initial commit

app.py

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+# AUTOGENERATED! DO NOT EDIT! File to edit: ../drive/MyDrive/Codici/Python/Gradio_App/SemanticSearch_QA-v1.ipynb.
+
+# %% auto 0
+__all__ = ['s_model', 'qa_model', 'question_1', 'question_2', 'question_3', 'question_4', 'question_5', 'question_6',
+           'question_7', 'question_8', 'question_9', 'question_10', 'contexts', 'answer_example', 'a_text', 'n_slider',
+           'intf', 'QA_similarity']
+
+# %% ../drive/MyDrive/Codici/Python/Gradio_App/SemanticSearch_QA-v1.ipynb 1
+!pip install -U sentence-transformers
+!pip install gradio
+
+# %% ../drive/MyDrive/Codici/Python/Gradio_App/SemanticSearch_QA-v1.ipynb 2
+import pandas as pd
+import gradio as gr
+
+from sentence_transformers import SentenceTransformer, util
+s_model = SentenceTransformer('clips/mfaq')
+
+from transformers import pipeline
+qa_model = pipeline("question-answering")
+
+# %% ../drive/MyDrive/Codici/Python/Gradio_App/SemanticSearch_QA-v1.ipynb 3
+# Define the question(s)
+question_1 = "What are the main features of the new XPhone 20?"
+question_2 = "What are some benefits of regular exercise?"
+question_3 = "What is the color of a rose?"
+question_4 = "How does photosynthesis work in plants?"
+question_5 = "At what temperature does water boil?"
+question_6 = "Where can I find potassium?"
+question_7 = "How does the internet function?"
+question_8 = "What are the ingredients for making a classic margarita?"
+question_9 = "How does cellular respiration work?"
+question_10 = "Is money important?"
+
+# Define the contexts as a list of strings
+contexts = [
+    "The XPhone 20 is expected to come with an improved camera system, featuring advanced image stabilization and enhanced low-light capabilities.",
+    "Regular exercise has been shown to reduce the risk of chronic diseases such as heart disease, diabetes, and certain types of cancer.",
+    "Roses come in various colors, including red, pink, yellow, white, and even blue (though blue roses are rare and often created through genetic modification).",
+    "Photosynthesis occurs in the chloroplasts of plant cells, where chlorophyll captures sunlight and converts it into chemical energy.",
+    "Water boils at different temperatures depending on factors like altitude and atmospheric pressure. At sea level, it boils at 100 degrees Celsius or 212 degrees Fahrenheit.",
+    "Potassium is an essential mineral that can be found in various foods such as bananas, potatoes, spinach, and oranges.",
+    "The internet functions through a complex system of data transmission protocols, routers, and servers that allow for the exchange of information globally.",
+    "A classic margarita typically consists of tequila, lime juice, triple sec (or orange liqueur), and is often served with a salted rim.",
+    "Cellular respiration takes place in the mitochondria of cells, where glucose and oxygen are converted into ATP (adenosine triphosphate) and carbon dioxide.",
+    "Money is a medium of exchange that facilitates transactions of goods and services. Its importance lies in its role in economic systems and the ability to represent value.",
+    "The XPhone 20 may feature an OLED display for vibrant colors and deep blacks, providing a high-quality visual experience.",
+    "Exercise releases endorphins, which are chemicals in the brain that help improve mood and reduce feelings of stress and anxiety.",
+    "Different species of roses can have variations in color, including shades of red, pink, yellow, and white.",
+    "During photosynthesis, plants also release oxygen as a byproduct, which is essential for the survival of many organisms on Earth.",
+    "Water boils at a lower temperature at higher altitudes due to the reduced atmospheric pressure. For example, in the mountains, it may boil below 100 degrees Celsius.",
+    "Potassium is crucial for proper muscle function, nerve function, and maintaining fluid balance in the body.",
+    "The internet relies on a system of interconnected networks, including wired and wireless connections, to transmit data across the globe.",
+    "In addition to the core ingredients, a classic margarita can also be garnished with a wedge of lime for added flavor.",
+    "Cellular respiration involves several stages, including glycolysis, the Krebs cycle, and the electron transport chain, to extract energy from glucose.",
+    "Money serves as a unit of account, allowing for standardized pricing and valuation of goods and services in economies worldwide."
+    "The XPhone 20 is rumored to feature a smaller notch, providing more screen real estate for users. This allows for an immersive viewing experience.",
+    "Photosynthesis is the process by which plants convert carbon dioxide, water, and sunlight into glucose and oxygen.",
+    "Bananas are a great source of potassium.",
+    "The theory of relativity was developed by Albert Einstein and revolutionized our understanding of space and time.",
+    "The Eiffel Tower is located in Paris, France.",
+    "Reports suggest that the XPhone 20 will have significant improvements in battery life compared to its predecessor. Users can expect a longer-lasting device.",
+    "A penny saved is a penny earned.",
+    "Water boils at 100 degrees Celsius.",
+    "The Great Wall of China is one of the most impressive architectural feats in history.",
+    "The capital of Japan is Tokyo.",
+    "One of the anticipated features of the XPhone 20 is a faster and more powerful A16 chip. This will result in smoother and more efficient performance.",
+    "Roses are red, violets are blue.",
+    "Regular exercise can help improve cardiovascular health and strengthen muscles.",
+    "A classic margarita is made with tequila, lime juice, and orange liqueur.",
+    "Cellular respiration is the process by which cells convert glucose and oxygen into energy, carbon dioxide, and water.",
+    "The internet is a global network of interconnected computers and servers that allows the sharing of information and resources.",
+    "Mount Everest is the highest mountain in the world, located in the Himalayas.",
+    "The sun rises in the east and sets in the west.",
+    "The Mona Lisa is a famous portrait painting by Leonardo da Vinci.",
+    "The Declaration of Independence was adopted by the Continental Congress on July 4, 1776.",
+]
+
+# %% ../drive/MyDrive/Codici/Python/Gradio_App/SemanticSearch_QA-v1.ipynb 5
+# Function to find similar answers in a list of contexts
+def QA_similarity(question, contexts, n_answers=1):
+
+    contexts = contexts.iloc[:,0].to_list()
+
+    # to use 'clips/mfaq' questions need to be prepended with <Q>, and answers with <A>.
+    question = "<Q>"+question
+    mfaq_contexts = ["<A>"+answer for answer in contexts]
+
+    # Import the necessary module for itemgetter
+    from operator import itemgetter
+
+    # Create context embedding
+    query_embedding = s_model.encode(question)
+    context_embeddings = s_model.encode(mfaq_contexts)
+
+    # Perform semantic search to find similar contexts
+    data = util.semantic_search(query_embedding, context_embeddings)[0]
+
+    # Sort the list of dictionaries by the 'score' key in descending order
+    sorted_answers = sorted(data, key=itemgetter('score'), reverse=True)
+
+    # Extract answer, context and score
+    answer_ids = [item['corpus_id'] for item in sorted_answers]
+    context_score = [item['score'] for item in sorted_answers]
+    answers_scores = [qa_model(question, contexts[n]) for n in answer_ids[:n_answers]]
+
+    # Extract relevant information for answers and scores
+    answer_context = [contexts[n] for n in answer_ids]
+    answers = [a['answer'] for a in answers_scores]
+    scores = [s['score'] for s in answers_scores]
+
+    # Create a DataFrame for the results
+    df = pd.DataFrame(zip(answer_ids, answers, context_score, answer_context), columns=["ANSWER_IDX", "ANSWER", "CONTEXT_SCORE", "CONTEXT"])
+
+    return df
+
+# %% ../drive/MyDrive/Codici/Python/Gradio_App/SemanticSearch_QA-v1.ipynb 7
+answer_example = pd.DataFrame(contexts, columns=['Context'])
+a_text = gr.components.Dataframe(answer_example,col_count=(1,"fixed"))
+
+n_slider = gr.components.Slider(minimum=1, maximum = 10, label = "Select n answers (max= 10)",step = 1)
+
+intf = gr.Interface(fn=QA_similarity,
+                    inputs= ["text", a_text, n_slider],
+                    outputs= gr.components.Dataframe(),
+                    examples=[
+                        [question_1],
+                        [question_2],
+                        [question_3],
+                        [question_4],
+                        [question_5],
+                        [question_6],
+                        [question_7],
+                        [question_8],
+                        [question_9],
+                        [question_10],],
+                    debug=True,
+)
+
+intf.launch(inline=False,
+            # share=True
+            )

requirements.txt

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+sentence-transformers==2.2.2
+gradio==3.44.3
+gradio_client==0.5.0