ReAct: Reasoning and Acting

import json
import re
import httpx
from openai import OpenAI

client = OpenAI()

SYSTEM_PROMPT = """You solve tasks step by step. Use this EXACT format:

Thought: [your reasoning about what to do next]
Action: [tool_name]
Action Input: [JSON input for the tool]

When you have the final answer:
Thought: I have enough information.
Action: finish
Action Input: {"answer": "your final answer here"}

Available tools:
- search: Search the web. Input: {"query": "your search query"}
- finish: End the task. Input: {"answer": "..."}
"""

def search(query: str) -> str:
    resp = httpx.post("https://api.tavily.com/search",
                       json={"api_key": TAVILY_API_KEY, "query": query, "max_results": 3})
    results = resp.json().get("results", [])
    return "\n".join(f"{r['title']}: {r['content'][:200]}" for r in results)

TOOLS = {"search": search}

def parse_action(text: str) -> tuple[str, dict] | None:
    """Extract the Action and Action Input from the model's raw text."""
    action_match = re.search(r"Action:\s*(.+)", text)
    input_match = re.search(r"Action Input:\s*(\{.+?\})", text, re.DOTALL)
    if not action_match:
        return None
    action = action_match.group(1).strip()
    try:
        action_input = json.loads(input_match.group(1)) if input_match else {}
    except json.JSONDecodeError:
        action_input = {}
    return action, action_input

def run_react_agent(task: str, max_iterations: int = 10) -> str:
    history = [{"role": "user", "content": task}]

    for _ in range(max_iterations):
        response = client.chat.completions.create(
            model="gpt-4o",
            messages=[{"role": "system", "content": SYSTEM_PROMPT}] + history,
        )
        text = response.choices[0].message.content
        history.append({"role": "assistant", "content": text})

        parsed = parse_action(text)
        if not parsed:
            break

        action, action_input = parsed
        if action == "finish":
            return action_input.get("answer", "No answer produced.")

        if action in TOOLS:
            observation = TOOLS[action](**action_input)
        else:
            observation = f"Error: unknown tool '{action}'"

        history.append({"role": "user", "content": f"Observation: {observation}"})

    return "Max iterations reached without a final answer."