small fixes to tutorials (#205)

tutorials/5.validation.ipynb

@@ -15,9 +15,9 @@
    "source": [
     "Instead of framing \"self-critique\" or \"self-reflection\" in AI as new concepts, we can view them as validation errors with clear error messages that the systen can use to self correct.\n",
     "\n",
-    "Pydantic offers an customizable and expressive validation framework for Python. Instructor leverages Pydantic's validation framework to provide a uniform developer experience for both code-based and LLM-based validation, as well as a reasking mechanism for correcting LLM outputs based on validation errors. To learn more check out the Pydantic docs on validators.\n",
+    "Pydantic offers an customizable and expressive validation framework for Python. Instructor leverages Pydantic's validation framework to provide a uniform developer experience for both code-based and LLM-based validation, as well as a reasking mechanism for correcting LLM outputs based on validation errors. To learn more check out the Pydantic [docs](https://docs.pydantic.dev/latest/) on validators.\n",
     "\n",
-    "Note: For the majourity of this notebook we won't be calling openai, just using validators to see how we can control the validation of the objects."
+    "Note: For the majority of this notebook we won't be calling openai, just using validators to see how we can control the validation of the objects."
    ]
   },
   {
@@ -686,7 +686,7 @@
    "source": [
     "Integrating these validation examples with the OpenAI API is streamlined using `instructor`. After patching the OpenAI client with `instructor`, you simply need to specify a `response_model` for your requests. This setup ensures that all the validation processes occur automatically.\n",
     "\n",
-    "Additionally, you can set a maximum number of retries. When calling the OpenAI client, the system can re-attempt to generate a correct answer. It does this by resending the original query along with feedback on why the previous response was rejected, guiding the LLM towards a more accurate answer in subsequent attempts."
+    "To enable reasking you can set a maximum number of retries. When calling the OpenAI client, the system can re-attempt to generate a correct answer. It does this by resending the original query along with feedback on why the previous response was rejected, guiding the LLM towards a more accurate answer in subsequent attempts."
    ]
   },
   {
@@ -736,6 +736,7 @@
   {
    "cell_type": "code",
    "execution_count": 80,
+   "id": "0328bbc5",
    "metadata": {},
    "outputs": [
     {
@@ -808,7 +809,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -822,7 +823,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,