Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| import openai | |
| import sqlite3 | |
| import pandas as pd | |
| def gpt4(): | |
| openai.api_type = "azure" | |
| openai.api_key = "ebbe2c995cb8911" | |
| openai.api_base = "https://sanofit2dvcopenaigpt4.openai.azure.com/" | |
| openai.api_version = "2023-07-01-preview" | |
| return "SanofiT2DGPT4Model" | |
| convlogs=[{"role":"system","content":"Assistant is an AI chatbot that helps users turn a natural language query into MySQL query. After users input a query, they want to generate a MySQL Query, if the user has not provided any, then ask the user to ask their query.\n\n\"Given the following schema for a \"food_supply_chain\" dataset:\n\nSupplier: The company that provides the specific food item.\nItem_Name: The specific name or type of the food product.\nMarket: The geographical region or country where the product is supplied.\nProduct_Category: The broad category to which the food item belongs, such as Bread/Bakery, Meat, Poultry, or Seafood.\nFacility: The location or organization where the food items are being delivered or distributed.\n\nPlease generate SQL queries for this given schema.\n\nNote: Do not provide explanation of the generated code.\nNote: Provide only valid MySQL query.\nNote: do not change the entity name provided in the query."}] | |
| responsegen_convlogs=[{"role":"system","content":"You are a Procurement specialist in Supply chain and McDonald employee. You will be asked a question and data delimited by $$$ to answer the question. your task is the analyze the question and generate the answer from the data. "}] | |
| nosql_convlogs=[{"role":"system","content":"You are an AI assistant who works as a procurement specialist in supply chain and McDonald employee. I am responsible for sourcing the ingredients and supply chain risk management.\n\nYou will be asked a query, your task is to reply as truthfully as possible."}] | |
| with gr.Blocks() as demo: | |
| chatbot = gr.Chatbot() | |
| msg = gr.Textbox() | |
| clear = gr.ClearButton([msg, chatbot]) | |
| def respond(message, chat_history): | |
| convlogs.append({"role":"user","content":message}) | |
| nosql_convlogs.append({"role":"user","content":message}) | |
| openai_response = openai.ChatCompletion.create( | |
| engine=gpt4(), | |
| messages = convlogs, | |
| temperature=0.3, | |
| max_tokens=800, | |
| top_p=0.95, | |
| frequency_penalty=0, | |
| presence_penalty=0, | |
| stop=None) | |
| reply = openai_response["choices"][0]["message"]["content"] | |
| if(not(reply.lower().startswith('select'))): | |
| #bot_message = reply | |
| openai_response = openai.ChatCompletion.create( | |
| engine=gpt4(), | |
| messages = nosql_convlogs, | |
| temperature=0.3, | |
| max_tokens=800, | |
| top_p=0.95, | |
| frequency_penalty=0, | |
| presence_penalty=0, | |
| stop=None) | |
| bot_message = openai_response["choices"][0]["message"]["content"] | |
| reply=bot_message | |
| else: | |
| conn = sqlite3.connect('Database.db') | |
| df = pd.read_sql_query(reply.replace("\n",""),conn ) | |
| conn.close() | |
| responsegen_convlogs.append({"role":"user","content":"query: {} $$${}$$$".format(message,str(df))}) | |
| openai_final_response = openai.ChatCompletion.create( | |
| engine=gpt4(), | |
| messages = responsegen_convlogs, | |
| temperature=0.3, | |
| max_tokens=800, | |
| top_p=0.95, | |
| frequency_penalty=0, | |
| presence_penalty=0, | |
| stop=None) | |
| final_reply = openai_final_response["choices"][0]["message"]["content"] | |
| bot_message= final_reply | |
| chat_history.append((message, bot_message)) | |
| convlogs.append({"role":"assistant","content":reply}) | |
| nosql_convlogs.append({"role":"assistant","content":bot_message}) | |
| responsegen_convlogs.append({"role":"assistant","content":bot_message}) | |
| return "", chat_history | |
| msg.submit(respond, [msg, chatbot], [msg, chatbot]) | |
| demo.launch(inline=False,width="70%") # debug=True |