more relevant documents
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@@ -38,7 +38,7 @@ python script.py seed
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And then you can do your search
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And then you can do your search
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```bash
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```bash
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python script.py search --query "How does AI change industries?"
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python script.py search --query "What is NAF and how can it help?"
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```
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```
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## Roadmap
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## Roadmap
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@@ -21,10 +21,9 @@ def get_embedding(text, embedding_model):
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def seed_database(embedding_model):
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def seed_database(embedding_model):
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"""Seed the ChromaDB with example documents."""
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"""Seed the ChromaDB with example documents."""
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documents = [
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documents = [
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"Artificial Intelligence is transforming industries.",
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"NAF is a architectural framework.",
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"Machine learning helps computers learn from data.",
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"C3 Taxonomi helps define capabilties.",
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"Deep learning uses neural networks to process information.",
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"Architectural framework help organizations define architecture in standardized way with diffrent view points.",
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"RAG enhances language models with retrieved knowledge."
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]
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]
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for i, doc in enumerate(documents):
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for i, doc in enumerate(documents):
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