Spaces:
Runtime error
Runtime error
update about tab
Browse files- Home.py +5 -3
- src/Speeches/querry.ipynb +174 -2
- src/vectordatabase.py +1 -1
Home.py
CHANGED
@@ -3,7 +3,7 @@ from src.chatbot import chatbot, keyword_search
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from gradio_calendar import Calendar
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from datetime import datetime
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-
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legislature_periods = [
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"All",
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"20. Legislaturperiode",
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@@ -28,6 +28,8 @@ legislature_periods = [
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"1. Legislaturperiode"
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]
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with gr.Blocks() as App:
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@@ -57,7 +59,7 @@ with gr.Blocks() as App:
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# Row orientation
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with gr.Row() as additional_input:
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n_slider = gr.Slider(label="Number of Results", minimum=1, maximum=100, step=1, value=10)
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party_dopdown = gr.Dropdown(value='All', choices=
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# ToDo: Add date or legislature filter as input
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#start_date = Calendar(value="1949-01-01", type="datetime", label="Select start date", info="Click the calendar icon to bring up the calendar.", interactive=True)
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#end_date = Calendar(value=datetime.today().strftime('%Y-%m-%d'), type="datetime", label="Select end date", info="Click the calendar icon to bring up the calendar.", interactive=True)
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@@ -109,7 +111,7 @@ with gr.Blocks() as App:
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)
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with gr.Tab("About"):
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gr.Markdown(
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The idea of this project is a combination of my curiosity in LLM application and my affection for speech data, that I developed during my bachelor thesis on measuring populism in text data.
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I would like to allow people to discover interesting discussions, opinions and positions that were communicated in the german parliament thoughout the years.
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**Development status:**
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from gradio_calendar import Calendar
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from datetime import datetime
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# Define important variables
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legislature_periods = [
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"All",
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"20. Legislaturperiode",
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"1. Legislaturperiode"
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]
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partys = ['All','CDU/CSU','SPD','AfD','Grüne','FDP','DIE LINKE.','GB/BHE','DRP', 'WAV', 'NR', 'BP', 'FU', 'SSW', 'KPD', 'DA', 'FVP','DP','Z', 'PDS','Fraktionslos', 'Gast','not found', 'Gast']
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+
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with gr.Blocks() as App:
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# Row orientation
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with gr.Row() as additional_input:
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n_slider = gr.Slider(label="Number of Results", minimum=1, maximum=100, step=1, value=10)
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party_dopdown = gr.Dropdown(value='All', choices=partys, label='Party')
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# ToDo: Add date or legislature filter as input
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#start_date = Calendar(value="1949-01-01", type="datetime", label="Select start date", info="Click the calendar icon to bring up the calendar.", interactive=True)
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#end_date = Calendar(value=datetime.today().strftime('%Y-%m-%d'), type="datetime", label="Select end date", info="Click the calendar icon to bring up the calendar.", interactive=True)
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)
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with gr.Tab("About"):
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gr.Markdown("""**Motivation:**
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The idea of this project is a combination of my curiosity in LLM application and my affection for speech data, that I developed during my bachelor thesis on measuring populism in text data.
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I would like to allow people to discover interesting discussions, opinions and positions that were communicated in the german parliament thoughout the years.
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**Development status:**
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src/Speeches/querry.ipynb
CHANGED
@@ -19,14 +19,14 @@
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\Tom\\AppData\\Local\\Temp\\
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" df = pd.read_sql_query(\"\"\"SELECT s.id,s.speech_content,s.date,f.abbreviation AS party\n"
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]
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}
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"### Data Cleaning"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"C:\\Users\\Tom\\AppData\\Local\\Temp\\ipykernel_22016\\2374447718.py:12: UserWarning: pandas only supports SQLAlchemy connectable (engine/connection) or database string URI or sqlite3 DBAPI2 connection. Other DBAPI2 objects are not tested. Please consider using SQLAlchemy.\n",
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" df = pd.read_sql_query(\"\"\"SELECT s.id,s.speech_content,s.date,f.abbreviation AS party\n"
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]
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}
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"### Data Cleaning"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'Z', 'FDP', 'GB/BHE', 'DIE LINKE.', 'DRP', 'WAV', 'Fraktionslos', 'NR', 'BP', 'not found', 'SPD', 'Gast', 'FU', 'SSW', 'KPD', 'DA', 'FVP', 'AfD', 'Grüne', 'DP', 'CDU/CSU', 'PDS'}\n"
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]
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}
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],
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"source": [
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"# Unique partys\n",
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"print(set(df['party'].to_list()))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>id</th>\n",
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" <th>speech_content</th>\n",
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" <th>date</th>\n",
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" <th>party</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>126</th>\n",
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" <td>121</td>\n",
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" <td>Meine Damen und Herren, die Zentrumsfraktion, ...</td>\n",
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" <td>1949-09-22</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>192</th>\n",
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" <td>181</td>\n",
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" <td>Meine Damen und Herren! Der Herr Bundeskanzler...</td>\n",
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" <td>1949-09-22</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>208</th>\n",
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" <td>196</td>\n",
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" <td>Die Zentrumsfraktion des Deutschen Bundestags ...</td>\n",
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" <td>1949-09-27</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>210</th>\n",
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" <td>198</td>\n",
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" <td>Den Antrag habe ich hier.\\n({0})\\n- Ich begrün...</td>\n",
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" <td>1949-09-27</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>211</th>\n",
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" <td>199</td>\n",
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" <td>Ich werde Ihnen, Herr Präsident, also den Antr...</td>\n",
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" <td>1949-09-27</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>...</th>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" <td>...</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16480</th>\n",
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" <td>16412</td>\n",
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" <td>Meine Damen und Herren! Das, was Herr Kollege ...</td>\n",
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" <td>1951-12-06</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16558</th>\n",
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" <td>16496</td>\n",
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" <td>Herr Präsident! Meine sehr verehrten Damen und...</td>\n",
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" <td>1951-12-12</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16592</th>\n",
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" <td>16526</td>\n",
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" <td>Herr Präsident! Meine Damen und Herren! Der He...</td>\n",
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" <td>1951-12-12</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16622</th>\n",
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" <td>16580</td>\n",
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" <td>Herr Präsident! Meine Herren und Damen! Entgeg...</td>\n",
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" <td>1951-12-12</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16699</th>\n",
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" <td>16634</td>\n",
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" <td>Herr Präsident! Meine Damen und Herren! Die Ze...</td>\n",
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" <td>1951-12-13</td>\n",
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" <td>Z</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>420 rows × 4 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" id speech_content date \\\n",
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"126 121 Meine Damen und Herren, die Zentrumsfraktion, ... 1949-09-22 \n",
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"192 181 Meine Damen und Herren! Der Herr Bundeskanzler... 1949-09-22 \n",
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"208 196 Die Zentrumsfraktion des Deutschen Bundestags ... 1949-09-27 \n",
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"210 198 Den Antrag habe ich hier.\\n({0})\\n- Ich begrün... 1949-09-27 \n",
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"211 199 Ich werde Ihnen, Herr Präsident, also den Antr... 1949-09-27 \n",
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"... ... ... ... \n",
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"16480 16412 Meine Damen und Herren! Das, was Herr Kollege ... 1951-12-06 \n",
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"16558 16496 Herr Präsident! Meine sehr verehrten Damen und... 1951-12-12 \n",
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"16592 16526 Herr Präsident! Meine Damen und Herren! Der He... 1951-12-12 \n",
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"16622 16580 Herr Präsident! Meine Herren und Damen! Entgeg... 1951-12-12 \n",
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"16699 16634 Herr Präsident! Meine Damen und Herren! Die Ze... 1951-12-13 \n",
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"\n",
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" party \n",
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"126 Z \n",
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"192 Z \n",
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"208 Z \n",
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"210 Z \n",
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"211 Z \n",
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"... ... \n",
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"16480 Z \n",
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"16558 Z \n",
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"16592 Z \n",
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"16622 Z \n",
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"16699 Z \n",
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"\n",
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"[420 rows x 4 columns]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"df[df['party'] == 'Z']\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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src/vectordatabase.py
CHANGED
@@ -18,7 +18,7 @@ import os
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# from dotenv import load_dotenv
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19 |
# load_dotenv()
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-
#
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embeddings = HuggingFaceEmbeddings(model_name="paraphrase-multilingual-MiniLM-L12-v2")
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db_all = FAISS.load_local(folder_path="./src/FAISS", index_name="speeches_1949_09_12",
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embeddings=embeddings, allow_dangerous_deserialization=True)
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# from dotenv import load_dotenv
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# load_dotenv()
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# Define important variables
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embeddings = HuggingFaceEmbeddings(model_name="paraphrase-multilingual-MiniLM-L12-v2")
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db_all = FAISS.load_local(folder_path="./src/FAISS", index_name="speeches_1949_09_12",
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embeddings=embeddings, allow_dangerous_deserialization=True)
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