patch unstructured embeddings gen example

examples/llm_and_nlp/unstructured-embeddings-gen.py

@@ -12,11 +12,11 @@
     group_broken_paragraphs,
     replace_unicode_quotes,
 )
-from unstructured.embed.huggingface import (
+from unstructured.partition.pdf import partition_pdf
+from unstructured_ingest.embed.huggingface import (
     HuggingFaceEmbeddingConfig,
     HuggingFaceEmbeddingEncoder,
 )
-from unstructured.partition.pdf import partition_pdf
 
 from datachain import C, DataChain, DataModel, File
 
@@ -43,6 +43,7 @@ def process_pdf(file: File) -> Iterator[Chunk]:
         chunks = partition_pdf(file=f, chunking_strategy="by_title", strategy="fast")
 
     # Clean the chunks and add new columns
+    chunks_cleaned = []
     for chunk in chunks:
         chunk.apply(
             lambda text: clean(
@@ -51,16 +52,17 @@ def process_pdf(file: File) -> Iterator[Chunk]:
         )
         chunk.apply(replace_unicode_quotes)
         chunk.apply(group_broken_paragraphs)
+        chunks_cleaned.append({"text": chunk.text})
 
     # create embeddings
-    chunks_embedded = embedding_encoder.embed_documents(chunks)
+    chunks_embedded = embedding_encoder.embed_documents(chunks_cleaned)
 
     # Add new rows to DataChain
     for chunk in chunks_embedded:
         yield Chunk(
             key=file.path,
-            text=chunk.text,
-            embeddings=chunk.embeddings,
+            text=chunk.get("text"),
+            embeddings=chunk.get("embeddings"),
         )
 
 

pyproject.toml

@@ -106,7 +106,8 @@ examples = [
   "numpy>=1,<2",
   "defusedxml",
   "accelerate",
-  "unstructured[pdf, embed-huggingface]",
+  "unstructured_ingest",
+  "unstructured[pdf]",
   "pdfplumber==0.11.4",
   "huggingface_hub[hf_transfer]",
   "onnx==1.16.1"