langchain/templates/rag-opensearch/dummy_data.txt
Kalyan ec53d983a1
TEMPLATES Add rag-opensearch template (#13501)
<!-- Thank you for contributing to LangChain!

Replace this entire comment with:
  - **Description:** a description of the change, 
  - **Issue:** the issue # it fixes (if applicable),
  - **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!

Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.

See contribution guidelines for more information on how to write/run
tests, lint, etc:

https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md

If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.

If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
 -->

Adding rag-opensearch template.

---------

Signed-off-by: kalyanr <kalyan.ben10@live.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
2023-11-27 16:21:39 -05:00

19 lines
2.2 KiB
Plaintext

[INFO] Initializing machine learning training job. Model: Convolutional Neural Network Dataset: MNIST Hyperparameters: ; - Learning Rate: 0.001; - Batch Size: 64
[INFO] Loading training data. Training data loaded successfully. Number of training samples: 60,000
[INFO] Loading validation data. Validation data loaded successfully. Number of validation samples: 10,000
[INFO] Training started. Epoch 1/10; - Loss: 0.532; - Accuracy: 0.812 Epoch 2/10; - Loss: 0.398; - Accuracy: 0.874 Epoch 3/10; - Loss: 0.325; - Accuracy: 0.901 ... (training progress) Training completed.
[INFO] Validation started. Validation loss: 0.287 Validation accuracy: 0.915 Model performance meets validation criteria. Saving the model.
[INFO] Testing the trained model. Test loss: 0.298 Test accuracy: 0.910
[INFO] Deploying the trained model to production. Model deployment successful. API endpoint: http://your-api-endpoint/predict
[INFO] Monitoring system initialized. Monitoring metrics:; - CPU Usage: 25%; - Memory Usage: 40%; - GPU Usage: 80%
[ALERT] High GPU Usage Detected! Scaling resources to handle increased load.
[INFO] Machine learning training job completed successfully. Total training time: 3 hours and 45 minutes.
[INFO] Cleaning up resources. Job artifacts removed. Training environment closed.
[INFO] Image processing web server started. Listening on port 8080.
[INFO] Received image processing request from client at IP address 192.168.1.100. Preprocessing image: resizing to 800x600 pixels. Image preprocessing completed successfully.
[INFO] Applying filters to enhance image details. Filters applied: sharpening, contrast adjustment. Image enhancement completed.
[INFO] Generating thumbnail for the processed image. Thumbnail generated successfully.
[INFO] Uploading processed image to the user's gallery. Image successfully added to the gallery. Image ID: 123456.
[INFO] Sending notification to the user: Image processing complete. Notification sent successfully.
[ERROR] Failed to process image due to corrupted file format. Informing the client about the issue. Client notified about the image processing failure.
[INFO] Image processing web server shutting down. Cleaning up resources. Server shutdown complete.