Update app.py

app.py

@@ -1,51 +1,51 @@
-from flask import Flask, render_template, request
-from knowledgeassistant.components.summarization import DataSummarization
-from knowledgeassistant.components.keywordextraction import KeywordExtraction
-from knowledgeassistant.components.RAG import RAG
-from knowledgeassistant.entity.config_entity import DataSummarizationConfig, PipelineConfig, DataInputConfig, KeywordExtractionConfig, RAGConfig
-from knowledgeassistant.utils.main_utils.utils import write_txt_file, read_txt_file
-
-app = Flask(__name__)
-
-@app.route('/', methods=['GET', 'POST'])
-def home():
-    if request.method == 'POST':
-        pipeline_config = PipelineConfig()
-        data_input_config = DataInputConfig(pipeline_config)
-
-        user_text = request.form['user_text']
-        user_option = request.form['tasks']
-        result_text = ""
-
-        if user_option == "Q&A":
-            user_question = request.form['user_question']
-        else:
-            user_number = int(request.form['user_number'])
-
-        input_text_path = data_input_config.input_text_file_path
-        write_txt_file(input_text_path, user_text, replace=True)
-
-        if user_option == "summarization":
-            data_summarization_config = DataSummarizationConfig(pipeline_config)
-            summarizer = DataSummarization(data_summarization_config)
-            file_path = data_summarization_config.summarized_text_file_path
-            summarizer.initiate_data_summarization(input_text_path=input_text_path, min_length=int(user_number))
-        elif user_option == "keywords":
-            keyword_extraction_config = KeywordExtractionConfig(pipeline_config)
-            extractor = KeywordExtraction(keyword_extraction_config)
-            file_path = keyword_extraction_config.extracted_keywords_file_path
-            extractor.initiate_keyword_extraction(input_text_path=input_text_path, keywords_count=int(user_number))
-        elif user_option == "Q&A":
-            rag_config = RAGConfig(pipeline_config)
-            rag = RAG(rag_config)
-            file_path = rag_config.rag_generated_text_path
-            rag.initiate_rag(input_text_path=input_text_path, query=user_question)
-
-        result_text = read_txt_file(file_path=file_path)
-
-        return render_template("index.html", task=user_option, text=result_text, user_text=user_text)
-
-    return render_template("index.html", task=None, text=None, user_text=None)
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=8080)
+from flask import Flask, render_template, request
+from knowledgeassistant.components.summarization import DataSummarization
+from knowledgeassistant.components.keywordextraction import KeywordExtraction
+from knowledgeassistant.components.RAG import RAG
+from knowledgeassistant.entity.config_entity import DataSummarizationConfig, PipelineConfig, DataInputConfig, KeywordExtractionConfig, RAGConfig
+from knowledgeassistant.utils.main_utils.utils import write_txt_file, read_txt_file
+
+app = Flask(__name__)
+
+@app.route('/', methods=['GET', 'POST'])
+def home():
+    if request.method == 'POST':
+        pipeline_config = PipelineConfig()
+        data_input_config = DataInputConfig(pipeline_config)
+
+        user_text = request.form['user_text']
+        user_option = request.form['tasks']
+        result_text = ""
+
+        if user_option == "Q&A":
+            user_question = request.form['user_question']
+        else:
+            user_number = int(request.form['user_number'])
+
+        input_text_path = data_input_config.input_text_file_path
+        write_txt_file(input_text_path, user_text, replace=True)
+
+        if user_option == "summarization":
+            data_summarization_config = DataSummarizationConfig(pipeline_config)
+            summarizer = DataSummarization(data_summarization_config)
+            file_path = data_summarization_config.summarized_text_file_path
+            summarizer.initiate_data_summarization(input_text_path=input_text_path, min_length=int(user_number))
+        elif user_option == "keywords":
+            keyword_extraction_config = KeywordExtractionConfig(pipeline_config)
+            extractor = KeywordExtraction(keyword_extraction_config)
+            file_path = keyword_extraction_config.extracted_keywords_file_path
+            extractor.initiate_keyword_extraction(input_text_path=input_text_path, keywords_count=int(user_number))
+        elif user_option == "Q&A":
+            rag_config = RAGConfig(pipeline_config)
+            rag = RAG(rag_config)
+            file_path = rag_config.rag_generated_text_path
+            rag.initiate_rag(input_text_path=input_text_path, query=user_question)
+
+        result_text = read_txt_file(file_path=file_path)
+
+        return render_template("index.html", task=user_option, text=result_text, user_text=user_text)
+
+    return render_template("index.html", task=None, text=None, user_text=None)
+
+if __name__ == '__main__':
+    app.run(debug=True, host='0.0.0.0', port=7860)