Create README.md

README.md

@@ -0,0 +1,41 @@
+---
+language:
+- en
+---
+This repository contains the index files required for the `SearchWikipediaTool` of the [grammar-based-agents](https://github.com/krasserm/grammar-based-agents) project.
+
+It is based on the `krasserm/wikipedia-2023-11-en-embed-mxbai-int8-binary` dataset and contains the following files:
+
+- `faiss-ubinary.index`: [Faiss](https://github.com/facebookresearch/faiss) index file containing the `binary` embeddings
+- `usearch-int8-index`: [usearch](https://github.com/unum-cloud/usearch) index files containing the `int8` embeddings
+- `document-url-mappings.sqlite`: [SQLite](https://www.sqlite.org/) database file containing mappings from document URLs to text chunk indices
+
+The following code snippet demonstrates how to use the index files with the `SearchWikipediaTool`:
+
+```python
+from sentence_transformers import CrossEncoder, SentenceTransformer
+from gba.tools.search import SearchWikipediaTool
+from gba.tools.search import ContentExtractor
+from gba.client import Llama3Instruct, LlamaCppClient
+from gba.utils import Scratchpad
+
+llm_model = Llama3Instruct(llm=LlamaCppClient(url="http://localhost:8084/completion", temperature=-1))
+embedding_model = SentenceTransformer("mixedbread-ai/mxbai-embed-large-v1", device="cuda")
+rerank_model = CrossEncoder("mixedbread-ai/mxbai-rerank-large-v1", device="cuda")
+
+search_wikipedia = SearchWikipediaTool(
+   llm=llm_model,
+   embedding_model=embedding_model,
+   rerank_model=rerank_model,
+   top_k_nodes=10,
+   top_k_related_documents=1,
+   top_k_related_nodes=3,
+   extractor=ContentExtractor(model=llm_model),
+)
+
+response = search_wikipedia.run(
+   task="Search Wikipedia for the launch date of the first iPhone.",
+   request="",
+   scratchpad=Scratchpad(),
+)
+```