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The MultiGen pathfinding model aims to predict a suitable model invocation path based on user input requirements, using known model information.

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Deployment and Implementation Process in Real Scenarios

1. Deploying the MultiGen Pathfinding Model on MainServer and Storing Model Information

The MultiGen pathfinding model aims to predict a suitable model invocation path based on user input requirements, using known model information. It directs the main server to call models deployed on different edge servers in a specific sequence.

All parameters of MultiGen have been tuned and configured, so users can directly use it. The user input is the sequence of modalities they want to use, for example:

  • Audio to Text -> Text to Text -> Text to Image -> Image to Video

The output generated is the sequence in which the main server calls the models on the edge servers, for example:

  • whisper (Server2) -> llama (Server1) -> sd2.1 (Server1) -> image2video (Server3)

Models Deployed for Real Scenario Testing:

Server 1

  • sd2.1 (Text to Image)
  • llama (Text to Text)

Server 2

  • whisper (Audio to Text)
  • sd2.1 (Text to Image)
  • Stable-Diffusion-Playground

Server 3

  • sd2.1 (Text to Image)
  • Sound-Diffusion (Text to Image)
  • image2video (Image to Video)

2. MainServer Invoking Models on Edge Servers

Based on the path predicted by MultiGen, the models on the edge servers are called in sequence. At this time, each edge server runs a receiving.py file continuously, waiting for instructions from the MainServer.

The sending.py file running on the MainServer sends the corresponding CMD commands to the edge servers via their IP addresses and port numbers, instructing them to invoke the models.

File Transfer Method: scp

scp -P [Port] [File Path] [Username]@[Target Server IP]:[Target Path]

We have integrated the scp transfer command into the corresponding Python files for the models.

Password-Free Transfer

Set up password-free scp for servers that need to transfer files mutually:

# Generate SSH key pair
ssh-keygen -t rsa -C "key pass"

# Copy the public key to the target server to enable password-free login
ssh-copy-id -p [Port] [Username]@[Target Server IP]

Example of the Testing Process

  • Model Invocation Sequence: whisper (Server2) -> llama (Server1) -> sd2.1 (Server1) -> image2video (Server3)
  1. Invoke the whisper Model

    • MainServer transfers the MP3 file to Server2.
    • MainServer sends the command to invoke whisper to Server2 via sending.py.
    • Server2 receives the command via receiving.py, calls whisper to process the file, and sends the generated text file back to MainServer.
  2. Invoke the llama Model

    • MainServer sends the command to invoke llama to Server1 via sending.py.
    • Server1 receives the command via receiving.py, calls llama to process the file, and sends the generated text file back to MainServer.
  3. Invoke the sd2.1 Model

    • MainServer sends the command to invoke sd2.1 to Server1 via sending.py.
    • Server1 receives the command via receiving.py, calls sd2.1 to process the file, and sends the generated image file back to MainServer.
  4. Invoke the image2video Model

    • MainServer transfers the image file to Server3.
    • MainServer sends the command to invoke image2video to Server3 via sending.py.
    • Server3 receives the command via receiving.py, calls image2video to process the file, and sends the generated video file back to MainServer.

Finally, you can view the final generated result and the intermediate results in the corresponding path on the MainServer.

Contact & Support

For questions, bug reports, or collaboration inquiries:


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The MultiGen pathfinding model aims to predict a suitable model invocation path based on user input requirements, using known model information.

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