+              {
+                "type": "string"
+              },
+              {
+                "type": "null"
+              }
+            ],
+            "title": "Model Id",
+            "description": "Optional trained model ID"
+          }
+        },
+        "type": "object",
+        "required": [
+          "stripe_key"
+        ],
+        "title": "StripeConnectInput"
+      },
+      "ValidationError": {
+        "properties": {
+          "loc": {
+            "items": {
+              "anyOf": [
+                {
+                  "type": "string"
+                },
+                {
+                  "type": "integer"
+                }
+              ]
+            },
+            "type": "array",
+            "title": "Location"
+          },
+          "msg": {
+            "type": "string",
+            "title": "Message"
+          },
+          "type": {
+            "type": "string",
+            "title": "Error Type"
+          },
+          "input": {
+            "title": "Input"
+          },
+          "ctx": {
+            "type": "object",
+            "title": "Context"
+          }
+        },
+        "type": "object",
+        "required": [
+          "loc",
+          "msg",
+          "type"
+        ],
+        "title": "ValidationError"
+      }
+    }
+  }
+}

examples/rapidapi_setup.md

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+# RapidAPI — add the 3 new connector endpoints
+
+The gateway only forwards endpoints defined in your RapidAPI API. Add these so
+buyers can reach them. Two ways:
+
+## Option A (fastest): re-import the OpenAPI
+RapidAPI Provider → your API → **Definitions / Import** → import from URL:
+    https://shaankar39-revai-api.hf.space/openapi.json
+This already contains ALL endpoints (old + new). Or upload the trimmed file
+`new_endpoints.openapi.json` (just the 3 new ones).
+
+## Option B: add each manually
+Provider → your API → **Endpoints → Create REST Endpoint**.
+
+### 1) Universal connector  (recommended default)
+- Name: Predict Smart
+- Method: **POST**
+- Path: **/v1/predict/smart**
+- Header: `Content-Type: application/json`
+- Body (JSON):
+  {"data":[{"account_id":"ACME","signup_date":"2024-01-10","last_seen":"2026-05-10","plan":"Monthly","missed_payments":3,"nps":2}],"model_type":"churn"}
+
+### 2) CSV upload
+- Name: Predict CSV
+- Method: **POST**
+- Path: **/v1/predict/csv**
+- Body type: **multipart/form-data**, fields:
+    file        (type: file)    — the customer's CSV
+    model_type  (type: text)    — "churn" or "lead"
+    model_id    (type: text, optional)
+
+### 3) Stripe connector
+- Name: Connect Stripe
+- Method: **POST**
+- Path: **/v1/connect/stripe**
+- Header: `Content-Type: application/json`
+- Body (JSON):
+  {"stripe_key":"rk_live_...","limit":100,"model_type":"churn"}
+
+After adding, hit **Send** on each in Studio to confirm 200 (the smart/csv ones
+work immediately; stripe needs a real read-only key).

examples/sample_customers.csv

@@ -0,0 +1,4 @@
+customer_id,tenure_days,days_since_last_login,login_frequency_7d,payment_delays_90d,support_tickets_last_30d,contract_type,nps_score,feature_adoption_score,avg_session_minutes
+C1,45,18,1,2,4,Month-to-Month,3,45,8
+C2,720,1,12,0,0,Annual,9,88,40
+C3,30,25,0,3,6,Month-to-Month,2,20,3

examples/test_stripe.sh

@@ -0,0 +1,23 @@
+#!/usr/bin/env bash
+# Smoke-test the Stripe connector with YOUR Stripe test key.
+# Usage:  ./test_stripe.sh  rk_test_xxx   [limit]
+#
+# Use a RESTRICTED, READ-ONLY test-mode key (Stripe Dashboard → Developers →
+# API keys → Create restricted key → read access: Customers, Invoices,
+# Subscriptions). Make sure your Stripe TEST account has a couple of customers.
+# The key is sent to the live Space over HTTPS, used in-memory, and not stored.
+
+set -euo pipefail
+KEY="${1:?Pass your Stripe test key: ./test_stripe.sh rk_test_xxx [limit]}"
+LIMIT="${2:-25}"
+BASE="https://shaankar39-revai-api.hf.space"
+
+# These two headers simulate the RapidAPI gateway. For a real gateway call,
+# use your RapidAPI key against revai1.p.rapidapi.com instead.
+curl -s -m60 \
+  -H "X-RapidAPI-User: stripe-smoke" \
+  -H "X-RapidAPI-Proxy-Secret: ${REVAI_PROXY_SECRET:?export REVAI_PROXY_SECRET=<your gateway proxy secret>}" \
+  -H "Content-Type: application/json" \
+  -X POST "$BASE/v1/connect/stripe" \
+  -d "{\"stripe_key\":\"$KEY\",\"limit\":$LIMIT,\"model_type\":\"churn\"}" \
+| python3 -m json.tool

examples/train_body.json

@@ -0,0 +1 @@
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2, "churned": 1}], "target_column": "churned", "model_type": "churn", "model_name": "churn-demo-v1"}