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awesome-llama: https://github.com/micheldumontier/gba-rag

health llama3 llamaindex llm qdrant-vector-database

Score: 1.0986122886681098

Last synced: about 13 hours ago
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Repository metadata:

This is a demonstration project to provide LLM-based question answering over the website and documents of German Federal Joint Committee (G-BA).


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Committers metadata

Last synced: 4 days ago

Total Commits: 12
Total Committers: 1
Avg Commits per committer: 12.0
Development Distribution Score (DDS): 0.0

Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
Michel Dumontier m****r@g****m 12

Issue and Pull Request metadata

Last synced: 26 days ago

Total issues: 0
Total pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Total issue authors: 0
Total pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull request: 0
Bot issues: 0
Bot pull requests: 0

Past year issues: 0
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 0
Past year pull request authors: 0
Past year average comments per issue: 0
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

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Dependencies

vectordb/docker-compose.yml docker
  • qdrant/qdrant latest
requirements.txt pypi
  • fastembed-gpu *
  • ipykernel *
  • llama-index *
  • llama-index-core *
  • llama-index-embeddings-fastembed *
  • llama-index-llms-ollama *
  • llama-index-readers-file *
  • llama-index-vector-stores-qdrant ==0.2.10
  • llama_index.embeddings.ollama *
  • qdrant_client *
  • torch *