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Update app.py
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app.py
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@@ -11,14 +11,14 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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from huggingface_hub import InferenceClient, cached_download
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# --- Configuration ---
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VERBOSE = True
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MAX_HISTORY = 5
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MAX_TOKENS = 2048
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TEMPERATURE = 0.7
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TOP_P = 0.8
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REPETITION_PENALTY = 1.5
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MODEL_NAME = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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API_KEY = "YOUR_API_KEY"
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# --- Logging Setup ---
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logging.basicConfig(
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@@ -138,32 +138,4 @@ def main():
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examples = [
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["What is the purpose of this AI agent?", "I am designed to assist with no-code development tasks."],
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["Can you help me generate a Python function to calculate the factorial of a number?", "Sure! Here is a Python function to calculate the factorial of a number:"],
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["Generate a simple HTML page with a heading and a paragraph.", "
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["Create a basic SQL query to select all data from a table named 'users'.", "```sql\nSELECT * FROM users;\n```"],
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["Design a user interface for a mobile app that allows users to track their daily expenses.", "Here's a basic UI design for a mobile expense tracker app:\n\n**Screen 1: Home**\n- Top: App Name and Balance Display\n- Middle: List of Recent Transactions (Date, Description, Amount)\n- Bottom: Buttons for Add Expense, Add Income, View Categories\n\n**Screen 2: Add Expense**\n- Input fields for Date, Category, Description, Amount\n- Buttons for Save, Cancel\n\n**Screen 3: Expense Categories**\n- List of expense categories (e.g., Food, Transportation, Entertainment)\n- Option to add/edit categories\n\n**Screen 4: Reports**\n- Charts and graphs to visualize spending by category, date range, etc.\n- Filters to customize the reports"],
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]
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def chat(purpose: str, message: str, agent_name: str, sys_prompt: str, temperature: float, max_new_tokens: int, top_p: float, repetition_penalty: float, history: List[Tuple[str, str]]) -> Tuple[List[Tuple[str, str]], List[Tuple[str, str]]]:
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"""Handles the chat interaction."""
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response = generate(message, history, agent_name, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty)
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history.append((message, response))
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return history, history
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submit_button.click(chat, inputs=[purpose, message, agent_name, sys_prompt, temperature, max_new_tokens, top_p, repetition_penalty, history], outputs=[chatbot, history])
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# Project Explorer Logic
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def explore_project(project_path: str) -> str:
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"""Explores the project directory and returns a file tree."""
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try:
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tree = subprocess.check_output(["tree", project_path]).decode("utf-8")
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return tree
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except Exception as e:
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return f"Error exploring project: {e}"
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explore_button.click(explore_project, inputs=[project_path], outputs=[project_output])
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demo.launch()
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if __name__ == "__main__":
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main()
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```
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from huggingface_hub import InferenceClient, cached_download
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# --- Configuration ---
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VERBOSE = True
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MAX_HISTORY = 5
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MAX_TOKENS = 2048
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TEMPERATURE = 0.7
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TOP_P = 0.8
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REPETITION_PENALTY = 1.5
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MODEL_NAME = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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API_KEY = "YOUR_API_KEY"
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# --- Logging Setup ---
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logging.basicConfig(
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examples = [
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["What is the purpose of this AI agent?", "I am designed to assist with no-code development tasks."],
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["Can you help me generate a Python function to calculate the factorial of a number?", "Sure! Here is a Python function to calculate the factorial of a number:"],
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["Generate a simple HTML page with a heading and a paragraph.", "
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