Update docs for ocean-cli for C2D free start compute

developers/ocean-cli/README.md

@@ -13,7 +13,7 @@ The Ocean CLI offers a wide range of functionalities, enabling you to:
 * [**Publish**](publish.md) 📤 data services: downloadable files or compute-to-data.
 * [**Edit**](edit.md) ✏️ existing assets.
 * [**Consume**](consume.md) 📥 data services, ordering datatokens and downloading data.
-* [**Compute to Data**](run-c2d.md) 💻 on public available datasets using a published algorithm.
+* [**Compute to Data**](run-c2d.md) 💻 on public available datasets using a published algorithm. Free version of compute-to-data feature is available
 
 ## Key Information
 

developers/ocean-cli/run-c2d.md

@@ -1,5 +1,15 @@
 # Run C2D Jobs 🚀
 
+## Get Compute Environments
+
+To proceed with compute-to-data job creation, the prerequisite is
+to select the preferred environment to run the algorithm on it. This can be
+accomplished by running the CLI command `getComputeEnvironments` likewise:
+```bash
+npm run cli getComputeEnvironments
+```
+
+
 ## Start a Compute Job 🎯
 
 Initiating a compute job can be accomplished through two primary methods. 
@@ -15,11 +25,44 @@ In this command, replace `DATASET_DID` with the specific DID of the dataset you
 
 <figure><img src="../../.gitbook/assets/cli/c2dstart.png" alt=""><figcaption>Start a compute job</figcaption></figure>
 
+## Start a Free Compute Job 🎯
+
+For running the algorithms free by starting a compute job, these are the following steps.
+**Note**
+Only for free start compute, the dataset is **not mandatory** for user to provide in the command line. The required command line parameters are the algorithm DID and environment ID, retrieved from `getComputeEnvironments`
+command. 
+1. The first step involves publishing the algorithm, as explained in the previous section, [Publish a Dataset](./publish.md) Once that's completed, you can proceed to initiate the compute job. 
+2. Alternatively, you have the option to explore available algorithms and kickstart a free compute-to-data job by combining your preferred choices.
+
+To illustrate the latter option, you can use the following command for running free start compute with **additional datasets**:
+
+```bash
+npm run cli freeStartCompute ['DATASET_DID1','DATASET_DID2'] 'ALGO_DID' 'ENV_ID'
+```
+
+In this command, replace `DATASET_DID` with the specific DID of the dataset you intend to utilize and `ALGO_DID` with the DID of the algorithm you want to apply and the environment for **free** start compute returned from `npm run cli getComputeEnvironments`.
+By executing this command, you'll trigger the initiation of a free compute-to-data job with the alogithm provided.
+Free start compute can be run **without** published datasets, only the algorithm and environment is required:
+```bash
+npm run cli freeStartCompute [] 'ALGO_DID' 'ENV_ID'
+```
+**NOTE:** For `zsh` console, please surround `[]` with quotes like this: `"[]"`.
+<figure><img src="../../.gitbook/assets/cli/freec2dstart1.png" alt=""><figcaption>Start a free compute job</figcaption></figure>
 
 ## Download Compute Results 🧮
 
 To obtain the compute results, we'll follow a two-step process. First, we'll employ the `getJobStatus`` method, patiently monitoring its status until it signals the job's completion. Afterward, we'll utilize this method to acquire the actual results.
 
+## Retriving Algorithm Logs
+
+To monitor the algorithm logs execution and setup configuration for algorithm,
+this command does the trick!
+
+```bash
+npm run cli computeStreamableLogs
+```
+
+
 ###  Monitor Job Status
 To track the status of a job, you'll require both the dataset DID and the compute job DID. You can initiate this process by executing the following command: