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Ted/remove eval from function calling examples (#518)

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* replaces eval with json.loads for better code safety

* fixes link to be relative, not URL
pull/522/head
Ted Sanders 1 year ago committed by GitHub
parent 0fa6534747
commit 31a3a7b406
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1 changed files with 55 additions and 92 deletions
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147
examples/How_to_call_functions_with_chat_models.ipynb
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@ -31,51 +31,14 @@
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"Requirement already satisfied: scipy in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (1.10.1)\n",
"Requirement already satisfied: numpy<1.27.0,>=1.19.5 in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (from scipy) (1.24.3)\n",
"Requirement already satisfied: tenacity in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (8.2.2)\n",
"Requirement already satisfied: tiktoken in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (0.4.0)\n",
"Requirement already satisfied: regex>=2022.1.18 in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (from tiktoken) (2023.6.3)\n",
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"Requirement already satisfied: idna<4,>=2.5 in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (from requests>=2.26.0->tiktoken) (3.4)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (from requests>=2.26.0->tiktoken) (2.0.3)\n",
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"Requirement already satisfied: yarl<2.0,>=1.0 in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (from aiohttp->openai) (1.9.2)\n",
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"Requirement already satisfied: aiosignal>=1.1.2 in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (from aiohttp->openai) (1.3.1)\n",
"Requirement already satisfied: requests in /Users/joe/.virtualenvs/openai-cookbook/lib/python3.9/site-packages (2.31.0)\n",
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"!pip install scipy\n",
"!pip install tenacity\n",
@ -87,7 +50,7 @@
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@ -113,7 +76,7 @@
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@ -250,7 +213,7 @@
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@ -258,10 +221,10 @@
"data": {
"text/plain": [
"{'role': 'assistant',\n",
" 'content': \"Sure, could you please tell me the city and state for which you'd like to know the weather?\"}"
" 'content': 'In which city and state would you like to know the current weather?'}"
]
},
"execution_count": 6,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@ -288,7 +251,7 @@
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@ -301,7 +264,7 @@
" 'arguments': '{\\n \"location\": \"Glasgow, Scotland\",\\n \"format\": \"celsius\"\\n}'}}"
]
},
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"metadata": {},
"output_type": "execute_result"
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@ -326,7 +289,7 @@
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@ -334,10 +297,10 @@
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"{'role': 'assistant',\n",
" 'content': 'Sure, I can help you with that. Just tell me how many days you would like to forecast for.'}"
" 'content': 'Sure, I can help you with that. Please provide me with the number of days you want to forecast for.'}"
]
},
"execution_count": 8,
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"output_type": "execute_result"
}
@ -364,7 +327,7 @@
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@ -379,7 +342,7 @@
" 'finish_reason': 'function_call'}"
]
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@ -410,7 +373,7 @@
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@ -423,7 +386,7 @@
" 'arguments': '{\\n \"location\": \"Toronto, Canada\",\\n \"format\": \"celsius\",\\n \"num_days\": 1\\n}'}}"
]
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@ -454,7 +417,7 @@
" 'arguments': '{\\n \"location\": \"Toronto, Canada\",\\n \"format\": \"celsius\"\\n}'}}"
]
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@ -480,18 +443,17 @@
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"{'role': 'assistant',\n",
" 'content': '{\\n \"location\": \"Toronto, Canada\",\\n \"format\": \"celsius\"\\n}'}"
"{'role': 'assistant', 'content': 'Sure, let me get that information for you.'}"
]
},
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"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
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@ -530,7 +492,7 @@
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@ -551,7 +513,7 @@
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@ -617,7 +579,7 @@
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@ -657,7 +619,7 @@
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@ -672,7 +634,7 @@
"\n",
"def execute_function_call(message):\n",
" if message[\"function_call\"][\"name\"] == \"ask_database\":\n",
" query = eval(message[\"function_call\"][\"arguments\"])[\"query\"]\n",
" query = json.loads(message[\"function_call\"][\"arguments\"])[\"query\"]\n",
" results = ask_database(conn, query)\n",
" else:\n",
" results = f\"Error: function {message['function_call']['name']} does not exist\"\n",
@ -681,7 +643,7 @@
},
{
"cell_type": "code",
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"execution_count": 17,
"id": "38c55083",
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"outputs": [
@ -689,14 +651,14 @@
"name": "stdout",
"output_type": "stream",
"text": [
"\u001B[31msystem: Answer user questions by generating SQL queries against the Chinook Music Database.\n",
"\u001B[0m\n",
"\u001B[32muser: Hi, who are the top 5 artists by number of tracks?\n",
"\u001B[0m\n",
"\u001B[34massistant: {'name': 'ask_database', 'arguments': '{\\n \"query\": \"SELECT Artist.Name, COUNT(Track.TrackId) AS TrackCount FROM Artist INNER JOIN Album ON Artist.ArtistId = Album.ArtistId INNER JOIN Track ON Album.AlbumId = Track.AlbumId GROUP BY Artist.Name ORDER BY TrackCount DESC LIMIT 5;\"\\n}'}\n",
"\u001B[0m\n",
"\u001B[35mfunction (ask_database): [('Iron Maiden', 213), ('U2', 135), ('Led Zeppelin', 114), ('Metallica', 112), ('Lost', 92)]\n",
"\u001B[0m\n"
"system: Answer user questions by generating SQL queries against the Chinook Music Database.\n",
"\n",
"user: Hi, who are the top 5 artists by number of tracks?\n",
"\n",
"assistant: {'name': 'ask_database', 'arguments': '{\\n \"query\": \"SELECT ar.Name, COUNT(t.TrackId) AS NumTracks FROM Artist ar INNER JOIN Album al ON ar.ArtistId = al.ArtistId INNER JOIN Track t ON al.AlbumId = t.AlbumId GROUP BY ar.ArtistId ORDER BY NumTracks DESC LIMIT 5\"\\n}'}\n",
"\n",
"function (ask_database): [('Iron Maiden', 213), ('U2', 135), ('Led Zeppelin', 114), ('Metallica', 112), ('Lost', 92)]\n",
"\n"
]
}
],
@ -715,7 +677,7 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 18,
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"metadata": {
"scrolled": true
@ -725,20 +687,20 @@
"name": "stdout",
"output_type": "stream",
"text": [
"\u001B[31msystem: Answer user questions by generating SQL queries against the Chinook Music Database.\n",
"\u001B[0m\n",
"\u001B[32muser: Hi, who are the top 5 artists by number of tracks?\n",
"\u001B[0m\n",
"\u001B[34massistant: {'name': 'ask_database', 'arguments': '{\\n \"query\": \"SELECT Artist.Name, COUNT(Track.TrackId) AS TrackCount FROM Artist INNER JOIN Album ON Artist.ArtistId = Album.ArtistId INNER JOIN Track ON Album.AlbumId = Track.AlbumId GROUP BY Artist.Name ORDER BY TrackCount DESC LIMIT 5;\"\\n}'}\n",
"\u001B[0m\n",
"\u001B[35mfunction (ask_database): [('Iron Maiden', 213), ('U2', 135), ('Led Zeppelin', 114), ('Metallica', 112), ('Lost', 92)]\n",
"\u001B[0m\n",
"\u001B[32muser: What is the name of the album with the most tracks?\n",
"\u001B[0m\n",
"\u001B[34massistant: {'name': 'ask_database', 'arguments': '{\\n \"query\": \"SELECT Album.Title, COUNT(Track.TrackId) AS TrackCount FROM Album INNER JOIN Track ON Album.AlbumId = Track.AlbumId GROUP BY Album.Title ORDER BY TrackCount DESC LIMIT 1;\"\\n}'}\n",
"\u001B[0m\n",
"\u001B[35mfunction (ask_database): [('Greatest Hits', 57)]\n",
"\u001B[0m\n"
"system: Answer user questions by generating SQL queries against the Chinook Music Database.\n",
"\n",
"user: Hi, who are the top 5 artists by number of tracks?\n",
"\n",
"assistant: {'name': 'ask_database', 'arguments': '{\\n \"query\": \"SELECT ar.Name, COUNT(t.TrackId) AS NumTracks FROM Artist ar INNER JOIN Album al ON ar.ArtistId = al.ArtistId INNER JOIN Track t ON al.AlbumId = t.AlbumId GROUP BY ar.ArtistId ORDER BY NumTracks DESC LIMIT 5\"\\n}'}\n",
"\n",
"function (ask_database): [('Iron Maiden', 213), ('U2', 135), ('Led Zeppelin', 114), ('Metallica', 112), ('Lost', 92)]\n",
"\n",
"user: What is the name of the album with the most tracks?\n",
"\n",
"assistant: {'name': 'ask_database', 'arguments': '{\\n \"query\": \"SELECT al.Title, COUNT(t.TrackId) AS NumTracks FROM Album al INNER JOIN Track t ON al.AlbumId = t.AlbumId GROUP BY al.AlbumId ORDER BY NumTracks DESC LIMIT 1\"\\n}'}\n",
"\n",
"function (ask_database): [('Greatest Hits', 57)]\n",
"\n"
]
}
],
@ -754,13 +716,14 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"id": "2d89073c",
"metadata": {},
"source": [
"## Next Steps\n",
"\n",
"See our other [notebook](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_call_functions_for_knowledge_retrieval.ipynb) that demonstrates how to use the Chat Completions API and functions for knowledge retrieval to interact conversationally with a knowledge base."
"See our other [notebook](How_to_call_functions_for_knowledge_retrieval.ipynb) that demonstrates how to use the Chat Completions API and functions for knowledge retrieval to interact conversationally with a knowledge base."
]
},
{

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