0a7bb114d2fe2b1bd5695ef8c163dbf1e6fefa79
Add removing of duplicates from pipeline. Add to sort step. Move score logic to robertaMetrics node.
Add removing of duplicates from pipeline. Add to sort step. Move score logic to robertaMetrics node.
AI models for identifying trigger events in disinformation analysis
Final Dissertation Submission Repository
Project Description
-- todo --
Solution Diagram
-- todo --
Repository Structure
├── run.sh # Bash script to run project elements from one place
├── data/ # Holder from project data
| ├── blocked.jsonl # Web search results blocked by the Iffy list
| ├── error.log # Log file containing critical exceptions
| ├── claims.json # Retreived claims from dbkf fetcher
| ├── dev-eng.csv
| ├── train-eng.csv # Normalized disinformation claims in CSV format from CLAN
| ├── Iffy.json # Iffy dataset of disinformation domains
| ├── input.jsonl # Response in cleaned format to give as context to agent
| ├── ranked.jsonl # Cleaned trigger event response from scorer frontend
| └── results.jsonl # Output from wrapper script, read and modified by scorer
├── literature/
| └── report.pdf # Final submission report
├── agent/ # Code for main project pipeline
| ├── agent.ts # Graph definition file
| ├── conditionals/ # Conditional translations
| ├── prompts/ # System promps, plus replacement code
| ├── tools/ # Internal and LLM facing tools
| └── utils/ # Logger
└── supporting/
├── dbkf/ # Tool to download claims from DBKF for use in wrapper
├── RAGAS_Service # Small python API to make RAGAS metrics available in the TS projects (required to run pipeline)
├── scorer # Frontend for labelling data, plus associated analysis
└── Wrapper # Bulk run pipeline on pre-downloaded claims
Description
Languages
Python
59.4%
TypeScript
39.7%
Shell
0.9%