Slack Perplexity
B+ 85 completed
Other
containerized / python · tiny
40
Files
2,594
LOC
1
Frameworks
6
Languages
Pipeline State
completedRun ID
#1545734Phase
doneProgress
0%Started
2026-04-16 23:32:01Finished
2026-04-16 23:32:01LLM tokens
0Pipeline Metadata
Stage
CatalogedDecision
proceedNovelty
24.38Framework unique
—Isolation
—Last stage change
2026-05-10 03:34:51Deduplication group #47900
Member of a group with 239 similar repo(s) — canonical #189084 view group →
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🧪 Code Distillation
Browse all specs →AI Prompt
Build me a containerized Slack bot using Python that integrates with Perplexity AI to answer questions with cited sources. The bot needs to handle multiple interaction methods: direct messages, @mentions in channels, and using the `/ask` slash command. It must intelligently use conversation context, understanding follow-up questions from threads or channels, and automatically resolving user mentions (`<@UID>`) to display names. The final response should format Markdown correctly for Slack and include clickable citations. Please structure the project using Docker Compose for deployment.
python slack perplexity bot docker ai api containerization
Generated by gemma4:latest
Catalog Information
Build me a containerized Slack bot using Python that integrates with Perplexity AI to answer questions with cited sources. The bot needs to handle multiple interaction methods: direct messages, @mentions in channels, and using the /ask slash command. It must intelligently use conversation context, understanding follow-up questions from threads or channels, and automatically resolving user mentions (<@UID>) to display names. The final response should format Markdown correctly for Slack and in
Tags
python slack perplexity bot docker ai api containerization
Quality Score
B+
85.2/100
Structure
78
Code Quality
100
Documentation
64
Testing
85
Practices
82
Security
100
Dependencies
90
Strengths
- CI/CD pipeline configured (github_actions)
- Good test coverage (108% test-to-source ratio)
- Consistent naming conventions (snake_case)
- Good security practices — no major issues detected
- Containerized deployment (Docker)
- Properly licensed project
Recommendations
- Add a linter configuration to enforce code style consistency
Languages
Frameworks
pytest
Symbols
function26
constant8
variable5
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