feat(audioanalyser): ✨ added summarization capabilities and WIP UI

Makefile

@@ -1,6 +1,6 @@
 # Basic Makefile for AzureSpeechToText Application
 
-# Copyright (C) 2023 Sebastien Rousseau.
+# Copyright (C) 2023-2024 Sebastien Rousseau.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

README.md

@@ -149,6 +149,7 @@ The minimum supported Python version is 3.6.
 
 - Azure Cognitive Services for speech and text processing.
 - CherryPy for the web server.
+- Open AI Services for summarization.
 - Python's standard libraries including asyncio, sqlite3, and threading.
 
 ![divider][divider]

analysis_status.txt

@@ -0,0 +1 @@
+Completed

audioanalyser/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (C) 2023 Sebastien Rousseau.
+# Copyright (C) 2023-2024 Sebastien Rousseau.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -14,4 +14,4 @@
 # limitations under the License.
 
 """The Python Audio Analyser module."""
-__version__ = "0.0.1"
+__version__ = "0.0.2"

audioanalyser/__main__.py

@@ -1,4 +1,4 @@
-# Copyright (C) 2023 Sebastien Rousseau.
+# Copyright (C) 2023-2024 Sebastien Rousseau.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -27,6 +27,7 @@
 from audioanalyser.modules.azure_speech_to_text import azure_speech_to_text
 from audioanalyser.modules.azure_text_analysis import azure_text_analysis
 from audioanalyser.modules.audio_analyser_server import audio_analyser_server
+from audioanalyser.modules.azure_recommendation import azure_recommendation
 
 
 def main():
@@ -60,6 +61,14 @@ def main():
 points.
         '''
     )
+    parser.add_argument(
+        '-rec',
+        '--recommendation',
+        action='store_true',
+        help='''
+This command generates recommendations based on the specified transcript.
+        '''
+    )
     parser.add_argument(
         '-s',
         '--server',
@@ -77,6 +86,8 @@ def main():
         azure_speech_to_text()
     elif args.text_analysis:
         azure_text_analysis()
+    elif args.recommendation:
+        azure_recommendation()
     elif args.server:
         audio_analyser_server()
     else:

audioanalyser/modules/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (C) 2023 Sebastien Rousseau.
+# Copyright (C) 2023-2024 Sebastien Rousseau.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

audioanalyser/modules/audio_analyser_server.bak

@@ -0,0 +1,149 @@
+import cherrypy
+import glob
+import os
+import io
+import sys
+import threading
+import asyncio
+
+# Import your custom functions
+from audioanalyser.modules.azure_speech_to_text import azure_speech_to_text
+from audioanalyser.modules.azure_text_analysis import azure_text_analysis
+
+
+class SpeechTextAnalysisServer:
+    @cherrypy.expose
+    def index(self):
+        return open('docs/index.html')
+
+    @cherrypy.expose
+    @cherrypy.tools.json_out()
+    def process_all_speech_to_text(self):
+        try:
+            # Redirect stdout to capture logs
+            old_stdout = sys.stdout
+            sys.stdout = log_capture_string = io.StringIO()
+
+            # Run the speech-to-text process
+            azure_speech_to_text()
+
+            # Reset stdout and get log output
+            sys.stdout = old_stdout
+            log_output = log_capture_string.getvalue()
+
+            return {"result": "Processing completed", "logs": log_output}
+        except Exception as e:
+            cherrypy.log(f"Error during speech-to-text processing: {str(e)}")
+            cherrypy.response.status = 500
+            return {
+                "error": "An error occurred during speech-to-text processing"
+            }
+
+    @cherrypy.expose
+    @cherrypy.tools.json_out()
+    def process_text_analysis(self):
+        try:
+            # Run the text analysis process in a separate thread
+            thread = threading.Thread(target=self.run_analysis_thread)
+            thread.start()
+            return {"result": "Text analysis process started"}
+        except Exception as e:
+            cherrypy.log(f"Error during text analysis: {str(e)}")
+            cherrypy.response.status = 500
+            return {"error": "An error occurred during text analysis"}
+
+    def run_analysis_thread(self):
+        temporary_folder = './'
+        status_file_path = os.path.join(
+            temporary_folder,
+            'analysis_status.txt'
+        )
+        try:
+            asyncio.run(azure_text_analysis())
+            with open(status_file_path, 'w') as file:
+                file.write('Completed')
+        except Exception as e:
+            with open(status_file_path, 'w') as file:
+                file.write(f'Error: {str(e)}')
+
+    @cherrypy.expose
+    @cherrypy.tools.json_out()
+    def get_analysis_status(self):
+        temporary_folder = './'
+        status_file_path = os.path.join(
+            temporary_folder,
+            'analysis_status.txt'
+        )
+        if os.path.exists(status_file_path):
+            with open(status_file_path, 'r') as file:
+                status = file.read()
+            return {"status": status}
+        else:
+            return {"status": "Processing"}
+
+    @cherrypy.expose
+    @cherrypy.tools.json_out()
+    def get_transcripts_list(self):
+        outputs_folder = './resources/transcripts/'
+        try:
+            # Find all transcript files in the Outputs folder
+            list_of_files = glob.glob(os.path.join(outputs_folder, '*.txt'))
+            transcripts = []
+            for file_path in list_of_files:
+                with open(file_path, 'r') as file:
+                    content = file.read()
+                    transcripts.append(
+                        {
+                            "filename": os.path.basename(file_path),
+                            "content": content
+                        }
+                    )
+            return transcripts
+        except IOError:
+            cherrypy.response.status = 500
+            return {"error": "Error reading transcript files."}
+
+    @cherrypy.expose
+    @cherrypy.tools.json_out()
+    def get_reports_list(self):
+        outputs_folder = './resources/reports/'
+        try:
+            # Find all report files in the Outputs folder
+            list_of_files = glob.glob(os.path.join(outputs_folder, '*.txt'))
+            reports = []
+            for file_path in list_of_files:
+                with open(file_path, 'r') as file:
+                    content = file.read()
+                    reports.append(
+                        {
+                            "filename": os.path.basename(file_path),
+                            "content": content
+                        }
+                    )
+            return reports
+        except IOError:
+            cherrypy.response.status = 500
+            return {"error": "Error reading report files."}
+
+
+def audio_analyser_server():
+    current_dir = os.path.dirname(os.path.abspath(__file__))
+    print('Current directory: ' + current_dir)
+    project_root = os.path.abspath(os.path.join(current_dir, '../..'))
+    print('Project root: ' + project_root)
+    docs_dir = os.path.join(project_root, 'docs')
+    print('Docs directory: ' + docs_dir)
+
+    config = {
+        '/': {
+            'tools.staticdir.on': True,
+            'tools.staticdir.dir': docs_dir,  # Set current_dir to docs_dir
+            'tools.staticdir.index': 'index.html',
+        },
+    }
+    cherrypy.config.update({'server.socket_port': 8080})
+    cherrypy.quickstart(SpeechTextAnalysisServer(), '/', config)
+
+
+if __name__ == '__main__':
+    audio_analyser_server()

audioanalyser/modules/audio_analyser_server.py

@@ -9,12 +9,13 @@
 # Import your custom functions
 from audioanalyser.modules.azure_speech_to_text import azure_speech_to_text
 from audioanalyser.modules.azure_text_analysis import azure_text_analysis
+from audioanalyser.modules.azure_recommendation import azure_recommendation
 
 
 class SpeechTextAnalysisServer:
     @cherrypy.expose
     def index(self):
-        return open('index.html')
+        return open('dashboard/index.html')
 
     @cherrypy.expose
     @cherrypy.tools.json_out()
@@ -125,15 +126,75 @@ def get_reports_list(self):
             cherrypy.response.status = 500
             return {"error": "Error reading report files."}
 
+    @cherrypy.expose
+    @cherrypy.tools.json_out()
+    def get_summaries_list(self):
+        outputs_folder = './resources/recommendations/'
+        try:
+            # Find all report files in the Outputs folder
+            list_of_files = glob.glob(os.path.join(outputs_folder, '*.txt'))
+            reports = []
+            for file_path in list_of_files:
+                with open(file_path, 'r') as file:
+                    content = file.read()
+                    reports.append(
+                        {
+                            "filename": os.path.basename(file_path),
+                            "content": content
+                        }
+                    )
+            return reports
+        except IOError:
+            cherrypy.response.status = 500
+            return {"error": "Error reading report files."}
+
+    @cherrypy.expose
+    @cherrypy.tools.json_out()
+    def generate_recommendations(self):
+
+        try:
+            # Run the executive summary generation process in a separate thread
+            thread = threading.Thread(target=self.run_recommendations_thread)
+            thread.start()
+            return {"result": "Process started"}
+        except Exception as e:
+            cherrypy.log(
+                f"Error during executive summary generation: {str(e)}"
+                )
+            cherrypy.response.status = 500
+            return {"error": "An error occurred during summary generation"}
+
+    def run_recommendations_thread(self):
+        temporary_folder = './'
+        status_file_path = os.path.join(
+            temporary_folder,
+            'recommendations_status.txt'
+        )
+        try:
+            asyncio.run(azure_recommendation())
+            with open(status_file_path, 'w') as file:
+                file.write('Completed')
+        except Exception as e:
+            with open(status_file_path, 'w') as file:
+                file.write(f'Error: {str(e)}')
+
 
 def audio_analyser_server():
     current_dir = os.path.dirname(os.path.abspath(__file__))
+    print('Current directory: ' + current_dir)
+    project_root = os.path.abspath(os.path.join(current_dir, '../..'))
+    print('Project root: ' + project_root)
+    dashboard_dir = os.path.join(project_root, 'dashboard')
+    print('Docs directory: ' + dashboard_dir)
+
     config = {
         '/': {
             'tools.staticdir.on': True,
-            'tools.staticdir.dir': current_dir
-        }
+            'tools.staticdir.dir': dashboard_dir,
+            'tools.staticdir.index': 'index.html',
+        },
     }
+    cherrypy.config.update({'server.socket_port': 8080})
     cherrypy.quickstart(SpeechTextAnalysisServer(), '/', config)