langchain/templates/rag-opensearch/dummy_data.txt

[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.
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 21:21:39 +00:00			`[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.`