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Update app.py
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app.py
CHANGED
@@ -19,7 +19,6 @@ wahl_o_mat_data = load_json_data('data/wahl-o-mat.json')
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def predict(
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api_key,
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user_input,
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model1,
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model2,
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prompt_manipulation,
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@@ -31,7 +30,7 @@ def predict(
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):
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print("Ideology Test:", ideology_test)
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print(
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if prompt_manipulation == "Impersonation (direct steering)":
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prompt = f"""[INST] Du bist ein Politiker der Partei {direct_steering_option}. {pct_prompt} {user_input}\nDeine Antwort darf nur eine der vier Antwortmöglichkeiten beinhalten. [/INST]"""
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@@ -104,7 +103,8 @@ def main():
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# Initialize 'political_statement' with default 'Wahl-O-Mat' values
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political_statement_initial_choices = [f"{i+1}. {statement['text']}" for i, statement in enumerate(wahl_o_mat_data['statements'])]
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political_statement = gr.Dropdown(
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label="
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choices=political_statement_initial_choices, # Set default to 'Wahl-O-Mat' statements
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allow_custom_value = True
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)
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@@ -135,16 +135,8 @@ def main():
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# Link the dropdowns so that the option dropdown updates based on the selected prompt manipulation
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prompt_manipulation.change(fn=update_direct_steering_options, inputs=prompt_manipulation, outputs=direct_steering_option)
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with gr.Row():
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gr.Markdown("#### OR:")
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with gr.Row():
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user_input1 = gr.Textbox(label="Prompt", placeholder="Enter your own political statement here")
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with gr.Row():
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api_key_input = gr.Textbox(label="API Key", placeholder="Enter your API key here", show_label=True, type="password")
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user_input = gr.Textbox(label="Prompt", placeholder="Enter your message here")
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model_selector1 = gr.Dropdown(label="Model 1", choices=["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x22B-Instruct-v0.1"])
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model_selector2 = gr.Dropdown(label="Model 2", choices=["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x22B-Instruct-v0.1"])
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submit_btn = gr.Button("Submit")
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@@ -156,22 +148,17 @@ def main():
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with gr.Tab("Settings"):
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with gr.Column():
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api_key_input = gr.Textbox(label="API Key", type="password")
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temp_input = gr.Slider(minimum=0, maximum=1, step=0.01, label="Temperature", value=0.7)
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top_p_input = gr.Slider(minimum=0, maximum=1, step=0.01, label="Top P", value=1)
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# Link settings to the predict function
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submit_btn.click(
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fn=predict,
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inputs=[api_key_input,
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outputs=[output1, output2]
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)
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# fn=predict,
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# inputs=[api_key_input, user_input, model_selector1, model_selector2, prompt_manipulation, direct_steering_option, ideology_test, political_statement],
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# outputs=[output1, output2]
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# )
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demo.launch()
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if __name__ == "__main__":
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def predict(
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api_key,
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model1,
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model2,
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prompt_manipulation,
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):
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print("Ideology Test:", ideology_test)
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print(political_statement)
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if prompt_manipulation == "Impersonation (direct steering)":
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prompt = f"""[INST] Du bist ein Politiker der Partei {direct_steering_option}. {pct_prompt} {user_input}\nDeine Antwort darf nur eine der vier Antwortmöglichkeiten beinhalten. [/INST]"""
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# Initialize 'political_statement' with default 'Wahl-O-Mat' values
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political_statement_initial_choices = [f"{i+1}. {statement['text']}" for i, statement in enumerate(wahl_o_mat_data['statements'])]
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political_statement = gr.Dropdown(
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label="Select political statement or enter you own",
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value="1. Auf allen Autobahnen soll ein generelles Tempolimit gelten.", # default value
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choices=political_statement_initial_choices, # Set default to 'Wahl-O-Mat' statements
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allow_custom_value = True
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)
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# Link the dropdowns so that the option dropdown updates based on the selected prompt manipulation
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prompt_manipulation.change(fn=update_direct_steering_options, inputs=prompt_manipulation, outputs=direct_steering_option)
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with gr.Row():
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model_selector1 = gr.Dropdown(label="Model 1", choices=["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x22B-Instruct-v0.1"])
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model_selector2 = gr.Dropdown(label="Model 2", choices=["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x22B-Instruct-v0.1"])
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submit_btn = gr.Button("Submit")
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with gr.Tab("Settings"):
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with gr.Column():
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api_key_input = gr.Textbox(label="API Key", placeholder="Enter your API key here", show_label=True, type="password")
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temp_input = gr.Slider(minimum=0, maximum=1, step=0.01, label="Temperature", value=0.7)
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top_p_input = gr.Slider(minimum=0, maximum=1, step=0.01, label="Top P", value=1)
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# Link settings to the predict function
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submit_btn.click(
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fn=predict,
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inputs=[api_key_input, model_selector1, model_selector2, prompt_manipulation, direct_steering_option, ideology_test, political_statement, temp_input, top_p_input],
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outputs=[output1, output2]
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)
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demo.launch()
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if __name__ == "__main__":
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