calpoly-csai / calpoly-csai/swanton
Getting Started With Rasa -- conversational design
Open
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 3
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Description
Objective
Initialize the codebase with code for the Rasa framework with an initial set of FAQs
Key Results
- updated README with
- created a markdown file with for intent classification by Rasa
- created a markdown file with for response selection by Rasa
- created a markdown file with for stories selection by Rasa
- entitites too
Details
Additional context
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the README and the existing markdown files for intent classification and stories, then compare the requested response-selection and entity content with the linked Rasa documentation. Done means the README and the missing markdown files cover intents, responses, stories, and entities for the initial FAQ set.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai, documentation
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100