import os
import json
import requests
from typing import Dict, Any

# Simple web search using DuckDuckGo instant answer API
class WebSearch:
    def __init__(self):
        self.base = "https://api.duckduckgo.com/"

    def run(self, query: str) -> str:
        params = {
            "q": query,
            "format": "json",
            "no_redirect": 1,
            "no_html": 1,
            "skip_disambig": 1,
        }
        r = requests.get(self.base, params=params)
        data = r.json()
        return data.get("AbstractText") or (data.get("RelatedTopics", [])[0].get("Text") if data.get("RelatedTopics") else "")

# DeepAgent without external libraries
class DeepAgent:
    def __init__(self, api_key: str):
        self.api_key = api_key
        self.search = WebSearch()
        self.virtual_fs: Dict[str, str] = {}

    def _chat(self, messages: list[dict]) -> str:
        url = "https://api.openai.com/v1/chat/completions"
        headers = {
            "Authorization": f"Bearer {self.api_key}",
            "Content-Type": "application/json",
        }
        payload = {
            "model": "gpt-4o-mini",
            "messages": messages,
            "temperature": 0.2,
        }
        r = requests.post(url, headers=headers, json=payload)
        r.raise_for_status()
        return r.json()["choices"][0]["message"]["content"]

    def run(self, task_description: str) -> None:
        # 1. Search web for context
        query = f"{task_description} example"
        context = self.search.run(query)
        if not context:
            context = "No relevant information found."

        # 2. Ask LLM to generate file content
        system_prompt = (
            "You are a developer assistant. Based on the provided context and task description, produce the content of a Python file named output.py that demonstrates the requested functionality."
        )
        user_prompt = f"Task: {task_description}\nContext: {context}\nProvide only the code for output.py."
        messages = [
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": user_prompt},
        ]
        result = self._chat(messages)
        self.virtual_fs["output.py"] = result.strip()

    def export_to_real_fs(self, repo_path: str) -> None:
        for filename, content in self.virtual_fs.items():
            full_path = os.path.join(repo_path, filename)
            with open(full_path, "w", encoding="utf-8") as f:
                f.write(content)

# Example usage
if __name__ == "__main__":
    api_key = os.getenv("OPENAI_API_KEY")
    if not api_key:
        raise RuntimeError("Please set OPENAI_API_KEY environment variable.")
    agent = DeepAgent(api_key)
    task_desc = "Create a simple Python script that prints 'Hello World'"
    agent.run(task_desc)
    repo_dir = os.path.abspath(".")
    agent.export_to_real_fs(repo_dir)
    print("Generated files:", list(agent.virtual_fs.keys()))