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lgautier/agent-ai.ipynb

Created May 14, 2025 17:26
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agent-ai.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4"
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "TCHGbz84vHHU",
"outputId": "be876f38-07a5-4b8c-aee3-75cbcd5c44e1"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[31mInstalling APT packages.\u001b[30m\n",
"W: Skipping acquire of configured file 'main/source/Sources' as repository 'https://r2u.stat.illinois.edu/ubuntu jammy InRelease' does not seem to provide it (sources.list entry misspelt?)\n",
"debconf: unable to initialize frontend: Dialog\n",
"debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 78, <> line 5.)\n",
"debconf: falling back to frontend: Readline\n",
"debconf: unable to initialize frontend: Readline\n",
"debconf: (This frontend requires a controlling tty.)\n",
"debconf: falling back to frontend: Teletype\n",
"dpkg-preconfigure: unable to re-open stdin: \n",
"Selecting previously unselected package pci.ids.\n",
"(Reading database ... 126102 files and directories currently installed.)\n",
"Preparing to unpack .../pci.ids_0.0~2022.01.22-1ubuntu0.1_all.deb ...\n",
"Unpacking pci.ids (0.0~2022.01.22-1ubuntu0.1) ...\n",
"Selecting previously unselected package libpci3:amd64.\n",
"Preparing to unpack .../libpci3_1%3a3.7.0-6_amd64.deb ...\n",
"Unpacking libpci3:amd64 (1:3.7.0-6) ...\n",
"Selecting previously unselected package lshw.\n",
"Preparing to unpack .../lshw_02.19.git.2021.06.19.996aaad9c7-2build1_amd64.deb ...\n",
"Unpacking lshw (02.19.git.2021.06.19.996aaad9c7-2build1) ...\n",
"Selecting previously unselected package pciutils.\n",
"Preparing to unpack .../pciutils_1%3a3.7.0-6_amd64.deb ...\n",
"Unpacking pciutils (1:3.7.0-6) ...\n",
"Selecting previously unselected package usb.ids.\n",
"Preparing to unpack .../usb.ids_2022.04.02-1_all.deb ...\n",
"Unpacking usb.ids (2022.04.02-1) ...\n",
"Setting up pci.ids (0.0~2022.01.22-1ubuntu0.1) ...\n",
"Setting up lshw (02.19.git.2021.06.19.996aaad9c7-2build1) ...\n",
"Setting up usb.ids (2022.04.02-1) ...\n",
"Setting up libpci3:amd64 (1:3.7.0-6) ...\n",
"Setting up pciutils (1:3.7.0-6) ...\n",
"Processing triggers for man-db (2.10.2-1) ...\n",
"Processing triggers for libc-bin (2.35-0ubuntu3.8) ...\n",
"/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc.so.2 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_5.so.3 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libtbb.so.12 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libumf.so.0 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libur_loader.so.0 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libhwloc.so.15 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libtcm_debug.so.1 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libtbbbind.so.3 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libur_adapter_opencl.so.0 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libtbbbind_2_0.so.3 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libtcm.so.1 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libur_adapter_level_zero.so.0 is not a symbolic link\n",
"\n",
"/sbin/ldconfig.real: /usr/local/lib/libtbbmalloc_proxy.so.2 is not a symbolic link\n",
"\n",
"\u001b[31mFetching Ollama.\u001b[30m\n",
">>> Installing ollama to /usr/local\n",
">>> Downloading Linux amd64 bundle\n",
"######################################################################## 100.0%\n",
">>> Creating ollama user...\n",
">>> Adding ollama user to video group...\n",
">>> Adding current user to ollama group...\n",
">>> Creating ollama systemd service...\n",
"\u001b[1m\u001b[31mWARNING:\u001b[m systemd is not running\n",
">>> NVIDIA GPU installed.\n",
">>> The Ollama API is now available at 127.0.0.1:11434.\n",
">>> Install complete. Run \"ollama\" from the command line.\n",
"\u001b[31mStarting Ollama server.\u001b[30m\n",
"\u001b[31mPulling LLM Gemma3.\u001b[30m\n"
]
}
],
"source": [
"# Derived from the the Google Cloud doc:\n",
"# https://medium.com/google-cloud/gemma-3-ollama-on-colab-a-developers-quickstart-7bbf93ab8fef\n",
"! echo $(tput setaf 1)\"Installing APT packages.\"$(tput setaf 0)\n",
"! sudo apt-get -qq update && sudo apt-get -qq install -y pciutils lshw\n",
"! echo $(tput setaf 1)\"Fetching Ollama.\"$(tput setaf 0)\n",
"! curl -fsSL https://ollama.com/install.sh | sh\n",
"! echo $(tput setaf 1)\"Starting Ollama server.\"$(tput setaf 0)\n",
"! nohup ollama serve > ollama.log 2>&1 &\n",
"! echo $(tput setaf 1)\"Pulling LLM Gemma3.\"$(tput setaf 0)\n",
"! ollama pull gemma3:12b > ollama_pull.log 2>&1"
]
},
{
"cell_type": "code",
"source": [
"!pip install --quiet -U ollama\n",
"import ollama"
],
"metadata": {
"id": "zf2DZ3TNwRT7"
},
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"source": [
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=[\n",
" {'role': 'user',\n",
" 'content': (\n",
" 'Make the following calculation: 392373366237 * 562310951975'\n",
" )\n",
" }\n",
" ]\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "jikEvoI84fHV",
"outputId": "7ed9dd06-a713-4aac-f7c1-5a89e030a519"
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Okay, let's calculate 392373366237 * 562310951975.\n",
"\n",
"This is a large multiplication, so I will use Python to perform the calculation:\n",
"\n",
"```python\n",
"num1 = 392373366237\n",
"num2 = 562310951975\n",
"result = num1 * num2\n",
"print(result)\n",
"```\n",
"\n",
"This code will output:\n",
"\n",
"2208270460914286076025\n",
"\n",
"Therefore, 392373366237 * 562310951975 = **2208270460914286076025**\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"response"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "N3XJWlAVARSd",
"outputId": "37423683-3c92-4294-85f8-4686706a118f"
},
"execution_count": 4,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"ChatResponse(model='gemma3:12b', created_at='2025-05-14T17:10:27.731411356Z', done=True, done_reason='stop', total_duration=45095128839, load_duration=34966617762, prompt_eval_count=41, prompt_eval_duration=1020168428, eval_count=189, eval_duration=9106979168, message=Message(role='assistant', content=\"Okay, let's calculate 392373366237 * 562310951975.\\n\\nThis is a large multiplication, so I will use Python to perform the calculation:\\n\\n```python\\nnum1 = 392373366237\\nnum2 = 562310951975\\nresult = num1 * num2\\nprint(result)\\n```\\n\\nThis code will output:\\n\\n2208270460914286076025\\n\\nTherefore, 392373366237 * 562310951975 = **2208270460914286076025**\\n\", images=None, tool_calls=None))"
]
},
"metadata": {},
"execution_count": 4
}
]
},
{
"cell_type": "code",
"source": [
"prompt_system = \"\"\"\n",
"You have access to functions. If you decide to invoke any of the function(s),\n",
"you MUST put it in the format of\n",
"{\"name\": function name,\n",
" \"parameters\": dictionary of argument name and its value}\n",
"\n",
"You SHOULD NOT include any other text in the response if you call a function.\n",
"\n",
"Functions:\n",
"[\n",
" {\n",
" \"name\": \"get_medication_stock\",\n",
" \"description\": \"Get the number of boxes of medication in stock.\",\n",
" \"parameters\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"ndc_code\": {\n",
" \"type\": \"string\"\n",
" }\n",
" },\n",
" \"required\": [\n",
" \"ndc_code\"\n",
" ]\n",
" }\n",
" },\n",
" {\n",
" \"name\": \"get_ndc_code\",\n",
" \"description\": \"Get possible ndc codes for a medication.\",\n",
" \"parameters\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"medication\": {\n",
" \"type\": \"string\"\n",
" }\n",
" },\n",
" \"required\": [\n",
" \"medication\"\n",
" ]\n",
" },\n",
" }\n",
"]\n",
"\"\"\""
],
"metadata": {
"id": "khMrhcjbw8w4"
},
"execution_count": 5,
"outputs": []
},
{
"cell_type": "code",
"source": [
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=[\n",
" {'role': 'system', 'content': prompt_system},\n",
" {'role': 'user',\n",
" 'content': \"\"\"\n",
" Name the first month of the year.\n",
" \"\"\"}\n",
" ]\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "A7pWGCS1dCFx",
"outputId": "a2339498-06ea-48d0-b121-212d98bb3fb2"
},
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"January\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=[\n",
" {'role': 'system', 'content': prompt_system},\n",
" {'role': 'user',\n",
" 'content': \"\"\"\n",
" How many boxes of medication with NDC code ABCD-EFG do we have left?\n",
" \"\"\"}\n",
" ]\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "f9kswHOZcjxr",
"outputId": "92a93884-a590-460c-c462-c89926487187"
},
"execution_count": 7,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"{\"name\": \"get_medication_stock\", \"parameters\": {\"ndc_code\": \"ABCD-EFG\"}}\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=[\n",
" {'role': 'system', 'content': prompt_system},\n",
" {'role': 'user',\n",
" 'content': \"\"\"\n",
" What are possible NDC codes for the medication 'Aspirin'?\n",
" \"\"\"}\n",
" ],\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "teaIL5crdqO3",
"outputId": "6184b04d-9644-4d20-847c-4ec444e429ff"
},
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"{\"name\": \"get_ndc_code\", \"parameters\": {\"medication\": \"Aspirin\"}}\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=[\n",
" {'role': 'user',\n",
" 'content': \"\"\"\n",
" How many boxes of Aspirin do we have in stock altogether?\n",
" \"\"\"}\n",
" ]\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "DJSD2NX3d34B",
"outputId": "12c5726f-ca60-41f6-fede-e73092e3050b"
},
"execution_count": 21,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"I need more information to answer your question. I need to know:\n",
"\n",
"* **Where are you tracking your inventory?** (e.g., a spreadsheet, a database, physical shelves, a store's inventory system)\n",
"* **Where are the stock quantities listed?** (I need to know what system I need to look at and where it's located)\n",
"\n",
"Once you provide me with that information, I can help you figure out how many boxes of Aspirin you have in stock.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"prompt_pseudocode_system = \"\"\"\n",
"access to functions = True\n",
"\n",
"if function invoked:\n",
" response MUST be in the format of\n",
" {\"name\": function name,\n",
" \"parameters\": dictionary of argument name and its value}\n",
"\n",
"Functions:\n",
"[\n",
" {\n",
" \"name\": \"get_medication_stock\",\n",
" \"description\": \"Get the number of boxes of medication in stock.\",\n",
" \"parameters\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"ndc_code\": {\n",
" \"type\": \"string\"\n",
" }\n",
" },\n",
" \"required\": [\n",
" \"ndc_code\"\n",
" ]\n",
" }\n",
" },\n",
" {\n",
" \"name\": \"get_ndc_code\",\n",
" \"description\": \"Get possible ndc codes for a medication.\",\n",
" \"parameters\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"medication\": {\n",
" \"type\": \"string\"\n",
" }\n",
" },\n",
" \"required\": [\n",
" \"medication\"\n",
" ]\n",
" },\n",
" }\n",
"]\n",
"\"\"\""
],
"metadata": {
"id": "HxBoNHVNvCRu"
},
"execution_count": 10,
"outputs": []
},
{
"cell_type": "code",
"source": [
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=[\n",
" {'role': 'system', 'content': prompt_pseudocode_system},\n",
" {'role': 'user',\n",
" 'content': \"\"\"\n",
" How many boxes of medication with NDC code ABCD-EFG do we have left?\n",
" \"\"\"}\n",
" ]\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Z6vYKd2cvUz1",
"outputId": "bbd907d0-caba-4e98-91a4-cb1f7f8535d6"
},
"execution_count": 11,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"```json\n",
"{\"name\": \"get_medication_stock\", \"parameters\": {\"ndc_code\": \"ABCD-EFG\"}}\n",
"```\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import ollama\n",
"\n",
"prompt_system_react = \"\"\"\n",
"You have access to functions. If you decide to invoke any of the function(s),\n",
"you MUST put it in the format of\n",
"{\"name\": function name,\n",
" \"parameters\": dictionary of argument name and its value}\n",
"\n",
"Functions:\n",
"[\n",
" {\n",
" \"name\": \"get_medication_stock\",\n",
" \"description\": \"Get the number of boxes of medication in stock.\",\n",
" \"parameters\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"ndc_code\": {\n",
" \"type\": \"string\"\n",
" }\n",
" },\n",
" \"required\": [\n",
" \"ndc_code\"\n",
" ]\n",
" }\n",
" },\n",
" {\n",
" \"name\": \"get_ndc_code\",\n",
" \"description\": \"Get possible ndc codes for a medication.\",\n",
" \"parameters\": {\n",
" \"type\": \"object\",\n",
" \"properties\": {\n",
" \"medication\": {\n",
" \"type\": \"string\"\n",
" }\n",
" },\n",
" \"required\": [\n",
" \"medication\"\n",
" ]\n",
" },\n",
" }\n",
"]\n",
"\n",
"Use the following multi-step conversation:\n",
"\n",
"Thought: I need to do something...\n",
"Action: I should use the tool `tool_name` with input `tool_input`\n",
"\n",
"Wait user to get the result of the tool is `tool_output`\n",
"\n",
"And finally answer the request.\n",
"\"\"\"\n",
"\n",
"messages = [\n",
" {\n",
" 'role': 'system',\n",
" 'content': prompt_system_react\n",
" },\n",
" {\n",
" 'role': 'user',\n",
" 'content': (\n",
" \"\"\"How many boxes of Aspirin do we have in stock altogether? \"\"\"\n",
" )\n",
" }\n",
"]\n",
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=messages\n",
")\n"
],
"metadata": {
"id": "8YotZj39_GM0"
},
"execution_count": 24,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ZH5t_2vW2Io7",
"outputId": "7fbdb201-5153-4f5c-b198-53fda3947592"
},
"execution_count": 25,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thought: I need to find the NDC code for Aspirin first, then I can check the stock.\n",
"Action: {\"name\": \"get_ndc_code\", \"parameters\": {\"medication\": \"Aspirin\"}}\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"__API_CALL_RESULT__ = \"\"\"\n",
"result of get_ndc_code:\n",
"Code: ABCD-DEF\n",
"Code: ABCD-GHI\n",
"\"\"\"\n",
"messages.append(\n",
" {'role': 'assistant', 'content': response.message.content},\n",
")\n",
"messages.append(\n",
" {'role': 'user', 'content': __API_CALL_RESULT__}\n",
")\n",
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=messages\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"id": "RWT_wygxsDo3",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "3af6e7d9-6567-4d0f-9693-502f298595d7"
},
"execution_count": 26,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thought: Now that I have the NDC codes, I can check the stock for each one and sum the results.\n",
"Action: {\"name\": \"get_medication_stock\", \"parameters\": {\"ndc_code\": \"ABCD-DEF\"}}\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"__API_CALL_RESULT__ = \"\"\"\n",
"result of get_medication_stock:\n",
"3 boxes\n",
"\"\"\"\n",
"messages.append(\n",
" {'role': 'assistant', 'content': response.message.content},\n",
")\n",
"messages.append(\n",
" {'role': 'user', 'content': __API_CALL_RESULT__}\n",
")\n",
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=messages\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "7uDqdjA8ZnRm",
"outputId": "49d5a735-c229-4ff0-867d-b3ea0f3501a1"
},
"execution_count": 27,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thought: I need to check the stock for the second NDC code as well.\n",
"Action: {\"name\": \"get_medication_stock\", \"parameters\": {\"ndc_code\": \"ABCD-GHI\"}}\n",
"\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"__API_CALL_RESULT__ = \"\"\"\n",
"result of get_medication_stock:\n",
"5 boxes\n",
"\"\"\"\n",
"messages.append(\n",
" {'role': 'assistant', 'content': response.message.content},\n",
")\n",
"messages.append(\n",
" {'role': 'user', 'content': __API_CALL_RESULT__}\n",
")\n",
"response = ollama.chat(\n",
" 'gemma3:12b',\n",
" messages=messages,\n",
" options={'seed': 121, 'temperature': 0.9}\n",
")\n",
"print(response.message.content)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "AtGPhoWNiCbX",
"outputId": "8d8a5f0b-71fd-47d0-bdd2-2079448b853d"
},
"execution_count": 48,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thought: I have the stock for both NDC codes. Now I need to add them together to get the total.\n",
"Answer: We have a total of 8 boxes of Aspirin in stock.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"def get_ndc_code(medication: str):\n",
" \"\"\"Mock lookup. Only knows about Aspirin.\"\"\"\n",
" if medication == 'Aspirin':\n",
" return ['ABCD-DEF', 'ABCD-GHI']\n",
" else:\n",
" return []\n",
"\n",
"\n",
"def get_medication_stock(ndc_code: str):\n",
" \"\"\"Mock inventory.\"\"\"\n",
" if ndc_code == 'ABCD-DEF':\n",
" return 3\n",
" elif ndc_code == 'ABCD-GHI':\n",
" return 5\n",
" else:\n",
" return 0\n",
"\n",
"def calculate(expression):\n",
" return eval(expression)\n",
"\n",
"\n",
"import re\n",
"import json\n",
"\n",
"\n",
"def get_action(response_message):\n",
" \"\"\"Get action from response message, if any.\"\"\"\n",
" m = re.match(r'(?:.|\\n)*\\n?Action: ({.+})$', response_message, re.MULTILINE)\n",
" if m:\n",
" return json.loads(m.group(1))\n",
" else:\n",
" return None\n",
"\n",
"def perform_action(action):\n",
" func = globals()[action['name']]\n",
" parameters = action['parameters']\n",
" res = func(**parameters)\n",
" return res\n",
"\n",
"def agent(user_prompt):\n",
" messages = [\n",
" {'role': 'system', 'content': prompt_system_react},\n",
" {'role': 'user',\n",
" 'content': user_prompt}\n",
" ]\n",
"\n",
" print('Thinking...')\n",
" response = ollama.chat('gemma3:12b', messages=messages)\n",
" action = get_action(response.message.content)\n",
"\n",
" while action:\n",
" print(f' Agent action: {action[\"name\"]}', end='', flush=True)\n",
" res = perform_action(action)\n",
" print(f' returned {res}')\n",
" messages.extend(\n",
" [\n",
" {'role': 'assistant',\n",
" 'content': response.message.content},\n",
" {'role': 'user',\n",
" 'content': f'Resulf of {action[\"name\"]}:\\n {res}'},\n",
" ]\n",
" )\n",
" print('Thinking...')\n",
" response = ollama.chat('gemma3:12b', messages=messages)\n",
" action = get_action(response.message.content)\n",
"\n",
" print(response.message.content)\n",
"\n",
"agent('How many boxes of Aspirin do we have in stock altogether?')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "TceYwkm5iP6X",
"outputId": "e8b7b037-0dff-49a3-fe3f-06e2fea9da87"
},
"execution_count": 17,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thinking...\n",
" Agent action: get_ndc_code returned ['ABCD-DEF', 'ABCD-GHI']\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 3\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 5\n",
"Thinking...\n",
"Thought: I have the stock for each NDC code. Now I need to sum them to find the total stock.\n",
"Answer: We have a total of 8 boxes of Aspirin in stock.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"agent('Do we have boxes of Aspirin left?')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Mpj9XKDbdwOB",
"outputId": "c4dd0dea-b82d-4c59-8004-a0e096f870e3"
},
"execution_count": 18,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thinking...\n",
" Agent action: get_ndc_code returned ['ABCD-DEF', 'ABCD-GHI']\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 3\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 5\n",
"Thinking...\n",
"We have 3 boxes of Aspirin with NDC code ABCD-DEF and 5 boxes of Aspirin with NDC code ABCD-GHI in stock.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"agent('Is there Aspirin in stock?')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "RA1zGT28d3NI",
"outputId": "72b23eda-3cb9-4b58-a4a2-8d5c4da6b0a7"
},
"execution_count": 19,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thinking...\n",
" Agent action: get_ndc_code returned ['ABCD-DEF', 'ABCD-GHI']\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 3\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 5\n",
"Thinking...\n",
"The stock for Aspirin (ABCD-DEF) is 3 boxes, and the stock for Aspirin (ABCD-GHI) is 5 boxes.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"agent('How much Aspirin do we have in total?')"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "1PKgiw4DfARB",
"outputId": "10fb63f3-1777-4c5a-9796-f842c03bcda3"
},
"execution_count": 20,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Thinking...\n",
" Agent action: get_ndc_code returned ['ABCD-DEF', 'ABCD-GHI']\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 3\n",
"Thinking...\n",
" Agent action: get_medication_stock returned 5\n",
"Thinking...\n",
"Thought: I have the stock for both NDC codes. Now I need to add them together.\n",
"Answer: We have a total of 8 boxes of Aspirin.\n"
]
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "3ziq1txifRsh"
},
"execution_count": 20,
"outputs": []
}
]
}
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