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In this lesson you’ll build an image-to-video automation end-to-end. The workflow gathers a user-supplied base image and a textual video idea, converts that idea into a model-ready video prompt, calls an image-to-video service (Seedance / Wavespeed), polls until the video is complete, and returns the result to the user in Telegram. Inputs required:
  • A base image (the source image the video will be derived from).
  • A Video Prompt (the user-provided description of the desired video).
We use Telegram as the central conversational interface in this demo and Google Drive to receive uploaded images. The trigger can be either a new file in a monitored Google Drive folder or a reply from the Telegram user. High-level flow:
  1. Google Drive trigger detects a new image upload.
  2. A Telegram bot notifies the user and requests a video idea.
  3. The image URL and timestamp are appended to a Google Sheet (Image to Video Log).
  4. A Telegram OnMessage trigger captures the user’s idea and the chat id.
  5. An OpenAI Chat model (Video Prompt agent) converts the idea into a concise, structured video-generation prompt and returns the image URL.
  6. POST to Seedance (via the Wavespeed API) starts video generation.
  7. Wait + GET loop polls the API until processing completes.
  8. Send the finished video back to the user on Telegram.
We’ll step through each node with recommended configuration and examples.
The image shows a setup screen for a Google Drive Trigger with parameters and output details. It includes configuration options for polling, triggering, and specific folder settings.
Google Drive trigger
  • Purpose: monitor a specific folder for newly created files (use polling, e.g., every minute).
  • Key options:
    • Folder: choose the folder to watch (e.g., image to video CodeCloud).
    • Event: File Created.
  • Output: the node returns metadata including a publicly shareable link in webContentLink. Use that field as the image URL downstream.
While testing, share the Drive file via a public view link so the downstream HTTP POST can access the image. Revoke or restrict permissions for production.
Telegram bot: create and connect
  • Create a bot via Telegram’s BotFather (@BotFather):
    • In Telegram, start a chat with @BotFather and run /newbot. Follow the prompts to get your bot token.
    • Useful BotFather commands:
/newbot - create a new bot
/mybots - list your bots

Edit Bots
/setname - change a bot's name
/setdescription - change bot description
/setabouttext - change bot about text
/setuserpic - change bot profile photo
/setcommands - change the list of commands
/deletebot - delete a bot

Bot Settings
/token - get authorization token
/revoke - revoke bot access token
...
  • Add the bot token as credentials in your automation platform (e.g., in n8n create a credential named Telegram Demo).
  • Test the credential to confirm connectivity.
Send a Photo message (Telegram node)
  • Add a Telegram node configured to Send a Photo.
  • Provide the chat_id (you’ll capture this from the Telegram trigger below; for testing you can hard-code it).
  • Photo URL: map the Google Drive webContentLink output.
  • Caption example: “You’ve uploaded this photo to the Google Drive folder. Kindly provide the video idea that you want to generate from this image.”
The image shows a workflow editor in the n8n platform, featuring a sequence from a Google Drive trigger to a Telegram message action. The sidebar displays various Telegram actions available for configuration.
Telegram OnMessage trigger (capture the video idea and chat ID)
  • Add a Telegram OnMessage trigger node using the same Telegram Demo credentials.
  • Execute the trigger node, then message the bot from Telegram (e.g., test or your video idea). The trigger output contains the message body and chat.id.
  • Use the captured chat.id as the chat_id in your Send a Photo or Send a Video nodes. Example mapping (platform specific):
{{ $node["Telegram Trigger"].json["message"]["chat"]["id"] }}
  • After a successful test run, copy the trigger execution back into the editor (e.g., using “Copy to Editor”) so earlier nodes can reference the test data.
Send the uploaded image to the user
  • In the Telegram Send a Photo node, map the Drive webContentLink into the photo URL and add the caption shown above.
  • Execute to confirm the bot posts the image and requests the video idea.
The image shows a software interface for configuring a Telegram API operation to send a photo, including input fields, settings, and JSON data.
Google Sheets: log the image
  • Add a Google Sheets node to append a row to Image to Video Log (Sheet1).
  • Suggested columns: image URL and date.
  • Mapping:
    • image URL: map to the Drive webContentLink.
    • date: set to Now (timestamp).
  • Purpose: the Video Prompt agent can use this sheet to fetch the most recent image URL if it needs to.
OpenAI Chat Model: Video Prompt agent
  • Purpose: transform the user’s free-text idea into a concise, structured prompt for the image-to-video model and return the image URL.
  • Add an OpenAI Chat node (e.g., GPT-4.1) and configure it to return raw JSON.
  • Desired agent output (JSON):
    1. prompt — the model-ready text prompt.
    2. image_url — the image URL to pass to Seedance.
System prompt guidance (what to instruct the agent)
  • Tell the Chat agent to:
    • Produce a concise, effective video prompt tailored to the image-to-video model.
    • Return a JSON object with keys prompt and image_url.
    • Use a provided “Google Sheet Lookup” tool to fetch the last uploaded image URL (if not directly provided).
  • Attach a tool to the Chat node named Google Sheet Lookup which reads the last row of the Image to Video Log and returns the image URL. The agent should populate image_url from that tool when necessary.
The image shows a workflow in n8n, which includes triggers and integrations for Telegram, Google Drive, and a video prompt agent with options to add tools such as Google Sheets.
  • Execute the Chat node and verify the response contains well-formed JSON with prompt and image_url.
The image shows a user interface for a video prompt agent with input from a Telegram trigger, displaying JSON data and a text prompt regarding a playful scene with a cat.
Seedance (Wavespeed) image-to-video POST request
  • Add an HTTP Request node to POST to the Seedance image-to-video endpoint. Import the cURL example from the Wavespeed docs when available.
  • Authentication: set Authorization header to Bearer ${WAVESPEED_API_KEY} (or your platform’s credential store).
    • If your automation platform already injects Authorization headers, remove duplicate header entries.
  • Map:
    • image → image_url from the Video Prompt agent.
    • prompt → prompt from the Video Prompt agent.
    • duration, camera_fixed, seed → set as appropriate (e.g., duration: 5).
Example POST (importable cURL): 
curl --location --request POST 'https://api.wavespeed.ai/api/v3/bytedance/seedance-v1-lite-i2v-720p' \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
  "camera_fixed": false,
  "duration": 5,
  "image": "https://d3gfnktk2yh29lr.wavespeed.ai/media/images/1750666203680632149_ZgAwspl.jpg",
  "prompt": "Tabby cat batting at goldfish bowl on windowsill, water droplets on glass, distorted fish shadows on floor. Paw tap causing ripples transitions to low-angle shot of fish darting, ending with cat’s whiskers twitching in close-up.",
  "seed": -1
}'
  • Response: capture the returned requestId or prediction id for polling.
Wait + GET polling loop
  • Pattern:
    1. POST request to start prediction → returns requestId.
    2. Wait node (e.g., 15 seconds).
    3. GET request to: https://api.wavespeed.ai/api/v3/predictions/${requestId}/result with same Authorization header.
    4. Check response status.
    5. If not completed, loop back to the Wait node and GET again until completed.
  • Example GET cURL:
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
If-node (status check) and retry handling
  • Add an If node to check whether the GET response’s status field equals completed.
    • True: proceed to the Telegram Send a Video node.
    • False: connect back to the Wait node to continue polling.
  • This prevents the workflow from failing when the video is still processing.
Visual overview in the workflow editor:
The image shows a visual workflow editor in an application called "n8n" where different nodes like "Video Prompt Agent" and "Seedance Post" are connected to automate tasks. The interface includes options for AI, app actions, data transformation, and more.
Send the generated video back to Telegram
  • In the If node true branch (when status == completed), add a Telegram node configured to Send a Video.
  • Map:
    • chat_id → the chat.id captured from the Telegram trigger (dynamic mapping is recommended).
    • video → the video URL returned in the completed prediction result payload.
  • Example mapping for chat id (platform-specific):
{{ $node["Telegram Trigger"].json["message"]["chat"]["id"] }}
  • Execute and verify the user receives the generated video in the Telegram chat.
The image displays a workflow interface involving a Telegram bot operation to send a video, with JSON input and output data panels shown for configuring and executing the process.
Results and prompt variations
  • Example outcome: a playful/cartoonish video of a cat jumping through rainbow hoops and deploying a parachute to land safely.
  • You can refine the system prompt and the Video Prompt to control style and behavior:
    • Styles: hyper-realistic, cinematic, stylized animation, cartoon, etc.
    • Camera: fixed vs moving, dolly, low/high angles, POV.
    • Duration and aspect ratio: map to the Seedance parameters.
    • Seed: set to a fixed number for reproducible results or -1 for varied outputs.
Closing diagram
  • Full workflow chain: Google Drive trigger → Telegram notification → Google Sheets logging → Telegram OnMessage → OpenAI (Video Prompt agent) → Seedance POST → Wait → GET → If → Telegram send video.
The image shows a workflow diagram in the n8n automation tool, with nodes connected to perform tasks like triggering messages, posting to an API, and sending videos via Telegram. The interface includes options for executing the workflow, managing projects, and accessing various settings.
Production hardening checklist
  • Secure Drive and Sheets: avoid public links in production; use signed URLs or a proxy for transient access.
  • Protect API keys: rotate keys, store them in a secrets manager, and scope tokens when possible.
  • Add retries, backoff, and alerting for API failures.
  • Validate user inputs (e.g., prompt length, forbidden content).
  • Add logging and observability for long-running jobs.
Before deploying to production, remove public Drive sharing and ensure API keys and credentials are stored securely. Implement rate limits, retries, and content validation to prevent unexpected costs or misuse.
Node configuration summary
NodePurposeKey fields / mapping
Google Drive TriggerWatch folder for new imagesFolder = image to video CodeCloud, Event = File Created, use webContentLink
Telegram Send a PhotoNotify user + request video ideachat_id → Telegram chat id; photo → Drive webContentLink; caption = request text
Telegram OnMessage TriggerCapture user idea + chat idExtract message.text and message.chat.id
Google Sheets Append RowLog image URL & timeColumns: image URL = webContentLink, date = Now
OpenAI Chat (Video Prompt agent)Convert free text to structured promptReturns JSON: prompt, image_url (use Google Sheet Lookup tool if needed)
HTTP POST (Seedance)Start image-to-video jobMap image, prompt, duration, camera_fixed, seed; capture requestId
Wait + HTTP GETPoll for completionGET /predictions/${requestId}/result, check status
If nodeBranch on statusCondition: status == completed
Telegram Send a VideoDeliver final video to userchat_id and video → completed result URL
Links and references Next steps
  • Build the workflow end-to-end in your automation tool.
  • Test with different prompt styles and durations.
  • Harden with the production checklist above and iterate on agent system prompts for improved results.

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