Generate AI Videos from Text or Images with Sora 2/Pro & GPT-5 Enhancement — n8n Workflow

Mittel Komplexität Auslöser13 Knoten AI👁 18 Aufrufevon Daniel Nkencho

Übersicht

Harness OpenAI's Sora 2 for instant video creation from text or images using fal.ai's API—powered by GPT-5 for refined prompts that ensure cinematic quality. This template processes form submissions, intelligently routes to text-to-video (with mandatory prompt enhancement) or image-to-video modes, and polls for completion before redirecting to your generated clip.

📋 What This Template Does Users submit prompts, aspect ratios (9:16 or 16:9), models (sora-2 or pro), durations (4s, 8s, or 12s), an

Verwendete Knoten

HTTP RequestBasic LLM ChainOpenAI Chat ModelStructured Output Parser

Workflow-Vorschau

🔀 Input Mode Router
Purpose: Branches to image-to-video if file uploaded, e
Note: Switch checks filename; ensures GPT-5 processes t
🖼️ Temp Image Upload
Purpose: Uploads reference image to tmpfiles.org for So
Note: Multipart POST; swaps URL to /dl/ for direct API
🤖 Prompt Refiner
Purpose: Uses GPT-5 to enhance text prompts for Sora 2
Note: Mandatory for text branch; outputs JSON with refi
🔍 JSON Output Parser
Purpose: Validates GPT-5 response against schema for cl
Note: Ensures prompt (50-4000 chars), ratio (16:9/9:16)
🎥 Text-to-Video Call
Purpose: Submits refined prompt to fal.ai Sora 2 text e
Note: Uses 720p res; calls /text-to-video or /pro; retu
🖼️ Image-to-Video Call
Purpose: Sends raw prompt + image URL to fal.ai Sora 2
Note: Auto res; calls /image-to-video or /pro; uses for
🎬 Sora 2 Video Generator via Fal with GPT-5
📋 What This Template Does
Generate videos using OpenAI's Sora 2 via fal.ai's four
📝 Video Input Form
Purpose: Captures user prompt, ratio, model, duration,
Note: Required fields validated; activates webhook URL
⏳ Status Polling Loop
Purpose: Waits 60s, checks Sora status, loops until COM
Note: Switch routes to result or retry; handles all fou
modelparser
V
Video Input Form
Prompt Refiner
JSON Output Parser
Temp Image Upload
Text-to-Video Call
I
Input Mode Router
Image-to-Video Call
W
Wait 60 Seconds
Status Check
S
Status Router
Retrieve Video
V
Video Redirect
Refiner Model
13 nodes14 edges

So funktioniert es

  1. 1

    Auslöser

    Der Workflow startet mit einem auslöser-Auslöser.

  2. 2

    Verarbeitung

    Die Daten fließen durch 13 Knoten, connecting chainllm, form, formtrigger.

  3. 3

    Ausgabe

    Der Workflow schließt seine Automatisierung ab und liefert das Ergebnis an das konfigurierte Ziel.

Knotendetails (13)

HT

HTTP Request

httpRequest

#1
BA

Basic LLM Chain

n8n-nodes-langchain.chainLlm

#2
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#3
ST

Structured Output Parser

n8n-nodes-langchain.outputParserStructured

#4

So importieren Sie diesen Workflow

  1. 1Klicken Sie rechts auf die Schaltfläche JSON herunterladen, um die Workflow-Datei zu speichern.
  2. 2Öffnen Sie Ihre n8n-Instanz. Gehen Sie zu Workflows → Neu → Aus Datei importieren.
  3. 3Wählen Sie die heruntergeladene Datei generate-ai-videos-from-text-or-images-with-sora-2pro-gpt-5-enhancement und klicken Sie auf Importieren.
  4. 4Richten Sie Anmeldedaten für jeden Dienstknoten ein (API-Schlüssel, OAuth usw.).
  5. 5Klicken Sie auf Workflow testen, um zu überprüfen, ob alles funktioniert, und aktivieren Sie es dann.

Oder direkt in n8n → Aus JSON importieren einfügen:

{ "name": "Generate AI Videos from Text or Images with Sora 2/Pro & GPT-5 Enhancement", "nodes": [...], ...}

Integrationen

chainllmformformtriggerhttprequestlmchatopenaioutputparserstructuredswitchwait

Diesen Workflow holen

Herunterladen und mit einem Klick importieren

JSON herunterladenAuf n8n.io ansehen
Knoten13
Komplexitätmedium
Auslösertrigger
Aufrufe18
KategorieAI

Erstellt von

Daniel Nkencho

Daniel Nkencho

@daniel-automates

Tags

chainllmformformtriggerhttprequestlmchatopenaioutputparserstructuredswitchwait

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