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Update app.py
Browse files
app.py
CHANGED
@@ -3,6 +3,7 @@ from huggingface_hub import InferenceClient
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import sys
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import io
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import traceback
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# Initialize the AI model
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model_name = "Qwen/Qwen2.5-72B-Instruct"
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@@ -12,8 +13,14 @@ def llm_inference(user_sample):
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eos_token = "<|endoftext|>"
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output = client.chat.completions.create(
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messages=[
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{
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],
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stream=False,
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temperature=0.7,
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@@ -26,11 +33,6 @@ def llm_inference(user_sample):
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response += choice['message']['content']
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return response
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def chat(user_input, history):
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response = llm_inference(user_input)
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history.append((user_input, response))
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return history, history
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def execute_code(code):
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old_stdout = sys.stdout
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redirected_output = sys.stdout = io.StringIO()
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@@ -43,14 +45,43 @@ def execute_code(code):
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sys.stdout = old_stdout
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return output
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def
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with gr.Blocks() as demo:
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gr.Markdown("# π Python Helper Chatbot")
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@@ -66,16 +97,6 @@ with gr.Blocks() as demo:
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code_output = gr.Textbox(label="Output")
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run_button.click(execute_code, inputs=code_input, outputs=code_output)
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with gr.Tab("Math Solver"):
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gr.Markdown("### π Math Task Solver")
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math_input = gr.Textbox(placeholder="Enter your mathematical task here...", lines=2)
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solve_button = gr.Button("Solve Task")
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with gr.Row():
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generated_code_output = gr.Code(label="Generated Python Code", language="python")
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with gr.Row():
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execution_output = gr.Textbox(label="Execution Result", lines=10)
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solve_button.click(solve_math_task, inputs=math_input, outputs=[generated_code_output, execution_output])
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with gr.Tab("Logs"):
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gr.Markdown("### π Logs")
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log_output = gr.Textbox(label="Logs", lines=10, interactive=False)
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import sys
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import io
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import traceback
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import re # Import the regular expressions module
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# Initialize the AI model
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model_name = "Qwen/Qwen2.5-72B-Instruct"
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eos_token = "<|endoftext|>"
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output = client.chat.completions.create(
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messages=[
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{
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"role": "system",
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"content": "You are a Python language guide. Write code on the user topic. If the input is code, correct it for mistakes."
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},
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{
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"role": "user",
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"content": f"Write only python code without any explanation: {user_sample}"
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},
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],
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stream=False,
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temperature=0.7,
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response += choice['message']['content']
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return response
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def execute_code(code):
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old_stdout = sys.stdout
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redirected_output = sys.stdout = io.StringIO()
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sys.stdout = old_stdout
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return output
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def is_math_task(user_input):
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"""
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Simple heuristic to determine if the user input is a math task.
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This can be enhanced with more sophisticated methods or NLP techniques.
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"""
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math_keywords = ['calculate', 'compute', 'solve', 'integrate', 'differentiate', 'derivative', 'integral', 'factorial', 'sum', 'product']
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operators = ['+', '-', '*', '/', '^', '**', 'sqrt', 'sin', 'cos', 'tan', 'log', 'exp']
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user_input_lower = user_input.lower()
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return any(keyword in user_input_lower for keyword in math_keywords) or any(op in user_input for op in operators)
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def chat(user_input, history):
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"""
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Handles the chat interaction. If the user input is detected as a math task,
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it generates Python code to solve it, strips any code tags, executes the code,
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and returns the result.
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"""
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if is_math_task(user_input):
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# Generate Python code for the math task
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generated_code = llm_inference(f"Create a Python program to solve the following math problem:\n{user_input}")
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# Strip code tags using regex
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# This regex removes ```python and ``` or any other markdown code fences
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cleaned_code = re.sub(r"```(?:python)?\n?", "", generated_code).strip()
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cleaned_code = re.sub(r"```", "", cleaned_code).strip()
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# Execute the cleaned code
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execution_result = execute_code(cleaned_code)
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# Prepare the responses
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assistant_response = f"**Generated Python Code:**\n```python\n{cleaned_code}\n```\n\n**Execution Result:**\n```\n{execution_result}\n```"
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else:
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# For regular chat messages, use the AI's response
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assistant_response = llm_inference(user_input)
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# Append to chat history
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history.append((user_input, assistant_response))
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return history, history
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with gr.Blocks() as demo:
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gr.Markdown("# π Python Helper Chatbot")
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code_output = gr.Textbox(label="Output")
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run_button.click(execute_code, inputs=code_input, outputs=code_output)
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with gr.Tab("Logs"):
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gr.Markdown("### π Logs")
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log_output = gr.Textbox(label="Logs", lines=10, interactive=False)
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