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| from sentence_transformers import SentenceTransformer, CrossEncoder, util | |
| import torch | |
| import pickle | |
| import pandas as pd | |
| import gradio as gr | |
| # bi_encoder = SentenceTransformer("microsoft/Multilingual-MiniLM-L12-H384") | |
| cross_encoder = CrossEncoder("cross-encoder/mmarco-mMiniLMv2-L12-H384-v1") | |
| # Corpus from quran | |
| my_file = open("quran-simple-clean.txt", "r",encoding="utf-8") | |
| data = my_file.read() | |
| quran = data.split("\n") | |
| my_file = open("mokhtasar-simple-clean.txt", "r",encoding="utf-8") | |
| data = my_file.read() | |
| corpus = data.split("\n") | |
| del data | |
| embedder = SentenceTransformer('symanto/sn-xlm-roberta-base-snli-mnli-anli-xnli') | |
| corpus_embeddings = embedder.encode(corpus, convert_to_tensor=True) | |
| def search(query,top_k=25): | |
| print("New query:") | |
| print(query) | |
| ans=[] | |
| ##### Sematic Search ##### | |
| # Encode the query using the bi-encoder and find potentially relevant passages | |
| question_embedding = embedder.encode(query, convert_to_tensor=True) | |
| hits = util.semantic_search(question_embedding, corpus_embeddings, top_k=top_k) | |
| hits = hits[0] # Get the hits for the first query | |
| ##### Re-Ranking ##### | |
| # Now, score all retrieved passages with the cross_encoder | |
| cross_inp = [[query, corpus[hit['corpus_id']]] for hit in hits] | |
| cross_scores = cross_encoder.predict(cross_inp) | |
| # Sort results by the cross-encoder scores | |
| for idx in range(len(cross_scores)): | |
| hits[idx]['cross-score'] = cross_scores[idx] | |
| hits = sorted(hits, key=lambda x: x['cross-score'], reverse=True) | |
| for idx, hit in enumerate(hits[0:5]): | |
| if hit["cross-score"] > -3: | |
| ans.append("{"+quran[hit['corpus_id']]+"}"+"\n"+corpus[hit['corpus_id']]) | |
| if len(ans) == 0: | |
| ans.append("لا يوجد نتائج الرجاء تقريب كلمات البحث") | |
| return "\n\n".join(ans) | |
| exp=[""] | |
| desc="هذا البحث يعتمد على المختصر في تفسير القرآن في البحث." | |
| inp=gr.inputs.Textbox(lines=1, placeholder=None, default="", label="أدخل كلمات البحث هنا") | |
| out=gr.outputs.Textbox(type="auto",label="نتائج البحث") | |
| iface = gr.Interface(fn=search, inputs=inp, outputs=out,examples=exp,article=desc,title="البحث بالمعنى في القرآن الكريم - باستخدام المختصر في التفسير") | |
| iface.launch() |