Basic QnA using tabular data of VNR #15

gen-ai/tabular/google-tapas/vnr-data.csv

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+S. No.,JNTUH Faculty Registration Number,Name of the Faculty Member,Designation,Highest Qualification,Department
+1,59150406-115722,Challa Dhanunjaya Naidu,Principal & Professor,Ph. D. ECE,Principal
+2,66150402-143755,Amjad Shaik,Professor,Ph. D. Automobile,Automobile
+3,63150402-144531,Praveen Kumar Thanikonda,Assistant Professor,M. E. Automobile,Automobile
+4,90150407-143953,Gumma V L Prasad,Assistant Professor,M.Tech. Automobile,Automobile
+5,1180-150410-161243,Kodanda Ram Kuchimanchi,Associate Professor,M. E. Automobile,Automobile
+6,2015-150413-105826,Ramu Ratlavath,Assistant Professor,M.Tech. Automobile,Automobile
+7,0476-161026-142919,Mohamadaziz Athani,Assistant Professor,M.Tech. Automobile,Automobile
+8,7560-170520-172558,Manda Krishna,Assistant Professor,M. E. Automobile,Automobile
+9,6710-170522-121340,Jakkula Snothaswini,Assistant Professor,M.Tech. Automobile,Automobile
+10,1714-170523-151148,Balappa Hadagali,Assistant Professor,M.Tech. Automobile,Automobile
+11,6071-180104-113045,Shet Nagaraj,Assistant Professor,M.Tech. Automobile,Automobile
+12,6835-180208-222923,Rathinam Veerappan,Assistant Professor,Ph. D. Automobile,Automobile
+13,2324-181123-000547,Gouthami Koduri,Assistant Professor,M. E. Automobile,Automobile
+14,1015-191113-144449,Thirunavakarasu Sukumaran Krishnakumar,Assistant Professor,M. E. Automobile,Automobile
+15,64150404-125217,Hanumara Rajitha,Assistant Professor,M. Sc. Chemistry,Chemistry
+16,90150404-163902,Jyotsna Cherukuri,Associate Professor,Ph. D. Chemistry,Chemistry
+17,91150406-113838,Mamatha Nakka,Assistant Professor,Ph. D. Chemistry,Chemistry
+18,07150406-161954,Kondapavuluri Madhavi,Assistant Professor,Ph. D. Chemistry,Chemistry
+19,46150406-214230,Padmavathi Papolu,Assistant Professor,Ph. D. Chemistry,Chemistry
+20,3827-160307-131739,Kum Shuchitiwari,Assistant Professor,Ph. D. Chemistry,Chemistry
+21,6687-160316-165018,Regun Balavardhana Rao Adapa,Assistant Professor,Ph. D. Chemistry,Chemistry
+22,3492-161216-195533,Pratyusha Satavalli,Assistant Professor,M. Sc. Chemistry,Chemistry
+23,1983-161226-003818,Lakshmi Viveka Tella,Assistant Professor,Ph. D. Chemistry,Chemistry
+24,5304-150430-153137,Jyothi Sabbani,Assistant Professor,M. Sc. Chemistry,Chemistry
+25,6441-161216-172334,Sultana Nazma,Assistant Professor,M. Sc. Chemistry,Chemistry
+26,25150406-185744,Padmaja Kakumanu,Assistant Professor,Ph. D. Chemistry,Chemistry
+27,0745-150409-122315,Suresh Kommu,Assistant Professor,M. E. Civil Engineering,Civil Engineering
+28,7749-151219-181423,Kadali Srinivas,Associate Professor,Ph. D. Civil Engineering,Civil Engineering

gen-ai/tabular/google-tapas/vnr-staff-qna-system.py

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+import pandas as pd
+from transformers import TapasTokenizer, TapasForQuestionAnswering
+
+# Step 1: Load the model and tokenizer
+model_name = "google/tapas-base-finetuned-wtq"
+tokenizer = TapasTokenizer.from_pretrained(model_name)
+model = TapasForQuestionAnswering.from_pretrained(model_name)
+
+# Step 2: Read the table data from a CSV file and convert all cells to strings
+table = pd.read_csv('vnr-data.csv').astype(str)
+
+# Step 3: Define the questions
+queries = ["What is Designation of C D Naidu", "Which Department Gouthami Koduri belong to?"]
+
+# Step 4: Tokenize the input
+inputs = tokenizer(table=table, queries=queries, padding="max_length", return_tensors="pt")
+
+# Step 5: Get predictions
+outputs = model(**inputs)
+logits = outputs.logits
+
+# Step 6: Post-process the predictions
+predicted_answer_coordinates, predicted_aggregation_indices = tokenizer.convert_logits_to_predictions(
+    inputs,
+    outputs.logits.detach(),
+    outputs.logits_aggregation.detach()
+)
+
+# Extract and print the answers
+answers = []
+for coordinates in predicted_answer_coordinates:
+    if len(coordinates) == 1:
+        answer = table.iat[coordinates[0]]
+    else:
+        answer = " & ".join(table.iat[coord] for coord in coordinates)
+    answers.append(answer)
+
+for query, answer in zip(queries, answers):
+    print(f"Question: {query}")
+    print(f"Answer: {answer}")
+
+# Optional: Save results to a CSV file
+df = pd.DataFrame({"Question": queries, "Answer": answers})
+df.to_csv("qa_results.csv", index=False)