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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+models/nmodelmain/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,86 @@
+from spacy.lang.en import English
+import tensorflow as tf
+import streamlit as st
+
+st.title("Research Abstract Classifier")
+st.markdown("""
+        This app classifies study abstracts into different sections such as BACKGROUND, OBJECTIVE, METHODS, RESULTS, and CONCLUSIONS.
+        Enter your study abstract in the text area below.
+    """)
+
+abstext = st.text_area("Enter the study")
+st.link_button("Reserch Paper National Library of Medicine", "https://pubmed.ncbi.nlm.nih.gov/")
+def split_chars(text):
+        return " ".join(list(text))
+
+loaded_model = tf.keras.models.load_model(
+        r'models/nmodelmain')
+
+if abstext:
+    nlp = English()
+    with st.spinner("Vectorizing..."):
+        sentencizer = nlp.add_pipe("sentencizer")
+        doc = nlp(abstext)
+        abstract_lines = [str(sent) for sent in list(doc.sents)]
+
+        total_lines_in_sample = len(abstract_lines)
+
+        sample_lines = []
+        for i, line in enumerate(abstract_lines):
+            sample_dict = {}
+            sample_dict["text"] = str(line)
+            sample_dict["line_number"] = i
+            sample_dict["total_lines"] = total_lines_in_sample - 1
+            sample_lines.append(sample_dict)
+
+
+        test_abstract_line_numbers = [line["line_number"] for line in sample_lines]
+        test_abstract_line_numbers_one_hot = tf.one_hot(
+            test_abstract_line_numbers, depth=15)
+
+
+        test_abstract_total_lines = [line["total_lines"] for line in sample_lines]
+        test_abstract_total_lines_one_hot = tf.one_hot(
+            test_abstract_total_lines, depth=20)
+        
+        abstract_chars = [split_chars(sentence) for sentence in abstract_lines]
+
+    with st.spinner("predicting......"):
+
+        test_abstract_pred_probs = loaded_model.predict(x=(test_abstract_line_numbers_one_hot,
+                                                    test_abstract_total_lines_one_hot,
+                                                    tf.constant(abstract_lines),
+                                                    tf.constant(abstract_chars)))
+
+
+        test_abstract_preds = tf.argmax(test_abstract_pred_probs, axis=1)
+
+    with st.spinner("Catogerizing...."):
+        numlab = []
+
+        for i in (test_abstract_preds):
+            numlab.append(int(i))
+        classnames = ['BACKGROUND', 'CONCLUSIONS', 'METHODS', 'OBJECTIVE', 'RESULTS']
+
+
+        dictionary = {}
+        for i in range(len(numlab)):
+            class_name = classnames[numlab[i]]
+            abstract_line = abstract_lines[i]
+            if class_name in dictionary:
+                dictionary[class_name].append(abstract_line)
+            else:
+                dictionary[class_name] = [abstract_line]
+        ordered_dictionary = {}
+        ordered_classnames = ['BACKGROUND', 'OBJECTIVE',
+                            'METHODS', 'RESULTS', 'CONCLUSIONS']
+        for class_name in ordered_classnames:
+            if class_name in dictionary:
+                ordered_dictionary[class_name] = dictionary[class_name]
+        lis = []
+        for class_name, lines in ordered_dictionary.items():
+            lis.append(class_name)
+            st.subheader(class_name)
+            for line in lines:
+                lis.append(line)
+                st.write(line)

models/nmodelmain/fingerprint.pb

@@ -0,0 +1,3 @@
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+oid sha256:c3981309d6e8fc78fbe750dc0e2e1b2b97ec4c268415a7a1f8be06882ca983c3
+size 56

models/nmodelmain/keras_metadata.pb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1ace2286dc0634d509e8c8ac16f460e7ad7b1ecbccbaf2b0c3ce99f8ce6b5d10
+size 37866

models/nmodelmain/saved_model.pb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a706863cf27c58db7371b15a5b51debf120d782337d16ac366787ee85bd9468f
+size 13707313

models/nmodelmain/variables/variables.data-00000-of-00001

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:85dfd722a93fec214e451db69f602d81a78c90dd30fd84ed4dc0d5f8f470dc5d
+size 1028864714

requirements.txt

@@ -0,0 +1,95 @@
+absl-py==2.1.0
+altair==5.2.0
+annotated-types==0.6.0
+astunparse==1.6.3
+attrs==23.2.0
+blinker==1.7.0
+blis==0.7.11
+cachetools==5.3.2
+catalogue==2.0.10
+certifi==2023.11.17
+charset-normalizer==3.3.2
+click==8.1.7
+cloudpathlib==0.16.0
+colorama==0.4.6
+confection==0.1.4
+cymem==2.0.8
+flatbuffers==23.5.26
+gast==0.5.4
+gitdb==4.0.11
+GitPython==3.1.41
+google-auth==2.26.2
+google-auth-oauthlib==1.2.0
+google-pasta==0.2.0
+grpcio==1.60.0
+h5py==3.10.0
+idna==3.6
+importlib-metadata==7.0.1
+Jinja2==3.1.3
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+keras==2.15.0
+langcodes==3.3.0
+libclang==16.0.6
+Markdown==3.5.2
+markdown-it-py==3.0.0
+MarkupSafe==2.1.4
+mdurl==0.1.2
+ml-dtypes==0.2.0
+murmurhash==1.0.10
+numpy==1.26.3
+oauthlib==3.2.2
+opt-einsum==3.3.0
+packaging==23.2
+pandas==2.2.0
+pillow==10.2.0
+preshed==3.0.9
+protobuf==4.23.4
+pyarrow==15.0.0
+pyasn1==0.5.1
+pyasn1-modules==0.3.0
+pydantic==2.5.3
+pydantic_core==2.14.6
+pydeck==0.8.1b0
+Pygments==2.17.2
+python-dateutil==2.8.2
+pytz==2023.3.post1
+referencing==0.32.1
+requests==2.31.0
+requests-oauthlib==1.3.1
+rich==13.7.0
+rpds-py==0.17.1
+rsa==4.9
+six==1.16.0
+smart-open==6.4.0
+smmap==5.0.1
+spacy==3.7.2
+spacy-legacy==3.0.12
+spacy-loggers==1.0.5
+srsly==2.4.8
+streamlit==1.30.0
+tenacity==8.2.3
+tensorboard==2.15.1
+tensorboard-data-server==0.7.2
+tensorflow==2.15.0
+tensorflow-estimator==2.15.0
+tensorflow-intel==2.15.0
+tensorflow-io-gcs-filesystem==0.31.0
+termcolor==2.4.0
+thinc==8.2.2
+toml==0.10.2
+toolz==0.12.0
+tornado==6.4
+tqdm==4.66.1
+typer==0.9.0
+typing_extensions==4.9.0
+tzdata==2023.4
+tzlocal==5.2
+urllib3==2.1.0
+validators==0.22.0
+wasabi==1.1.2
+watchdog==3.0.0
+weasel==0.3.4
+Werkzeug==3.0.1
+wrapt==1.14.1
+zipp==3.17.0