Update app.py
Browse files
app.py
CHANGED
@@ -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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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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-
if
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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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import os
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+
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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openai.api_key = os.environ["OPENAI_API_KEY"]
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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 restaurant-specific details
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retrieval_model_name = 'output/sentence-transformer-finetuned/'
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# Initialize the system message for the chatbot
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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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+
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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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+
# Load the SentenceTransformer model
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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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+
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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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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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+
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segments = load_and_preprocess_text(filename)
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+
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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.
|
44 |
This version finds the best match based on the content of the query.
|
45 |
"""
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46 |
try:
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lower_query = user_query.lower()
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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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similarities = util.pytorch_cos_sim(query_embedding, segment_embeddings)[0]
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best_idx = similarities.argmax()
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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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+
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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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messages.append({"role": "user", "content": user_message})
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response = openai.ChatCompletion.create(
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+
model="gpt-4",
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messages=messages,
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67 |
max_tokens=150,
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temperature=0.2,
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frequency_penalty=0,
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presence_penalty=0
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)
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output_text = response['choices'][0]['message']['content'].strip()
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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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+
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+
# Define a sample list of restaurants (replace this with your actual data source)
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+
restaurants = [
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"name": "Harvest Beat",
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"price": "High",
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"cuisine": "American",
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+
"gluten_free": true,
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"vegan": true,
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+
"lactose_intolerant": true,
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"pescatarian": true,
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"allergen_friendly": true,
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"halal": false,
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"kosher": false,
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"vegetarian": true,
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"website": "https://www.harvestbeat.com/"
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},
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{
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"name": "Plum Bistro",
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"price": "Moderate",
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"cuisine": "American",
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+
"gluten_free": true,
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+
"vegan": true,
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+
"lactose_intolerant": true,
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"pescatarian": true,
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+
"allergen_friendly": true,
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+
"halal": false,
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+
"kosher": false,
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+
"vegetarian": true,
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"website": "https://plumbistro.com/"
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+
},
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+
{
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"name": "Portage Bay Cafe",
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"price": "Low",
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+
"cuisine": "American",
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+
"gluten_free": true,
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+
"vegan": true,
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+
"lactose_intolerant": true,
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+
"pescatarian": true,
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+
"allergen_friendly": false,
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+
"halal": false,
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+
"kosher": false,
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+
"vegetarian": true,
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+
"website": "https://www.portagebaycafe.com/"
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+
},
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+
{
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"name": "Duke's Seafood",
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"price": "High",
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+
"cuisine": "American",
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+
"gluten_free": true,
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+
"vegan": false,
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"lactose_intolerant": true,
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+
"pescatarian": true,
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"allergen_friendly": true,
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+
"halal": false,
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+
"kosher": false,
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+
"vegetarian": false,
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+
"website": "https://www.dukesseafood.com/"
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},
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+
{
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"name": "Olmstead",
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"price": "Moderate",
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140 |
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"cuisine": "American",
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+
"gluten_free": false,
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+
"vegan": false,
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+
"lactose_intolerant": false,
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+
"pescatarian": false,
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145 |
+
"allergen_friendly": false,
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+
"halal": false,
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147 |
+
"kosher": false,
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148 |
+
"vegetarian": false,
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149 |
+
"website": "https://www.olmsteadseattle.com/home"
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150 |
+
},
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151 |
+
{
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152 |
+
"name": "Veggie Grill",
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153 |
+
"price": "Low",
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154 |
+
"cuisine": "American",
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155 |
+
"gluten_free": true,
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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!
|