Update prompt_response_projects.ipynb

Author: x-eun

project_configuration/prompt_response_projects.ipynb

@@ -63,7 +63,7 @@
       "metadata": {},
       "source": [
         "## API key and client\n",
-        "Please provide a valid API key below to connect to the Labelbox client properly. For more information, please review the [Create API key guide](https://docs.labelbox.com/reference/create-api-key)."
+        "Replace the value of `API_KEY` with a valid [API key]([ref:create-api-key](https://docs.labelbox.com/reference/create-api-key)) to connect to the Labelbox client."
       ]
     },
     {
@@ -80,9 +80,9 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "## Example: Create prompt response projects and ontologies\n",
+        "## Example: Create prompt and response projects and ontologies\n",
         "\n",
-        "The steps to creating prompt response projects and ontologies through the Labelbox-Python SDK are similar to creating a regular project. However, they vary slightly, and we will showcase the different methods in this example workflow."
+        "The steps of creating prompt and response projects and corresponding ontologies using the Labelbox-Python SDK are similar to creating a regular project, and we will describe the slight differences for each scenario."
       ]
     },
     {
@@ -91,7 +91,7 @@
       "source": [
         "### Create a prompt and response ontology\n",
         "\n",
-        "You can create ontologies for prompt and response projects in the same way as other project ontologies using two methods: `client.create_ontology` and `client.create_ontology_from_feature_schemas`. For response creation projects the only difference between other projects is the media_type for the project needs to be set to `lb.MediaType.Text`. For prompt and prompt response creation projects you need to include their respective media type: `lb.MediaType.LLMPromptCreation` and `lb.MediaType.LLMPromptResponseCreation`. Additional you also need to provide an `ontology_kind` parameter, which needs to be set to `lb.OntologyKind.ResponseCreation` this is only applicable for prompt and prompt response creation projects."
+        "You can create ontologies for prompt and response projects in the same way as other project ontologies using two methods: `client.create_ontology` and `client.create_ontology_from_feature_schemas`. You also need to include the respective `media_type`: `lb.MediaType.LLMPromptCreation` and `lb.MediaType.LLMPromptResponseCreation`. Additionally, you need to provide an `ontology_kind` parameter set to `lb.OntologyKind.ResponseCreation` that is only applicable for prompt and prompt response creation projects."
       ]
     },
     {
@@ -100,9 +100,9 @@
       "source": [
         "#### Option A: `client.create_ontology`\n",
         "\n",
-        "Typically, you create ontologies and generate the associated features simultaneously. Below is an example of creating an ontology for your prompt and response projects using supported classifications; for information on supported annotation types, visit our [prompt and response generation](https://docs.labelbox.com/docs/prompt-and-response-generation-editor) guide.\n",
+        "Typically, you create ontologies and generate the associated features simultaneously. Below is an example of creating an ontology for your prompt and response projects using supported classifications; for information on supported annotation types, see [prompt and response generation](https://docs.labelbox.com/docs/prompt-and-response-generation-editor).\n",
         "\n",
-        "Depending if you were creating a prompt, response, or prompt and response creation projects you would not need certain classifications inside your ontologies. For information on supported annotation types, visit our [prompt and response generation](doc:prompt-and-response-generation-editor#supported-prompt-formats) guide. In this notebook, we will be creating a prompt and response creation ontology. "
+        "Depending if you were creating a prompt, response, or prompt and response creation projects, you don't need certain classifications inside your ontologies. For information on supported annotation types, see [prompt and response generation](doc:prompt-and-response-generation-editor#supported-prompt-formats). In this notebook, we will create a prompt and response creation ontology. "
       ]
     },
     {
@@ -165,7 +165,7 @@
       "metadata": {},
       "source": [
         "### Option B: `client.create_ontology_from_feature_schemas`\n",
-        "Ontologies can also be created with feature schema IDs. This makes your ontologies with existing features compared to generating new features. You can get these features by going to the _Schema_ tab inside Labelbox. (uncomment the below code block for this option)"
+        "You can also create ontologies using feature schema IDs, which make your ontologies with existing features instead of generating new features. You can get these features by going to the _Schema_ tab inside Labelbox."
       ]
     },
     {
@@ -174,6 +174,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
+        "# Uncomment the follwing code block for this option\n",
         "# ontology = client.create_ontology_from_feature_schemas(\n",
         "#     \"LMC ontology\",\n",
         "#     feature_schema_ids=[\"<list of feature schema ids\"],\n",
@@ -209,7 +210,7 @@
       "source": [
         "## Create prompt response and prompt creation projects\n",
         "\n",
-        "When creating a prompt response or prompt creation project using client.create_prompt_response_generation_project, you do not need to create data rows because they are generated automatically. This method takes the same parameters as the traditional client.create_project but with a few specific additional parameters.\n",
+        "When creating a prompt response or prompt creation project using `client.create_prompt_response_generation_project()`, you do not need to create data rows because they are generated automatically. This method takes the same parameters as the traditional client.create_project but with a few specific additional parameters.\n",
         "\n",
         "Parameters\n",
         "The `client.create_prompt_response_generation_project` method requires the following parameters:\n",