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Add parallel function call examples (google-gemini#115)
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* pyink first

* Add parallel function call/response examples

* 2nd person prose fixup
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@markmcd
markmcd authored May 7, 2024
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Showing 1 changed file with 202 additions and 56 deletions.
258 changes: 202 additions & 56 deletions quickstarts/Function_calling.ipynb
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},
"outputs": [],
"source": [
"#@title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# @title Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"#\n",
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"metadata": {
"id": "9OEoeosRTv-5"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m137.4/137.4 kB\u001b[0m \u001b[31m933.2 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25h"
]
}
],
"outputs": [],
"source": [
"!pip install -U -q google-generativeai # Install the Python SDK"
"!pip install -U -q google-generativeai # Install the Python SDK"
]
},
{
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"outputs": [],
"source": [
"from google.colab import userdata\n",
"GOOGLE_API_KEY=userdata.get('GOOGLE_API_KEY')\n",
"\n",
"GOOGLE_API_KEY = userdata.get(\"GOOGLE_API_KEY\")\n",
"genai.configure(api_key=GOOGLE_API_KEY)"
]
},
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}
],
"source": [
"def add(a:float, b:float):\n",
"def add(a: float, b: float):\n",
" \"\"\"returns a + b.\"\"\"\n",
" return a+b\n",
" return a + b\n",
"\n",
"\n",
"def subtract(a:float, b:float):\n",
"def subtract(a: float, b: float):\n",
" \"\"\"returns a - b.\"\"\"\n",
" return a-b\n",
" return a - b\n",
"\n",
"def multiply(a:float, b:float):\n",
"\n",
"def multiply(a: float, b: float):\n",
" \"\"\"returns a * b.\"\"\"\n",
" return a*b\n",
" return a * b\n",
"\n",
"\n",
"def divide(a:float, b:float):\n",
"def divide(a: float, b: float):\n",
" \"\"\"returns a / b.\"\"\"\n",
" return a*b\n",
" return a * b\n",
"\n",
"\n",
"model = genai.GenerativeModel(model_name='gemini-1.0-pro',\n",
" tools=[add, subtract, multiply, divide])\n",
"model = genai.GenerativeModel(\n",
" model_name=\"gemini-1.0-pro\", tools=[add, subtract, multiply, divide]\n",
")\n",
"\n",
"model"
]
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}
],
"source": [
"response = chat.send_message('I have 57 cats, each owns 44 mittens, how many mittens is that in total?')\n",
"response = chat.send_message(\n",
" \"I have 57 cats, each owns 44 mittens, how many mittens is that in total?\"\n",
")\n",
"response.text"
]
},
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}
],
"source": [
"57*44"
"57 * 44"
]
},
{
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"source": [
"for content in chat.history:\n",
" print(content.role, \"->\", [type(part).to_dict(part) for part in content.parts])\n",
" print('-'*80)"
" print(\"-\" * 80)"
]
},
{
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},
"outputs": [],
"source": [
"def find_movies(description: str, location: str = ''):\n",
" \"\"\"find movie titles currently playing in theaters based on any description, genre, title words, etc.\n",
"def find_movies(description: str, location: str = \"\"):\n",
" \"\"\"find movie titles currently playing in theaters based on any description, genre, title words, etc.\n",
"\n",
" Args:\n",
" description: Any kind of description including category or genre, title words, attributes, etc.\n",
" location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n",
" \"\"\"\n",
" return ['Barbie', 'Oppenheimer']\n",
" Args:\n",
" description: Any kind of description including category or genre, title words, attributes, etc.\n",
" location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n",
" \"\"\"\n",
" return [\"Barbie\", \"Oppenheimer\"]\n",
"\n",
"def find_theaters(location: str, movie: str = ''):\n",
"\n",
"def find_theaters(location: str, movie: str = \"\"):\n",
" \"\"\"Find theaters based on location and optionally movie title which are is currently playing in theaters.\n",
"\n",
" Args:\n",
" location: The city and state, e.g. San Francisco, CA or a zip code e.g. 95616\n",
" movie: Any movie title\n",
" \"\"\"\n",
" return ['Googleplex 16', 'Android Theatre']\n",
" return [\"Googleplex 16\", \"Android Theatre\"]\n",
"\n",
"\n",
"def get_showtimes(location:str, movie:str, theater:str, date:str):\n",
"def get_showtimes(location: str, movie: str, theater: str, date: str):\n",
" \"\"\"\n",
" Find the start times for movies playing in a specific theater.\n",
"\n",
Expand All @@ -401,7 +402,7 @@
" thearer: Name of the theater\n",
" date: Date for requested showtime\n",
" \"\"\"\n",
" return ['10:00', '11:00']"
" return [\"10:00\", \"11:00\"]"
]
},
{
Expand All @@ -422,13 +423,12 @@
"outputs": [],
"source": [
"functions = {\n",
" 'find_movies': find_movies,\n",
" 'find_theaters': find_theaters,\n",
" 'get_showtimes': get_showtimes,\n",
" \"find_movies\": find_movies,\n",
" \"find_theaters\": find_theaters,\n",
" \"get_showtimes\": get_showtimes,\n",
"}\n",
"\n",
"model = genai.GenerativeModel(model_name='gemini-1.0-pro',\n",
" tools=functions.values())"
"model = genai.GenerativeModel(model_name=\"gemini-1.0-pro\", tools=functions.values())"
]
},
{
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}
],
"source": [
"response = model.generate_content('Which theaters in Mountain View show the Barbie movie?')\n",
"response = model.generate_content(\n",
" \"Which theaters in Mountain View show the Barbie movie?\"\n",
")\n",
"response.candidates[0].content.parts"
]
},
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"elif ...\n",
"```\n",
"\n",
"However, since we made the `functions` dictionary earlier, we can simplify this to:"
"However, since you already made the `functions` dictionary, this can be simplified to:"
]
},
{
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],
"source": [
"def call_function(function_call, functions):\n",
" function_name = function_call.name\n",
" function_args = function_call.args\n",
" return functions[function_name](**function_args)\n",
" function_name = function_call.name\n",
" function_args = function_call.args\n",
" return functions[function_name](**function_args)\n",
"\n",
"\n",
"part = response.candidates[0].content.parts[0]\n",
"\n",
"# Check if it's a function call; in real use you'd need to also handle text\n",
"# responses as you won't know what the model will respond with.\n",
"if part.function_call:\n",
" result = call_function(part.function_call, functions)\n",
" result = call_function(part.function_call, functions)\n",
"\n",
"print(result)"
]
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"\n",
"# Put the result in a protobuf Struct\n",
"s = Struct()\n",
"s.update({'result': result})\n",
"s.update({\"result\": result})\n",
"\n",
"# Update this after https://github.com/google/generative-ai-python/issues/243\n",
"function_response = glm.Part(\n",
" function_response=glm.FunctionResponse(name='find_theaters', response=s))\n",
" function_response=glm.FunctionResponse(name=\"find_theaters\", response=s)\n",
")\n",
"\n",
"# Build the message history\n",
"messages = [\n",
" {'role':'user',\n",
" 'parts': ['Which theaters in Mountain View show the Barbie movie?.']},\n",
" {'role':'model',\n",
" 'parts': response.candidates[0].content.parts},\n",
" {'role':'user',\n",
" 'parts': [function_response]}\n",
" # fmt: off\n",
" {\"role\": \"user\",\n",
" \"parts\": [\"Which theaters in Mountain View show the Barbie movie?.\"]},\n",
" {\"role\": \"model\",\n",
" \"parts\": response.candidates[0].content.parts},\n",
" {\"role\": \"user\",\n",
" \"parts\": [function_response]},\n",
" # fmt: on\n",
"]\n",
"\n",
"# Generate the next response\n",
"response = model.generate_content(messages)\n",
"print(response.text)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "EuwKoNIhGBJN"
},
"source": [
"## Parallel function calls\n",
"\n",
"The Gemini API can call multiple functions in a single turn. This caters for scenarios where there are multiple function calls that can take place independently to complete a task.\n",
"\n",
"First set the tools up. Unlike the movie example above, these functions do not require input from each other to be called so they should be good candidates for parallel calling."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "cJ-mSixWGqLv"
},
"outputs": [],
"source": [
"def power_disco_ball(power: bool) -> bool:\n",
" \"\"\"Powers the spinning disco ball.\"\"\"\n",
" print(f\"Disco ball is {'spinning!' if power else 'stopped.'}\")\n",
" return True\n",
"\n",
"\n",
"def start_music(energetic: bool, loud: bool, bpm: int) -> str:\n",
" \"\"\"Play some music matching the specified parameters.\n",
"\n",
" Args:\n",
" energetic: Whether the music is energetic or not.\n",
" loud: Whether the music is loud or not.\n",
" bpm: The beats per minute of the music.\n",
"\n",
" Returns: The name of the song being played.\n",
" \"\"\"\n",
" print(f\"Starting music! {energetic=} {loud=}, {bpm=}\")\n",
" return \"Never gonna give you up.\"\n",
"\n",
"\n",
"def dim_lights(brightness: float) -> bool:\n",
" \"\"\"Dim the lights.\n",
"\n",
" Args:\n",
" brightness: The brightness of the lights, 0.0 is off, 1.0 is full.\n",
" \"\"\"\n",
" print(f\"Lights are now set to {brightness:.0%}\")\n",
" return True"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "zlrmXN7fxQi0"
},
"source": [
"Now call the model with an instruction that could use all of the specified tools."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "21ecYHLgIsCl"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"power_disco_ball(power=True)\n",
"start_music(energetic=True, loud=True, bpm=120.0)\n",
"dim_lights(brightness=0.3)\n"
]
}
],
"source": [
"# Set the model up with tools.\n",
"house_fns = [power_disco_ball, start_music, dim_lights]\n",
"# Try this out with Pro and Flash...\n",
"model = genai.GenerativeModel(model_name=\"gemini-1.5-pro-latest\", tools=house_fns)\n",
"\n",
"# Call the API.\n",
"chat = model.start_chat()\n",
"response = chat.send_message(\"Turn this place into a party!\")\n",
"\n",
"# Print out each of the function calls requested from this single call.\n",
"for part in response.parts:\n",
" if fn := part.function_call:\n",
" args = \", \".join(f\"{key}={val}\" for key, val in fn.args.items())\n",
" print(f\"{fn.name}({args})\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "t6iYpty7yZct"
},
"source": [
"Each of the printed results reflects a single function call that the model has requested. To send the results back, include the responses in the same order as they were requested."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "L7RxoiR3foBR"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Let's get this party started! I've turned on the disco ball, started playing some upbeat music, and dimmed the lights. 🎶✨ Get ready to dance! 🕺💃 \n",
"\n",
"\n"
]
}
],
"source": [
"import google.ai.generativelanguage as glm\n",
"\n",
"# Simulate the responses from the specified tools.\n",
"responses = {\n",
" \"power_disco_ball\": True,\n",
" \"start_music\": \"Never gonna give you up.\",\n",
" \"dim_lights\": True,\n",
"}\n",
"\n",
"# Build the response parts.\n",
"response_parts = [\n",
" glm.Part(function_response=glm.FunctionResponse(name=fn, response={\"result\": val}))\n",
" for fn, val in responses.items()\n",
"]\n",
"\n",
"response = chat.send_message(response_parts)\n",
"print(response.text)"
]
},
{
"cell_type": "markdown",
"metadata": {
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