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Facebook Videos Scraper & Spoken Text Transcript

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Facebook Videos Scraper: Extract video details, captions, creators, URLs, views, likes, comments, shares, timestamps, and engagement metrics. Generate spoken-text transcripts from videos to analyze keywords, topics, content trends, competitor activity, and audience engagement.

Pricing

from $5.99 / 1,000 results

Rating

0.0

(0)

Developer

Scrapier

Actor stats

Bookmarked

Total users

Monthly active users

16 days ago

Last modified

Categories

Lead generation

Social media

Videos

You can access the Facebook Videos Scraper & Spoken Text Transcript programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

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      "inputSchema": {
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          "videoUrls": {
            "title": "🎬 Facebook Reel URLs",
            "type": "array",
            "description": "Public Facebook Reel links, one per line — for example https://www.facebook.com/reel/1076980157988172. Reel URLs are the surface that carries video data logged-out; /username/videos/<id>/ and /watch/?v= pages do not contain the requested video and are returned as uncharged empty rows. The legacy 'urls' input key is still accepted.",
            "items": {
              "type": "string"
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          },
          "textExtraction": {
            "title": "🗣️ Spoken text source",
            "enum": [
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              "captionsOnly",
              "speechToTextOnly",
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            ],
            "type": "string",
            "description": "How to obtain the spoken words. 'auto' uses the platform caption track and falls back to speech-to-text only if you enabled it below. 'captionsOnly' never calls an external service. Rows always state which path was used.",
            "default": "auto"
          },
          "transcriptFormat": {
            "title": "📝 Transcript format",
            "enum": [
              "text",
              "srt",
              "vtt",
              "cues"
            ],
            "type": "string",
            "description": "Shape of the 'transcript' column. 'text' is one readable paragraph with no timecodes; 'srt' and 'vtt' are subtitle files you can ship straight to a player; 'cues' is a JSON array of {start, end, text} for programmatic use.",
            "default": "text"
          },
          "captionLanguage": {
            "title": "🌐 Preferred caption language",
            "type": "string",
            "description": "Locale to prefer, such as en_US or just en. Facebook often publishes an original auto-generated track plus machine-translated locales. Leave blank to take the video's first listed track. If you name a language the video does not have, the row says 'requested_language_not_available' rather than quietly returning a different language."
          },
          "enableSpeechToText": {
            "title": "🎙️ Enable speech-to-text fallback",
            "type": "boolean",
            "description": "Off by default. When on, Reels with no caption track have their audio sent to the transcription endpoint below. This calls a third-party service you pay for directly and adds runtime. Rows produced this way are stamped transcriptIsOfficialCaptionTrack=false so a machine transcript is never mistaken for a publisher caption.",
            "default": false
          },
          "speechToTextApiKey": {
            "title": "🔑 Transcription API key",
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          },
          "speechToTextApiUrl": {
            "title": "🔗 Transcription endpoint",
            "type": "string",
            "description": "Any OpenAI-compatible /audio/transcriptions endpoint. Defaults to https://api.openai.com/v1/audio/transcriptions.",
            "default": "https://api.openai.com/v1/audio/transcriptions"
          },
          "speechToTextModel": {
            "title": "🧠 Transcription model",
            "type": "string",
            "description": "Model name passed to the endpoint, for example whisper-1.",
            "default": "whisper-1"
          },
          "speechToTextMaxAudioMb": {
            "title": "📦 Audio size cap (MB)",
            "minimum": 1,
            "maximum": 24,
            "type": "integer",
            "description": "Stop downloading audio after this many megabytes before transcribing. Values are clamped to 1–24 MB to stay under typical upload limits.",
            "default": 20
          },
          "proxyConfiguration": {
            "title": "🔒 Proxy",
            "type": "object",
            "description": "Optional. Facebook Reel pages resolved without a proxy in testing; enable a proxy if you hit blocks at volume."
          }
        }
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Facebook Videos Scraper & Spoken Text Transcript OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for Facebook Videos Scraper & Spoken Text Transcript from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

Facebook Videos Scraper & Spoken Text Transcript API in Python

Facebook Videos Scraper & Spoken Text Transcript API in JavaScript

Facebook Videos Scraper & Spoken Text Transcript API through CLI

Facebook Videos Scraper & Spoken Text Transcript API

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