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| import asyncio | |
| import gradio as gr | |
| from langchain_community.llms import HuggingFaceEndpoint | |
| from langchain_core.prompts import PromptTemplate | |
| from langchain.agents import create_react_agent, AgentExecutor | |
| from langchain_core.tools import BaseTool | |
| from typing import List | |
| import yaml | |
| import os | |
| import json | |
| import logging | |
| from functools import lru_cache | |
| import time | |
| import pygments | |
| from pygments.lexers import get_lexer_by_name | |
| from pygments.formatters import HtmlFormatter | |
| # Set up logging | |
| logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') | |
| logger = logging.getLogger(__name__) | |
| def load_config(): | |
| config_path = os.path.join(os.path.dirname(__file__), "config.yaml") | |
| try: | |
| with open(config_path, "r") as config_file: | |
| return yaml.safe_load(config_file) | |
| except FileNotFoundError: | |
| logger.warning("Config file not found. Using default configuration.") | |
| return { | |
| "model": "mistralai/Mixtral-8x7B-Instruct-v0.1", | |
| "hf_api_token": os.environ.get("HUGGINGFACEHUB_API_TOKEN", "your_default_token_here") | |
| } | |
| config = load_config() | |
| class AgentInitializationError(Exception): | |
| pass | |
| class CodeGenerationTool(BaseTool): | |
| name = "CodeGeneration" | |
| description = "Generates code based on a prompt" | |
| def _run(self, prompt: str) -> str: | |
| logger.info(f"Generating code for prompt: {prompt}") | |
| if "Flask app structure" in prompt: | |
| return self.generate_flask_app_structure() | |
| elif "binary search algorithm" in prompt: | |
| return self.generate_binary_search() | |
| elif "responsive navbar" in prompt: | |
| return self.generate_responsive_navbar() | |
| else: | |
| return f"Generated code placeholder for: {prompt}" | |
| async def _arun(self, prompt: str) -> str: | |
| return self._run(prompt) | |
| def generate_flask_app_structure(self): | |
| return """ | |
| # app.py | |
| from flask import Flask, render_template | |
| app = Flask(__name__) | |
| @app.route('/') | |
| def home(): | |
| return render_template('index.html') | |
| if __name__ == '__main__': | |
| app.run(debug=True) | |
| # templates/index.html | |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Flask App</title> | |
| </head> | |
| <body> | |
| <h1>Welcome to Flask!</h1> | |
| </body> | |
| </html> | |
| """ | |
| def generate_binary_search(self): | |
| return """ | |
| def binary_search(arr, target): | |
| left, right = 0, len(arr) - 1 | |
| while left <= right: | |
| mid = (left + right) // 2 | |
| if arr[mid] == target: | |
| return mid | |
| elif arr[mid] < target: | |
| left = mid + 1 | |
| else: | |
| right = mid - 1 | |
| return -1 # Target not found | |
| # Example usage | |
| sorted_array = [1, 3, 5, 7, 9, 11, 13, 15] | |
| target = 7 | |
| result = binary_search(sorted_array, target) | |
| print(f"Target {target} found at index: {result}") | |
| """ | |
| def generate_responsive_navbar(self): | |
| return """ | |
| <!-- HTML --> | |
| <nav class="navbar"> | |
| <div class="navbar-logo">Logo</div> | |
| <ul class="navbar-links"> | |
| <li><a href="#home">Home</a></li> | |
| <li><a href="#about">About</a></li> | |
| <li><a href="#services">Services</a></li> | |
| <li><a href="#contact">Contact</a></li> | |
| </ul> | |
| <div class="navbar-toggle"> | |
| <span class="bar"></span> | |
| <span class="bar"></span> | |
| <span class="bar"></span> | |
| </div> | |
| </nav> | |
| <!-- CSS --> | |
| <style> | |
| .navbar { | |
| display: flex; | |
| justify-content: space-between; | |
| align-items: center; | |
| padding: 1rem 2rem; | |
| background-color: #333; | |
| color: white; | |
| } | |
| .navbar-logo { | |
| font-size: 1.5rem; | |
| font-weight: bold; | |
| } | |
| .navbar-links { | |
| display: flex; | |
| list-style: none; | |
| } | |
| .navbar-links li { | |
| margin-left: 1rem; | |
| } | |
| .navbar-links a { | |
| color: white; | |
| text-decoration: none; | |
| } | |
| .navbar-toggle { | |
| display: none; | |
| flex-direction: column; | |
| cursor: pointer; | |
| } | |
| .bar { | |
| width: 25px; | |
| height: 3px; | |
| background-color: white; | |
| margin: 3px 0; | |
| } | |
| @media (max-width: 768px) { | |
| .navbar-links { | |
| display: none; | |
| flex-direction: column; | |
| width: 100%; | |
| position: absolute; | |
| top: 60px; | |
| left: 0; | |
| background-color: #333; | |
| } | |
| .navbar-links.active { | |
| display: flex; | |
| } | |
| .navbar-links li { | |
| margin: 1rem 0; | |
| } | |
| .navbar-toggle { | |
| display: flex; | |
| } | |
| } | |
| </style> | |
| <!-- JavaScript --> | |
| <script> | |
| document.querySelector('.navbar-toggle').addEventListener('click', function() { | |
| document.querySelector('.navbar-links').classList.toggle('active'); | |
| }); | |
| </script> | |
| """ | |
| class Agent: | |
| def __init__(self, name: str, description: str, tools: List[BaseTool]): | |
| self.name = name | |
| self.description = description | |
| try: | |
| self.llm = HuggingFaceEndpoint( | |
| repo_id=config["model"], | |
| task="text-generation", | |
| model_kwargs={"temperature": 0.7, "max_length": 1024}, | |
| huggingfacehub_api_token=config["hf_api_token"] | |
| ) | |
| self.prompt_template = PromptTemplate( | |
| template="You are {name}, {description}. Respond to the following: {input}", | |
| input_variables=["name", "description", "input"] | |
| ) | |
| self.agent = create_react_agent(self.llm, tools, self.prompt_template) | |
| self.agent_executor = AgentExecutor(agent=self.agent, tools=tools, verbose=True) | |
| except Exception as e: | |
| logger.error(f"Failed to initialize agent: {e}") | |
| raise AgentInitializationError(f"Failed to initialize agent: {e}") | |
| async def run(self, input_text: str) -> str: | |
| try: | |
| result = await self.agent_executor.arun(input_text) | |
| return result | |
| except Exception as e: | |
| logger.error(f"Error in agent execution: {e}") | |
| return f"Error: {str(e)}" | |
| class CodeFusion: | |
| def __init__(self): | |
| code_gen_tool = CodeGenerationTool() | |
| self.agents = [ | |
| Agent("CodeFusion_Structure", "App Structure Designer", [code_gen_tool]), | |
| Agent("CodeFusion_Logic", "Logic Implementation Expert", [code_gen_tool]), | |
| Agent("CodeFusion_UI", "User Interface Designer", [code_gen_tool]) | |
| ] | |
| async def run(self, input_text: str) -> str: | |
| results = [] | |
| for agent in self.agents: | |
| result = await agent.run(input_text) | |
| results.append(f"{agent.name}: {result}") | |
| return "\n\n".join(results) | |
| code_fusion = CodeFusion() | |
| def highlight_code(code: str, language: str) -> str: | |
| lexer = get_lexer_by_name(language, stripall=True) | |
| formatter = HtmlFormatter(style="monokai") | |
| return pygments.highlight(code, lexer, formatter) | |
| def save_code_to_file(code: str, filename: str) -> str: | |
| try: | |
| with open(filename, 'w') as f: | |
| f.write(code) | |
| return f"Code saved to {filename}" | |
| except Exception as e: | |
| logger.error(f"Error saving code to file: {e}") | |
| return f"Error saving code: {str(e)}" | |
| async def chat(message, history): | |
| start_time = time.time() | |
| response = await code_fusion.run(message) | |
| end_time = time.time() | |
| # Highlight code in the response | |
| highlighted_response = response | |
| for lang in ['python', 'html', 'css', 'javascript']: | |
| if f"```{lang}" in response: | |
| code = response.split(f"```{lang}")[1].split("```")[0] | |
| highlighted_code = highlight_code(code, lang) | |
| highlighted_response = highlighted_response.replace(f"```{lang}{code}```", highlighted_code) | |
| # Save code to file if requested | |
| if "save code" in message.lower(): | |
| filename = f"generated_code_{int(time.time())}.py" | |
| save_result = save_code_to_file(response, filename) | |
| highlighted_response += f"\n\n{save_result}" | |
| execution_time = end_time - start_time | |
| highlighted_response += f"\n\nExecution time: {execution_time:.2f} seconds" | |
| return highlighted_response | |
| async def main(): | |
| iface = gr.ChatInterface( | |
| fn=chat, | |
| title="CodeFusion AI", | |
| description="Your AI-powered coding assistant", | |
| examples=[ | |
| "Create a basic Flask app structure", | |
| "Implement a binary search algorithm in Python", | |
| "Design a responsive navbar using HTML and CSS", | |
| "Generate a simple REST API using Flask and save the code" | |
| ], | |
| retry_btn=None, | |
| undo_btn="Delete Previous", | |
| clear_btn="Clear", | |
| ) | |
| await iface.launch() | |
| if __name__ == "__main__": | |
| asyncio.run(main()) |