rename retriever

integrations/pinecone/examples/example.py

@@ -0,0 +1,50 @@
+# Install the Pinecone integration, Haystack will come as a dependency
+# Install also some optional dependencies needed for Markdown conversion and text embedding
+# pip install -U pinecone-haystack markdown-it-py mdit_plain "sentence-transformers>=2.2.0"
+
+# Download some markdown files to index
+# git clone https://github.com/anakin87/neural-search-pills
+
+
+# Create the indexing Pipeline and index some documents
+
+import glob
+
+from haystack import Pipeline
+from haystack.components.converters import MarkdownToDocument
+from haystack.components.embedders import SentenceTransformersDocumentEmbedder, SentenceTransformersTextEmbedder
+from haystack.components.preprocessors import DocumentSplitter
+from haystack.components.writers import DocumentWriter
+from pinecone_haystack import PineconeDocumentStore
+from pinecone_haystack.dense_retriever import PineconeEmbeddingRetriever
+
+file_paths = glob.glob("neural-search-pills/pills/*.md")
+
+document_store = PineconeDocumentStore(
+    api_key="YOUR-PINECONE-API-KEY", environment="gcp-starter", index="default", namespace="default", dimension=768
+)
+
+indexing = Pipeline()
+indexing.add_component("converter", MarkdownToDocument())
+indexing.add_component("splitter", DocumentSplitter(split_by="sentence", split_length=2))
+indexing.add_component("embedder", SentenceTransformersDocumentEmbedder())
+indexing.add_component("writer", DocumentWriter(document_store))
+indexing.connect("converter", "splitter")
+indexing.connect("splitter", "embedder")
+indexing.connect("embedder", "writer")
+
+indexing.run({"converter": {"sources": file_paths}})
+
+
+# Create the querying Pipeline and try a query
+
+querying = Pipeline()
+querying.add_component("embedder", SentenceTransformersTextEmbedder())
+querying.add_component("retriever", PineconeEmbeddingRetriever(document_store=document_store, top_k=3))
+querying.connect("embedder", "retriever")
+
+results = querying.run({"embedder": {"text": "What is Question Answering?"}})
+
+for doc in results["retriever"]["documents"]:
+    print(doc)
+    print("-" * 10)