Foundations exercises

1_foundations/1_lab1.ipynb

@@ -149,6 +149,8 @@
     "\n",
     "import os\n",
     "openai_api_key = os.getenv('OPENAI_API_KEY')\n",
+    "openai_base_url = os.getenv('OPENAI_BASE_URL') # access firm provided API\n",
+    "openai_model = \"gpt-5-nano-2025-08-07\" # access firm provided mdoel endpoint\n",
     "\n",
     "if openai_api_key:\n",
     "    print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
@@ -181,7 +183,7 @@
     "# If you get a NameError - head over to the guides folder (guide 6)to learn about NameErrors - always instantly fixable\n",
     "# If you're not using OpenAI, you just need to slightly modify this - precise instructions are in the AI APIs guide (guide 9)\n",
     "\n",
-    "openai = OpenAI()"
+    "openai = OpenAI(api_key=openai_api_key, base_url=openai_base_url)\n"
    ]
   },
   {
@@ -207,7 +209,7 @@
     "# If you get a NameError, head to the guides folder (guide 6) to learn about NameErrors - always instantly fixable\n",
     "\n",
     "response = openai.chat.completions.create(\n",
-    "    model=\"gpt-4.1-nano\",\n",
+    "    model=openai_model,\n",
     "    messages=messages\n",
     ")\n",
     "\n",
@@ -322,30 +324,90 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# First create the messages:\n",
+    "# Q1: \n",
+    "question = \"You are a senior venture capitalist with experience around the world on what markets are present, what are the trends, where are the fast growing opportunities. Pick a business area which is unexplored from an agentic AI oppurtunity perspective. Think from first principles and provide data based rationales.\"\n",
+    "messages = [{\"role\": \"user\", \"content\": question}]\n",
     "\n",
-    "messages = [{\"role\": \"user\", \"content\": \"Something here\"}]\n",
+    "response = openai.chat.completions.create(\n",
+    "    model=openai_model,\n",
+    "    messages=messages\n",
+    ")\n",
     "\n",
-    "# Then make the first call:\n",
+    "business_idea = response.choices[0].message.content\n",
     "\n",
-    "response =\n",
+    "print(business_idea)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Q2\n",
     "\n",
-    "# Then read the business idea:\n",
+    "question = f\"\"\"\n",
+    "present a pain-point in the following business area/idea - something challenging that might be ripe for an Agentic solution\n",
     "\n",
-    "business_idea = response.\n",
+    "{business_idea}\n",
+    "\"\"\"\n",
+    "messages = [{\"role\": \"user\", \"content\": question}]\n",
     "\n",
-    "# And repeat! In the next message, include the business idea within the message"
+    "response = openai.chat.completions.create(\n",
+    "    model=openai_model,\n",
+    "    messages=messages\n",
+    ")\n",
+    "\n",
+    "opportunities = response.choices[0].message.content\n",
+    "\n",
+    "print(opportunities)\n"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "\n",
+    "# Q2\n",
+    "\n",
+    "question = f\"\"\"\n",
+    "propose the Agentic AI solution for following business idea considering it's pain points\n",
+    "---\n",
+    "Business idea:\n",
+    "{business_idea}\n",
+    "\n",
+    "---\n",
+    "Pain points:\n",
+    "{opportunities}\n",
+    "\"\"\"\n",
+    "messages = [{\"role\": \"user\", \"content\": question}]\n",
+    "\n",
+    "response = openai.chat.completions.create(\n",
+    "    model=openai_model,\n",
+    "    messages=messages\n",
+    ")\n",
+    "\n",
+    "solution = response.choices[0].message.content\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
-   "source": []
+   "outputs": [],
+   "source": [
+    "from IPython.display import Markdown, display\n",
+    "\n",
+    "display(Markdown(solution))\n"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "Python 3.12.10 ('.venv': venv)",
    "language": "python",
    "name": "python3"
   },
@@ -359,7 +421,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.9"
+   "version": "3.12.10"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "fb00a60d65a3c46c8a5f9d7b24f2a346cd4f17f0d7f92ab129f47d7a251c252d"
+   }
   }
  },
  "nbformat": 4,