Agentic Paper Digest

When to use

Fetch a recent paper digest from arXiv and Hugging Face.
Produce JSON output for downstream agents.
Run a local API server when a polling workflow is needed.

Prereqs

Python 3 and network access.
LLM access via
```
OPENAI_API_KEY
```
or an OpenAI-compatible provider via
```
LITELLM_API_BASE
```
+
```
LITELLM_API_KEY
```
.
```
git
```
is optional for bootstrap; otherwise
```
curl
```
/
```
wget
```
(or Python) is used to download the repo.

Get the code and install

Preferred: run the bootstrap helper script. It uses git when available or falls back to a zip download.

bash "{baseDir}/scripts/bootstrap.sh"

Override the clone location by setting
```
PROJECT_DIR
```
.

PROJECT_DIR="$HOME/agentic_paper_digest" bash "{baseDir}/scripts/bootstrap.sh"

Run (CLI preferred)

bash "{baseDir}/scripts/run_cli.sh"

Pass through CLI flags as needed.

bash "{baseDir}/scripts/run_cli.sh" --window-hours 24 --sources arxiv,hf

Run (API optional)

bash "{baseDir}/scripts/run_api.sh"

Trigger runs and read results.

curl -X POST http://127.0.0.1:8000/api/run
curl http://127.0.0.1:8000/api/status
curl http://127.0.0.1:8000/api/papers

Stop the API server if needed.

bash "{baseDir}/scripts/stop_api.sh"

Outputs

CLI

--json

prints

run_id

seen

kept

window_start

, and

window_end

Data store:
```
data/papers.sqlite3
```
(under
```
PROJECT_DIR
```
).

API:

POST /api/run

GET /api/status

GET /api/papers

GET/POST /api/topics

GET/POST /api/settings

Configuration

Config files live in

PROJECT_DIR/config

. Environment variables can be set in the shell or via a

.env

file. The wrappers here auto-load

.env

from

PROJECT_DIR

(override with

ENV_FILE=/path/to/.env

Environment (.env or exported vars)

```
OPENAI_API_KEY
```
: required for OpenAI models (litellm reads this).
```
LITELLM_API_BASE
```
,
```
LITELLM_API_KEY
```
: use an OpenAI-compatible proxy/provider.
```
LITELLM_MODEL_RELEVANCE
```
,
```
LITELLM_MODEL_SUMMARY
```
: models for relevance and summarization (summary defaults to relevance model if unset).

LITELLM_TEMPERATURE_RELEVANCE

LITELLM_TEMPERATURE_SUMMARY

: lower for more deterministic output.

```
LITELLM_MAX_RETRIES
```
: retry count for LLM calls.
```
LITELLM_DROP_PARAMS=1
```
: drop unsupported params to avoid provider errors.
```
WINDOW_HOURS
```
,
```
APP_TZ
```
: recency window and timezone.
```
ARXIV_CATEGORIES
```
: comma-separated categories (default includes
```
cs.CL,cs.AI,cs.LG,stat.ML,cs.CR
```
).
```
ARXIV_API_BASE
```
,
```
HF_API_BASE
```
: override source endpoints if needed.
```
ARXIV_MAX_RESULTS
```
,
```
ARXIV_PAGE_SIZE
```
: arXiv paging limits.
```
MAX_CANDIDATES_PER_SOURCE
```
: cap candidates per source before LLM filtering.
```
FETCH_TIMEOUT_S
```
,
```
REQUEST_TIMEOUT_S
```
: source fetch and per-request timeouts.
```
ENABLE_PDF_TEXT=1
```
: include first-page PDF text in summaries; requires
```
PyMuPDF
```
(
```
pip install pymupdf
```
).
```
DATA_DIR
```
: location for
```
papers.sqlite3
```
.
```
CORS_ORIGINS
```
: comma-separated origins allowed by the API server (UI use).

Path overrides:

TOPICS_PATH

SETTINGS_PATH

AFFILIATION_BOOSTS_PATH

Config files

```
config/topics.json
```
: list of topics with
```
id
```
,
```
label
```
,
```
description
```
,
```
max_per_topic
```
, and
```
keywords
```
. The relevance classifier must output topic IDs exactly as defined here.
```
max_per_topic
```
also caps results in
```
GET /api/papers
```
when
```
apply_topic_caps=1
```
.

config/settings.json

: overrides fetch limits (

arxiv_max_results

arxiv_page_size

fetch_timeout_s

max_candidates_per_source

). Updated via

POST /api/settings

```
config/affiliations.json
```
: list of
```
{pattern, weight}
```
boosts applied by substring match over affiliations. Weights add up and are capped at 1.0. Invalid JSON disables boosts, so keep the file strict JSON (no trailing commas).

Mandatory workflow (follow step-by-step)

You first MUST open and read the configuration from the github repo: https://github.com/matanle51/agentic_paper_digest you downloaded:
- Load
```
config/topics.json
```
  ,
```
config/settings.json
```
  , and
```
config/affiliations.json
```
  (if present).
- Note current topic IDs, caps, and fetch limits before asking the user to change them.
ASK THE USER TO PROVIDE IT'S PREFERENCES ABOUT THE FOLLOWING (HELP THE USER):
- Topics of interest → update
```
config/topics.json
```
  (
```
topics[].id/label/description/keywords
```
  ,
```
max_per_topic
```
  ).
  Show current defaults and ask whether to keep or change them.
- Time window (hours) → set
```
WINDOW_HOURS
```
  (or pass
```
--window-hours
```
  to CLI) only if the user cares; otherwise keep default to 24h.
- ASK THE USER TO FILL THE FOLLOWING PARAMETERS (explain the user why are their intent):
```
ARXIV_CATEGORIES
```
  ,
```
ARXIV_MAX_RESULTS
```
  ,
```
ARXIV_PAGE_SIZE
```
  ,
```
MAX_CANDIDATES_PER_SOURCE
```
  .
  Ask whether to keep defaults and show the current values.
- Model/provider → set
```
OPENAI_API_KEY
```
  or
```
LITELLM_API_KEY
```
  (+
```
LITELLM_API_BASE
```
  if proxy), and set
```
LITELLM_MODEL_RELEVANCE
```
  /
```
LITELLM_MODEL_SUMMARY
```
  .
- Do NOT ask by default: timezone, quality vs cost, timeouts, PDF text, affiliation biasing, sources list. Use defaults unless the user requests changes.
Confirm workspace path: Ask where to clone/run. Default to
```
PROJECT_DIR="$HOME/agentic_paper_digest"
```
if the user doesn’t care. Never hardcode
```
/Users/...
```
paths.
Bootstrap the repo: Run the bootstrap script (unless the repo already exists and the user says to skip).
Create or verify
.env
:
- If
```
.env
```
  is missing, create it from
```
.env.example
```
  (in the repo), then ask the user to fill keys and any requested preferences.
- Ensure at least one of
```
OPENAI_API_KEY
```
  or
```
LITELLM_API_KEY
```
  is set before running.
Apply config changes:
- Edit JSON files directly (or use
```
POST /api/topics
```
  and
```
POST /api/settings
```
  if running the API).
Run the pipeline:
- Prefer
```
scripts/run_cli.sh
```
  for one-off JSON output.
- Use
```
scripts/run_api.sh
```
  only if the user explicitly asks for UI/API access or polling.
Report results:
- If results are sparse, suggest increasing
```
WINDOW_HOURS
```
  ,
```
ARXIV_MAX_RESULTS
```
  , or broadening topics.

Getting good results

Help the user define and keep topics focused and mutually exclusive so the classifier can choose the right IDs.
Use a stronger model for summaries than for relevance if quality matters.
If using openAI's model, defualy to gpt-5-mini for good tradeoff.
Increase
```
WINDOW_HOURS
```
or
```
ARXIV_MAX_RESULTS
```
when results are sparse, or lower them if results are too noisy.
Tune
```
ARXIV_CATEGORIES
```
to your research domains.
Enable PDF text (
```
ENABLE_PDF_TEXT=1
```
) when abstracts are too thin.
Use modest affiliation weights to bias ranking without swamping relevance.
BE PROACTIVE AND HELP THE USER TUNE THE SKILL FOR GOOD RESULTS!

Troubleshooting

Port 8000 busy: run
```
bash "{baseDir}/scripts/stop_api.sh"
```
or pass
```
--port
```
to the API command.
Empty results: increase
```
WINDOW_HOURS
```
or verify the API key in
```
.env
```
.
Missing API key errors: export
```
OPENAI_API_KEY
```
or
```
LITELLM_API_KEY
```
in the shell before running.

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Agentic Paper Digest

When to use

Prereqs

Get the code and install

Run (CLI preferred)

Run (API optional)

Outputs

Configuration

Mandatory workflow (follow step-by-step)

Getting good results

Troubleshooting

Quick Start

Manual Installation

TEAR & SHARE

Tags

获取微博热搜榜数据，返回热搜标题、热度值和跳转链接。当用户需要查看微博热搜、微博热点、微博热榜时使用此技能。支持自定义获取条数（默认50条）。

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