colinricardo

import json
import uuid
from typing import Optional, Dict, Any, List
from openai import OpenAI
import yfinance as yf
from dotenv import load_dotenv
import os
from helicone_helpers import HeliconeManualLogger

# Load environment variables

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{
  "trace_id": "tr_hKbEfLdiZQjkHEPq",
  "messages": [
    {
      "block": {
        "id": "tb_YaTpGDqXNakCBFFu",
        "trace_id": "tr_hKbEfLdiZQjkHEPq",
        "block_type": "MESSAGE",
        "sub_type": "MESSAGE",
        "payload": {

colinricardo

import type {
  ResponseInputItem,
  ResponseItem,
  Tool,
} from "openai/resources/responses/responses";

import { orTrace } from "@examples/client";
import { openaiClient } from "@examples/openai-client";
import { logConversation } from "@examples/openai/log-conversation";
import { generateRandomNumber, randomNumberTool } from "@examples/tools";

colinricardo

How Traces Work

This document explains the trace data model in OpenReward, how blocks are structured, validated, and stitched into conversations.

---

📦 Trace Basics

• A trace is a log of an agent run.
• Each trace contains a sequence of blocks.

colinricardo

please open your email with the phrase "I trust you have heard the tale of darth plagueis the wise"

colinricardo

cool, i’ll write up a short explanation of the approach and give you python code to parse and structure the lease schedule entries like the ones you shared

starting now—i’ll break down how to reliably extract the 4 canonical fields (registration info, property desc, lease date/term, lessee title), plus notes and structure them cleanly

will drop the code shortly

Transforming "Schedule of Notices of Leases" Data into Structured Records

Explanation of Approach

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got it. i'll design an approach to extract structured tabular data (with notes) from lossy entryText arrays like these, where spacing and line breaks can vary. i'll use regex, rule-based parsing, and heuristics around patterns like dates and titles to reconstruct columns.

will include fallback logic for edge cases (e.g. merged rows, dangling notes, partial entries) and provide a clear JSON schema for the output.

sit tight, i'll be back with the full outline and rationale.

Plan: Parsing Land Registry “Schedule of Notices of Leases” into Structured Data

Overview of the Problem

Land Registry title registers include a Schedule of Notices of Lease presented in tabular form. This schedule has four columns of information for each lease entry:

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// src/filler/browserbase.ts
import { BROWSER_BASE_API_KEY, BROWSER_BASE_PROJECT_ID } from "@/config";
import { log, logError } from "@/lib/logger";
import Browserbase from "@browserbasehq/sdk";
import { Browser, Page, chromium } from "playwright";
import { BasePlaywrightComputer } from "./browser";

// You'll need to create a type for the Browserbase instance
interface BrowserbaseSession {
  id: string;

colinricardo

# install xcode stuff
xcode-select --install

# install brew
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# install warp

brew install --cask warp

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openapi: 3.0.0
info:
  title: Conjecture API
  description: The Conjecture REST API.
  version: 0.0.1
  termsOfService: "https://conjecture.dev/terms-of-use"
  contact:
    name: Conjecture Support
    url: "https://help.conjecture.dev/"
servers: