import gradio as gr
import os
import subprocess
import requests
import json
import re
import time
# --- 1. 환경 설정 및 강화된 API 호출 함수 ---
MISTRAL_API_KEY = os.environ.get("MISTRAL_API_KEY")
CODESTRAL_ENDPOINT = "https://codestral.mistral.ai/v1/chat/completions"
def call_mistral_api(system_prompt: str, user_prompt: str):
"""향상된 Mistral API 호출 함수"""
if not MISTRAL_API_KEY:
raise gr.Error("MISTRAL_API_KEY is not set. Please add it to your Space Secrets.")
headers = {"Authorization": f"Bearer {MISTRAL_API_KEY}", "Content-Type": "application/json"}
messages = [{"role": "system", "content": system_prompt}, {"role": "user", "content": user_prompt}]
data = {"model": "codestral-latest", "messages": messages}
try:
response = requests.post(CODESTRAL_ENDPOINT, headers=headers, data=json.dumps(data), timeout=60)
response.raise_for_status()
return response.json()["choices"][0]["message"]["content"]
except requests.exceptions.RequestException as e:
raise gr.Error(f"API Call Error: {e}")
# --- 2. 백엔드 핵심 기능 (안정성 강화) ---
def parse_code_from_response(response_text: str) -> str | None:
"""C 코드 블록을 파싱하는 안정적인 함수"""
match = re.search(r'```(?:c)?\n(.*?)\n```', response_text, re.DOTALL)
if match: return match.group(1).strip()
# 비상시 순수 코드 응답 처리
if response_text.strip().startswith("#include") and response_text.strip().endswith("}"):
return response_text.strip()
return None
def generate_c_code(description: str) -> str:
system_prompt = "You are an expert C code generator..." # (이전과 동일)
user_prompt = f"Generate C code for: '{description}'"
response = call_mistral_api(system_prompt, user_prompt)
return parse_code_from_response(response) or f"// Failed to parse code from response:\n{response}"
def compile_and_run_c_code(code: str) -> str:
"""컴파일 및 실행 함수"""
if not code.strip(): return "--- SYSTEM ERROR ---\nCode is empty."
with open("main.c", "w", encoding='utf-8') as f: f.write(code)
compile_proc = subprocess.run(["gcc", "main.c", "-o", "main.out", "-lm", "-w"], capture_output=True, text=True, timeout=15)
if compile_proc.returncode != 0: return f"--- COMPILATION FAILED ---\n{compile_proc.stderr}"
run_proc = subprocess.run(["./main.out"], capture_output=True, text=True, timeout=15)
if run_proc.returncode != 0: return f"--- RUNTIME ERROR ---\n{run_proc.stderr}"
output = run_proc.stdout
return f"--- EXECUTION SUCCEEDED ---\n{output}" if output.strip() else "--- EXECUTION SUCCEEDED ---\n(No output)"
def analyze_and_refactor_code(code: str, instruction: str) -> str:
system_prompt = "You are a world-class C code reviewer..." # (이전과 동일)
user_prompt = f"Instruction: '{instruction}'\n\nC Code:\n```c\n{code}\n```"
return call_mistral_api(system_prompt, user_prompt)
# ⭐️ 새로운 기능: 외부 MCP 툴을 사용하는 클라이언트 함수
def call_external_mcp_tool(tool_url: str, code: str, instruction: str) -> str:
"""다른 Gradio Space MCP 툴을 API로 호출하는 함수"""
# Gradio 클라이언트를 사용하여 외부 API 호출 (gradio_client 설치 필요)
from gradio_client import Client
try:
client = Client(tool_url)
# 외부 툴의 API 엔드포인트와 파라미터 이름에 맞춰야 함
# 예시: predict(code_to_analyze=code, user_instruction=instruction)
result = client.predict(code, instruction, api_name="/predict") # api_name은 외부 툴에 따라 다름
return f"--- EXTERNAL TOOL SUCCEEDED ---\n{result}"
except Exception as e:
return f"--- EXTERNAL TOOL FAILED ---\nCould not call tool at {tool_url}. Error: {e}"
# --- 3. 1등을 위한 지능형 에이전트 로직 (최종 버전) ---
def ultimate_agent_ide(initial_code: str, full_instruction: str):
tasks = [task.strip() for task in re.split(r'\s+and then\s+|\s+and\s+|,\s*then\s*|\s*그리고\s+|\s*후에\s*', full_instruction, flags=re.IGNORECASE) if task.strip()]
current_code = initial_code
log = []
# Step 1: 계획 수립
log.append("### 📝 Agent's Plan")
plan = "".join([f"\n{i+1}. {task}" for i, task in enumerate(tasks)])
log.append(plan)
yield current_code, "\n".join(log)
time.sleep(1)
# Step 2: 계획 실행
for i, task in enumerate(tasks):
log.append(f"\n▶ Step {i+1}: {task}
\n")
yield current_code, "\n".join(log)
time.sleep(0.5)
lower_task = task.lower()
# ⭐️ 에이전트의 '생각'과 '행동'
if "generate" in lower_task or "create" in lower_task or "만들어" in lower_task:
log.append("🧠 **Thought:** The user wants new code. Using `generate_c_code` tool.")
yield current_code, "\n".join(log)
new_code = generate_c_code(task)
if new_code and not new_code.startswith("//"):
current_code = new_code
log.append("\n✅ **Action Result:** Code generated and updated in the editor.")
else:
log.append(f"\n❌ **Action Result:** Generation failed. {new_code}")
elif "compile" in lower_task or "run" in lower_task or "실행" in lower_task:
log.append("🧠 **Thought:** The user wants to compile and run. Using `compile_and_run_c_code` tool.")
yield current_code, "\n".join(log)
result = compile_and_run_c_code(current_code)
log.append(f"\n💻 **Action Result:**\n```\n{result}\n```")
# ⭐️⭐️ 자가 수정 (SELF-CORRECTION) 로직 ⭐️⭐️
if "COMPILATION FAILED" in result:
log.append("\n\n🧠 **Thought:** Compilation failed. I will try to fix the code myself.")
yield current_code, "\n".join(log)
time.sleep(1)
error_message = result.split("--- COMPILATION FAILED ---")[1]
fix_instruction = f"The following C code failed to compile with this error:\n\n**Error:**\n```\n{error_message}\n```\n\nPlease fix the code so it compiles successfully. Provide only the complete, corrected C code."
log.append("\n🛠️ **Self-Correction:** Asking the LLM to fix the error...")
yield current_code, "\n".join(log)
fixed_code_response = analyze_and_refactor_code(current_code, fix_instruction)
fixed_code = parse_code_from_response(fixed_code_response)
if fixed_code:
current_code = fixed_code
log.append("\n✅ **Self-Correction Result:** A potential fix has been applied to the code editor. Please try compiling again.")
else:
log.append("\n❌ **Self-Correction Result:** Failed to automatically fix the code.")
# ⭐️⭐️ 외부 MCP 툴 사용 예시 ⭐️⭐️
elif "security" in lower_task or "보안" in lower_task:
log.append("🧠 **Thought:** The user wants a security analysis. I will use an external MCP tool for this.")
yield current_code, "\n".join(log)
# 이 URL은 예시이며, 실제 작동하는 보안 분석 MCP Space가 있다면 그 주소를 넣어야 합니다.
# 해커톤 제출 시, 직접 간단한 보안분석 툴을 하나 더 만들거나, 다른 참가자의 툴을 사용하는 모습을 보여주면 최고입니다.
external_tool_url = "user-provided-security-tool-space-url"
log.append(f"\n🔌 **Action:** Calling external tool at `{external_tool_url}`...")
yield current_code, "\n".join(log)
# 실제로는 instruction에서 URL을 파싱해야 하지만, 여기서는 하드코딩으로 예시를 보여줍니다.
security_result = call_external_mcp_tool(external_tool_url, current_code, task)
log.append(f"\n🛡️ **Action Result:**\n```\n{security_result}\n```")
else:
log.append("🧠 **Thought:** The user wants to analyze or refactor. Using `analyze_and_refactor_code` tool.")
yield current_code, "\n".join(log)
analysis_result = analyze_and_refactor_code(current_code, task)
refactored_code = parse_code_from_response(analysis_result)
if refactored_code:
current_code = refactored_code
log.append("\n✅ **Action Result:** Code refactored and updated in the editor.")
log.append(f"\n🔎 **Analysis Result:**\n{analysis_result}")
log.append("