Complete Hermes + Jimeng CLI Tutorial: Automate Image and Video Generation to Eliminate Repetitive Work

Core Question This Article Answers: For technical, product, or engineering professionals with college-level or higher education, how can you integrate the Jimeng CLI with Hermes to automatically submit text-to-image and text-to-video tasks, check results, and connect them to your workflow—freeing short drama teams and creators from tedious manual monitoring?

Jimeng’s Seedance 2.0 currently limits simultaneous task submissions to 10. Many short drama production teams shift work to late nights or even stay up all night to avoid peak hours. Once you connect the Jimeng CLI, Hermes can handle repetitive tasks like passing prompts, waiting for jobs, and retrieving results. Taking it further by linking your storyboard library enables fully automated queuing—so you can sleep through the night and wake up to a complete set of shot materials for your short drama.

This guide consolidates the full setup process along with every pitfall encountered. If you’re preparing to configure it, simply share this article with Hermes and let it follow the steps (the same applies to OpenClaw). After completion, your Hermes will at minimum be able to:

• Call the Jimeng CLI
• Check login status
• Query credit balance
• Submit image or video generation tasks
• Query asynchronous task results
• Feed results directly into your existing workflows

Important Note: The Jimeng CLI is currently available only to Jimeng advanced members, who enjoy free image generation.

Here is a short demonstration of Hermes generating images and videos and returning the results:

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Environment Prerequisites: What Must Be Ready Before Installing and Integrating the Jimeng CLI?

Core Question This Section Answers: What hardware and software conditions need to be confirmed before installing the Jimeng CLI and integrating it with Hermes to ensure every subsequent step runs smoothly?

The Jimeng CLI supports Linux, macOS, and Windows (with official Linux arm64 support starting from v1.3.4). Before getting started, verify the following:

• Hermes is already running normally.
• Hermes has terminal execution capabilities.
• The terminal can run curl or wget commands.
• For headless login (strongly recommended in Agent scenarios), Google Chrome must be installed on the machine.
• For local browser login, a normally launchable default browser must be available.

These basics may seem simple, but they directly determine whether login and task submission will succeed. Many users get stuck here by overlooking Chrome dependency for headless mode or missing curl support in the terminal. Confirming these prerequisites first prevents unnecessary detours.

Personal Reflection: During my initial setup, I skipped the Chrome check and jumped straight to headless login, only to waste time troubleshooting. Reviewing the environment requirements afterward taught me that every step builds on the reliability of the previous one. That’s why environment verification comes first—it’s the foundation of the entire chain, not just a checklist.

Installation and Verification: How to Install the CLI with One Command and Quickly Confirm It Works

Core Question This Section Answers: How do you install the Jimeng CLI, and what commands verify that it is truly functional rather than just appearing installed?

The official one-line installation command is straightforward:

curl -fsSL https://jimeng.jianying.com/cli | bash

This script downloads the CLI binary, version.json, and attempts to add the installation directory to your PATH. It also places the SKILL.md file in ~/.dreamina_cli/dreamina/SKILL.md. Note that this SKILL.md is only downloaded locally and does not automatically install into Hermes’s skills directory—you will need to incorporate it manually later.

After installation, verify immediately with:

which dreamina
dreamina -h

If the first command returns the path and dreamina -h displays the following subcommands, the CLI core is successfully installed:

• login / relogin / logout — login management
• user_credit — query credit balance
• text2image / text2video — text-to-image and text-to-video
• image2image / image2video — image-to-image and image-to-video
• multiframe2video / multimodal2video — multi-frame or multimodal video generation
• query_result — query asynchronous task results
• list_task — view task history

Real-World Scenario: Imagine you are a short drama production engineer generating dozens of shots daily. Once CLI verification passes, Hermes can call these subcommands directly instead of you opening the web interface and submitting one by one. This verification step is critical—it ensures all automation scripts later rely on a solid CLI foundation.

Personal Reflection: I once assumed installation alone was enough, but dreamina -h worked while login failed. This experience reinforced the habit of immediately validating the help output for any new tool. It made Hermes automation far more reliable.

Login Process: Choosing the Best Method for Hermes and Performing Quick Self-Checks

Core Question This Section Answers: What login options does the Jimeng CLI provide, which is most efficient for Hermes or Agent scenarios, and how do you immediately confirm that login and environment are fully active?

For manual login, simply run:

dreamina login

The CLI will launch your default browser and guide you through authorization.

For Hermes or Agent scenarios, headless mode is recommended:

dreamina login --headless

The current version requires Google Chrome for –headless. If Chrome is unavailable or the browser fails to launch, you can manually import login credentials by following the on-screen instructions.

If the browser does not open automatically or the process stalls, retry with debug mode for detailed output:

dreamina login --debug

This prints callback URLs and debugging information in the terminal to help diagnose issues quickly.

Immediately after successful login, run the self-check:

dreamina user_credit

If the terminal returns JSON data containing balance information, both login status and environment configuration are confirmed active. You can now start submitting generation tasks.

Scenario Explanation: Short drama teams generating batches of materials late at night benefit greatly from headless login, allowing Hermes to handle authorization without human intervention. This is the key enabler for “wake up to finished materials.”

Personal Reflection: My first attempt with Safari resulted in callback errors. Switching to Chrome with headless mode succeeded on the first try. It highlighted how tool compatibility often hides in small details—choosing the right login method is essential for truly unattended operation.

Core Command Usage: Practical Examples for Image Generation, Video Generation, and Result Queries

Core Question This Section Answers: How do you use the most common Jimeng CLI commands for text-to-image and text-to-video generation? What are the key parameters, and how does the –poll option enable automation while feeding results into your workflow?

All task submission commands support the universal --poll=<seconds> parameter (for example, --poll=30). When added, the CLI polls task status once per second for up to the specified duration. If the task completes within the wait time, it outputs the final result directly in the terminal. If it times out, it returns an intermediate “querying” status, which you can follow up with the query_result command.

1. Text-to-Image (text2image)

dreamina text2image \
  --prompt="A orange cat wearing sunglasses" \
  --ratio=1:1 \
  --resolution_type=2k \
  --poll=30

Scenario: Need a cartoon-style character for a short drama opening shot? Hermes can generate a 2K square image and return results within 30 seconds of polling.

2. Text-to-Video (text2video)

dreamina text2video \
  --prompt="Camera pushing in, an orange cat jumps off the sofa" \
  --duration=5 \
  --ratio=16:9 \
  --video_resolution=720P \
  --poll=30

Scenario: Require a 5-second dynamic shot? Hermes submits the prompt and automatically waits to return a 720P landscape video for seamless integration into editing.

3. Image-to-Image (image2image)

dreamina image2image \
  --images ./input.png \
  --prompt="Convert to watercolor style" \
  --resolution_type=2k \
  --poll=30

Note: The –images parameter must point to a local image file path.

Scenario: You have a rough character sketch and want to iterate quickly into watercolor for storyboard preview. Hermes automates the style transfer and returns 2K results.

4. Image-to-Video (image2video)

dreamina image2video \
  --image ./first_frame.png \
  --prompt="Camera slowly zooming in" \
  --duration=5 \
  --poll=30

Note: The –image parameter (singular) points to the local first-frame image.

Scenario: Starting from an existing static frame, generate a 5-second push-in video. Hermes converts the static input into dynamic material automatically.

5. Query Asynchronous Task Results (query_result)

If –poll is not used or polling times out, you receive a submit_id. Query with:

# Basic query
dreamina query_result --submit_id=<your_submit_id>

# Query and download directly to a directory
dreamina query_result --submit_id=<your_submit_id> --download_dir=./downloads

Scenario: After submitting 10 batch tasks, Hermes records each submit_id, periodically queries them, and automatically downloads successful results to your working directory for the next editing stage.

6. View Task History (list_task)

# View all tasks
dreamina list_task

# View only successful tasks
dreamina list_task --gen_status=success

# Filter by submit_id
dreamina list_task --submit_id=<your_submit_id>

Scenario: During project review, Hermes quickly lists all successful materials from the day, helping the team analyze which prompts performed best.

Personal Reflection: I noticed that parameter details vary significantly across subcommands (for example, image2image uses plural –images while image2video uses singular –image). Running the corresponding -h command before every submission has become standard practice. It prevents 80% of syntax errors and makes Hermes automation scripts much more robust.

Integrating with Hermes: How to Turn the CLI into a Solid Skill for Truly Unattended Workflows

Core Question This Section Answers: After CLI installation and login, how do you make Hermes fully understand these commands and encapsulate the entire process into a repeatable skill?

When Hermes and the CLI are on the same machine, the simplest verification is to have Hermes execute these three commands in sequence:

dreamina -h
dreamina user_credit
dreamina text2image --prompt="A orange cat wearing sunglasses" --ratio=1:1 --resolution_type=2k --poll=30

If all three run successfully, Hermes can now call the Jimeng CLI properly.

For long-term use, solidify the process into a Hermes skill. The official SKILL.md (located at ~/.dreamina_cli/dreamina/SKILL.md) serves as a ready reference template. A good skill should at least include these rules:

1. First run dreamina -h to confirm CLI availability.
2. First run dreamina user_credit to verify login status and balance.
3. Always record the submit_id when submitting tasks.
4. Judge success based on gen_status when querying results.
5. Read fail_reason for specific error details on failure.
6. Never rely solely on exit code to determine task success.

Value in Practice: Once your storyboard library is connected, Hermes can automatically read the next prompt, submit the task, wait for results, download the material, and push it to editing software. The entire short drama material generation becomes fully automated. Teams no longer need to monitor tasks overnight, boosting efficiency dramatically.

Personal Reflection: Encapsulating the CLI into a skill truly showed me the power of tool empowerment. What started as saving a few minutes of repetition evolved into automating an entire production line. It reinforced starting with the smallest reliable chain before scaling complexity.

Pitfalls and Lessons Learned: Common Issues and How to Avoid Them

Core Question This Section Answers: What are the most frequent pitfalls when integrating the Jimeng CLI with Hermes, and how can you identify and prevent them in advance?

Here are the real pitfalls encountered along with solutions:

• dreamina -h works ≠ fully usable
  It only confirms installation. You must complete login + user_credit to ensure login state and account are valid.

• Advanced membership required
  Non-advanced accounts will receive a “not vip” error. The CLI is currently open only to Jimeng advanced members.

• Exit code = 0 ≠ generation success
  For asynchronous tasks, exit code 0 only means “submission successful,” not “generation completed.” Always check gen_status.

• Safari login compatibility issues
  Some users report callback exceptions with Safari. Prefer Chrome or switch directly to –headless / manual import.

• Test images before videos
  Video workflows involve more parameters and longer processing. Use text2image for the first minimal viable chain.

• Parameter differences across subcommands
  For example, image2image uses –images (plural) while image2video uses –image (singular). Always check the specific help with -h before submitting.

Personal Reflection: I stepped on nearly every one of these pitfalls. The biggest lesson was “never treat surface success as real success”—cases where exit code is 0 but gen_status fails are especially misleading. Adding these rules into the skill dramatically improved Hermes fault tolerance and saved countless hours in later projects.

Practical Checklist: One-Click Implementation Summary

• [ ] Confirm environment prerequisites (Hermes, terminal, curl, Chrome)
• [ ] Run the one-line installation and verify with dreamina -h
• [ ] Complete login (prefer –headless) and run dreamina user_credit
• [ ] Solidify skill rules (including login checks and gen_status judgment)
• [ ] Test minimal chain: text2image with –poll=30
• [ ] Expand to batch tasks + query_result + download
• [ ] Connect storyboard library for automatic queuing

One-Page Quick Summary

Core Capabilities: Hermes uses the Jimeng CLI for login, credit checking, asynchronous image/video generation, result polling, and downloading.
Minimal Working Chain: Install → Login → user_credit → text2image –poll → query_result.
Advanced Usage: Connect storyboard library → automatic queuing → fully unattended short drama material generation.
Key Success Criterion: Always judge by gen_status rather than exit code.
Target Users: Short drama teams, AI workflow engineers, and product/technical professionals needing batch material generation.

FAQ

1. Does the Jimeng CLI support Windows?
Yes. It also supports Linux arm64 from v1.3.4 onward. With the environment ready, one-line installation completes the setup.

2. Is Google Chrome required for headless login?
Yes, the current version depends on Google Chrome. If unavailable, use manual import of login state.

3. The command returns exit code 0, but why don’t I see the final image?
This is an asynchronous task. Exit code 0 only indicates successful submission. You must check gen_status or use query_result to confirm completion.

4. Can non-advanced members use the CLI?
No. It will report a “not vip” error. The CLI is currently restricted to Jimeng advanced members.

5. How can Hermes automatically handle multiple storyboard tasks?
Incorporate the storyboard library into the skill. Check user_credit first, then loop through submissions of text2image or text2video while recording submit_ids, and finally batch-download using query_result.

6. What should I do if Safari login fails?
Switch to Chrome or use –headless mode directly. You can also add the –debug flag to view callback details.

7. Where is the SKILL.md file after CLI installation?
It is located at ~/.dreamina_cli/dreamina/SKILL.md. Use it as a reference and manually add it to your Hermes skill system.

8. How long does it typically take to run through the minimal viable chain?
With proper environment preparation, usually 10–15 minutes for installation, login, self-check, and the first text-to-image test.

This comprehensive guide gives you a practical, replicable, and extensible Hermes + Jimeng CLI workflow. It is designed to help anyone struggling with material generation efficiency turn repetitive work into automated results. If you encounter specific error messages during implementation, feel free to share them so we can continue refining the process together.