├── .gitattributes
└── app.py


/.gitattributes:
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1 | # Auto detect text files and perform LF normalization
2 | * text=auto
3 | 


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/app.py:
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  1 | import openai
  2 | import json
  3 | import os
  4 | from dotenv import load_dotenv
  5 | from pyairtable import Table
  6 | import requests
  7 | 
  8 | load_dotenv()
  9 | openai.api_key = os.getenv("OPENAI_API_KEY")
 10 | rapid_api_key = os.getenv("X-RapidAPI-Key")
 11 | smart_light_api_key = os.getenv("SMART_LIGHT_API_KEY")
 12 | 
 13 | airtable_api_key = os.getenv("AIRTABLE_API_KEY")
 14 | table = Table(airtable_api_key, "appHojHIE4y8gVBgc", "tbldUUKZFngr78ogg")
 15 | 
 16 | function_descriptions = [
 17 |     {
 18 |         "name": "get_stock_movers",
 19 |         "description": "Get the stocks that has biggest price/volume moves, e.g. actives, gainers, losers, etc.",
 20 |         "parameters": {
 21 |             "type": "object",
 22 |             "properties": {
 23 |             },
 24 |         }
 25 |     },
 26 |     {
 27 |         "name": "get_stock_news",
 28 |         "description": "Get the latest news for a stock",
 29 |         "parameters": {
 30 |             "type": "object",
 31 |             "properties": {
 32 |                 "performanceId": {
 33 |                     "type": "string",
 34 |                     "description": "id of the stock, which is referred as performanceID in the API"
 35 |                 },
 36 |             },
 37 |             "required": ["performanceId"]
 38 |         }
 39 |     },
 40 |     {
 41 |         "name": "add_stock_news_airtable",
 42 |         "description": "Add the stock, news summary & price move to Airtable",
 43 |         "parameters": {
 44 |             "type": "object",
 45 |             "properties": {
 46 |                 "stock": {
 47 |                     "type": "string",
 48 |                     "description": "stock ticker"
 49 |                 },
 50 |                 "move": {
 51 |                     "type": "string",
 52 |                     "description": "price move in %"
 53 |                 },
 54 |                 "news_summary": {
 55 |                     "type": "string",
 56 |                     "description": "news summary of the stock"
 57 |                 },
 58 |             }
 59 |         }
 60 |     },
 61 |     {
 62 |         "name": "control_light",
 63 |         "description": "Turn on/off the light",
 64 |         "parameters": {
 65 |             "type": "object",
 66 |             "properties": {
 67 |                 "state": {
 68 |                     "type": "string",
 69 |                     "description": "the state of the light, should be on or off",
 70 |                     "enum": ["on", "off"]
 71 |                 }
 72 |             }
 73 |         }
 74 |     }
 75 | ]
 76 | 
 77 | 
 78 | def add_stock_news_airtable(stock, move, news_summary):
 79 |     table.create({"stock":stock, "move%": move, "news_summary":news_summary})
 80 | 
 81 | def get_stock_news(performanceId):
 82 |     url = "https://morning-star.p.rapidapi.com/news/list"
 83 | 
 84 |     querystring = {"performanceId":performanceId}
 85 | 
 86 |     headers = {
 87 |         "X-RapidAPI-Key": rapid_api_key,
 88 |         "X-RapidAPI-Host": "morning-star.p.rapidapi.com"
 89 |     }
 90 | 
 91 |     response = requests.get(url, headers=headers, params=querystring)
 92 | 
 93 |     short_news_list = response.json()[:5]
 94 | 
 95 |     print("response:", response, " json response:", short_news_list)
 96 | 
 97 |     return short_news_list
 98 | 
 99 | 
100 | def get_stock_movers():
101 |     url = "https://morning-star.p.rapidapi.com/market/v2/get-movers"
102 | 
103 |     headers = {
104 |         "X-RapidAPI-Key": rapid_api_key,
105 |         "X-RapidAPI-Host": "morning-star.p.rapidapi.com"
106 |     }
107 | 
108 |     response = requests.get(url, headers=headers)
109 |     
110 |     return response.json()
111 | 
112 | 
113 | def control_light(state):
114 |     token = smart_light_api_key
115 | 
116 |     headers = {
117 |         "Authorization": f"Bearer {token}",
118 |     }
119 | 
120 |     payload = {
121 |         "power": state,
122 |     }
123 | 
124 |     response = requests.put('https://api.lifx.com/v1/lights/all/state', data=payload, headers=headers)
125 | 
126 |     return response.json()
127 | 
128 | 
129 | def function_call(ai_response):
130 |     function_call = ai_response["choices"][0]["message"]["function_call"]
131 |     function_name = function_call["name"]
132 |     arguments = function_call["arguments"]
133 |     if function_name == "get_stock_movers":
134 |         return get_stock_movers()
135 |     elif function_name == "get_stock_news":
136 |         performanceId = eval(arguments).get("performanceId")
137 |         return get_stock_news(performanceId)
138 |     elif function_name == "add_stock_news_airtable":
139 |         stock = eval(arguments).get("stock")
140 |         news_summary = eval(arguments).get("news_summary")
141 |         move = eval(arguments).get("move")
142 |         return add_stock_news_airtable(stock, move, news_summary)
143 |     elif function_name == "control_light":
144 |         state = eval(arguments).get("state")
145 |         return control_light(state)
146 |     else:
147 |         return
148 |         
149 | 
150 | def ask_function_calling(query):
151 |     messages = [{"role": "user", "content": query}]
152 | 
153 |     response = openai.ChatCompletion.create(
154 |         model="gpt-4-0613",
155 |         messages=messages,
156 |         functions = function_descriptions,
157 |         function_call="auto"
158 |     )
159 | 
160 |     print(response)
161 | 
162 |     while response["choices"][0]["finish_reason"] == "function_call":
163 |         function_response = function_call(response)
164 |         messages.append({
165 |             "role": "function",
166 |             "name": response["choices"][0]["message"]["function_call"]["name"],
167 |             "content": json.dumps(function_response)
168 |         })
169 | 
170 |         print("messages: ", messages) 
171 | 
172 |         response = openai.ChatCompletion.create(
173 |             model="gpt-4-0613",
174 |             messages=messages,
175 |             functions = function_descriptions,
176 |             function_call="auto"
177 |         )   
178 | 
179 |         print("response: ", response) 
180 |     else:
181 |         print(response)
182 | 
183 | 
184 | user_query = "Turn on the light"
185 | 
186 | ask_function_calling(user_query)


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