Spaces:
Sleeping
Sleeping
File size: 9,070 Bytes
e96849b 74935d1 25bbda2 74935d1 25bbda2 e96849b 2eacfd4 25bbda2 e96849b d8ebd13 e96849b d8ebd13 e96849b d8ebd13 e96849b d8ebd13 e96849b d8ebd13 e96849b d8ebd13 e96849b 25bbda2 e96849b 25bbda2 e96849b 25bbda2 d8ebd13 e96849b 25bbda2 e96849b 25bbda2 e96849b 25bbda2 e96849b 25bbda2 52165bc 25bbda2 52165bc 25bbda2 52165bc 25bbda2 d8ebd13 25bbda2 d8ebd13 25bbda2 d8ebd13 25bbda2 d8ebd13 25bbda2 d8ebd13 25bbda2 d8ebd13 25bbda2 d8ebd13 25bbda2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 |
import os
import json
import logging
from typing import List, Dict, Optional, Any
import re
from abc import ABC, abstractmethod
from huggingface_hub import HfApi, InferenceClient
from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
from dataclasses import dataclass
@dataclass
class ProjectConfig:
name: str
description: str
technologies: List[str]
structure: Dict[str, List[str]]
class WebDevelopmentTool(ABC):
def __init__(self, name: str, description: str):
self.name = name
self.description = description
@abstractmethod
def generate_code(self, *args, **kwargs):
pass
class HTMLGenerator(WebDevelopmentTool):
def __init__(self):
super().__init__("HTML Generator", "Generates HTML code for web pages")
def generate_code(self, structure: Dict[str, Any]) -> str:
html = "<html><body>"
for tag, content in structure.items():
html += f"<{tag}>{content}</{tag}>"
html += "</body></html>"
return html
class CSSGenerator(WebDevelopmentTool):
def __init__(self):
super().__init__("CSS Generator", "Generates CSS code for styling web pages")
def generate_code(self, styles: Dict[str, Dict[str, str]]) -> str:
css = ""
for selector, properties in styles.items():
css += f"{selector} {{\n"
for prop, value in properties.items():
css += f" {prop}: {value};\n"
css += "}\n"
return css
class JavaScriptGenerator(WebDevelopmentTool):
def __init__(self):
super().__init__("JavaScript Generator", "Generates JavaScript code for web functionality")
def generate_code(self, functions: List[Dict[str, Any]]) -> str:
js = ""
for func in functions:
js += f"function {func['name']}({', '.join(func['params'])}) {{\n"
js += f" {func['body']}\n"
js += "}\n\n"
return js
class ProjectConfig:
def __init__(self, name: str, description: str, technologies: List[str], structure: Dict[str, List[str]]):
self.name = name
self.description = description
self.technologies = technologies
self.structure = structure
class HTMLGenerator:
def generate(self, content: str) -> str:
return f"<html><body>{content}</body></html>"
class CSSGenerator:
def generate(self, styles: Dict[str, str]) -> str:
return "\n".join([f"{selector} {{ {'; '.join([f'{prop}: {value}' for prop, value in properties.items()])} }}" for selector, properties in styles.items()])
class JavaScriptGenerator:
def generate(self, functionality: str) -> str:
return f"function main() {{ {functionality} }}"
class EnhancedAIAgent:
def __init__(self, name: str, description: str, skills: List[str], model_name: str):
self.name = name
self.description = description
self.skills = skills
self.model_name = model_name
self.html_gen_tool = HTMLGenerator()
self.css_gen_tool = CSSGenerator()
self.js_gen_tool = JavaScriptGenerator()
self.hf_api = HfApi()
self.inference_client = InferenceClient(model=model_name, token=os.environ.get("HF_API_TOKEN"))
self.tokenizer = AutoTokenizer.from_pretrained(model_name, clean_up_tokenization_spaces=True)
self.model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
self.text_generation = pipeline("text-generation", model=self.model, tokenizer=self.tokenizer, clean_up_tokenization_spaces=True)
self.logger = logging.getLogger(__name__)
self.logger.setLevel(logging.INFO)
handler = logging.StreamHandler()
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
self.logger.addHandler(handler)
def generate_agent_response(self, prompt: str) -> str:
try:
response = self.inference_client.text_generation(prompt, max_new_tokens=100)
self.logger.info(f"Generated response for prompt: {prompt[:50]}...")
return response.generated_text
except Exception as e:
self.logger.error(f"Error generating response: {str(e)}", exc_info=True)
return f"Error: Unable to generate response. {str(e)}"
def generate_project_config(self, project_description: str) -> Optional[ProjectConfig]:
prompt = f"""
Based on the following project description, generate a ProjectConfig object:
Description: {project_description}
The ProjectConfig should include:
- name: A short, descriptive name for the project
- description: A brief summary of the project
- technologies: A list of technologies to be used (e.g., ["HTML", "CSS", "JavaScript", "React"])
- structure: A dictionary representing the file structure, where keys are directories and values are lists of files
Respond with a JSON object representing the ProjectConfig.
"""
response = self.generate_agent_response(prompt)
try:
json_start = response.find('{')
json_end = response.rfind('}') + 1
if json_start != -1 and json_end != -1:
json_str = response[json_start:json_end]
config_dict = json.loads(json_str)
return ProjectConfig(**config_dict)
else:
raise ValueError("No JSON object found in the response")
except (json.JSONDecodeError, ValueError) as e:
self.logger.error(f"Error parsing JSON from response: {str(e)}")
self.logger.error(f"Full response from model: {response}")
try:
partial_config = self.extract_partial_config(response)
if partial_config:
self.logger.warning("Extracted partial config from malformed response")
return partial_config
except Exception as ex:
self.logger.error(f"Failed to extract partial config: {str(ex)}")
return None
def extract_partial_config(self, response: str) -> Optional[ProjectConfig]:
name = self.extract_field(response, "name")
description = self.extract_field(response, "description")
technologies = self.extract_list(response, "technologies")
structure = self.extract_dict(response, "structure")
if name and description:
return ProjectConfig(
name=name,
description=description,
technologies=technologies or [],
structure=structure or {}
)
return None
def extract_field(self, text: str, field: str) -> Optional[str]:
match = re.search(rf'"{field}"\s*:\s*"([^"]*)"', text)
return match.group(1) if match else None
def extract_list(self, text: str, field: str) -> Optional[List[str]]:
match = re.search(rf'"{field}"\s*:\s*\[(.*?)\]', text, re.DOTALL)
if match:
items = re.findall(r'"([^"]*)"', match.group(1))
return items
return None
def extract_dict(self, text: str, field: str) -> Optional[Dict[str, List[str]]]:
match = re.search(rf'"{field}"\s*:\s*\{{(.*?)\}}', text, re.DOTALL)
if match:
dict_str = match.group(1)
result = {}
for item in re.finditer(r'"([^"]*)"\s*:\s*\[(.*?)\]', dict_str, re.DOTALL):
key = item.group(1)
values = re.findall(r'"([^"]*)"', item.group(2))
result[key] = values
return result
return None
def generate_html(self, content: str) -> str:
return self.html_gen_tool.generate(content)
def generate_css(self, styles: Dict[str, str]) -> str:
return self.css_gen_tool.generate(styles)
def generate_javascript(self, functionality: str) -> str:
return self.js_gen_tool.generate(functionality)
def create_project_files(self, config: ProjectConfig) -> Dict[str, str]:
files = {}
for directory, file_list in config.structure.items():
for file in file_list:
file_path = os.path.join(directory, file)
if file.endswith('.html'):
files[file_path] = self.generate_html(f"Content for {file}")
elif file.endswith('.css'):
files[file_path] = self.generate_css({"body": {"font-family": "Arial, sans-serif"}})
elif file.endswith('.js'):
files[file_path] = self.generate_javascript(f"console.log('Script for {file}');")
else:
files[file_path] = f"Content for {file}"
return files
def execute_project(self, project_description: str) -> Dict[str, str]:
config = self.generate_project_config(project_description)
if config:
return self.create_project_files(config)
else:
self.logger.error("Failed to generate project configuration")
return {} |