141 lines
5 KiB
Plaintext
141 lines
5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import openai\n",
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"import json"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"client = openai.OpenAI(\n",
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" base_url = \"https://api.fireworks.ai/inference/v1\",\n",
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" api_key = \"YOUR_API_KEY\"\n",
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")\n",
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"\n",
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"messages = [\n",
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" {\"role\": \"system\", \"content\": f\"You are a helpful assistant with access to functions.\" \n",
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" \t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Use them if required.\"},\n",
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" {\"role\": \"user\", \"content\": \"What are Nike's net income in 2022?\"}\n",
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"]\n",
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"\n",
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"tools = [\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" # name of the function \n",
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" \"name\": \"get_financial_data\",\n",
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" # a good, detailed description for what the function is supposed to do\n",
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" \"description\": \"Get financial data for a company given the metric and year.\",\n",
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" # a well defined json schema: https://json-schema.org/learn/getting-started-step-by-step#define\n",
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" \"parameters\": {\n",
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" # for OpenAI compatibility, we always declare a top level object for the parameters of the function\n",
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" \"type\": \"object\",\n",
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" # the properties for the object would be any arguments you want to provide to the function\n",
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" \"properties\": {\n",
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" \"metric\": {\n",
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" # JSON Schema supports string, number, integer, object, array, boolean and null\n",
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" # for more information, please check out https://json-schema.org/understanding-json-schema/reference/type\n",
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" \"type\": \"string\",\n",
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" # You can restrict the space of possible values in an JSON Schema\n",
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" # you can check out https://json-schema.org/understanding-json-schema/reference/enum for more examples on how enum works\n",
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" \"enum\": [\"net_income\", \"revenue\", \"ebdita\"],\n",
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" },\n",
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" \"financial_year\": {\n",
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" \"type\": \"integer\", \n",
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" # If the model does not understand how it is supposed to fill the field, a good description goes a long way \n",
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" \"description\": \"Year for which we want to get financial data.\"\n",
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" },\n",
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" \"company\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"Name of the company for which we want to get financial data.\"\n",
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" }\n",
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" },\n",
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" # You can specify which of the properties from above are required\n",
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" # for more info on `required` field, please check https://json-schema.org/understanding-json-schema/reference/object#required\n",
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" \"required\": [\"metric\", \"financial_year\", \"company\"],\n",
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" },\n",
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" },\n",
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" }\n",
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"]\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": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{\n",
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" \"content\": null,\n",
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" \"role\": \"assistant\",\n",
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" \"function_call\": null,\n",
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" \"tool_calls\": [\n",
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" {\n",
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" \"id\": \"call_W4IUqQRFF9vYINQ74tfBwmqr\",\n",
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" \"function\": {\n",
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" \"arguments\": \"{\\\"metric\\\": \\\"net_income\\\", \\\"financial_year\\\": 2022, \\\"company\\\": \\\"Nike\\\"}\",\n",
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" \"name\": \"get_financial_data\"\n",
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" },\n",
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" \"type\": \"function\",\n",
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" \"index\": 0\n",
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" }\n",
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" ]\n",
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"}\n"
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]
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}
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],
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"source": [
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"\n",
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"chat_completion = client.chat.completions.create(\n",
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" model=\"accounts/fireworks/models/firefunction-v2\",\n",
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" messages=messages,\n",
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" tools=tools,\n",
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" temperature=0.1\n",
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")\n",
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"print(chat_completion.choices[0].message.model_dump_json(indent=4))\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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"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": ".venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.12.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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