Align the finance agent loop and finance_sec_search resource server with the vals-ai

[ushnish-de]

Changes vs main

• finance_agent loop parity — On text-only model responses (no tool calls), injects a "Continue." user message and keeps looping until submit_final_result or max_steps, instead of stopping after one step. Matches vals-ai get_agent.py behavior and avoids rollouts ending early when the model emits explanatory text between tool calls.
• Fresh filings for eval — Adds use_cache (default false) to finance_sec_search; when off, all on-disk cache reads/writes are skipped so every request fetches live SEC data. README documents eval vs training usage.
• Uncapped retrieval tokens for eval — retrieval_max_output_tokens is now Optional[int] (None = no cap, inherits full generation budget; set an int to cap for training).
• Better retrieval error diagnostics — retrieve_information surfaces HTTP 4xx/5xx with status + body excerpt (≤500 chars), and empty-output cases include incomplete_details.reason (e.g. max_output_tokens) instead of a generic “no output” message.
• Tool description fix — Restores the explicit {{key_name}} placeholder example in the retrieve_information prompt field description to cut down tool-format violations.
• Standalone config resolution — Wraps tavily_api_key and search_judge_model_* in ${oc.select:...} so gym env start / +dry_run works without supplying every key; NVFlow overlays still override.
• Tests — New/updated unit tests for Continue-injection loop behavior, HTTP error surfacing, empty-output diagnostics, and cache gating (~270 lines of new test coverage in finance_sec_search).