Welcome to Transactional Machine Learning (TML) Solution: [tml-server-v1-plugin-3f10-ml_agenticai_restapi] Documentation!

Generated On: 2026-04-25 16:31:29 UTC

Project Name: tml-server-v1-plugin-3f10

TML REST API Server Plugin

This is a TML server plug-in that uses REST API - allowing access from ANY application

Important

This documentation is auto-generated by the TML Solution Studio (TSS).

Documentation for TML solutions are very important, and should be shared with broader audience.

Contents

• [tml-server-v1-plugin-3f10-ml_agenticai_restapi] Operating Details
  • Github Logs
  • TSS Docker Run Command
    • TSS Docker Run Command: Parameter Explanation
  • TSS Dashboard URL
  • TSS Airflow Port
  • TSS Log File Dashboard
  • Your Solution Docker Container
  • Your Solution Docker Run Command
    • Your Solution Docker Run Command: Parameter Explanation
  • Your Solution Airflow Port
  • Your Solution External Port
    • Non-Solution vs Solution Ports
  • Your Solution Dashboard URL
  • Your Solution Log File Dashboard
    • Your Solution Dashboard URL: Parameter Explanation
  • [tml-server-v1-plugin-3f10-ml_agenticai_restapi] Github Repo
  • Readthedocs URL
  • Solution Trigger DAG
  • Your Solution TML Binaries
  • Your Solution TMUX Windows
• [tml-server-v1-plugin-3f10-ml_agenticai_restapi] Details
  • TML Solution DAG Parameters' Details: User Chosen Parametets
    • STEP 1: Get TML Core Params: tml_system_step_1_getparams_dag
    • STEP 2: Create Kafka Topics: tml_system_step_2_kafka_createtopic_dag
    • STEP 3: Produce to Kafka Topics
    • STEP 4: Preprocesing Data: tml-system-step-4-kafka-preprocess-dag
    • STEP 4a: Preprocesing Data: tml-system-step-4a-kafka-preprocess-dag
    • STEP 4b: Preprocesing Data: tml-system-step-4b-kafka-preprocess-dag
    • STEP 4c: Preprocesing Data: tml-system-step-4c-kafka-preprocess-dag
    • STEP 5: Entity Based Machine Learning : tml-system-step-5-kafka-machine-learning-dag
    • STEP 6: Entity Based Predictions: tml-system-step-6-kafka-predictions-dag
    • STEP 7: Real-Time Visualization: tml-system-step-7-kafka-visualization-dag
    • STEP 8: tml_system_step_8_deploy_solution_to_docker_dag
    • STEP 9: tml_system_step_9_privategpt_qdrant_dag
    • STEP 9b: tml_system_step_9b_agenticai_dag
    • STEP 10: tml_system_step_10_documentation_dag
• Transactional Machine Learning Solution Studio (TSS) Usage
  • TSS Container Run Procedure
• Scaling [tml-server-v1-plugin-3f10-ml_agenticai_restapi] With Kubernetes
  • kubectl Apply command
  • tml-server-v1-plugin-3f10-ml_agenticai_restapi.yml
  • secrets.yml
  • mysql-storage.yml
  • mysql-db-deployment.yml
  • kafka.yml
  • privategpt.yml
  • ollama.yml
  • qdrant.yml
  • Kubernetes Dashboard Visualization
  • Scaling with NGINX Ingress and Ingress Controller
  • nginx-ingress-tml-server-v1-plugin-3f10-ml_agenticai_restapi.yml
  • Ingress Dashboard Visualization
  • Making Secure TLS Connection with gRPC
    • Here are the Steps to follow.
      • Step 1: Get Server Certificates
      • Step 2: Apply the Server Certificates to Kubernetes Cluster
      • Step 3: Apply the secret-tls to Kubernetes Cluster
  • Using gRPcurl to Write Data to the TML gRPC Server
    • Run the gRPCurl Commands
    • Send data to the sever:
  • Kubernetes Pod Access Commands
• Latest Logs From Latest Build