ReMe/plugins/auto-fin

Auto Fin Plugin

中文

Auto Fin fetches a rolling window of CLS telegraph news (24 hours by default), groups items by configured topics, researches each topic against ReMe history, and writes one Chinese Markdown report with validated wikilinks. Current news and topic selection stay in runtime memory; only the final report becomes durable memory. This directory is an independent Python distribution. Its single reme.plugins entry point exposes a plugin.yaml containing the three Step backends and their Job configuration under application_defaults. Enable the installed plugin explicitly through plugins=["auto-fin"].

Auto Fin has no reliable market-price feed. It does not calculate returns, targets, or entry points and is not investment advice.

Quick start

1. Install ReMe and Auto Fin

python -m pip install "reme-ai[core]>=0.4.1.12"
reme plugins install plugins/auto-fin

2. Configure the model environment

Configure the LLM environment variables as described in the ReMe model-configuration guide. Other compatible models and providers can also be used.

3. Start ReMe with the plugin

reme start plugins='["auto-fin"]'

With no explicit config, ReMe loads default.yaml and adds the plugin to that service.

From another terminal, call the running HTTP service through ReMe's CLI client:

reme auto_fin topics="黄金,AI,存储芯片"

Or call its HTTP endpoint directly:

curl -s http://127.0.0.1:2333/auto_fin \
  -H 'Content-Type: application/json' \
  -d '{"topics":"黄金,AI,存储芯片"}'

The HTTP service also exposes the same Job as the auto_fin MCP tool at /mcp. The default topics are 黄金,机器人,半导体; an empty value also uses these defaults.

To host the application with both JSON and MCP access:

reme start plugins='["auto-fin"]' \
  service.backend=http

Custom application configs must provide agent_wrapper.default, a file_store.default with an enabled tag index, and the search, list_tags, frontmatter_read, and frontmatter_update Jobs used by Auto Fin and automatic tagging.

Pipeline

CLS public telegraph endpoint (rolling 24 hours)
        ↓
normalize and deduplicate in RuntimeContext
        ↓
topic Agent returns topic-to-news-ID mappings in prompt-sized batches
        ↓
one research Agent per topic examines its latest 20 articles and searches history up to three times
        ↓
combine topic results and validate historical wikilinks in code
        ↓
daily/YYYY-MM-DD/auto_fin.md
        ↓
generate memory tags; the background file watcher refreshes indexes

auto_fin_data_step signs and paginates the same endpoint used by the CLS website. It starts at the decision time and stops only after covering the exact preceding 24 hours. Requests are rate-limited and retried; malformed records and records outside the window are discarded.

auto_fin_topic_step batches current news under a 100,000-character full-prompt limit and returns related news_id values for each topic. Code ignores unknown IDs and deduplicates repeated IDs, then preserves source-news order. One article may belong to multiple topics. If nothing is relevant, the job succeeds as a skip without writing a report.

auto_fin_merge_step researches each nonempty topic with its latest 20 articles. It exposes only search, enforces a three-call search budget per topic, and keeps current CLS IDs, times, and titles as plain evidence. The prompt limits wikilinks to historical Markdown actually used by the Agent; the code-level boundary independently keeps only existing, workspace-relative Markdown targets. Missing, absolute, escaping, backslash, and self-referential targets are degraded to their readable aliases.

Same-day reruns use up to the first 30,000 characters of the existing report as context and replace it with the revised result. The combined final write is atomic and refreshes the daily index. The workflow then runs auto_tag_step to update the generated report's memory-tag frontmatter; the normal background file watcher observes that source-file change and refreshes derived indexes. No JSONL, intermediate Markdown, or structured Agent output is written.

Parameters

Parameter	Default	Purpose
date	""	Empty uses today in Shanghai; an explicit value must equal today
now	""	Optional ISO 8601 decision time for testing or replay
topics	"黄金,机器人,半导体"	Comma-separated topics; empty also uses these defaults
window_hours	24	Rolling number of hours of CLS telegraph news to fetch; must be positive
request_interval	10	Minimum delay in seconds after every CLS request attempt; may be zero
max_retries	3	Maximum attempts for each CLS page request; must be at least one

The plugin cron Job starts with the application and runs daily at 09:00 in the application timezone, which defaults to Asia/Shanghai. The rolling window uses timestamps and may cross calendar days. Report completion depends on news volume and model latency.

Output

.reme/daily/YYYY-MM-DD/auto_fin.md

The report includes a title, description, current CLS evidence, historical analysis, contextual wikilinks, and a fixed non-investment disclaimer. Network errors and invalid Agent output fail explicitly; no relevant current news is a successful skip.

Validation

python -m pytest plugins/auto-fin -v

Unit tests mock the CLS and Agent boundaries and do not contact external services.