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class Company {
  name string
  @description("Formal name of the company with corporate suffix")
  ...
}

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{
  "permissions": {
    "allow": [
      "Bash(git status:*)",
      "Bash(git diff:*)",
      "Bash(git log:*)",
      "Bash(git add:*)",
      "Bash(git grep:*)",
      "Bash(poetry update:*)",
      "Bash(pip show:*)",

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client<llm> Gemini25Pro {
    provider google-ai
    retry_policy ThreeRetries
    options {
        model "gemini-2.5-pro"
        api_key env.GEMINI_API_KEY
    }
}

retry_policy ThreeRetries {

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client<llm> Gemini25Pro {
    provider google-ai
    retry_policy ThreeRetries
    options {
        model "gemini-2.5-pro"
        api_key env.GEMINI_API_KEY
    }
}

retry_policy ThreeRetries {

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class NewsArticle {
  
  title string

  url string?
  @description("URL of the article")
  
  summary string
  @description("Summary of the article. What is it about? What are the key points?")
  

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Python 3.12.9 | packaged by conda-forge | (main, Mar  4 2025, 22:44:42) [Clang 18.1.8 ]
Type 'copyright', 'credits' or 'license' for more information
IPython 9.0.2 -- An enhanced Interactive Python. Type '?' for help.
Tip: Use `--theme`, or the `%colors` magic to change ipython themes and colors.
25/07/17 21:48:25 WARN Utils: Your hostname, Achilles-3.local resolves to a loopback address: 127.0.0.1; using 10.26.184.245 instead (on interface en0)
25/07/17 21:48:25 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
:: loading settings :: url = jar:file:/Users/rjurney/Software/spark/assembly/target/scala-2.12/jars/ivy-2.5.1.jar!/org/apache/ivy/core/settings/ivysettings.xml
Ivy Default Cache set to: /Users/rjurney/.ivy2/cache
The jars for the packages stored in: /Users/rjurney/.ivy2/jars
graphframes#graphframes added as a dependency

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CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Commands

• Install Dependencies: poetry install
• Run CLI: poetry run abzu
• Build/Generate abzu/baml_client code: baml-cli generate
• Test baml_src code: baml-cli test, poetry run pytest tests/

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# This will effectively train the embedding model. MultipleNegativesRankingLoss did not work.
loss: losses.ContrastiveLoss = losses.ContrastiveLoss(model=sbert_model)

# These are default arguments for OnlineContrastiveLoss
loss: losses.OnlineContrastiveLoss = losses.OnlineContrastiveLoss(
    model=sbert_model,
    margin=0.5,  # Margin for contrastive loss
    distance_metric=SiameseDistanceMetric.COSINE_DISTANCE,
)

rjurney

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Commands

• Install Dependencies: poetry install
• Run CLI: poetry run abzu
• Build/Generate abzu/baml_client code: baml-cli generate
• Test baml_src code: baml-cli test, poetry run pytest tests/

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I'll show you how to structure data and prompts for effective technical analysis with LLMs. Here's a comprehensive approach:

1. Data Preparation Structure

import pandas as pd
import numpy as np
from typing import Dict, List, Tuple

def prepare_ta_data(df: pd.DataFrame) -> pd.DataFrame: