Update app.py
Browse files
app.py
CHANGED
@@ -1,14 +1,14 @@
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import os
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import gradio as gr
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import pandas as pd
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import
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Set up OpenAI
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# Simple database using pandas DataFrames
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class SimpleDatabase:
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@@ -83,7 +83,7 @@ class QueryRouter:
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def _classify_query(self, query):
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"""Classify the query to determine which agent should handle it"""
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# Use OpenAI to classify the query
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response =
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": """
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@@ -122,7 +122,7 @@ class QueryRouter:
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Example: {{"product_name": "laptop"}} or {{"date": "2025-04-29"}}
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"""
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response =
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You extract parameters from customer queries for a shop assistant."},
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@@ -142,7 +142,7 @@ class QueryRouter:
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def _handle_general_knowledge(self, query):
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"""Handle general knowledge queries using OpenAI"""
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response =
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": """
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import os
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import gradio as gr
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import pandas as pd
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from openai import OpenAI
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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# Set up OpenAI client
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client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
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# Simple database using pandas DataFrames
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class SimpleDatabase:
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def _classify_query(self, query):
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"""Classify the query to determine which agent should handle it"""
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# Use OpenAI to classify the query
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response = client.chat.completions.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": """
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Example: {{"product_name": "laptop"}} or {{"date": "2025-04-29"}}
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"""
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response = client.chat.completions.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You extract parameters from customer queries for a shop assistant."},
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def _handle_general_knowledge(self, query):
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"""Handle general knowledge queries using OpenAI"""
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response = client.chat.completions.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": """
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