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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsUse a template API when the scene layout stays the same, a direct video API when each clip is generated from a prompt, and an agent workflow when software must choose inputs, submit jobs, and recover from failures. In all three cases, treat rendering as asynchronous: save the job ID, status, input metadata, callback information, and output location instead of waiting in a web request.
This guide explains the architecture, compares the documented options, provides runnable request patterns in Python, JavaScript, and cURL, and shows how to scale personalized clips without coupling your application to one model.
The three layers of an AI video system
Reusable templates
A template is a fixed scene and layout with named variables. Your application supplies changing values such as a script, headline, image, or avatar while the composition remains stable. This is the right abstraction for sales-personalization, onboarding, localized announcements, and other high-volume jobs where brand rules must not drift.
Synthesia’s documented workflow is to build the template in its editor, add variables, publish it, copy the resulting template ID, and call the template endpoint with key-value data. The request requires templateId; metadata can include a title, description, visibility, and callback settings. Processing is asynchronous, so you either poll the returned job or receive a webhook.
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Direct generation APIs
A direct API creates a clip from a prompt and optional reference media. OpenAI’s Videos API exposes the sora-2 and sora-2-pro models. A create request can include a prompt, an input image or video reference, a duration of 4, 8, or 12 seconds, and one of these documented sizes: 720×1280, 1280×720, 1024×1792, or 1792×1024. The response represents a job rather than an immediately downloadable movie.
Agent orchestration
An agent adds decisions around either kind of API. It can select a template, rewrite a prompt, choose a model, submit a job, monitor moderation or rendering failures, and route the finished asset to storage or a publishing system. Keep those decisions separate from the provider adapter so a model change does not require rewriting business logic.
Choose an architecture before choosing a model
| Requirement | Best fit | Reason |
|---|---|---|
| Stable scenes with changing names, copy, media, or avatars | Template API | Variables change without rebuilding the composition. |
| Novel shots directed by text or reference media | Direct generation API | The prompt and optional reference are the primary inputs. |
| Multiple providers, policies, or fallback paths | Agent plus provider adapters | Routing and recovery stay in your application. |
| Broadcast or post-production deliverables | Provider exposing professional formats | Runway documents ProRes, PNG image sequences, 10-bit SDR, and HDR outputs for flagship workflows. |
Compare candidates on the same axes: template and variable support; text, image, or video inputs; duration and size limits; callbacks and status values; model routing; audio and editing controls; output formats; moderation states; and account or regional availability. Model names, limits, plans, and regional access change, so verify them in the provider documentation when you implement.
Building a template-driven pipeline
1. Design the variable contract
Define a versioned schema before opening the editor. For example, a product announcement might require customer_name, offer_text, hero_image, and locale. Decide which variables are required, their maximum lengths, allowed media types, and the fallback value for an empty field. Reject invalid data before creating a job; a failed render should not be your validation layer.
2. Publish and record the template ID
After adding variables, publish the template and store its ID with your own template version. Do not put the ID only in source code: a database record lets an agent select the correct language or campaign version and lets you retire an old layout safely.
3. Submit asynchronously
Send the template ID and a key-value object to the provider’s template endpoint. Include a callback URL if your deployment can receive webhooks; otherwise persist the returned job ID and poll from a worker. Store the request hash, provider name, template version, and your internal content ID together.
4. Handle completion
Accept a webhook only after authenticating it according to the provider’s instructions, then make the handler idempotent. A retry or duplicate delivery must not publish the same video twice. When polling, use increasing delays and stop at an application deadline; mark the job for review rather than polling forever.
Direct video generation with a job API
OpenAI’s documented create-video pattern accepts a prompt, optional input-reference file, model, duration, and output size. Select sora-2 for the standard model or sora-2-pro when that model is appropriate for your account and use case. Keep prompts explicit about subject, action, camera movement, composition, and any text that must appear on screen; then validate the returned asset rather than assuming the prompt was followed.
The following provider-neutral client is runnable once you set the documented create and status URLs for your chosen service. It deliberately keeps provider-specific field names in one adapter, making it easier to switch between a template endpoint and a direct-generation endpoint.
import os, time, hashlib, json, requests
CREATE_URL = os.environ["VIDEO_CREATE_URL"]
STATUS_URL = os.environ["VIDEO_STATUS_URL"]
TOKEN = os.environ["VIDEO_API_KEY"]
payload = {
"model": "sora-2",
"prompt": "A clean product close-up, slow dolly movement, soft studio light",
"duration": 4,
"size": "1280x720"
}
headers = {"Authorization": f"Bearer {TOKEN}", "Content-Type": "application/json"}
request_key = hashlib.sha256(json.dumps(payload, sort_keys=True).encode()).hexdigest()
headers["Idempotency-Key"] = request_key
created = requests.post(CREATE_URL, json=payload, headers=headers, timeout=90)
created.raise_for_status()
job = created.json()
job_id = job["id"]
for attempt in range(12):
status = requests.get(f"{STATUS_URL}/{job_id}", headers=headers, timeout=30)
status.raise_for_status()
data = status.json()
state = data.get("status")
if state in {"completed", "succeeded"}:
print(data.get("output") or data)
break
if state in {"failed", "moderated", "cancelled"}:
raise RuntimeError(data)
time.sleep(min(60, 2 ** attempt))
else:
raise TimeoutError("job did not finish before the polling deadline")Use the provider’s exact status names and authentication rules in the adapter. The control flow—create, persist ID, poll or receive a callback, then download—is the portable part.
Equivalent request patterns
cURL
curl -X POST "$VIDEO_CREATE_URL"
-H "Authorization: Bearer $VIDEO_API_KEY"
-H "Content-Type: application/json"
-d '{
"model":"sora-2",
"prompt":"A clean product close-up, slow dolly movement, soft studio light",
"duration":4,
"size":"1280x720"
}'Node.js
const createUrl = process.env.VIDEO_CREATE_URL;
const token = process.env.VIDEO_API_KEY;
const payload = {
model: 'sora-2',
prompt: 'A clean product close-up, slow dolly movement, soft studio light',
duration: 4,
size: '1280x720'
};
const response = await fetch(createUrl, {
method: 'POST',
headers: {
Authorization: `Bearer ${token}`,
'Content-Type': 'application/json'
},
body: JSON.stringify(payload)
});
if (!response.ok) throw new Error(`${response.status}: ${await response.text()}`);
const job = await response.json();
console.log(job.id);Python
import os, requests
r = requests.post(
os.environ["VIDEO_CREATE_URL"],
headers={"Authorization": f"Bearer {os.environ['VIDEO_API_KEY']}"},
json={"model": "sora-2", "prompt": "A clean product close-up", "duration": 4, "size": "1280x720"},
timeout=90,
)
r.raise_for_status()
print(r.json())For a Synthesia template request, replace the direct-generation fields with the required templateId and your published variable key-value data. Keep callback metadata and your internal correlation ID in the same record.
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What the major documented platforms emphasize
Synthesia: repeatable presenter videos
Synthesia centers on finished videos generated from reusable templates. Its asynchronous API supports polling or webhooks, which suits a queue that renders hundreds of individualized variants while your web request returns immediately.
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Runway: model choice and professional outputs
Runway’s getting-started material demonstrates SDK/API image-to-video usage. Its catalog includes Gen-4.5 and Veo 3.1, and its flagship workflows document ProRes, PNG image sequences, 10-bit SDR, and HDR. The Model Router accepts a configuration ID and chooses an eligible model according to an optimization preference. That lets your application express a goal such as quality or cost without hard-coding one model name.
OpenAI: focused asynchronous jobs
The Videos API has a narrow create-job shape: prompt, optional reference, Sora model, duration, and size. It is straightforward for a service that already has a queue and only needs to submit, monitor, and retrieve clips.
Google Gemini and Veo: multimodal direction
Google documents Gemini Omni Flash as a fast multimodal, conversational video option. Veo 3.1 adds native audio, extension, frame-specific generation, and image-based direction. Those controls matter when an agent must continue a shot, direct a particular frame, or generate sound as part of the result.
Designing an agent that survives real failures
Persist a state machine
Use states such as queued, submitted, running, completed, moderated, failed, and expired. Store provider job ID, internal request ID, template or model, prompt hash, input references, callback receipt time, output metadata, and the last error. This makes retries auditable and prevents an agent from creating duplicate videos after a timeout.
Separate policy from generation
Run prompt and media checks before submission. Treat moderation as a first-class outcome, not a generic HTTP error: notify the caller with a safe explanation, retain the provider status, and avoid automatic retries that would submit the same disallowed content.
Use webhooks and polling together
Webhooks reduce delay and API traffic, while a reconciliation poller catches lost deliveries. Make both paths call the same idempotent completion function. Verify signatures where supported, reject stale events, and download output to storage you control before notifying downstream systems.
Scale without overwhelming the provider
- Put requests on a durable queue and cap concurrency per provider and account.
- Batch validation and metadata writes before rendering; do not hold database transactions open during video generation.
- Use exponential backoff with a maximum delay and a dead-letter queue for jobs that exceed the retry budget.
- Cache identical input hashes when your rights and provider terms allow it.
- Record duration, size, model, and outcome so cost and latency can be analyzed by workload rather than guessed from averages.
Performance, reliability, and cost decisions
Shorter duration and smaller frames generally reduce work, but the provider’s current limits and pricing determine the real trade-off. Keep a preview path for review and a final-render path for publication. Templates usually offer the most predictable composition at scale; direct generation offers more visual variety but requires stronger output checks. A model router can optimize selection while keeping your application contract stable.
Do not promise synchronous completion to callers. Return your own request ID, expose a status endpoint, and provide a callback option. Set a deadline for each job, then surface a useful failure reason—invalid input, moderation, provider timeout, or download error—rather than a generic “generation failed.”
Troubleshooting
Template variables are ignored
Confirm that the template was published after the variables were added, that keys exactly match the published names, and that you are sending the required templateId. Log the outgoing key set (not sensitive values) and the template version.
The request succeeds but no video appears
A successful create response normally means a job was accepted, not that rendering finished. Persist the job ID, poll the status endpoint or wait for the webhook, and check your worker logs for a failed download.
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Polling never completes
Check that you are using the provider’s status URL and status vocabulary, not the create URL. Add a reconciliation poller for missed webhooks, enforce a deadline, and move exhausted jobs to manual review.
A job is moderated
Keep the moderation state distinct from transport errors. Inspect the prompt and reference media against the provider’s policy, notify the user, and do not retry unchanged input automatically.
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Validate the requested size against the model’s documented sizes, and pass the orientation explicitly. For professional delivery, choose a provider and workflow that documents the required format, such as Runway’s listed ProRes, PNG sequence, 10-bit SDR, or HDR paths.
Agent retries create duplicates
Derive an idempotency key from your internal content ID and normalized inputs, persist it before submission, and treat a timeout after submission as “unknown” until reconciliation finds the provider job.
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Frequently Asked Questions
Can one template contain conditional scenes?
Treat the published template contract as authoritative. If a scene must appear or disappear based on data, model that behavior explicitly in the template system or maintain separate template versions rather than assuming an arbitrary variable will change the layout.
Should an agent wait for a video before replying to a user?
Usually no. Return an internal request ID immediately, expose status through polling or a webhook, and notify the user when the asset is ready. Reserve synchronous waits for short, tightly bounded preview operations.
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Define an internal job schema and implement one adapter per provider. Keep model names, field mappings, status translation, authentication, and download logic inside adapters; keep queues, policy checks, retries, and publication outside them.
Quick Recap
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