Skip to main content

LangGraph-based AI landscape synthesis for banking/FS consulting

Project description

ai-landscape-review

LangGraph-based editorial pipeline for generating AI landscape snapshots across weekly, monthly, quarterly, and yearly cadences.

Usage

ai-landscape-review --period weekly --dry-run
ai-landscape-review --period monthly

Pipeline

The graph is:

Gather -> Gap Analysis -> Research -> Synthesise -> Write

Research is skipped when gap analysis returns NO GAPS.

Notes

  • LLM calls are made via claude --print; no LangChain model wrappers are used.
  • The tool reads from ~/notes/AI News Log.md and ~/notes/AI Landscape.md.
  • In --dry-run mode, the synthesis is printed and no files are modified.
  • LaunchAgent plist templates are generated under launchd/.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

theoria-0.1.0.tar.gz (9.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

theoria-0.1.0-py3-none-any.whl (9.5 kB view details)

Uploaded Python 3

File details

Details for the file theoria-0.1.0.tar.gz.

File metadata

  • Download URL: theoria-0.1.0.tar.gz
  • Upload date:
  • Size: 9.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.2

File hashes

Hashes for theoria-0.1.0.tar.gz
Algorithm Hash digest
SHA256 4d2bcdf53c9fa6f0221ac221a82b190989ee35e3e680fe67ab744f9bade09178
MD5 f843e4c618e0cfdafc0c5ed27e150624
BLAKE2b-256 cdc1eaf373b966127f7725963de208975e8b514d5f5fe51f751b44da87b841df

See more details on using hashes here.

File details

Details for the file theoria-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: theoria-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 9.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.8.2

File hashes

Hashes for theoria-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 81aedffd14318fbd20baf99c74f068fde52d41b4ead7aa5f0665c9558bd3cf55
MD5 2df91399387dcd777fded019c9cfe943
BLAKE2b-256 30373f8501f5abc628b1331ed933f12cc8a48df02bbe2051a174b4cbdeab128d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page