$ -weight: 500;">pip -weight: 500;">install aider aider --help -weight: 500;">pip -weight: 500;">install aider aider --help -weight: 500;">pip -weight: 500;">install aider aider --help -weight: 500;">npm -weight: 500;">install -g continue -weight: 500;">npm -weight: 500;">install -g continue -weight: 500;">npm -weight: 500;">install -g continue -weight: 500;">pip -weight: 500;">install opencode -weight: 500;">pip -weight: 500;">install opencode -weight: 500;">pip -weight: 500;">install opencode #!/usr/bin/env python3 import os import subprocess import sys #!/usr/bin/env python3 import os import subprocess import sys #!/usr/bin/env python3 import os import subprocess import sys # macOS -weight: 500;">brew -weight: 500;">install lm-studio # Ubuntu/Debian -weight: 500;">wget -O - https://repo.lm-studio.ai/gpg.key | -weight: 600;">sudo -weight: 500;">apt-key add - echo "deb [arch=amd64] https://repo.lm-studio.ai/ stable main" | -weight: 600;">sudo tee /etc/-weight: 500;">apt/sources.list.d/lm-studio.list -weight: 600;">sudo -weight: 500;">apt -weight: 500;">update && -weight: 600;">sudo -weight: 500;">apt -weight: 500;">install lm-studio # macOS -weight: 500;">brew -weight: 500;">install lm-studio # Ubuntu/Debian -weight: 500;">wget -O - https://repo.lm-studio.ai/gpg.key | -weight: 600;">sudo -weight: 500;">apt-key add - echo "deb [arch=amd64] https://repo.lm-studio.ai/ stable main" | -weight: 600;">sudo tee /etc/-weight: 500;">apt/sources.list.d/lm-studio.list -weight: 600;">sudo -weight: 500;">apt -weight: 500;">update && -weight: 600;">sudo -weight: 500;">apt -weight: 500;">install lm-studio # macOS -weight: 500;">brew -weight: 500;">install lm-studio # Ubuntu/Debian -weight: 500;">wget -O - https://repo.lm-studio.ai/gpg.key | -weight: 600;">sudo -weight: 500;">apt-key add - echo "deb [arch=amd64] https://repo.lm-studio.ai/ stable main" | -weight: 600;">sudo tee /etc/-weight: 500;">apt/sources.list.d/lm-studio.list -weight: 600;">sudo -weight: 500;">apt -weight: 500;">update && -weight: 600;">sudo -weight: 500;">apt -weight: 500;">install lm-studio # Docker로 LocalAI 실행 -weight: 500;">docker run -p 8080:8080 localai/localai:latest # 모델 다운로드 -weight: 500;">curl -X POST http://localhost:8080/models -d '{ "name": "llama3", "url": "https://huggingface.co/TheBloke/Llama-3-8B-Instruct-GGUF/resolve/main/llama-3-8b-instruct.Q4_K_M.gguf" }' # Docker로 LocalAI 실행 -weight: 500;">docker run -p 8080:8080 localai/localai:latest # 모델 다운로드 -weight: 500;">curl -X POST http://localhost:8080/models -d '{ "name": "llama3", "url": "https://huggingface.co/TheBloke/Llama-3-8B-Instruct-GGUF/resolve/main/llama-3-8b-instruct.Q4_K_M.gguf" }' # Docker로 LocalAI 실행 -weight: 500;">docker run -p 8080:8080 localai/localai:latest # 모델 다운로드 -weight: 500;">curl -X POST http://localhost:8080/models -d '{ "name": "llama3", "url": "https://huggingface.co/TheBloke/Llama-3-8B-Instruct-GGUF/resolve/main/llama-3-8b-instruct.Q4_K_M.gguf" }' #!/usr/bin/env python3 import json import requests import subprocess import sys class TerminalAI: def __init__(self, api_url="http://localhost:8080"): self.api_url = api_url def call_model(self, prompt, functions=None): data = { "prompt": prompt, "model": "llama3" } if functions: data["functions"] = functions response = requests.post(f"{self.api_url}/completion", json=data) return response.json() def run(self, prompt): result = self.call_model(prompt) print(result["response"]) # 사용법 if __name__ == "__main__": ai = TerminalAI() ai.run(sys.argv[1]) #!/usr/bin/env python3 import json import requests import subprocess import sys class TerminalAI: def __init__(self, api_url="http://localhost:8080"): self.api_url = api_url def call_model(self, prompt, functions=None): data = { "prompt": prompt, "model": "llama3" } if functions: data["functions"] = functions response = requests.post(f"{self.api_url}/completion", json=data) return response.json() def run(self, prompt): result = self.call_model(prompt) print(result["response"]) # 사용법 if __name__ == "__main__": ai = TerminalAI() ai.run(sys.argv[1]) #!/usr/bin/env python3 import json import requests import subprocess import sys class TerminalAI: def __init__(self, api_url="http://localhost:8080"): self.api_url = api_url def call_model(self, prompt, functions=None): data = { "prompt": prompt, "model": "llama3" } if functions: data["functions"] = functions response = requests.post(f"{self.api_url}/completion", json=data) return response.json() def run(self, prompt): result = self.call_model(prompt) print(result["response"]) # 사용법 if __name__ == "__main__": ai = TerminalAI() ai.run(sys.argv[1]) #!/bin/bash # terminal-agent.sh tmux new-session -d -s ai-session tmux send-keys -t ai-session "python3 ai_agent.py 'write a python function to sort list'" Enter tmux attach -t ai-session #!/bin/bash # terminal-agent.sh tmux new-session -d -s ai-session tmux send-keys -t ai-session "python3 ai_agent.py 'write a python function to sort list'" Enter tmux attach -t ai-session #!/bin/bash # terminal-agent.sh tmux new-session -d -s ai-session tmux send-keys -t ai-session "python3 ai_agent.py 'write a python function to sort list'" Enter tmux attach -t ai-session import subprocess import os class TmuxManager: def __init__(self, session_name): self.session_name = session_name def create_session(self): subprocess.run(["tmux", "new-session", "-d", "-s", self.session_name]) def send_command(self, command): subprocess.run([ "tmux", "send-keys", "-t", self.session_name, command, "Enter" ]) def attach(self): subprocess.run(["tmux", "attach", "-t", self.session_name]) # 사용 예시 tmux = TmuxManager("dev-agent") tmux.create_session() tmux.send_command("ls -la") import subprocess import os class TmuxManager: def __init__(self, session_name): self.session_name = session_name def create_session(self): subprocess.run(["tmux", "new-session", "-d", "-s", self.session_name]) def send_command(self, command): subprocess.run([ "tmux", "send-keys", "-t", self.session_name, command, "Enter" ]) def attach(self): subprocess.run(["tmux", "attach", "-t", self.session_name]) # 사용 예시 tmux = TmuxManager("dev-agent") tmux.create_session() tmux.send_command("ls -la") import subprocess import os class TmuxManager: def __init__(self, session_name): self.session_name = session_name def create_session(self): subprocess.run(["tmux", "new-session", "-d", "-s", self.session_name]) def send_command(self, command): subprocess.run([ "tmux", "send-keys", "-t", self.session_name, command, "Enter" ]) def attach(self): subprocess.run(["tmux", "attach", "-t", self.session_name]) # 사용 예시 tmux = TmuxManager("dev-agent") tmux.create_session() tmux.send_command("ls -la") import os import re from pathlib import Path class CodeSearch: def __init__(self, root_dir="."): self.root_dir = Path(root_dir) def search_pattern(self, pattern, file_extensions=None): results = [] if file_extensions is None: file_extensions = [".py", ".js", ".ts", ".java", ".cpp"] for ext in file_extensions: for file_path in self.root_dir.rglob(f"*{ext}"): try: with open(file_path, 'r') as f: content = f.read() if re.search(pattern, content): results.append({ "file": str(file_path), "match": pattern }) except Exception: continue return results # 사용 예시 searcher = CodeSearch() results = searcher.search_pattern(r"def\s+(\w+)\s*\(.*?\):") print(json.dumps(results, indent=2)) import os import re from pathlib import Path class CodeSearch: def __init__(self, root_dir="."): self.root_dir = Path(root_dir) def search_pattern(self, pattern, file_extensions=None): results = [] if file_extensions is None: file_extensions = [".py", ".js", ".ts", ".java", ".cpp"] for ext in file_extensions: for file_path in self.root_dir.rglob(f"*{ext}"): try: with open(file_path, 'r') as f: content = f.read() if re.search(pattern, content): results.append({ "file": str(file_path), "match": pattern }) except Exception: continue return results # 사용 예시 searcher = CodeSearch() results = searcher.search_pattern(r"def\s+(\w+)\s*\(.*?\):") print(json.dumps(results, indent=2)) import os import re from pathlib import Path class CodeSearch: def __init__(self, root_dir="."): self.root_dir = Path(root_dir) def search_pattern(self, pattern, file_extensions=None): results = [] if file_extensions is None: file_extensions = [".py", ".js", ".ts", ".java", ".cpp"] for ext in file_extensions: for file_path in self.root_dir.rglob(f"*{ext}"): try: with open(file_path, 'r') as f: content = f.read() if re.search(pattern, content): results.append({ "file": str(file_path), "match": pattern }) except Exception: continue return results # 사용 예시 searcher = CodeSearch() results = searcher.search_pattern(r"def\s+(\w+)\s*\(.*?\):") print(json.dumps(results, indent=2)) import subprocess import json class GitManager: def get_changed_files(self): result = subprocess.run( ["-weight: 500;">git", "diff", "--name-only", "HEAD~1", "HEAD"], capture_output=True, text=True ) return [line.strip() for line in result.stdout.split('\n') if line.strip()] def get_commit_history(self, limit=5): result = subprocess.run([ "-weight: 500;">git", "log", f"--oneline", f"-{limit}" ], capture_output=True, text=True) return result.stdout.strip().split('\n') # 사용 예시 git_manager = GitManager() files = git_manager.get_changed_files() print(json.dumps(files, indent=2)) import subprocess import json class GitManager: def get_changed_files(self): result = subprocess.run( ["-weight: 500;">git", "diff", "--name-only", "HEAD~1", "HEAD"], capture_output=True, text=True ) return [line.strip() for line in result.stdout.split('\n') if line.strip()] def get_commit_history(self, limit=5): result = subprocess.run([ "-weight: 500;">git", "log", f"--oneline", f"-{limit}" ], capture_output=True, text=True) return result.stdout.strip().split('\n') # 사용 예시 git_manager = GitManager() files = git_manager.get_changed_files() print(json.dumps(files, indent=2)) import subprocess import json class GitManager: def get_changed_files(self): result = subprocess.run( ["-weight: 500;">git", "diff", "--name-only", "HEAD~1", "HEAD"], capture_output=True, text=True ) return [line.strip() for line in result.stdout.split('\n') if line.strip()] def get_commit_history(self, limit=5): result = subprocess.run([ "-weight: 500;">git", "log", f"--oneline", f"-{limit}" ], capture_output=True, text=True) return result.stdout.strip().split('\n') # 사용 예시 git_manager = GitManager() files = git_manager.get_changed_files() print(json.dumps(files, indent=2)) class ContextManager: def __init__(self, max_tokens=4096): self.max_tokens = max_tokens self.context = [] def add_file_context(self, file_path, max_lines=100): try: with open(file_path, 'r') as f: lines = f.readlines() if len(lines) > max_lines: # 중간 부분만 포함 -weight: 500;">start = len(lines) // 2 - max_lines // 2 end = -weight: 500;">start + max_lines context_lines = lines[-weight: 500;">start:end] else: context_lines = lines self.context.append({ "file": file_path, "lines": [line.rstrip() for line in context_lines] }) except Exception as e: print(f"Error reading {file_path}: {e}") def get_context_prompt(self): prompt = "Context information:\n" for item in self.context: prompt += f"\nFile: {item['file']}\n" for line in item['lines']: prompt += f"{line}\n" return prompt class ContextManager: def __init__(self, max_tokens=4096): self.max_tokens = max_tokens self.context = [] def add_file_context(self, file_path, max_lines=100): try: with open(file_path, 'r') as f: lines = f.readlines() if len(lines) > max_lines: # 중간 부분만 포함 -weight: 500;">start = len(lines) // 2 - max_lines // 2 end = -weight: 500;">start + max_lines context_lines = lines[-weight: 500;">start:end] else: context_lines = lines self.context.append({ "file": file_path, "lines": [line.rstrip() for line in context_lines] }) except Exception as e: print(f"Error reading {file_path}: {e}") def get_context_prompt(self): prompt = "Context information:\n" for item in self.context: prompt += f"\nFile: {item['file']}\n" for line in item['lines']: prompt += f"{line}\n" return prompt class ContextManager: def __init__(self, max_tokens=4096): self.max_tokens = max_tokens self.context = [] def add_file_context(self, file_path, max_lines=100): try: with open(file_path, 'r') as f: lines = f.readlines() if len(lines) > max_lines: # 중간 부분만 포함 -weight: 500;">start = len(lines) // 2 - max_lines // 2 end = -weight: 500;">start + max_lines context_lines = lines[-weight: 500;">start:end] else: context_lines = lines self.context.append({ "file": file_path, "lines": [line.rstrip() for line in context_lines] }) except Exception as e: print(f"Error reading {file_path}: {e}") def get_context_prompt(self): prompt = "Context information:\n" for item in self.context: prompt += f"\nFile: {item['file']}\n" for line in item['lines']: prompt += f"{line}\n" return prompt # LLM quantization python -m llama_cpp.quantize --model-path models/llama3-8b.Q4_K_M.gguf --output-path models/llama3-8b-q4.gguf # 메모리 최적화 export CUDA_VISIBLE_DEVICES=0 export LLM_CACHE_SIZE=1000 # LLM quantization python -m llama_cpp.quantize --model-path models/llama3-8b.Q4_K_M.gguf --output-path models/llama3-8b-q4.gguf # 메모리 최적화 export CUDA_VISIBLE_DEVICES=0 export LLM_CACHE_SIZE=1000 # LLM quantization python -m llama_cpp.quantize --model-path models/llama3-8b.Q4_K_M.gguf --output-path models/llama3-8b-q4.gguf # 메모리 최적화 export CUDA_VISIBLE_DEVICES=0 export LLM_CACHE_SIZE=1000 import time import requests def benchmark_model(api_url, prompt, iterations=5): times = [] for i in range(iterations): -weight: 500;">start = time.time() response = requests.post(f"{api_url}/completion", json={ "prompt": prompt, "model": "llama3" }) end = time.time() times.append(end - -weight: 500;">start) avg_time = sum(times) / len(times) print(f"Average time: {avg_time:.2f}s") return avg_time # 로컬 vs API 비교 local_time = benchmark_model("http://localhost:8080", "Hello world") import time import requests def benchmark_model(api_url, prompt, iterations=5): times = [] for i in range(iterations): -weight: 500;">start = time.time() response = requests.post(f"{api_url}/completion", json={ "prompt": prompt, "model": "llama3" }) end = time.time() times.append(end - -weight: 500;">start) avg_time = sum(times) / len(times) print(f"Average time: {avg_time:.2f}s") return avg_time # 로컬 vs API 비교 local_time = benchmark_model("http://localhost:8080", "Hello world") import time import requests def benchmark_model(api_url, prompt, iterations=5): times = [] for i in range(iterations): -weight: 500;">start = time.time() response = requests.post(f"{api_url}/completion", json={ "prompt": prompt, "model": "llama3" }) end = time.time() times.append(end - -weight: 500;">start) avg_time = sum(times) / len(times) print(f"Average time: {avg_time:.2f}s") return avg_time # 로컬 vs API 비교 local_time = benchmark_model("http://localhost:8080", "Hello world") bash # 1. 새 기능 생성 mkdir feature-auth touch feature-auth/auth_service.py # 2. AI 에이전트를 통한 코드 생성 python ai_agent.py "Create authentication -weight: 500;">service with login, register, and token refresh functions" # 3. tmux 세션 생성 ./ --- 📥 **Get the full guide on Gumroad**: https://gumroad.com/l/auto ($5) bash # 1. 새 기능 생성 mkdir feature-auth touch feature-auth/auth_service.py # 2. AI 에이전트를 통한 코드 생성 python ai_agent.py "Create authentication -weight: 500;">service with login, register, and token refresh functions" # 3. tmux 세션 생성 ./ --- 📥 **Get the full guide on Gumroad**: https://gumroad.com/l/auto ($5) bash # 1. 새 기능 생성 mkdir feature-auth touch feature-auth/auth_service.py # 2. AI 에이전트를 통한 코드 생성 python ai_agent.py "Create authentication -weight: 500;">service with login, register, and token refresh functions" # 3. tmux 세션 생성 ./ --- 📥 **Get the full guide on Gumroad**: https://gumroad.com/l/auto ($5)