Update app.py

app.py

@@ -2,9 +2,20 @@ import streamlit as st
 import pytesseract
 from io import StringIO
 from PIL import Image
+import json
+import openai
+import pandas as pd
+
+openai.api_key = st.secrets["open_ai_key"]
+
+def get_response(context, prompt):
+    
+
+    return gpt_response
 
 uploaded_file = st.file_uploader("Choose a file")
 if uploaded_file is not None:
+
     
 
     #image = Image.open(uploaded_file)
@@ -12,3 +23,24 @@ if uploaded_file is not None:
     extractedInformation = pytesseract.image_to_string(image)
     st.write(extractedInformation)
 
+    context = '''parse the unstructured input of a cooking recipe into a valid JSON array of objects in the following format:
+    [{
+    "recipe_name": "the name of the recipe expressed as a string",
+    "recipe_ingredients": "list of ingredients specified in the recipe expressed as string",
+    "recipe_steps": "list of steps to cook the recipe expressed as a string"
+    }]'''
+
+    gpt_response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": context},
+            {"role": "user", "content": extractedInformation}
+        ],
+        temperature=0.2,
+        max_tokens=1000
+    )
+
+    st.json((json.loads(gpt_response['choices'][0]['message']['content'])))
+    cost = gpt_response['usage']["prompt_tokens"]*(0.0015/1000) + gpt_response['usage']["completion_tokens"]*(0.002/1000)
+    st.write(f'Cost for query was approx ${cost}')
+