As a service, I want to monitor unanswered questions on platforms like Twitter, identify them using a question mark at the end, and provide answers efficiently and accurately using an LLM (Language Model) agent.
Acceptance Criteria
[ ] The system continuously monitors Twitter posts for unanswered questions.
[ ] Detected questions are filtered to ensure relevance and appropriateness for public response.
[ ] The LLM agent generates accurate and contextually relevant answers.
[ ] Answers are posted as replies to the original Twitter post or appropriately delivered.
[ ] The system adheres to rate limits and usage guidelines provided by the Twitter API.
[ ] User feedback on answers is monitored, and the LLM model is fine-tuned accordingly.
[ ] The system logs all activities, including questions parsed and answers posted, for review and monitoring.
[ ] Appropriate fallback and error handling processes are in place to deal with unrecognized or ambiguous questions.
sequenceDiagram
participant T as Twitter API
participant M as Monitoring Service
participant L as Language Model
M->>T: Fetch recent posts
loop Check for '?'
T-->>M: Return posts
end
M->>L: Send unanswered questions
L-->>M: Generate answers
M->>T: Post answers as replies
MonitoringAndEvaluation Specification
As a service, I want to monitor unanswered questions on platforms like Twitter, identify them using a question mark at the end, and provide answers efficiently and accurately using an LLM (Language Model) agent.
Acceptance Criteria