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docs: update README.md with metadata filtering documentation #168

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16 changes: 13 additions & 3 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -161,11 +161,14 @@ content = """
It is known that Maxwell...
"""
documents = [
Document.from_text(content)
Document.from_text(content, author="Einstein", topic="physics", year=1905)
]
insert_documents(documents, config=my_config)
```

> [!TIP]
> 📝 Documents can include metadata by passing keyword arguments to `Document.from_text()` or `Document.from_path()`. This metadata can later be used for filtering during retrieval.

You may also want to expand the document metadata before insertion:

```python
Expand Down Expand Up @@ -226,7 +229,12 @@ my_config = replace(my_config, search_method=vector_search) # Or `hybrid_search

# Retrieve relevant chunk spans with the configured search method
user_prompt = "How is intelligence measured?"
chunk_spans = retrieve_context(query=user_prompt, num_chunks=5, config=my_config)
chunk_spans = retrieve_context(
query=user_prompt,
num_chunks=5,
metadata_filter={"author": "Einstein"}, # Optional: filter by metadata
config=my_config
)

# Append a RAG instruction based on the user prompt and context to the message history
messages = [] # Or start with an existing message history
Expand Down Expand Up @@ -263,7 +271,9 @@ from raglite import hybrid_search, keyword_search, vector_search
user_prompt = "How is intelligence measured?"
chunk_ids_vector, _ = vector_search(user_prompt, num_results=20, config=my_config)
chunk_ids_keyword, _ = keyword_search(user_prompt, num_results=20, config=my_config)
chunk_ids_hybrid, _ = hybrid_search(user_prompt, num_results=20, config=my_config)
chunk_ids_hybrid, _ = hybrid_search(
user_prompt, num_results=20, metadata_filter={"topic": "physics"}, config=my_config
) # Filter results to only include chunks from documents with topic="physics" (works with any search method)

# Retrieve chunks
from raglite import retrieve_chunks
Expand Down