Update app.py
Browse files
app.py
CHANGED
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@@ -2,20 +2,27 @@ import gradio as gr
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from sentence_transformers import SentenceTransformer, util
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import openai
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import os
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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# Initialize paths and model identifiers for easy configuration and maintenance
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-
filename = "output_topic_details.txt" # Path to the file storing
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retrieval_model_name = 'output/sentence-transformer-finetuned/'
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-
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system_message = "You are a restaurant recommending chatbot that suggests one restaurant in Seattle from the restaurant database based on the criteria the user provides."
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# Initial system message to set the behavior of the assistant
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messages = [{"role": "system", "content": system_message}]
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-
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try:
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retrieval_model = SentenceTransformer(retrieval_model_name)
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print("Models loaded successfully.")
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except Exception as e:
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print(f"Failed to load models: {e}")
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def load_and_preprocess_text(filename):
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"""
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Load and preprocess text from a file, removing empty lines and stripping whitespace.
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@@ -28,37 +35,34 @@ def load_and_preprocess_text(filename):
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except Exception as e:
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print(f"Failed to load or preprocess text: {e}")
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return []
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segments = load_and_preprocess_text(filename)
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def find_relevant_segment(user_query, segments):
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"""
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Find the most relevant text segment for a user's query using cosine similarity among sentence embeddings.
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This version finds the best match based on the content of the query.
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"""
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try:
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# Lowercase the query for better matching
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lower_query = user_query.lower()
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-
# Encode the query and the segments
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query_embedding = retrieval_model.encode(lower_query)
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segment_embeddings = retrieval_model.encode(segments)
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# Compute cosine similarities between the query and the segments
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similarities = util.pytorch_cos_sim(query_embedding, segment_embeddings)[0]
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# Find the index of the most similar segment
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best_idx = similarities.argmax()
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# Return the most relevant segment
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return segments[best_idx]
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except Exception as e:
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print(f"Error in finding relevant segment: {e}")
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return ""
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def generate_response(user_query, relevant_segment):
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"""
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Generate a response emphasizing the bot's capability in suggesting a restaurant.
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"""
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try:
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user_message = f"Here is a local restaurant based on your information: {relevant_segment}"
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# Append user's message to messages list
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messages.append({"role": "user", "content": user_message})
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response = openai.ChatCompletion.create(
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model="gpt-
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messages=messages,
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max_tokens=150,
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temperature=0.2,
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@@ -66,25 +70,636 @@ def generate_response(user_query, relevant_segment):
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frequency_penalty=0,
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presence_penalty=0
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)
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# Extract the response text
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output_text = response['choices'][0]['message']['content'].strip()
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# Append assistant's message to messages list for context
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messages.append({"role": "assistant", "content": output_text})
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return output_text
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except Exception as e:
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print(f"Error in generating response: {e}")
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return f"Error in generating response: {e}"
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def query_model(question):
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"""
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Process a question, find relevant information, and generate a response.
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"""
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if question == "":
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return "Give me your preferences..."
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-
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-
if
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-
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return response
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# Define the welcome message and specific topics the chatbot can provide information about
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welcome_message = """
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# Welcome to Ethical Eats Explorer!
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from sentence_transformers import SentenceTransformer, util
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import openai
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| 4 |
import os
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| 5 |
+
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| 6 |
os.environ["TOKENIZERS_PARALLELISM"] = "false"
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| 7 |
+
openai.api_key = os.environ["OPENAI_API_KEY"]
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| 8 |
+
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| 9 |
# Initialize paths and model identifiers for easy configuration and maintenance
|
| 10 |
+
filename = "output_topic_details.txt" # Path to the file storing restaurant-specific details
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| 11 |
retrieval_model_name = 'output/sentence-transformer-finetuned/'
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| 12 |
+
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| 13 |
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# Initialize the system message for the chatbot
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| 14 |
system_message = "You are a restaurant recommending chatbot that suggests one restaurant in Seattle from the restaurant database based on the criteria the user provides."
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| 15 |
+
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| 16 |
# Initial system message to set the behavior of the assistant
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| 17 |
messages = [{"role": "system", "content": system_message}]
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| 18 |
+
|
| 19 |
+
# Load the SentenceTransformer model
|
| 20 |
try:
|
| 21 |
retrieval_model = SentenceTransformer(retrieval_model_name)
|
| 22 |
print("Models loaded successfully.")
|
| 23 |
except Exception as e:
|
| 24 |
print(f"Failed to load models: {e}")
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| 25 |
+
|
| 26 |
def load_and_preprocess_text(filename):
|
| 27 |
"""
|
| 28 |
Load and preprocess text from a file, removing empty lines and stripping whitespace.
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|
|
| 35 |
except Exception as e:
|
| 36 |
print(f"Failed to load or preprocess text: {e}")
|
| 37 |
return []
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| 38 |
+
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| 39 |
segments = load_and_preprocess_text(filename)
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| 40 |
+
|
| 41 |
def find_relevant_segment(user_query, segments):
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| 42 |
"""
|
| 43 |
Find the most relevant text segment for a user's query using cosine similarity among sentence embeddings.
|
| 44 |
This version finds the best match based on the content of the query.
|
| 45 |
"""
|
| 46 |
try:
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|
| 47 |
lower_query = user_query.lower()
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| 48 |
query_embedding = retrieval_model.encode(lower_query)
|
| 49 |
segment_embeddings = retrieval_model.encode(segments)
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|
| 50 |
similarities = util.pytorch_cos_sim(query_embedding, segment_embeddings)[0]
|
|
|
|
| 51 |
best_idx = similarities.argmax()
|
|
|
|
| 52 |
return segments[best_idx]
|
| 53 |
except Exception as e:
|
| 54 |
print(f"Error in finding relevant segment: {e}")
|
| 55 |
return ""
|
| 56 |
+
|
| 57 |
def generate_response(user_query, relevant_segment):
|
| 58 |
"""
|
| 59 |
Generate a response emphasizing the bot's capability in suggesting a restaurant.
|
| 60 |
"""
|
| 61 |
try:
|
| 62 |
user_message = f"Here is a local restaurant based on your information: {relevant_segment}"
|
|
|
|
| 63 |
messages.append({"role": "user", "content": user_message})
|
| 64 |
response = openai.ChatCompletion.create(
|
| 65 |
+
model="gpt-4",
|
| 66 |
messages=messages,
|
| 67 |
max_tokens=150,
|
| 68 |
temperature=0.2,
|
|
|
|
| 70 |
frequency_penalty=0,
|
| 71 |
presence_penalty=0
|
| 72 |
)
|
|
|
|
| 73 |
output_text = response['choices'][0]['message']['content'].strip()
|
|
|
|
| 74 |
messages.append({"role": "assistant", "content": output_text})
|
| 75 |
return output_text
|
| 76 |
except Exception as e:
|
| 77 |
print(f"Error in generating response: {e}")
|
| 78 |
return f"Error in generating response: {e}"
|
| 79 |
+
|
| 80 |
+
# Define a sample list of restaurants (replace this with your actual data source)
|
| 81 |
+
restaurants = [
|
| 82 |
+
"name": "Harvest Beat",
|
| 83 |
+
"price": "High",
|
| 84 |
+
"cuisine": "American",
|
| 85 |
+
"gluten_free": true,
|
| 86 |
+
"vegan": true,
|
| 87 |
+
"lactose_intolerant": true,
|
| 88 |
+
"pescatarian": true,
|
| 89 |
+
"allergen_friendly": true,
|
| 90 |
+
"halal": false,
|
| 91 |
+
"kosher": false,
|
| 92 |
+
"vegetarian": true,
|
| 93 |
+
"website": "https://www.harvestbeat.com/"
|
| 94 |
+
},
|
| 95 |
+
{
|
| 96 |
+
"name": "Plum Bistro",
|
| 97 |
+
"price": "Moderate",
|
| 98 |
+
"cuisine": "American",
|
| 99 |
+
"gluten_free": true,
|
| 100 |
+
"vegan": true,
|
| 101 |
+
"lactose_intolerant": true,
|
| 102 |
+
"pescatarian": true,
|
| 103 |
+
"allergen_friendly": true,
|
| 104 |
+
"halal": false,
|
| 105 |
+
"kosher": false,
|
| 106 |
+
"vegetarian": true,
|
| 107 |
+
"website": "https://plumbistro.com/"
|
| 108 |
+
},
|
| 109 |
+
{
|
| 110 |
+
"name": "Portage Bay Cafe",
|
| 111 |
+
"price": "Low",
|
| 112 |
+
"cuisine": "American",
|
| 113 |
+
"gluten_free": true,
|
| 114 |
+
"vegan": true,
|
| 115 |
+
"lactose_intolerant": true,
|
| 116 |
+
"pescatarian": true,
|
| 117 |
+
"allergen_friendly": false,
|
| 118 |
+
"halal": false,
|
| 119 |
+
"kosher": false,
|
| 120 |
+
"vegetarian": true,
|
| 121 |
+
"website": "https://www.portagebaycafe.com/"
|
| 122 |
+
},
|
| 123 |
+
{
|
| 124 |
+
"name": "Duke's Seafood",
|
| 125 |
+
"price": "High",
|
| 126 |
+
"cuisine": "American",
|
| 127 |
+
"gluten_free": true,
|
| 128 |
+
"vegan": false,
|
| 129 |
+
"lactose_intolerant": true,
|
| 130 |
+
"pescatarian": true,
|
| 131 |
+
"allergen_friendly": true,
|
| 132 |
+
"halal": false,
|
| 133 |
+
"kosher": false,
|
| 134 |
+
"vegetarian": false,
|
| 135 |
+
"website": "https://www.dukesseafood.com/"
|
| 136 |
+
},
|
| 137 |
+
{
|
| 138 |
+
"name": "Olmstead",
|
| 139 |
+
"price": "Moderate",
|
| 140 |
+
"cuisine": "American",
|
| 141 |
+
"gluten_free": false,
|
| 142 |
+
"vegan": false,
|
| 143 |
+
"lactose_intolerant": false,
|
| 144 |
+
"pescatarian": false,
|
| 145 |
+
"allergen_friendly": false,
|
| 146 |
+
"halal": false,
|
| 147 |
+
"kosher": false,
|
| 148 |
+
"vegetarian": false,
|
| 149 |
+
"website": "https://www.olmsteadseattle.com/home"
|
| 150 |
+
},
|
| 151 |
+
{
|
| 152 |
+
"name": "Veggie Grill",
|
| 153 |
+
"price": "Low",
|
| 154 |
+
"cuisine": "American",
|
| 155 |
+
"gluten_free": true,
|
| 156 |
+
"vegan": true,
|
| 157 |
+
"lactose_intolerant": true,
|
| 158 |
+
"pescatarian": true,
|
| 159 |
+
"allergen_friendly": true,
|
| 160 |
+
"halal": false,
|
| 161 |
+
"kosher": false,
|
| 162 |
+
"vegetarian": true,
|
| 163 |
+
"website": "https://www.veggiegrill.com/menus/"
|
| 164 |
+
},
|
| 165 |
+
{
|
| 166 |
+
"name": "Cafe Flora",
|
| 167 |
+
"price": "Moderate",
|
| 168 |
+
"cuisine": "American",
|
| 169 |
+
"gluten_free": false,
|
| 170 |
+
"vegan": true,
|
| 171 |
+
"lactose_intolerant": false,
|
| 172 |
+
"pescatarian": true,
|
| 173 |
+
"allergen_friendly": false,
|
| 174 |
+
"halal": false,
|
| 175 |
+
"kosher": false,
|
| 176 |
+
"vegetarian": true,
|
| 177 |
+
"website": "https://florarestaurantgroup.com/"
|
| 178 |
+
},
|
| 179 |
+
{
|
| 180 |
+
"name": "Bounty Kitchen",
|
| 181 |
+
"price": "Low",
|
| 182 |
+
"cuisine": "American",
|
| 183 |
+
"gluten_free": true,
|
| 184 |
+
"vegan": true,
|
| 185 |
+
"lactose_intolerant": false,
|
| 186 |
+
"pescatarian": true,
|
| 187 |
+
"allergen_friendly": true,
|
| 188 |
+
"halal": false,
|
| 189 |
+
"kosher": false,
|
| 190 |
+
"vegetarian": true,
|
| 191 |
+
"website": "http://www.bountykitchenseattle.com/"
|
| 192 |
+
},
|
| 193 |
+
{
|
| 194 |
+
"name": "No Bones Beach Club",
|
| 195 |
+
"price": "Low",
|
| 196 |
+
"cuisine": "American",
|
| 197 |
+
"gluten_free": true,
|
| 198 |
+
"vegan": true,
|
| 199 |
+
"lactose_intolerant": false,
|
| 200 |
+
"pescatarian": true,
|
| 201 |
+
"allergen_friendly": true,
|
| 202 |
+
"halal": false,
|
| 203 |
+
"kosher": false,
|
| 204 |
+
"vegetarian": true,
|
| 205 |
+
"website": "https://nobonesbeachclub.com/menu/"
|
| 206 |
+
},
|
| 207 |
+
{
|
| 208 |
+
"name": "Chiho Bistro",
|
| 209 |
+
"price": "Low",
|
| 210 |
+
"cuisine": "Chinese",
|
| 211 |
+
"gluten_free": false,
|
| 212 |
+
"vegan": true,
|
| 213 |
+
"lactose_intolerant": false,
|
| 214 |
+
"pescatarian": false,
|
| 215 |
+
"allergen_friendly": false,
|
| 216 |
+
"halal": false,
|
| 217 |
+
"kosher": false,
|
| 218 |
+
"vegetarian": false,
|
| 219 |
+
"website": "https://www.chihobistro.com/"
|
| 220 |
+
},
|
| 221 |
+
{
|
| 222 |
+
"name": "Uptown China",
|
| 223 |
+
"price": "Moderate",
|
| 224 |
+
"cuisine": "Chinese",
|
| 225 |
+
"gluten_free": false,
|
| 226 |
+
"vegan": true,
|
| 227 |
+
"lactose_intolerant": true,
|
| 228 |
+
"pescatarian": true,
|
| 229 |
+
"allergen_friendly": false,
|
| 230 |
+
"halal": false,
|
| 231 |
+
"kosher": false,
|
| 232 |
+
"vegetarian": true,
|
| 233 |
+
"website": "https://uptown-china.com/"
|
| 234 |
+
},
|
| 235 |
+
{
|
| 236 |
+
"name": "Meskel Ethiopian Restaurant",
|
| 237 |
+
"price": "Moderate",
|
| 238 |
+
"cuisine": "Ethiopian",
|
| 239 |
+
"gluten_free": true,
|
| 240 |
+
"vegan": true,
|
| 241 |
+
"lactose_intolerant": true,
|
| 242 |
+
"pescatarian": true,
|
| 243 |
+
"allergen_friendly": true,
|
| 244 |
+
"halal": false,
|
| 245 |
+
"kosher": false,
|
| 246 |
+
"vegetarian": true,
|
| 247 |
+
"website": "https://meskelethiopian.com/menu"
|
| 248 |
+
},
|
| 249 |
+
{
|
| 250 |
+
"name": "Habesha Cafe",
|
| 251 |
+
"price": "Moderate",
|
| 252 |
+
"cuisine": "Ethiopian",
|
| 253 |
+
"gluten_free": false,
|
| 254 |
+
"vegan": true,
|
| 255 |
+
"lactose_intolerant": false,
|
| 256 |
+
"pescatarian": true,
|
| 257 |
+
"allergen_friendly": false,
|
| 258 |
+
"halal": false,
|
| 259 |
+
"kosher": false,
|
| 260 |
+
"vegetarian": true,
|
| 261 |
+
"website": "https://habesha.cafe/"
|
| 262 |
+
},
|
| 263 |
+
{
|
| 264 |
+
"name": "Musang",
|
| 265 |
+
"price": "High",
|
| 266 |
+
"cuisine": "Filipino",
|
| 267 |
+
"gluten_free": true,
|
| 268 |
+
"vegan": false,
|
| 269 |
+
"lactose_intolerant": true,
|
| 270 |
+
"pescatarian": true,
|
| 271 |
+
"allergen_friendly": true,
|
| 272 |
+
"halal": false,
|
| 273 |
+
"kosher": false,
|
| 274 |
+
"vegetarian": false,
|
| 275 |
+
"website": "https://www.musangseattle.com/"
|
| 276 |
+
},
|
| 277 |
+
{
|
| 278 |
+
"name": "Musang Seattle",
|
| 279 |
+
"price": "Moderate",
|
| 280 |
+
"cuisine": "Filipino",
|
| 281 |
+
"gluten_free": true,
|
| 282 |
+
"vegan": true,
|
| 283 |
+
"lactose_intolerant": true,
|
| 284 |
+
"pescatarian": true,
|
| 285 |
+
"allergen_friendly": false,
|
| 286 |
+
"halal": false,
|
| 287 |
+
"kosher": false,
|
| 288 |
+
"vegetarian": true,
|
| 289 |
+
"website": "https://www.musangseattle.com/musang"
|
| 290 |
+
},
|
| 291 |
+
{
|
| 292 |
+
"name": "Gold Coast Ghal",
|
| 293 |
+
"price": "Moderate",
|
| 294 |
+
"cuisine": "Ghanaian",
|
| 295 |
+
"gluten_free": false,
|
| 296 |
+
"vegan": false,
|
| 297 |
+
"lactose_intolerant": false,
|
| 298 |
+
"pescatarian": false,
|
| 299 |
+
"allergen_friendly": false,
|
| 300 |
+
"halal": false,
|
| 301 |
+
"kosher": false,
|
| 302 |
+
"vegetarian": false,
|
| 303 |
+
"website": "https://www.goldcoastghal.com/"
|
| 304 |
+
},
|
| 305 |
+
{
|
| 306 |
+
"name": "Marination Ma Kai",
|
| 307 |
+
"price": "Low",
|
| 308 |
+
"cuisine": "Hawaiian-Korean",
|
| 309 |
+
"gluten_free": true,
|
| 310 |
+
"vegan": false,
|
| 311 |
+
"lactose_intolerant": true,
|
| 312 |
+
"pescatarian": true,
|
| 313 |
+
"allergen_friendly": true,
|
| 314 |
+
"halal": false,
|
| 315 |
+
"kosher": false,
|
| 316 |
+
"vegetarian": true,
|
| 317 |
+
"website": "https://marinationmobile.com/menu"
|
| 318 |
+
},
|
| 319 |
+
{
|
| 320 |
+
"name": "Pabla Indian Cuisine",
|
| 321 |
+
"price": "Low",
|
| 322 |
+
"cuisine": "Indian",
|
| 323 |
+
"gluten_free": true,
|
| 324 |
+
"vegan": true,
|
| 325 |
+
"lactose_intolerant": true,
|
| 326 |
+
"pescatarian": true,
|
| 327 |
+
"allergen_friendly": false,
|
| 328 |
+
"halal": true,
|
| 329 |
+
"kosher": false,
|
| 330 |
+
"vegetarian": true,
|
| 331 |
+
"website": "http://www.pablacuisine
|
| 332 |
+
10:16
|
| 333 |
+
{
|
| 334 |
+
"name": "Mint Progressive Indian",
|
| 335 |
+
"price": "Moderate",
|
| 336 |
+
"cuisine": "Indian",
|
| 337 |
+
"gluten_free": true,
|
| 338 |
+
"vegan": true,
|
| 339 |
+
"lactose_intolerant": true,
|
| 340 |
+
"pescatarian": true,
|
| 341 |
+
"allergen_friendly": false,
|
| 342 |
+
"halal": false,
|
| 343 |
+
"kosher": false,
|
| 344 |
+
"vegetarian": true,
|
| 345 |
+
"website": "https://www.mintprogressive.com/"
|
| 346 |
+
},
|
| 347 |
+
{
|
| 348 |
+
"name": "Cantinetta",
|
| 349 |
+
"price": "Moderate",
|
| 350 |
+
"cuisine": "Italian",
|
| 351 |
+
"gluten_free": false,
|
| 352 |
+
"vegan": false,
|
| 353 |
+
"lactose_intolerant": false,
|
| 354 |
+
"pescatarian": false,
|
| 355 |
+
"allergen_friendly": false,
|
| 356 |
+
"halal": false,
|
| 357 |
+
"kosher": false,
|
| 358 |
+
"vegetarian": false,
|
| 359 |
+
"website": "https://www.cantinettausa.com/wallingfordYes"
|
| 360 |
+
},
|
| 361 |
+
{
|
| 362 |
+
"name": "The Pink Door",
|
| 363 |
+
"price": "High",
|
| 364 |
+
"cuisine": "Italian",
|
| 365 |
+
"gluten_free": true,
|
| 366 |
+
"vegan": true,
|
| 367 |
+
"lactose_intolerant": true,
|
| 368 |
+
"pescatarian": false,
|
| 369 |
+
"allergen_friendly": false,
|
| 370 |
+
"halal": false,
|
| 371 |
+
"kosher": false,
|
| 372 |
+
"vegetarian": true,
|
| 373 |
+
"website": "https://www.thepinkdoor.net/"
|
| 374 |
+
},
|
| 375 |
+
{
|
| 376 |
+
"name": "Mashiko",
|
| 377 |
+
"price": "High",
|
| 378 |
+
"cuisine": "Japanese",
|
| 379 |
+
"gluten_free": false,
|
| 380 |
+
"vegan": true,
|
| 381 |
+
"lactose_intolerant": true,
|
| 382 |
+
"pescatarian": true,
|
| 383 |
+
"allergen_friendly": false,
|
| 384 |
+
"halal": false,
|
| 385 |
+
"kosher": false,
|
| 386 |
+
"vegetarian": false,
|
| 387 |
+
"website": "https://www.mashikorestaurant.com/"
|
| 388 |
+
},
|
| 389 |
+
{
|
| 390 |
+
"name": "Ben's Fast Food",
|
| 391 |
+
"price": "Low",
|
| 392 |
+
"cuisine": "Mexican",
|
| 393 |
+
"gluten_free": true,
|
| 394 |
+
"vegan": true,
|
| 395 |
+
"lactose_intolerant": true,
|
| 396 |
+
"pescatarian": true,
|
| 397 |
+
"allergen_friendly": false,
|
| 398 |
+
"halal": false,
|
| 399 |
+
"kosher": false,
|
| 400 |
+
"vegetarian": true,
|
| 401 |
+
"website": "https://bensfastfood.com/"
|
| 402 |
+
},
|
| 403 |
+
{
|
| 404 |
+
"name": "Sal y Limon",
|
| 405 |
+
"price": "Moderate",
|
| 406 |
+
"cuisine": "Mexican",
|
| 407 |
+
"gluten_free": false,
|
| 408 |
+
"vegan": false,
|
| 409 |
+
"lactose_intolerant": false,
|
| 410 |
+
"pescatarian": false,
|
| 411 |
+
"allergen_friendly": false,
|
| 412 |
+
"halal": false,
|
| 413 |
+
"kosher": false,
|
| 414 |
+
"vegetarian": true,
|
| 415 |
+
"website": "https://www.salylimonseattle.com/"
|
| 416 |
+
},
|
| 417 |
+
{
|
| 418 |
+
"name": "El Borracho",
|
| 419 |
+
"price": "Low",
|
| 420 |
+
"cuisine": "Mexican",
|
| 421 |
+
"gluten_free": true,
|
| 422 |
+
"vegan": true,
|
| 423 |
+
"lactose_intolerant": true,
|
| 424 |
+
"pescatarian": true,
|
| 425 |
+
"allergen_friendly": false,
|
| 426 |
+
"halal": false,
|
| 427 |
+
"kosher": false,
|
| 428 |
+
"vegetarian": true,
|
| 429 |
+
"website": "https://www.elborracho.co/"
|
| 430 |
+
},
|
| 431 |
+
{
|
| 432 |
+
"name": "Tanoor",
|
| 433 |
+
"price": "Moderate",
|
| 434 |
+
"cuisine": "Middle Eastern",
|
| 435 |
+
"gluten_free": true,
|
| 436 |
+
"vegan": true,
|
| 437 |
+
"lactose_intolerant": true,
|
| 438 |
+
"pescatarian": true,
|
| 439 |
+
"allergen_friendly": true,
|
| 440 |
+
"halal": true,
|
| 441 |
+
"kosher": false,
|
| 442 |
+
"vegetarian": true,
|
| 443 |
+
"website": "https://www.tanoor.com/"
|
| 444 |
+
},
|
| 445 |
+
{
|
| 446 |
+
"name": "Mamnoon",
|
| 447 |
+
"price": "Moderate",
|
| 448 |
+
"cuisine": "Middle Eastern",
|
| 449 |
+
"gluten_free": true,
|
| 450 |
+
"vegan": true,
|
| 451 |
+
"lactose_intolerant": true,
|
| 452 |
+
"pescatarian": true,
|
| 453 |
+
"allergen_friendly": false,
|
| 454 |
+
"halal": false,
|
| 455 |
+
"kosher": false,
|
| 456 |
+
"vegetarian": true,
|
| 457 |
+
"website": "https://nadimama.com/mamnoon"
|
| 458 |
+
},
|
| 459 |
+
{
|
| 460 |
+
"name": "Gorgeous George's",
|
| 461 |
+
"price": "Moderate",
|
| 462 |
+
"cuisine": "Middle Eastern",
|
| 463 |
+
"gluten_free": true,
|
| 464 |
+
"vegan": true,
|
| 465 |
+
"lactose_intolerant": true,
|
| 466 |
+
"pescatarian": true,
|
| 467 |
+
"allergen_friendly": false,
|
| 468 |
+
"halal": false,
|
| 469 |
+
"kosher": false,
|
| 470 |
+
"vegetarian": true,
|
| 471 |
+
"website": "https://www.gorgeousgeorges.com/"
|
| 472 |
+
},
|
| 473 |
+
{
|
| 474 |
+
"name": "Zaina",
|
| 475 |
+
"price": "Low",
|
| 476 |
+
"cuisine": "Middle Eastern",
|
| 477 |
+
"gluten_free": true,
|
| 478 |
+
"vegan": true,
|
| 479 |
+
"lactose_intolerant": true,
|
| 480 |
+
"pescatarian": true,
|
| 481 |
+
"allergen_friendly": true,
|
| 482 |
+
"halal": true,
|
| 483 |
+
"kosher": false,
|
| 484 |
+
"vegetarian": true,
|
| 485 |
+
"website": "https://www.yelp.com/biz/zaina-food-drinks-and-friends-seattle-3"
|
| 486 |
+
},
|
| 487 |
+
{
|
| 488 |
+
"name": "Gold Schnitzel",
|
| 489 |
+
"price": "Moderate",
|
| 490 |
+
"cuisine": "Middle Eastern",
|
| 491 |
+
"gluten_free": false,
|
| 492 |
+
"vegan": false,
|
| 493 |
+
"lactose_intolerant": true,
|
| 494 |
+
"pescatarian": false,
|
| 495 |
+
"allergen_friendly": true,
|
| 496 |
+
"halal": false,
|
| 497 |
+
"kosher": false,
|
| 498 |
+
"vegetarian": false,
|
| 499 |
+
"website": "https://goldschnitzel.com/"
|
| 500 |
+
},
|
| 501 |
+
{
|
| 502 |
+
"name": "Maza Grill",
|
| 503 |
+
"price": "Moderate",
|
| 504 |
+
"cuisine": "Pakistani",
|
| 505 |
+
"gluten_free": false,
|
| 506 |
+
"vegan": false,
|
| 507 |
+
"lactose_intolerant": false,
|
| 508 |
+
"pescatarian": false,
|
| 509 |
+
"allergen_friendly": true,
|
| 510 |
+
"halal": false,
|
| 511 |
+
"kosher": false,
|
| 512 |
+
"vegetarian": false,
|
| 513 |
+
"website": "https://mazagrill.co/"
|
| 514 |
+
},
|
| 515 |
+
{
|
| 516 |
+
"name": "Terra Plata",
|
| 517 |
+
"price": "High",
|
| 518 |
+
"cuisine": "Spanish",
|
| 519 |
+
"gluten_free": false,
|
| 520 |
+
"vegan": false,
|
| 521 |
+
"lactose_intolerant": false,
|
| 522 |
+
"pescatarian": true,
|
| 523 |
+
"allergen_friendly": false,
|
| 524 |
+
"halal": false,
|
| 525 |
+
"kosher": false,
|
| 526 |
+
"vegetarian": false,
|
| 527 |
+
"website": "https://www.terraplata.com/"
|
| 528 |
+
},
|
| 529 |
+
{
|
| 530 |
+
"name": "Pestle Rock",
|
| 531 |
+
"price": "Moderate",
|
| 532 |
+
"cuisine": "Thai",
|
| 533 |
+
"gluten_free": true,
|
| 534 |
+
"vegan": true,
|
| 535 |
+
"lactose_intolerant": true,
|
| 536 |
+
"pescatarian": true,
|
| 537 |
+
"allergen_friendly": false,
|
| 538 |
+
"halal": false,
|
| 539 |
+
"kosher": false,
|
| 540 |
+
"vegetarian": true,
|
| 541 |
+
"website": "https://pestlerock.com/"
|
| 542 |
+
},
|
| 543 |
+
{
|
| 544 |
+
"name": "Araya's Place",
|
| 545 |
+
"price": "Low",
|
| 546 |
+
"cuisine": "Thai",
|
| 547 |
+
"gluten_free": false,
|
| 548 |
+
"vegan": true,
|
| 549 |
+
"lactose_intolerant": false,
|
| 550 |
+
"pescatarian": false,
|
| 551 |
+
"allergen_friendly": false,
|
| 552 |
+
"halal": false,
|
| 553 |
+
"kosher": false,
|
| 554 |
+
"vegetarian": true,
|
| 555 |
+
"website": "https://www.arayasplace.com/"
|
| 556 |
+
},
|
| 557 |
+
{
|
| 558 |
+
"name": "Cafe Turko",
|
| 559 |
+
"price": "Moderate",
|
| 560 |
+
"cuisine": "Turkish",
|
| 561 |
+
"gluten_free": true,
|
| 562 |
+
"vegan": true,
|
| 563 |
+
"lactose_intolerant": true,
|
| 564 |
+
"pescatarian": true,
|
| 565 |
+
"allergen_friendly": false,
|
| 566 |
+
"halal": true,
|
| 567 |
+
"kosher": false,
|
| 568 |
+
"vegetarian": true,
|
| 569 |
+
"website": "https://cafeturko.com/#"
|
| 570 |
+
},
|
| 571 |
+
{
|
| 572 |
+
"name": "Blossom Vegetarian",
|
| 573 |
+
"price": "Low",
|
| 574 |
+
"cuisine": "Vietnamese",
|
| 575 |
+
"gluten_free": true,
|
| 576 |
+
"vegan": true,
|
| 577 |
+
"lactose_intolerant": true,
|
| 578 |
+
"pescatarian": false,
|
| 579 |
+
"allergen_friendly": false,
|
| 580 |
+
"halal": false,
|
| 581 |
+
"kosher": false,
|
| 582 |
+
"vegetarian": true,
|
| 583 |
+
"website": "https://www.blossomrenton.com/"
|
| 584 |
+
},
|
| 585 |
+
{
|
| 586 |
+
"name": "Tilikum",
|
| 587 |
+
"price": "Moderate",
|
| 588 |
+
"cuisine": "European",
|
| 589 |
+
"gluten_free": false,
|
| 590 |
+
"vegan": false,
|
| 591 |
+
"lactose_intolerant": false,
|
| 592 |
+
"pescatarian": true,
|
| 593 |
+
"allergen_friendly": false,
|
| 594 |
+
"halal": false,
|
| 595 |
+
"kosher": false,
|
| 596 |
+
"vegetarian": false,
|
| 597 |
+
"website": "https://www.tilikumplacecafe.com/"
|
| 598 |
+
}
|
| 599 |
+
# Add more restaurant entries as needed
|
| 600 |
+
]
|
| 601 |
+
|
| 602 |
+
def find_restaurants(criteria):
|
| 603 |
+
"""
|
| 604 |
+
Finds restaurants based on the given criteria.
|
| 605 |
+
Parameters:
|
| 606 |
+
criteria (dict): Dictionary containing filtering criteria.
|
| 607 |
+
Returns:
|
| 608 |
+
List of restaurants that match the criteria.
|
| 609 |
+
"""
|
| 610 |
+
matching_restaurants = []
|
| 611 |
+
for restaurant in restaurants:
|
| 612 |
+
match = True
|
| 613 |
+
for key, value in criteria.items():
|
| 614 |
+
if key in restaurant:
|
| 615 |
+
if isinstance(restaurant[key], bool):
|
| 616 |
+
if restaurant[key] != value:
|
| 617 |
+
match = False
|
| 618 |
+
break
|
| 619 |
+
elif restaurant[key].lower() != value.lower():
|
| 620 |
+
match = False
|
| 621 |
+
break
|
| 622 |
+
if match:
|
| 623 |
+
matching_restaurants.append(restaurant)
|
| 624 |
+
return matching_restaurants
|
| 625 |
+
|
| 626 |
+
def generate_recommendation(criteria):
|
| 627 |
+
"""
|
| 628 |
+
Generates a recommendation based on the criteria.
|
| 629 |
+
Parameters:
|
| 630 |
+
criteria (dict): Dictionary containing filtering criteria.
|
| 631 |
+
Returns:
|
| 632 |
+
String with the recommendation or a message if no matches are found.
|
| 633 |
+
"""
|
| 634 |
+
results = find_restaurants(criteria)
|
| 635 |
+
if results:
|
| 636 |
+
recommendations = []
|
| 637 |
+
for result in results:
|
| 638 |
+
recommendation = (
|
| 639 |
+
f"Based on your criteria, I recommend {result['name']}. "
|
| 640 |
+
f"It's a {result['price'].lower()} priced {result['cuisine'].lower()} restaurant with "
|
| 641 |
+
f"{'gluten-free options' if result['gluten_free'] else 'no gluten-free options'}, "
|
| 642 |
+
f"{'vegan options' if result['vegan'] else 'no vegan options'}, "
|
| 643 |
+
f"{'lactose-intolerant options' if result['lactose_intolerant'] else 'no lactose-intolerant options'}, "
|
| 644 |
+
f"{'pescatarian options' if result['pescatarian'] else 'no pescatarian options'}, "
|
| 645 |
+
f"{'allergen-friendly options' if result['allergen_friendly'] else 'no allergen-friendly options'}, "
|
| 646 |
+
f"{'halal options' if result['halal'] else 'no halal options'}, "
|
| 647 |
+
f"{'kosher options' if result['kosher'] else 'no kosher options'}, "
|
| 648 |
+
f"and { 'vegetarian options' if result['vegetarian'] else 'no vegetarian options'}. "
|
| 649 |
+
f"Visit their website for more details: {result['website']}"
|
| 650 |
+
)
|
| 651 |
+
recommendations.append(recommendation)
|
| 652 |
+
return "\n".join(recommendations)
|
| 653 |
+
else:
|
| 654 |
+
return "Sorry, no restaurants meet your criteria. Please try adjusting your filters."
|
| 655 |
+
|
| 656 |
def query_model(question):
|
| 657 |
"""
|
| 658 |
Process a question, find relevant information, and generate a response.
|
| 659 |
"""
|
| 660 |
if question == "":
|
| 661 |
return "Give me your preferences..."
|
| 662 |
+
|
| 663 |
+
if "restaurant" in question.lower():
|
| 664 |
+
# Extract criteria from the question
|
| 665 |
+
criteria = {}
|
| 666 |
+
if "gluten-free" in question.lower():
|
| 667 |
+
criteria["gluten_free"] = True
|
| 668 |
+
if "vegan" in question.lower():
|
| 669 |
+
criteria["vegan"] = True
|
| 670 |
+
if "lactose-intolerant" in question.lower():
|
| 671 |
+
criteria["lactose_intolerant"] = True
|
| 672 |
+
if "pescatarian" in question.lower():
|
| 673 |
+
criteria["pescatarian"] = True
|
| 674 |
+
if "allergen-friendly" in question.lower():
|
| 675 |
+
criteria["allergen_friendly"] = True
|
| 676 |
+
if "halal" in question.lower():
|
| 677 |
+
criteria["halal"] = True
|
| 678 |
+
if "kosher" in question.lower():
|
| 679 |
+
criteria["kosher"] = True
|
| 680 |
+
if "vegetarian" in question.lower():
|
| 681 |
+
criteria["vegetarian"] = True
|
| 682 |
+
|
| 683 |
+
# Extract price and cuisine
|
| 684 |
+
if "low" in question.lower():
|
| 685 |
+
criteria["price"] = "Low"
|
| 686 |
+
elif "moderate" in question.lower():
|
| 687 |
+
criteria["price"] = "Moderate"
|
| 688 |
+
elif "high" in question.lower():
|
| 689 |
+
criteria["price"] = "High"
|
| 690 |
+
|
| 691 |
+
if any(cuisine in question.lower() for cuisine in ["american", "indian", "middle eastern", "chinese", "italian", "thai", "hawaiian-korean", "japanese", "ethiopian", "pakistani", "mexican", "ghanaian", "vietnamese", "filipino", "spanish", "turkish"]):
|
| 692 |
+
criteria["cuisine"] = next(cuisine for cuisine in ["american", "indian", "middle eastern", "chinese", "italian", "thai", "hawaiian-korean", "japanese", "ethiopian", "pakistani", "mexican", "ghanaian", "vietnamese", "filipino", "spanish", "turkish"] if cuisine in question.lower())
|
| 693 |
+
|
| 694 |
+
response = generate_recommendation(criteria)
|
| 695 |
+
else:
|
| 696 |
+
relevant_segment = find_relevant_segment(question, segments)
|
| 697 |
+
if not relevant_segment:
|
| 698 |
+
return "Could not find specific information. Please refine your question."
|
| 699 |
+
response = generate_response(question, relevant_segment)
|
| 700 |
+
|
| 701 |
return response
|
| 702 |
+
|
| 703 |
# Define the welcome message and specific topics the chatbot can provide information about
|
| 704 |
welcome_message = """
|
| 705 |
# Welcome to Ethical Eats Explorer!
|