Merge pull request #13 from voyage-ai/main

Add Voyage Query Engine

llama_hub/llama_packs/voyage_query_engine/README.md

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+# Voyage Query Engine Pack
+
+Create a query engine using GPT4 and [Voyage AI](https://docs.voyageai.com/embeddings/) Embeddings.
+
+## CLI Usage
+
+You can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:
+
+```bash
+llamaindex-cli download-llamapack VoyageQueryEnginePack --download-dir ./voyage_pack
+```
+
+You can then inspect the files at `./voyage_pack` and use them as a template for your own project.
+
+## Code Usage
+
+You can download the pack to a the `./voyage_pack` directory:
+
+```python
+from llama_index.llama_packs import download_llama_pack
+
+# download and install dependencies
+VoyageQueryEnginePack = download_llama_pack(
+  "VoyageQueryEnginePack", "./voyage_pack"
+)
+
+# You can use any llama-hub loader to get documents!
+voyage_pack = VoyageQueryEnginePack(documents)
+```
+
+From here, you can use the pack, or inspect and modify the pack in `./voyage_pack`.
+
+The `run()` function is a light wrapper around `index.as_query_engine().query()`.
+
+```python
+response = voyage_pack.run("What did the author do growing up?", similarity_top_k=2)
+```
+
+You can also use modules individually.
+
+```python
+# Use the index directly
+index = voyage_pack.index
+query_engine = index.as_query_engine()
+retriver = index.as_retriever()
+```

llama_hub/llama_packs/voyage_query_engine/__init__.py

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+from llama_hub.llama_packs.voyage_query_engine.base import VoyageQueryEnginePack
+
+__all__ = ["VoyageQueryEnginePack"]

llama_hub/llama_packs/voyage_query_engine/base.py

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+from typing import Any, Dict, List
+from llama_index import ServiceContext, VectorStoreIndex
+from llama_index.llms import OpenAI
+from llama_index.embeddings import VoyageEmbedding
+from llama_index.llama_pack.base import BaseLlamaPack
+from llama_index.schema import Document
+import os
+
+class VoyageQueryEnginePack(BaseLlamaPack):
+    def __init__(self, documents: List[Document]) -> None:
+
+        llm = OpenAI(model='gpt-4')
+        embed_model = VoyageEmbedding(model_name="voyage-01", voyage_api_key=os.environ['VOYAGE_API_KEY'])
+        service_context = ServiceContext.from_defaults(
+            llm=llm, embed_model=embed_model
+        )
+        self.llm = llm
+        self.index = VectorStoreIndex.from_documents(
+            documents, service_context=service_context
+        )
+
+    def get_modules(self) -> Dict[str, Any]:
+        """Get modules."""
+        return {"llm": self.llm, "index": self.index}
+
+    def run(self, query_str: str, **kwargs: Any) -> Any:
+        """Run the pipeline."""
+        query_engine = self.index.as_query_engine(**kwargs)
+        return query_engine.query(query_str)

llama_hub/llama_packs/voyage_query_engine/requirements.txt

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+openai
+voyageai