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| 1 | +# Finance SEC Search |
| 2 | + |
| 3 | +50-question financial information retrieval benchmark from the |
| 4 | +[Vals AI finance-agent](https://github.com/vals-ai/finance-agent) public |
| 5 | +dataset. Questions cover SEC EDGAR filings, financial metrics, and |
| 6 | +company analysis. |
| 7 | + |
| 8 | +## Verification |
| 9 | + |
| 10 | +Uses LLM-as-judge with a financial grading rubric (0/1/2 scale). |
| 11 | +Only fully correct answers (`[[2]]`) receive reward 1.0. The judge |
| 12 | +prompt and rubric are defined in the `finance_sec_search` resource |
| 13 | +server's `/prompt_templates`. |
| 14 | + |
| 15 | +## Tools |
| 16 | + |
| 17 | +| Tool | Description | |
| 18 | +|------|-------------| |
| 19 | +| `sec_filing_search` | Search SEC EDGAR for filing metadata by stock ticker symbol | |
| 20 | +| `parse_html_page` | Fetch and parse any HTML page (SEC URLs use disk cache), store under a key | |
| 21 | +| `retrieve_information` | Query stored documents via LLM prompt with `{{key}}` placeholders | |
| 22 | +| `submit_final_result` | Submit the final answer (required to receive a reward) | |
| 23 | +| `web_search` | Internet search via Tavily API (optional — requires `tavily_api_key` in `env.yaml`) | |
| 24 | + |
| 25 | +## Data preparation |
| 26 | + |
| 27 | +Without web search: |
| 28 | + |
| 29 | +```bash |
| 30 | +ng_prepare_benchmark '+config_paths=[benchmarks/finance_sec_search/config_no_web_search.yaml]' |
| 31 | +``` |
| 32 | + |
| 33 | +With web search (requires `tavily_api_key` in `env.yaml`): |
| 34 | + |
| 35 | +```bash |
| 36 | +ng_prepare_benchmark '+config_paths=[benchmarks/finance_sec_search/config_web_search.yaml]' |
| 37 | +``` |
| 38 | + |
| 39 | +Downloads `public.csv` from the Vals AI GitHub repo and writes benchmark |
| 40 | +JSONL to `data/`. |
| 41 | + |
| 42 | +| Config | Output file | |
| 43 | +|--------|-------------| |
| 44 | +| `config_no_web_search.yaml` | `data/finance_sec_search_benchmark.jsonl` | |
| 45 | +| `config_web_search.yaml` | `data/finance_sec_search_benchmark_web_search.jsonl` | |
| 46 | + |
| 47 | +## Running servers |
| 48 | + |
| 49 | +```bash |
| 50 | +config_paths="responses_api_models/vllm_model/configs/vllm_model.yaml,\ |
| 51 | +benchmarks/finance_sec_search/config_no_web_search.yaml" |
| 52 | +ng_run "+config_paths=[$config_paths]" |
| 53 | +``` |
| 54 | + |
| 55 | +## Collecting rollouts |
| 56 | + |
| 57 | +```bash |
| 58 | +ng_collect_rollouts \ |
| 59 | + +agent_name=finance_sec_search_benchmark_agent \ |
| 60 | + +input_jsonl_fpath=benchmarks/finance_sec_search/data/finance_sec_search_benchmark.jsonl \ |
| 61 | + +output_jsonl_fpath=results/finance_sec_search_rollouts.jsonl |
| 62 | +``` |
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