From b97cada6af92c13688228668a37cccb207bf378d Mon Sep 17 00:00:00 2001
From: ashishj1729 <jain.ashish@samsung.com>
Date: Tue, 7 Jan 2025 16:13:20 +0530
Subject: [PATCH] Updation Documentation for Model-Retraining

Change-Id: I363a3eaef0c444b071d087f1cbf88ed9ea9748a8
Signed-off-by: ashishj1729 <jain.ashish@samsung.com>
---
 docs/installation-guide.rst | 44 ++++++++++++++++++++++++++++++++++++++++++--
 docs/ranpm-installation.rst |  4 ++--
 2 files changed, 44 insertions(+), 4 deletions(-)

diff --git a/docs/installation-guide.rst b/docs/installation-guide.rst
index da35d65..5f8d5e2 100755
--- a/docs/installation-guide.rst
+++ b/docs/installation-guide.rst
@@ -487,11 +487,51 @@ Or You can curl the following API endpoint to obtain Trainingjob Info and fetch
 
     curl --location 'http://<AIMLFW-Ip>:32002/ai-ml-model-training/v1/training-jobs/<TrainingjobId>'
 
-Or you can directly download the model once the training is complete using the following API endpoint:
+Model-Retraining
+----------------------------------------
+A previously trained model can be retrained with different configurations/data as follows:
 
 .. code:: bash
 
-    curl --location 'http://<AIMLFW-Ip>:32002/model/<modelname>/<modelversion>/<artifactversion>/Model.zip'
+        curl --location 'localhost:32002/ai-ml-model-training/v1/training-jobs' \
+        --header 'Content-Type: application/json' \
+        --data '{
+                "modelId": {
+                "modelname":"<MODEL_TO_RETRAIN>",
+                "modelversion":"<MODEL_VERSION_TO_RETRAIN>"
+        },
+        "training_config": {
+                "description": "Retraining-Example",
+                "dataPipeline": {
+                "feature_group_name": "<FEATUREGROUP_NAME>",
+                "query_filter": "",
+                "arguments": {"epochs": 20}
+                },
+                "trainingPipeline": {
+                        "training_pipeline_name": "qoe_Pipeline",
+                        "training_pipeline_version": "qoe_Pipeline",
+                        "retraining_pipeline_name": "qoe_Pipeline_retrain",
+                        "retraining_pipeline_version": "qoe_Pipeline_retrain"
+                }
+        },
+        "model_location": ""
+        }'
+
+| The user can specify different configurations as well as retraining-pipeline by modifying the training-config.
+| The default `qoe_Pipeline_retrain` pipeline fetches and loads the existing model, retrains it with new arguments or data, and updates the artifact version from 1.0.0 to 1.1.0.
+
+Verify Updated Artifact-Version after retraining from MME
+
+.. code:: bash
+
+        curl --location 'localhost:32006/ai-ml-model-discovery/v1/models/?model-name=<MODEL_NAME>&model-version=<MODEL_VERSION>'
+
+
+| Note: 
+| a. The QoE retraining function does not come pre uploaded, we need to go to training function, create training function and run the `qoe-pipeline-retrain-2` notebook.
+| b. Subsequent retrainings will update the artifact version as follows: 
+|               From 1.x.0 to 1.(x + 1).0
+
 
 ..  _reference4:
 
diff --git a/docs/ranpm-installation.rst b/docs/ranpm-installation.rst
index 0fea1db..7316412 100644
--- a/docs/ranpm-installation.rst
+++ b/docs/ranpm-installation.rst
@@ -320,7 +320,7 @@ Using Non-RT RIC DME as data source for AIMLFW
 
         .. code-block:: bash
 
-                curl --location '<AIMLFW-Ip>:32002/featureGroup' \
+                curl --location '<AIMLFW-Ip>:32002/ai-ml-model-training/v1/featureGroup' \
                 --header 'Content-Type: application/json' \
                 --data '{
                         "featuregroup_name": "<FEATURE_GROUP_NAME>",
@@ -373,5 +373,5 @@ Using Non-RT RIC DME as data source for AIMLFW
 
 4. Create TrainingJob
 
-        Please refer `here <https://docs.o-ran-sc.org/projects/o-ran-sc-aiml-fw-aimlfw-dep/en/latest/installation-guide.html#training-job-creation-with-dme-as-data-source>`__ and use the featureGroup created in Step 2. 
+        Please refer `here <https://docs.o-ran-sc.org/projects/o-ran-sc-aiml-fw-aimlfw-dep/en/latest/installation-guide.html#training-job-creation-with-dme-or-standalone-influxdb-as-data-source>`__ and use the featureGroup created in Step 2. 
  
\ No newline at end of file
-- 
2.16.6