Launching refreshed version of LLM Engineering weeks 1-4 - see README
This commit is contained in:
Edward Donner
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week2/day1.ipynb
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week2/day1.ipynb
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week2/day2.ipynb
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week2/day2.ipynb
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week2/day3.ipynb
194
week2/day3.ipynb
@@ -35,23 +35,11 @@
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"\n",
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"load_dotenv(override=True)\n",
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"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
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"anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n",
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"google_api_key = os.getenv('GOOGLE_API_KEY')\n",
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"\n",
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"if openai_api_key:\n",
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" print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
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"else:\n",
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" print(\"OpenAI API Key not set\")\n",
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" \n",
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"if anthropic_api_key:\n",
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" print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n",
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"else:\n",
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" print(\"Anthropic API Key not set\")\n",
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"\n",
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"if google_api_key:\n",
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" print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n",
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"else:\n",
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" print(\"Google API Key not set\")"
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" print(\"OpenAI API Key not set\")"
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]
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},
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{
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@@ -64,7 +52,7 @@
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"# Initialize\n",
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"\n",
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"openai = OpenAI()\n",
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"MODEL = 'gpt-4o-mini'"
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"MODEL = 'gpt-4.1-mini'"
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]
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},
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{
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@@ -74,6 +62,8 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"# Again, I'll be in scientist-mode and change this global during the lab\n",
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"\n",
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"system_message = \"You are a helpful assistant\""
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]
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},
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@@ -82,32 +72,75 @@
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"id": "98e97227-f162-4d1a-a0b2-345ff248cbe7",
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"metadata": {},
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"source": [
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"# Please read this! A change from the video:\n",
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"## And now, writing a new callback\n",
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"\n",
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"In the video, I explain how we now need to write a function called:\n",
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"We now need to write a function called:\n",
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"\n",
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"`chat(message, history)`\n",
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"\n",
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"Which expects to receive `history` in a particular format, which we need to map to the OpenAI format before we call OpenAI:\n",
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"Which will be a callback function we will give gradio.\n",
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"\n",
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"```\n",
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"[\n",
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" {\"role\": \"system\", \"content\": \"system message here\"},\n",
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" {\"role\": \"user\", \"content\": \"first user prompt here\"},\n",
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" {\"role\": \"assistant\", \"content\": \"the assistant's response\"},\n",
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" {\"role\": \"user\", \"content\": \"the new user prompt\"},\n",
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"]\n",
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"```\n",
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"### The job of this function\n",
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"\n",
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"But Gradio has been upgraded! Now it will pass in `history` in the exact OpenAI format, perfect for us to send straight to OpenAI.\n",
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"\n",
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"So our work just got easier!\n",
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"\n",
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"We will write a function `chat(message, history)` where: \n",
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"**message** is the prompt to use \n",
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"**history** is the past conversation, in OpenAI format \n",
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"\n",
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"We will combine the system message, history and latest message, then call OpenAI."
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"Take a message, take the prior conversation, and return the response.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "354ce793",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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" return \"bananas\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e87f3417",
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"metadata": {},
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"outputs": [],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5d4996e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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" return f\"You said {message} and the history is {history} but I still say bananas\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "434a0417",
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"metadata": {},
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"outputs": [],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "7890cac3",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"id": "f7330d7f",
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"metadata": {},
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"source": [
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"## OK! Let's write a slightly better chat callback!"
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]
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},
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{
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@@ -117,46 +150,61 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"# Simpler than in my video - we can easily create this function that calls OpenAI\n",
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"# It's now just 1 line of code to prepare the input to OpenAI!\n",
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"\n",
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"# Student Octavio O. has pointed out that this isn't quite as straightforward for Claude -\n",
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"# see the excellent contribution in community-contributions \"Gradio_issue_with_Claude\" that handles Claude.\n",
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"\n",
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"def chat(message, history):\n",
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" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
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" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
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" return response.choices[0].message.content\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0ab706f9",
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"metadata": {},
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"outputs": [],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3bce145a",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
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"\n",
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" print(\"History is:\")\n",
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" print(history)\n",
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" print(\"And messages is:\")\n",
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" print(messages)\n",
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"\n",
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" stream = openai.chat.completions.create(model=MODEL, messages=messages, stream=True)\n",
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"\n",
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" response = \"\"\n",
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" for chunk in stream:\n",
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" response += chunk.choices[0].delta.content or ''\n",
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" yield response"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1334422a-808f-4147-9c4c-57d63d9780d0",
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"metadata": {},
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"source": [
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"## And then enter Gradio's magic!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0866ca56-100a-44ab-8bd0-1568feaf6bf2",
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"id": "b8beeca6",
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"metadata": {},
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"outputs": [],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1334422a-808f-4147-9c4c-57d63d9780d0",
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"metadata": {},
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"source": [
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"## OK let's keep going!\n",
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"\n",
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"Using a system message to add context, and to give an example answer.. this is \"one shot prompting\" again"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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@@ -171,24 +219,6 @@
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"Encourage the customer to buy hats if they are unsure what to get.\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4e5be3ec-c26c-42bc-ac16-c39d369883f6",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
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"\n",
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" stream = openai.chat.completions.create(model=MODEL, messages=messages, stream=True)\n",
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"\n",
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" response = \"\"\n",
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" for chunk in stream:\n",
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" response += chunk.choices[0].delta.content or ''\n",
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" yield response"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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@@ -227,13 +257,11 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"# Fixed a bug in this function brilliantly identified by student Gabor M.!\n",
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"# I've also improved the structure of this function\n",
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"\n",
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"def chat(message, history):\n",
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"\n",
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" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
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" relevant_system_message = system_message\n",
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" if 'belt' in message:\n",
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" if 'belt' in message.lower():\n",
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" relevant_system_message += \" The store does not sell belts; if you are asked for belts, be sure to point out other items on sale.\"\n",
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" \n",
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" messages = [{\"role\": \"system\", \"content\": relevant_system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
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@@ -264,7 +292,7 @@
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"<table style=\"margin: 0; text-align: left;\">\n",
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" <tr>\n",
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" <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
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" <img src=\"../business.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
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" <img src=\"../assets/business.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
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" </td>\n",
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" <td>\n",
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" <h2 style=\"color:#181;\">Business Applications</h2>\n",
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@@ -277,17 +305,15 @@
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6dfb9e21-df67-4c2b-b952-5e7e7961b03d",
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"cell_type": "markdown",
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"id": "acc0e5a9",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"display_name": ".venv",
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"language": "python",
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"name": "python3"
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},
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@@ -301,7 +327,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.13"
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"version": "3.12.9"
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}
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},
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"nbformat": 4,
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274
week2/day4.ipynb
274
week2/day4.ipynb
@@ -17,8 +17,6 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports\n",
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"\n",
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"import os\n",
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"import json\n",
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"from dotenv import load_dotenv\n",
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@@ -43,7 +41,7 @@
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"else:\n",
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" print(\"OpenAI API Key not set\")\n",
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" \n",
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"MODEL = \"gpt-4o-mini\"\n",
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"MODEL = \"gpt-4.1-mini\"\n",
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"openai = OpenAI()\n",
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"\n",
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"# As an alternative, if you'd like to use Ollama instead of OpenAI\n",
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@@ -59,9 +57,11 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"system_message = \"You are a helpful assistant for an Airline called FlightAI. \"\n",
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"system_message += \"Give short, courteous answers, no more than 1 sentence. \"\n",
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"system_message += \"Always be accurate. If you don't know the answer, say so.\""
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"system_message = \"\"\"\n",
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"You are a helpful assistant for an Airline called FlightAI.\n",
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"Give short, courteous answers, no more than 1 sentence.\n",
|
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"Always be accurate. If you don't know the answer, say so.\n",
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"\"\"\""
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]
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},
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{
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@@ -71,9 +71,8 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"# This function looks rather simpler than the one from my video, because we're taking advantage of the latest Gradio updates\n",
|
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"\n",
|
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"def chat(message, history):\n",
|
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" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
" return response.choices[0].message.content\n",
|
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@@ -109,9 +108,9 @@
|
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"ticket_prices = {\"london\": \"$799\", \"paris\": \"$899\", \"tokyo\": \"$1400\", \"berlin\": \"$499\"}\n",
|
||||
"\n",
|
||||
"def get_ticket_price(destination_city):\n",
|
||||
" print(f\"Tool get_ticket_price called for {destination_city}\")\n",
|
||||
" city = destination_city.lower()\n",
|
||||
" return ticket_prices.get(city, \"Unknown\")"
|
||||
" print(f\"Tool called for city {destination_city}\")\n",
|
||||
" price = ticket_prices.get(destination_city.lower(), \"Unknown ticket price\")\n",
|
||||
" return f\"The price of a ticket to {destination_city} is {price}\"\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -121,7 +120,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"get_ticket_price(\"Berlin\")"
|
||||
"get_ticket_price(\"London\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -135,7 +134,7 @@
|
||||
"\n",
|
||||
"price_function = {\n",
|
||||
" \"name\": \"get_ticket_price\",\n",
|
||||
" \"description\": \"Get the price of a return ticket to the destination city. Call this whenever you need to know the ticket price, for example when a customer asks 'How much is a ticket to this city'\",\n",
|
||||
" \"description\": \"Get the price of a return ticket to the destination city.\",\n",
|
||||
" \"parameters\": {\n",
|
||||
" \"type\": \"object\",\n",
|
||||
" \"properties\": {\n",
|
||||
@@ -162,6 +161,16 @@
|
||||
"tools = [{\"type\": \"function\", \"function\": price_function}]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "818b4b2b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"tools"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c3d3554f-b4e3-4ce7-af6f-68faa6dd2340",
|
||||
@@ -184,12 +193,13 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def chat(message, history):\n",
|
||||
" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
"\n",
|
||||
" if response.choices[0].finish_reason==\"tool_calls\":\n",
|
||||
" message = response.choices[0].message\n",
|
||||
" response, city = handle_tool_call(message)\n",
|
||||
" response = handle_tool_call(message)\n",
|
||||
" messages.append(message)\n",
|
||||
" messages.append(response)\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
@@ -208,15 +218,16 @@
|
||||
"\n",
|
||||
"def handle_tool_call(message):\n",
|
||||
" tool_call = message.tool_calls[0]\n",
|
||||
" arguments = json.loads(tool_call.function.arguments)\n",
|
||||
" city = arguments.get('destination_city')\n",
|
||||
" price = get_ticket_price(city)\n",
|
||||
" response = {\n",
|
||||
" \"role\": \"tool\",\n",
|
||||
" \"content\": json.dumps({\"destination_city\": city,\"price\": price}),\n",
|
||||
" \"tool_call_id\": tool_call.id\n",
|
||||
" }\n",
|
||||
" return response, city"
|
||||
" if tool_call.function.name == \"get_ticket_price\":\n",
|
||||
" arguments = json.loads(tool_call.function.arguments)\n",
|
||||
" city = arguments.get('destination_city')\n",
|
||||
" price_details = get_ticket_price(city)\n",
|
||||
" response = {\n",
|
||||
" \"role\": \"tool\",\n",
|
||||
" \"content\": price_details,\n",
|
||||
" \"tool_call_id\": tool_call.id\n",
|
||||
" }\n",
|
||||
" return response"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -228,11 +239,224 @@
|
||||
"source": [
|
||||
"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "47f30fbe",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Let's make a couple of improvements\n",
|
||||
"\n",
|
||||
"Handling multiple tool calls in 1 response\n",
|
||||
"\n",
|
||||
"Handling multiple tool calls 1 after another"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b6f5c860",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def chat(message, history):\n",
|
||||
" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
"\n",
|
||||
" if response.choices[0].finish_reason==\"tool_calls\":\n",
|
||||
" message = response.choices[0].message\n",
|
||||
" responses = handle_tool_calls(message)\n",
|
||||
" messages.append(message)\n",
|
||||
" messages.extend(responses)\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
" \n",
|
||||
" return response.choices[0].message.content"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "9c46a861",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def handle_tool_calls(message):\n",
|
||||
" responses = []\n",
|
||||
" for tool_call in message.tool_calls:\n",
|
||||
" if tool_call.function.name == \"get_ticket_price\":\n",
|
||||
" arguments = json.loads(tool_call.function.arguments)\n",
|
||||
" city = arguments.get('destination_city')\n",
|
||||
" price_details = get_ticket_price(city)\n",
|
||||
" responses.append({\n",
|
||||
" \"role\": \"tool\",\n",
|
||||
" \"content\": price_details,\n",
|
||||
" \"tool_call_id\": tool_call.id\n",
|
||||
" })\n",
|
||||
" return responses"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "95f02a4d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "cf262abc",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def chat(message, history):\n",
|
||||
" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
"\n",
|
||||
" while response.choices[0].finish_reason==\"tool_calls\":\n",
|
||||
" message = response.choices[0].message\n",
|
||||
" responses = handle_tool_calls(message)\n",
|
||||
" messages.append(message)\n",
|
||||
" messages.extend(responses)\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
" \n",
|
||||
" return response.choices[0].message.content"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "47d50e70",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import sqlite3\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "bb61a45d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"DB = \"prices.db\"\n",
|
||||
"\n",
|
||||
"with sqlite3.connect(DB) as conn:\n",
|
||||
" cursor = conn.cursor()\n",
|
||||
" cursor.execute('CREATE TABLE IF NOT EXISTS prices (city TEXT PRIMARY KEY, price REAL)')\n",
|
||||
" conn.commit()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "12c73b6a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def get_ticket_price(city):\n",
|
||||
" print(f\"DATABASE TOOL CALLED: Getting price for {city}\", flush=True)\n",
|
||||
" with sqlite3.connect(DB) as conn:\n",
|
||||
" cursor = conn.cursor()\n",
|
||||
" cursor.execute('SELECT price FROM prices WHERE city = ?', (city.lower(),))\n",
|
||||
" result = cursor.fetchone()\n",
|
||||
" return f\"Ticket price to {city} is ${result[0]}\" if result else \"No price data available for this city\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "7cb2e079",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"get_ticket_price(\"London\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "46e43463",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def set_ticket_price(city, price):\n",
|
||||
" with sqlite3.connect(DB) as conn:\n",
|
||||
" cursor = conn.cursor()\n",
|
||||
" cursor.execute('INSERT INTO prices (city, price) VALUES (?, ?) ON CONFLICT(city) DO UPDATE SET price = ?', (city.lower(), price, price))\n",
|
||||
" conn.commit()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "9185228e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"ticket_prices = {\"london\":799, \"paris\": 899, \"tokyo\": 1420, \"sydney\": 2999}\n",
|
||||
"for city, price in ticket_prices.items():\n",
|
||||
" set_ticket_price(city, price)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "cda459b9",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"get_ticket_price(\"Tokyo\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "bfbfa251",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d1a9e9c7",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Exercise\n",
|
||||
"\n",
|
||||
"Add a tool to set the price of a ticket!"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6aeba34c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"<table style=\"margin: 0; text-align: left;\">\n",
|
||||
" <tr>\n",
|
||||
" <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
|
||||
" <img src=\"../assets/business.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
|
||||
" </td>\n",
|
||||
" <td>\n",
|
||||
" <h2 style=\"color:#181;\">Business Applications</h2>\n",
|
||||
" <span style=\"color:#181;\">Hopefully this hardly needs to be stated! You now have the ability to give actions to your LLMs. This Airline Assistant can now do more than answer questions - it could interact with booking APIs to make bookings!</span>\n",
|
||||
" </td>\n",
|
||||
" </tr>\n",
|
||||
"</table>"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"display_name": ".venv",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
@@ -246,7 +470,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.13"
|
||||
"version": "3.12.9"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
609
week2/day5.ipynb
609
week2/day5.ipynb
@@ -23,7 +23,8 @@
|
||||
"import json\n",
|
||||
"from dotenv import load_dotenv\n",
|
||||
"from openai import OpenAI\n",
|
||||
"import gradio as gr"
|
||||
"import gradio as gr\n",
|
||||
"import sqlite3"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -43,8 +44,10 @@
|
||||
"else:\n",
|
||||
" print(\"OpenAI API Key not set\")\n",
|
||||
" \n",
|
||||
"MODEL = \"gpt-4o-mini\"\n",
|
||||
"openai = OpenAI()"
|
||||
"MODEL = \"gpt-4.1-mini\"\n",
|
||||
"openai = OpenAI()\n",
|
||||
"\n",
|
||||
"DB = \"prices.db\""
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -54,83 +57,49 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"system_message = \"You are a helpful assistant for an Airline called FlightAI. \"\n",
|
||||
"system_message += \"Give short, courteous answers, no more than 1 sentence. \"\n",
|
||||
"system_message += \"Always be accurate. If you don't know the answer, say so.\""
|
||||
"system_message = \"\"\"\n",
|
||||
"You are a helpful assistant for an Airline called FlightAI.\n",
|
||||
"Give short, courteous answers, no more than 1 sentence.\n",
|
||||
"Always be accurate. If you don't know the answer, say so.\n",
|
||||
"\"\"\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "61a2a15d-b559-4844-b377-6bd5cb4949f6",
|
||||
"id": "c3e8173c",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# This function looks rather simpler than the one from my video, because we're taking advantage of the latest Gradio updates\n",
|
||||
"\n",
|
||||
"def chat(message, history):\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
" return response.choices[0].message.content\n",
|
||||
"\n",
|
||||
"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "36bedabf-a0a7-4985-ad8e-07ed6a55a3a4",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Tools\n",
|
||||
"\n",
|
||||
"Tools are an incredibly powerful feature provided by the frontier LLMs.\n",
|
||||
"\n",
|
||||
"With tools, you can write a function, and have the LLM call that function as part of its response.\n",
|
||||
"\n",
|
||||
"Sounds almost spooky.. we're giving it the power to run code on our machine?\n",
|
||||
"\n",
|
||||
"Well, kinda."
|
||||
"def get_ticket_price(city):\n",
|
||||
" print(f\"DATABASE TOOL CALLED: Getting price for {city}\", flush=True)\n",
|
||||
" with sqlite3.connect(DB) as conn:\n",
|
||||
" cursor = conn.cursor()\n",
|
||||
" cursor.execute('SELECT price FROM prices WHERE city = ?', (city.lower(),))\n",
|
||||
" result = cursor.fetchone()\n",
|
||||
" return f\"Ticket price to {city} is ${result[0]}\" if result else \"No price data available for this city\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "0696acb1-0b05-4dc2-80d5-771be04f1fb2",
|
||||
"id": "03f19289",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Let's start by making a useful function\n",
|
||||
"\n",
|
||||
"ticket_prices = {\"london\": \"$799\", \"paris\": \"$899\", \"tokyo\": \"$1400\", \"berlin\": \"$499\"}\n",
|
||||
"\n",
|
||||
"def get_ticket_price(destination_city):\n",
|
||||
" print(f\"Tool get_ticket_price called for {destination_city}\")\n",
|
||||
" city = destination_city.lower()\n",
|
||||
" return ticket_prices.get(city, \"Unknown\")"
|
||||
"get_ticket_price(\"Paris\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "80ca4e09-6287-4d3f-997d-fa6afbcf6c85",
|
||||
"id": "bcfb6523",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"get_ticket_price(\"London\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "4afceded-7178-4c05-8fa6-9f2085e6a344",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# There's a particular dictionary structure that's required to describe our function:\n",
|
||||
"\n",
|
||||
"price_function = {\n",
|
||||
" \"name\": \"get_ticket_price\",\n",
|
||||
" \"description\": \"Get the price of a return ticket to the destination city. Call this whenever you need to know the ticket price, for example when a customer asks 'How much is a ticket to this city'\",\n",
|
||||
" \"description\": \"Get the price of a return ticket to the destination city.\",\n",
|
||||
" \"parameters\": {\n",
|
||||
" \"type\": \"object\",\n",
|
||||
" \"properties\": {\n",
|
||||
@@ -142,52 +111,46 @@
|
||||
" \"required\": [\"destination_city\"],\n",
|
||||
" \"additionalProperties\": False\n",
|
||||
" }\n",
|
||||
"}"
|
||||
"}\n",
|
||||
"tools = [{\"type\": \"function\", \"function\": price_function}]\n",
|
||||
"tools"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "bdca8679-935f-4e7f-97e6-e71a4d4f228c",
|
||||
"id": "61a2a15d-b559-4844-b377-6bd5cb4949f6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# And this is included in a list of tools:\n",
|
||||
"\n",
|
||||
"tools = [{\"type\": \"function\", \"function\": price_function}]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c3d3554f-b4e3-4ce7-af6f-68faa6dd2340",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Getting OpenAI to use our Tool\n",
|
||||
"def chat(message, history):\n",
|
||||
" history = [{\"role\": h[\"role\"], \"content\": h[\"content\"]} for h in history]\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
" return response.choices[0].message.content\n",
|
||||
"\n",
|
||||
"There's some fiddly stuff to allow OpenAI \"to call our tool\"\n",
|
||||
"\n",
|
||||
"What we actually do is give the LLM the opportunity to inform us that it wants us to run the tool.\n",
|
||||
"\n",
|
||||
"Here's how the new chat function looks:"
|
||||
"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ce9b0744-9c78-408d-b9df-9f6fd9ed78cf",
|
||||
"id": "c91d012e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def chat(message, history):\n",
|
||||
" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
"\n",
|
||||
" if response.choices[0].finish_reason==\"tool_calls\":\n",
|
||||
" while response.choices[0].finish_reason==\"tool_calls\":\n",
|
||||
" message = response.choices[0].message\n",
|
||||
" response, city = handle_tool_call(message)\n",
|
||||
" responses = handle_tool_calls(message)\n",
|
||||
" messages.append(message)\n",
|
||||
" messages.append(response)\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
" messages.extend(responses)\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
" \n",
|
||||
" return response.choices[0].message.content"
|
||||
]
|
||||
@@ -195,35 +158,59 @@
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b0992986-ea09-4912-a076-8e5603ee631f",
|
||||
"id": "956c3b61",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# We have to write that function handle_tool_call:\n",
|
||||
"\n",
|
||||
"def handle_tool_call(message):\n",
|
||||
" tool_call = message.tool_calls[0]\n",
|
||||
" arguments = json.loads(tool_call.function.arguments)\n",
|
||||
" city = arguments.get('destination_city')\n",
|
||||
" price = get_ticket_price(city)\n",
|
||||
" response = {\n",
|
||||
" \"role\": \"tool\",\n",
|
||||
" \"content\": json.dumps({\"destination_city\": city,\"price\": price}),\n",
|
||||
" \"tool_call_id\": tool_call.id\n",
|
||||
" }\n",
|
||||
" return response, city"
|
||||
"def handle_tool_calls(message):\n",
|
||||
" responses = []\n",
|
||||
" for tool_call in message.tool_calls:\n",
|
||||
" if tool_call.function.name == \"get_ticket_price\":\n",
|
||||
" arguments = json.loads(tool_call.function.arguments)\n",
|
||||
" city = arguments.get('destination_city')\n",
|
||||
" price_details = get_ticket_price(city)\n",
|
||||
" responses.append({\n",
|
||||
" \"role\": \"tool\",\n",
|
||||
" \"content\": price_details,\n",
|
||||
" \"tool_call_id\": tool_call.id\n",
|
||||
" })\n",
|
||||
" return responses"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f4be8a71-b19e-4c2f-80df-f59ff2661f14",
|
||||
"id": "8eca803e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"gr.ChatInterface(fn=chat, type=\"messages\").launch()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "b369bf10",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## A bit more about what Gradio actually does:\n",
|
||||
"\n",
|
||||
"1. Gradio constructs a frontend Svelte app based on our Python description of the UI\n",
|
||||
"2. Gradio starts a server built upon the Starlette web framework listening on a free port that serves this React app\n",
|
||||
"3. Gradio creates backend routes for our callbacks, like chat(), which calls our functions\n",
|
||||
"\n",
|
||||
"And of course when Gradio generates the frontend app, it ensures that the the Submit button calls the right backend route.\n",
|
||||
"\n",
|
||||
"That's it!\n",
|
||||
"\n",
|
||||
"It's simple, and it has a resut that feels magical."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "863aac34",
|
||||
"metadata": {},
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "473e5b39-da8f-4db1-83ae-dbaca2e9531e",
|
||||
@@ -289,414 +276,128 @@
|
||||
"id": "728a12c5-adc3-415d-bb05-82beb73b079b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f4975b87-19e9-4ade-a232-9b809ec75c9a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Audio (NOTE - Audio is optional for this course - feel free to skip Audio if it causes trouble!)\n",
|
||||
"\n",
|
||||
"And let's make a function talker that uses OpenAI's speech model to generate Audio\n",
|
||||
"\n",
|
||||
"### Troubleshooting Audio issues\n",
|
||||
"\n",
|
||||
"If you have any problems running this code below (like a FileNotFound error, or a warning of a missing package), you may need to install FFmpeg, a very popular audio utility.\n",
|
||||
"\n",
|
||||
"**For PC Users**\n",
|
||||
"\n",
|
||||
"Detailed instructions are [here](https://chatgpt.com/share/6724efee-6b0c-8012-ac5e-72e2e3885905) and summary instructions:\n",
|
||||
"\n",
|
||||
"1. Download FFmpeg from the official website: https://ffmpeg.org/download.html\n",
|
||||
"\n",
|
||||
"2. Extract the downloaded files to a location on your computer (e.g., `C:\\ffmpeg`)\n",
|
||||
"\n",
|
||||
"3. Add the FFmpeg bin folder to your system PATH:\n",
|
||||
"- Right-click on 'This PC' or 'My Computer' and select 'Properties'\n",
|
||||
"- Click on 'Advanced system settings'\n",
|
||||
"- Click on 'Environment Variables'\n",
|
||||
"- Under 'System variables', find and edit 'Path'\n",
|
||||
"- Add a new entry with the path to your FFmpeg bin folder (e.g., `C:\\ffmpeg\\bin`)\n",
|
||||
"- Restart your command prompt, and within Jupyter Lab do Kernel -> Restart kernel, to pick up the changes\n",
|
||||
"\n",
|
||||
"4. Open a new command prompt and run this to make sure it's installed OK\n",
|
||||
"`ffmpeg -version`\n",
|
||||
"\n",
|
||||
"**For Mac Users**\n",
|
||||
"\n",
|
||||
"1. Install homebrew if you don't have it already by running this in a Terminal window and following any instructions: \n",
|
||||
"`/bin/bash -c \"$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)\"`\n",
|
||||
"\n",
|
||||
"2. Then install FFmpeg with `brew install ffmpeg`\n",
|
||||
"\n",
|
||||
"3. Verify your installation with `ffmpeg -version` and if everything is good, within Jupyter Lab do Kernel -> Restart kernel to pick up the changes\n",
|
||||
"\n",
|
||||
"Message me or email me at ed@edwarddonner.com with any problems!"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "4cc90e80-c96e-4dd4-b9d6-386fe2b7e797",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## To check you now have ffmpeg and can access it here\n",
|
||||
"\n",
|
||||
"Excecute the next cell to see if you get a version number. (Putting an exclamation mark before something in Jupyter Lab tells it to run it as a terminal command rather than python code).\n",
|
||||
"\n",
|
||||
"If this doesn't work, you may need to actually save and close down your Jupyter lab, and start it again from a new Terminal window (Mac) or Anaconda prompt (PC), remembering to activate the llms environment. This ensures you pick up ffmpeg.\n",
|
||||
"\n",
|
||||
"And if that doesn't work, please contact me!"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "7b3be0fb-1d34-4693-ab6f-dbff190afcd7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"!ffmpeg -version\n",
|
||||
"!ffprobe -version\n",
|
||||
"!ffplay -version"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "d91d3f8f-e505-4e3c-a87c-9e42ed823db6",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# For Mac users - and possibly many PC users too\n",
|
||||
"\n",
|
||||
"This version should work fine for you. It might work for Windows users too, but you might get a Permissions error writing to a temp file. If so, see the next section!\n",
|
||||
"\n",
|
||||
"As always, if you have problems, please contact me! (You could also comment out the audio talker() in the later code if you're less interested in audio generation)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ffbfe93b-5e86-4e68-ba71-b301cd5230db",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from pydub import AudioSegment\n",
|
||||
"from pydub.playback import play\n",
|
||||
"\n",
|
||||
"def talker(message):\n",
|
||||
" response = openai.audio.speech.create(\n",
|
||||
" model=\"tts-1\",\n",
|
||||
" voice=\"onyx\", # Also, try replacing onyx with alloy\n",
|
||||
" model=\"gpt-4o-mini-tts\",\n",
|
||||
" voice=\"onyx\", # Also, try replacing onyx with alloy or coral\n",
|
||||
" input=message\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" audio_stream = BytesIO(response.content)\n",
|
||||
" audio = AudioSegment.from_file(audio_stream, format=\"mp3\")\n",
|
||||
" play(audio)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b88d775d-d357-4292-a1ad-5dc5ed567281",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"talker(\"Well, hi there\")"
|
||||
" return response.content"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ad89a9bd-bb1e-4bbb-a49a-83af5f500c24",
|
||||
"id": "3bc7580b",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# For Windows users (or any Mac users with problems above)\n",
|
||||
"## Let's bring this home:\n",
|
||||
"\n",
|
||||
"## First try the Mac version above, but if you get a permissions error writing to a temp file, then this code should work instead.\n",
|
||||
"\n",
|
||||
"A collaboration between students Mark M. and Patrick H. and Claude got this resolved!\n",
|
||||
"\n",
|
||||
"Below are 4 variations - hopefully one of them will work on your PC. If not, message me please!\n",
|
||||
"\n",
|
||||
"And for Mac people - all 3 of the below work on my Mac too - please try these if the Mac version gave you problems.\n",
|
||||
"\n",
|
||||
"## PC Variation 1"
|
||||
"1. A multi-modal AI assistant with image and audio generation\n",
|
||||
"2. Tool callling with database lookup\n",
|
||||
"3. A step towards an Agentic workflow\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d104b96a-02ca-4159-82fe-88e0452aa479",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import base64\n",
|
||||
"from io import BytesIO\n",
|
||||
"from PIL import Image\n",
|
||||
"from IPython.display import Audio, display\n",
|
||||
"\n",
|
||||
"def talker(message):\n",
|
||||
" response = openai.audio.speech.create(\n",
|
||||
" model=\"tts-1\",\n",
|
||||
" voice=\"onyx\",\n",
|
||||
" input=message)\n",
|
||||
"\n",
|
||||
" audio_stream = BytesIO(response.content)\n",
|
||||
" output_filename = \"output_audio.mp3\"\n",
|
||||
" with open(output_filename, \"wb\") as f:\n",
|
||||
" f.write(audio_stream.read())\n",
|
||||
"\n",
|
||||
" # Play the generated audio\n",
|
||||
" display(Audio(output_filename, autoplay=True))\n",
|
||||
"\n",
|
||||
"talker(\"Well, hi there\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "3a5d11f4-bbd3-43a1-904d-f684eb5f3e3a",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## PC Variation 2"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d59c8ebd-79c5-498a-bdf2-3a1c50d91aa0",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import tempfile\n",
|
||||
"import subprocess\n",
|
||||
"from io import BytesIO\n",
|
||||
"from pydub import AudioSegment\n",
|
||||
"import time\n",
|
||||
"\n",
|
||||
"def play_audio(audio_segment):\n",
|
||||
" temp_dir = tempfile.gettempdir()\n",
|
||||
" temp_path = os.path.join(temp_dir, \"temp_audio.wav\")\n",
|
||||
" try:\n",
|
||||
" audio_segment.export(temp_path, format=\"wav\")\n",
|
||||
" time.sleep(3) # Student Dominic found that this was needed. You could also try commenting out to see if not needed on your PC\n",
|
||||
" subprocess.call([\n",
|
||||
" \"ffplay\",\n",
|
||||
" \"-nodisp\",\n",
|
||||
" \"-autoexit\",\n",
|
||||
" \"-hide_banner\",\n",
|
||||
" temp_path\n",
|
||||
" ], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\n",
|
||||
" finally:\n",
|
||||
" try:\n",
|
||||
" os.remove(temp_path)\n",
|
||||
" except Exception:\n",
|
||||
" pass\n",
|
||||
" \n",
|
||||
"def talker(message):\n",
|
||||
" response = openai.audio.speech.create(\n",
|
||||
" model=\"tts-1\",\n",
|
||||
" voice=\"onyx\", # Also, try replacing onyx with alloy\n",
|
||||
" input=message\n",
|
||||
" )\n",
|
||||
" audio_stream = BytesIO(response.content)\n",
|
||||
" audio = AudioSegment.from_file(audio_stream, format=\"mp3\")\n",
|
||||
" play_audio(audio)\n",
|
||||
"\n",
|
||||
"talker(\"Well hi there\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "96f90e35-f71e-468e-afea-07b98f74dbcf",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## PC Variation 3"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "8597c7f8-7b50-44ad-9b31-db12375cd57b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"from pydub import AudioSegment\n",
|
||||
"from pydub.playback import play\n",
|
||||
"from io import BytesIO\n",
|
||||
"\n",
|
||||
"def talker(message):\n",
|
||||
" # Set a custom directory for temporary files on Windows\n",
|
||||
" custom_temp_dir = os.path.expanduser(\"~/Documents/temp_audio\")\n",
|
||||
" os.environ['TEMP'] = custom_temp_dir # You can also use 'TMP' if necessary\n",
|
||||
" \n",
|
||||
" # Create the folder if it doesn't exist\n",
|
||||
" if not os.path.exists(custom_temp_dir):\n",
|
||||
" os.makedirs(custom_temp_dir)\n",
|
||||
" \n",
|
||||
" response = openai.audio.speech.create(\n",
|
||||
" model=\"tts-1\",\n",
|
||||
" voice=\"onyx\", # Also, try replacing onyx with alloy\n",
|
||||
" input=message\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" audio_stream = BytesIO(response.content)\n",
|
||||
" audio = AudioSegment.from_file(audio_stream, format=\"mp3\")\n",
|
||||
"\n",
|
||||
" play(audio)\n",
|
||||
"\n",
|
||||
"talker(\"Well hi there\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "e821224c-b069-4f9b-9535-c15fdb0e411c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## PC Variation 4\n",
|
||||
"\n",
|
||||
"### Let's try a completely different sound library\n",
|
||||
"\n",
|
||||
"First run the next cell to install a new library, then try the cell below it."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "69d3c0d9-afcc-49e3-b829-9c9869d8b472",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"!pip install simpleaudio"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "28f9cc99-36b7-4554-b3f4-f2012f614a13",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from pydub import AudioSegment\n",
|
||||
"from io import BytesIO\n",
|
||||
"import tempfile\n",
|
||||
"import os\n",
|
||||
"import simpleaudio as sa\n",
|
||||
"\n",
|
||||
"def talker(message):\n",
|
||||
" response = openai.audio.speech.create(\n",
|
||||
" model=\"tts-1\",\n",
|
||||
" voice=\"onyx\", # Also, try replacing onyx with alloy\n",
|
||||
" input=message\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" audio_stream = BytesIO(response.content)\n",
|
||||
" audio = AudioSegment.from_file(audio_stream, format=\"mp3\")\n",
|
||||
"\n",
|
||||
" # Create a temporary file in a folder where you have write permissions\n",
|
||||
" with tempfile.NamedTemporaryFile(suffix=\".wav\", delete=False, dir=os.path.expanduser(\"~/Documents\")) as temp_audio_file:\n",
|
||||
" temp_file_name = temp_audio_file.name\n",
|
||||
" audio.export(temp_file_name, format=\"wav\")\n",
|
||||
" \n",
|
||||
" # Load and play audio using simpleaudio\n",
|
||||
" wave_obj = sa.WaveObject.from_wave_file(temp_file_name)\n",
|
||||
" play_obj = wave_obj.play()\n",
|
||||
" play_obj.wait_done() # Wait for playback to finish\n",
|
||||
"\n",
|
||||
" # Clean up the temporary file afterward\n",
|
||||
" os.remove(temp_file_name)\n",
|
||||
" \n",
|
||||
"talker(\"Well hi there\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "7986176b-cd04-495f-a47f-e057b0e462ed",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## PC Users - if none of those 4 variations worked!\n",
|
||||
"\n",
|
||||
"Please get in touch with me. I'm sorry this is causing problems! We'll figure it out.\n",
|
||||
"\n",
|
||||
"Alternatively: playing audio from your PC isn't super-critical for this course, and you can feel free to focus on image generation and skip audio for now, or come back to it later."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "1d48876d-c4fa-46a8-a04f-f9fadf61fb0d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Our Agent Framework\n",
|
||||
"\n",
|
||||
"The term 'Agentic AI' and Agentization is an umbrella term that refers to a number of techniques, such as:\n",
|
||||
"\n",
|
||||
"1. Breaking a complex problem into smaller steps, with multiple LLMs carrying out specialized tasks\n",
|
||||
"2. The ability for LLMs to use Tools to give them additional capabilities\n",
|
||||
"3. The 'Agent Environment' which allows Agents to collaborate\n",
|
||||
"4. An LLM can act as the Planner, dividing bigger tasks into smaller ones for the specialists\n",
|
||||
"5. The concept of an Agent having autonomy / agency, beyond just responding to a prompt - such as Memory\n",
|
||||
"\n",
|
||||
"We're showing 1 and 2 here, and to a lesser extent 3 and 5. In week 8 we will do the lot!"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ba820c95-02f5-499e-8f3c-8727ee0a6c0c",
|
||||
"id": "b119ed1b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def chat(history):\n",
|
||||
" history = [{\"role\":h[\"role\"], \"content\":h[\"content\"]} for h in history]\n",
|
||||
" messages = [{\"role\": \"system\", \"content\": system_message}] + history\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
" cities = []\n",
|
||||
" image = None\n",
|
||||
" \n",
|
||||
" if response.choices[0].finish_reason==\"tool_calls\":\n",
|
||||
"\n",
|
||||
" while response.choices[0].finish_reason==\"tool_calls\":\n",
|
||||
" message = response.choices[0].message\n",
|
||||
" response, city = handle_tool_call(message)\n",
|
||||
" responses, cities = handle_tool_calls_and_return_cities(message)\n",
|
||||
" messages.append(message)\n",
|
||||
" messages.append(response)\n",
|
||||
" image = artist(city)\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
" \n",
|
||||
" messages.extend(responses)\n",
|
||||
" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
|
||||
"\n",
|
||||
" reply = response.choices[0].message.content\n",
|
||||
" history += [{\"role\":\"assistant\", \"content\":reply}]\n",
|
||||
"\n",
|
||||
" # Comment out or delete the next line if you'd rather skip Audio for now..\n",
|
||||
" talker(reply)\n",
|
||||
" voice = talker(reply)\n",
|
||||
"\n",
|
||||
" if cities:\n",
|
||||
" image = artist(cities[0])\n",
|
||||
" \n",
|
||||
" return history, image"
|
||||
" return history, voice, image\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f38d0d27-33bf-4992-a2e5-5dbed973cde7",
|
||||
"id": "5846bc77",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# More involved Gradio code as we're not using the preset Chat interface!\n",
|
||||
"# Passing in inbrowser=True in the last line will cause a Gradio window to pop up immediately.\n",
|
||||
"def handle_tool_calls_and_return_cities(message):\n",
|
||||
" responses = []\n",
|
||||
" cities = []\n",
|
||||
" for tool_call in message.tool_calls:\n",
|
||||
" if tool_call.function.name == \"get_ticket_price\":\n",
|
||||
" arguments = json.loads(tool_call.function.arguments)\n",
|
||||
" city = arguments.get('destination_city')\n",
|
||||
" cities.append(city)\n",
|
||||
" price_details = get_ticket_price(city)\n",
|
||||
" responses.append({\n",
|
||||
" \"role\": \"tool\",\n",
|
||||
" \"content\": price_details,\n",
|
||||
" \"tool_call_id\": tool_call.id\n",
|
||||
" })\n",
|
||||
" return responses, cities"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "6e520161",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## The 3 types of Gradio UI\n",
|
||||
"\n",
|
||||
"`gr.Interface` is for standard, simple UIs\n",
|
||||
"\n",
|
||||
"`gr.ChatInterface` is for standard ChatBot UIs\n",
|
||||
"\n",
|
||||
"`gr.Blocks` is for custom UIs where you control the components and the callbacks"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "9f250915",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Callbacks (along with the chat() function above)\n",
|
||||
"\n",
|
||||
"def put_message_in_chatbot(message, history):\n",
|
||||
" return \"\", history + [{\"role\":\"user\", \"content\":message}]\n",
|
||||
"\n",
|
||||
"# UI definition\n",
|
||||
"\n",
|
||||
"with gr.Blocks() as ui:\n",
|
||||
" with gr.Row():\n",
|
||||
" chatbot = gr.Chatbot(height=500, type=\"messages\")\n",
|
||||
" image_output = gr.Image(height=500)\n",
|
||||
" image_output = gr.Image(height=500, interactive=False)\n",
|
||||
" with gr.Row():\n",
|
||||
" entry = gr.Textbox(label=\"Chat with our AI Assistant:\")\n",
|
||||
" audio_output = gr.Audio(autoplay=True)\n",
|
||||
" with gr.Row():\n",
|
||||
" clear = gr.Button(\"Clear\")\n",
|
||||
" message = gr.Textbox(label=\"Chat with our AI Assistant:\")\n",
|
||||
"\n",
|
||||
" def do_entry(message, history):\n",
|
||||
" history += [{\"role\":\"user\", \"content\":message}]\n",
|
||||
" return \"\", history\n",
|
||||
"# Hooking up events to callbacks\n",
|
||||
"\n",
|
||||
" entry.submit(do_entry, inputs=[entry, chatbot], outputs=[entry, chatbot]).then(\n",
|
||||
" chat, inputs=chatbot, outputs=[chatbot, image_output]\n",
|
||||
" message.submit(put_message_in_chatbot, inputs=[message, chatbot], outputs=[message, chatbot]).then(\n",
|
||||
" chat, inputs=chatbot, outputs=[chatbot, audio_output, image_output]\n",
|
||||
" )\n",
|
||||
" clear.click(lambda: None, inputs=None, outputs=chatbot, queue=False)\n",
|
||||
"\n",
|
||||
"ui.launch(inbrowser=True)"
|
||||
"ui.launch(inbrowser=True, auth=(\"ed\", \"bananas\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
@@ -719,7 +420,7 @@
|
||||
"<table style=\"margin: 0; text-align: left;\">\n",
|
||||
" <tr>\n",
|
||||
" <td style=\"width: 150px; height: 150px; vertical-align: middle;\">\n",
|
||||
" <img src=\"../thankyou.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
|
||||
" <img src=\"../assets/thankyou.jpg\" width=\"150\" height=\"150\" style=\"display: block;\" />\n",
|
||||
" </td>\n",
|
||||
" <td>\n",
|
||||
" <h2 style=\"color:#090;\">I have a special request for you</h2>\n",
|
||||
@@ -734,7 +435,7 @@
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"display_name": ".venv",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
@@ -748,7 +449,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.13"
|
||||
"version": "3.12.9"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
4459
week2/hamlet.txt
Normal file
4459
week2/hamlet.txt
Normal file
File diff suppressed because it is too large
Load Diff
37
week2/scraper.py
Normal file
37
week2/scraper.py
Normal file
@@ -0,0 +1,37 @@
|
||||
from bs4 import BeautifulSoup
|
||||
import requests
|
||||
|
||||
|
||||
# Standard headers to fetch a website
|
||||
headers = {
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36"
|
||||
}
|
||||
|
||||
|
||||
def fetch_website_contents(url):
|
||||
"""
|
||||
Return the title and contents of the website at the given url;
|
||||
truncate to 2,000 characters as a sensible limit
|
||||
"""
|
||||
response = requests.get(url, headers=headers)
|
||||
soup = BeautifulSoup(response.content, "html.parser")
|
||||
title = soup.title.string if soup.title else "No title found"
|
||||
if soup.body:
|
||||
for irrelevant in soup.body(["script", "style", "img", "input"]):
|
||||
irrelevant.decompose()
|
||||
text = soup.body.get_text(separator="\n", strip=True)
|
||||
else:
|
||||
text = ""
|
||||
return (title + "\n\n" + text)[:2_000]
|
||||
|
||||
|
||||
def fetch_website_links(url):
|
||||
"""
|
||||
Return the links on the webiste at the given url
|
||||
I realize this is inefficient as we're parsing twice! This is to keep the code in the lab simple.
|
||||
Feel free to use a class and optimize it!
|
||||
"""
|
||||
response = requests.get(url, headers=headers)
|
||||
soup = BeautifulSoup(response.content, "html.parser")
|
||||
links = [link.get("href") for link in soup.find_all("a")]
|
||||
return [link for link in links if link]
|
||||
Reference in New Issue
Block a user