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Running
abrakjamson
commited on
Commit
•
f631e46
1
Parent(s):
1eb09b2
debugging
Browse files
app.py
CHANGED
@@ -6,13 +6,14 @@ import gradio as gr
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from huggingface_hub import login
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# Initialize model and tokenizer
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mistral_path = "mistralai/Mistral-7B-Instruct-v0.3"
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access_token = os.getenv("mistralaccesstoken")
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login(access_token)
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tokenizer = AutoTokenizer.from_pretrained(mistral_path)
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#tokenizer = AutoTokenizer.from_pretrained("E:/language_models/models/mistral")
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tokenizer.pad_token_id = 0
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model = AutoModelForCausalLM.from_pretrained(
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@@ -48,6 +49,7 @@ def toggle_slider(checked):
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# Function to generate the model's response
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def generate_response(system_prompt, user_message, *args, history=None):
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# args contains alternating checkbox and slider values
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num_controls = len(control_vector_files)
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checkboxes = args[0::2] # Extract every first item in each pair
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sliders = args[1::2] # Extract every second item in each pair
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@@ -55,14 +57,17 @@ def generate_response(system_prompt, user_message, *args, history=None):
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# Reset any previous control vectors
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model.reset()
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# Apply selected control vectors with their corresponding weights
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for i in range(num_controls):
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if checkboxes[i]:
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cv_file = control_vector_files[i]
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weight = sliders[i]
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try:
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control_vector = ControlVector.import_gguf(cv_file)
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model.set_control(control_vector, weight)
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except Exception as e:
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print(f"Failed to set control vector {cv_file}: {e}")
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@@ -101,12 +106,7 @@ with gr.Blocks() as demo:
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placeholder="Enter system-level instructions here..."
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)
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user_input = gr.Textbox(
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label="User Message",
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lines=2,
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placeholder="Type your message here..."
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)
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gr.Markdown("### 📊 Control Vectors")
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@@ -145,6 +145,13 @@ with gr.Blocks() as demo:
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with gr.Column(scale=2):
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# Chatbot to display conversation
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chatbot = gr.Chatbot(label="🗨️ Conversation")
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# State to keep track of conversation history
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state = gr.State([])
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@@ -164,4 +171,7 @@ with gr.Blocks() as demo:
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# Launch the Gradio app
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if __name__ == "__main__":
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demo.launch()
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from huggingface_hub import login
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# Initialize model and tokenizer
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mistral_path = "mistralai/Mistral-7B-Instruct-v0.3"
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# mistral_path = "E:/language_models/models/mistral"
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access_token = os.getenv("mistralaccesstoken")
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login(access_token)
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#tokenizer = AutoTokenizer.from_pretrained(mistral_path)
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tokenizer = AutoTokenizer.from_pretrained(mistral_path)
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tokenizer.pad_token_id = 0
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model = AutoModelForCausalLM.from_pretrained(
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# Function to generate the model's response
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def generate_response(system_prompt, user_message, *args, history=None):
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# args contains alternating checkbox and slider values
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print("generating response for user query {user_message}")
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num_controls = len(control_vector_files)
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checkboxes = args[0::2] # Extract every first item in each pair
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sliders = args[1::2] # Extract every second item in each pair
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# Reset any previous control vectors
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model.reset()
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print("applying weights")
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# Apply selected control vectors with their corresponding weights
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for i in range(num_controls):
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if checkboxes[i]:
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print(f"checkbox: {i} True for {cv_file}, weight: {weight}")
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cv_file = control_vector_files[i]
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weight = sliders[i]
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try:
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control_vector = ControlVector.import_gguf(cv_file)
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model.set_control(control_vector, weight)
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print("control vector set for {cv_file}")
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except Exception as e:
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print(f"Failed to set control vector {cv_file}: {e}")
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placeholder="Enter system-level instructions here..."
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)
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gr.Markdown("### 📊 Control Vectors")
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with gr.Column(scale=2):
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# Chatbot to display conversation
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chatbot = gr.Chatbot(label="🗨️ Conversation")
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# User Message Input
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user_input = gr.Textbox(
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label="User Message",
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lines=2,
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placeholder="Type your message here..."
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)
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# State to keep track of conversation history
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state = gr.State([])
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# Launch the Gradio app
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if __name__ == "__main__":
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demo.launch()
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# control_checks = []
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# control_checks.append()
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# generate_response("helpful assistant", "help me come up with a lie to my boss about why I'm late", ((True), (-1.0)), None)
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