# Review Insight AI (`pearlescent_idiom/review-insight-ai`) Actor

Turn customer reviews into sentiment, recurring themes, complaints, requests, and prioritized actions.

- **URL**: https://apify.com/pearlescent\_idiom/review-insight-ai.md
- **Developed by:** [Ezgi Uysal](https://apify.com/pearlescent_idiom) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $60.00 / 1,000 small review analyses

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Review Insight AI

Turn customer reviews into a clear, actionable business report without maintaining fragile website scrapers. Upload existing CSV, JSON, or text reviews and receive sentiment, recurring themes, complaints, requests, praise, and prioritized actions.

### What it produces

- Positive, neutral, and negative review counts
- Executive summary
- Ranked complaint, request, praise, question, and other themes
- Theme frequency and prevalence
- Business-impact severity from 1 to 5
- Suggested action for every theme
- Prioritized action list
- Short anonymized signals instead of long customer quotes

### Input

Use one or more of:

- `reviews`: up to 500 flexible JSON objects
- `files`: up to five CSV, JSON, TXT, or Markdown files
- `reviewsText`: pasted JSON, CSV, or one review per line

Field names can vary. Records may contain `text`, `review`, `rating`, `title`, `date`, `product`, or other useful fields.

```json
{
  "reviews": [
    { "rating": 5, "text": "Beautiful necklace and luxury packaging." },
    { "rating": 2, "text": "Shipping took too long." },
    { "rating": 3, "text": "Please add more chain lengths." }
  ],
  "outputLanguage": "English",
  "instructions": "Focus on product, delivery, and new collection opportunities."
}
```

### Reliable analysis flow

Reviews are processed in bounded batches and then synthesized into one report. Each stage uses strict JSON validation, exact sentiment totals, bounded occurrence counts, duplicate-theme checks, and correction retries. Review content is treated as untrusted data.

For privacy, the Actor asks for short paraphrased signals and excludes customer names, contact details, and long verbatim quotes from its output.

### Output

- Dataset: one ranked row per theme
- `OUTPUT.json`: executive summary, sentiment, themes, actions, and processing metadata
- `OUTPUT.csv`: UTF-8, Excel-compatible theme table
- `SUMMARY.json`: counts, batch information, and metering event

### Environment and local test

Set `LLM_API_KEY` or `OPENAI_API_KEY` in the environment. Optional settings are `LLM_MODEL`, `LLM_BASE_URL`, and `LLM_TIMEOUT_MS`.

```bash
pnpm install
pnpm test
export LLM_API_KEY="your-key"
export DISABLE_METERING=true
apify run --input-file samples/cloud-input.json
```

Never put API keys in input or source files. The deployed Actor uses an encrypted Apify secret.

### Deploy to Apify

```bash
apify login
apify push
```

Run `samples/cloud-input.json` and verify that delivery complaints, product praise, sizing requests, and action items appear in the outputs.

### Suggested pay-per-event pricing

One event is emitted only after the complete report has been saved:

| Event | Reviews per run | Suggested price |
| --- | ---: | ---: |
| `insight-small` | 1–25 | $0.06 |
| `insight-medium` | 26–100 | $0.20 |
| `insight-large` | 101–500 | $0.75 |

Review real token costs before later price changes.

### Publish in Apify Store

Keep the Actor private until sample and real-file tests pass. Then open **Actor → Publication**, select **Pay per event**, add the three exact event names above, complete the Store metadata, and submit it for review.

Suggested Store title: **Review Insight AI**

Suggested description: **Turn CSV, JSON, or text reviews into sentiment, recurring themes, complaints, feature requests, and prioritized actions.**

# Actor input Schema

## `reviews` (type: `array`):

Paste a JSON array of review objects. Fields can use any names, such as text, rating, title, date, or product.

## `files` (type: `array`):

Upload up to five UTF-8 CSV, JSON, TXT, or Markdown files containing reviews.

## `reviewsText` (type: `string`):

Paste JSON, CSV, or one review per non-empty line.

## `inputFormat` (type: `string`):

Automatic detection works for standard JSON and comma-separated CSV.

## `outputLanguage` (type: `string`):

Choose the language for summaries, theme names, and actions.

## `instructions` (type: `string`):

Optional product context, target audience, or business priorities.

## `retryCount` (type: `integer`):

Number of correction attempts for malformed or inconsistent analysis output.

## Actor input object example

```json
{
  "inputFormat": "auto",
  "outputLanguage": "English",
  "retryCount": 2
}
```

# Actor output Schema

## `themes` (type: `string`):

No description

## `json` (type: `string`):

No description

## `csv` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("pearlescent_idiom/review-insight-ai").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("pearlescent_idiom/review-insight-ai").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call pearlescent_idiom/review-insight-ai --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,pearlescent_idiom/review-insight-ai"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/8zAsMrf0A3dywnkKM/builds/MkG2nazem3yaXbAHi/openapi.json