Update app.py

app.py

@@ -1,80 +1,69 @@
-#user_query = """
-#which stock in the market has the highest price movement today?
-#Summarise the latest news to analyse the potential cause and add it to my airtable data.
-#"""
-
 import openai
 import os
-import json
 from dotenv import load_dotenv
-from pyairtable import Table
-import requests
-import streamlit as st
 
 load_dotenv()
 openai.api_key = os.getenv("OPENAI_API_KEY")
-#rapid_api_key = os.getenv("X-RapidAPI-Key")
-#airtable_api_key = os.getenv("AIRTABLE_API_KEY")
-#table = Table(airtable_api_key, "appHojHIE4y8gVBgc", "tbldUUKZFngr78ogg")
+
 
 function_descriptions = [
     {
-        "name": "get_stock_movers",
-        "description": "Get the stocks that has biggest price/volume moves, e.g. actives, gainers, losers, etc.",
-        "parameters": {
-            "type": "object",
-            "properties": {
-            },
-        }
-    },
-    {
-        "name": "get_stock_news",
-        "description": "Get the latest news for a stock",
+        "name": "extract_info_from_email",
+        "description": "categorise & extract key info from an email, such as use case, company name, contact details, etc.",
         "parameters": {
             "type": "object",
             "properties": {
-                "performanceId": {
+                "companyName": {
+                    "type": "string",
+                    "description": "the name of the company that sent the email"
+                },                                        
+                "product": {
                     "type": "string",
-                    "description": "id of the stock, which is referred as performanceID in the API"
+                    "description": "Try to identify which product the client is interested in, if any"
                 },
-            },
-            "required": ["performanceId"]
-        }
-    },
-    {
-        "name": "add_stock_news_airtable",
-        "description": "Add the stock, news summary & price move to Airtable",
-        "parameters": {
-            "type": "object",
-            "properties": {
-                "stock": {
+                "amount":{
                     "type": "string",
-                    "description": "stock ticker"
+                    "description": "Try to identify the amount of products the client wants to purchase, if any"
                 },
-                "move": {
+                "category": {
                     "type": "string",
-                    "description": "price move in %"
+                    "description": "Try to categorise this email into categories like those: 1. Sales 2. customer support; 3. consulting; 4. partnership; etc."
                 },
-                "news_summary": {
+                "nextStep":{
                     "type": "string",
-                    "description": "news summary of the stock"
+                    "description": "What is the suggested next step to move this forward?"
                 },
-            }
+                "priority": {
+                    "type": "string",
+                    "description": "Try to give a priority score to this email based on how likely this email will leads to a good business opportunity, from 0 to 10; 10 most important"
+                },
+            },
+            "required": ["companyName", "amount", "product", "priority", "category", "nextStep"]
         }
-    },
+    }
 ]
 
-query = "Give me a summary of what happend to the tesla stock today?"
-messages = [{"role":"user", "content":query}]
+email = """
+Dear Jason 
+I hope this message finds you well. I'm Shirley from Gucci;
+
+I'm looking to purchase some company T-shirt for my team, we are a team of 100k people, and we want to get 2 t-shirt per personl
+
+Please let me know the price and timeline you can work with;
+
+Looking forward
+
+Shirley Lou
+"""
+
+prompt = f"Please extract key information from this email: {email} "
+message = [{"role": "user", "content": prompt}]
 
 response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=messages,
-            functions = function_descriptions,
-            function_call="auto"
-        )   
+    model="gpt-3.5-turbo",
+    messages=message,
+    functions = function_descriptions,
+    function_call="auto"
+)
 
 print(response)
-
-st.header("Start:")
-st.header(response)