[#342] RAG - fix PDF format in vector database

llama_stack/providers/tests/memory/test_vector_store.py

@@ -0,0 +1,76 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import base64
+import mimetypes
+import os
+from pathlib import Path
+
+import pytest
+
+from llama_stack.apis.memory.memory import MemoryBankDocument, URL
+from llama_stack.providers.utils.memory.vector_store import content_from_doc
+
+DUMMY_PDF_PATH = Path(os.path.abspath(__file__)).parent / "fixtures" / "dummy.pdf"
+
+
+def read_file(file_path: str) -> bytes:
+    with open(file_path, "rb") as file:
+        return file.read()
+
+
+def data_url_from_file(file_path: str) -> str:
+    with open(file_path, "rb") as file:
+        file_content = file.read()
+
+    base64_content = base64.b64encode(file_content).decode("utf-8")
+    mime_type, _ = mimetypes.guess_type(file_path)
+
+    data_url = f"data:{mime_type};base64,{base64_content}"
+
+    return data_url
+
+
+class TestVectorStore:
+    @pytest.mark.asyncio
+    async def test_returns_content_from_pdf_data_uri(self):
+        data_uri = data_url_from_file(DUMMY_PDF_PATH)
+        doc = MemoryBankDocument(
+            document_id="dummy",
+            content=data_uri,
+            mime_type="application/pdf",
+            metadata={},
+        )
+        content = await content_from_doc(doc)
+        assert content == "Dummy PDF file"
+
+    @pytest.mark.asyncio
+    async def test_downloads_pdf_and_returns_content(self):
+        # Using GitHub to host the PDF file
+        url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf"
+        doc = MemoryBankDocument(
+            document_id="dummy",
+            content=url,
+            mime_type="application/pdf",
+            metadata={},
+        )
+        content = await content_from_doc(doc)
+        assert content == "Dummy PDF file"
+
+    @pytest.mark.asyncio
+    async def test_downloads_pdf_and_returns_content_with_url_object(self):
+        # Using GitHub to host the PDF file
+        url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf"
+        doc = MemoryBankDocument(
+            document_id="dummy",
+            content=URL(
+                uri=url,
+            ),
+            mime_type="application/pdf",
+            metadata={},
+        )
+        content = await content_from_doc(doc)
+        assert content == "Dummy PDF file"

llama_stack/providers/utils/memory/vector_store.py

@@ -45,6 +45,13 @@ def get_embedding_model(model: str) -> "SentenceTransformer":
     return loaded_model
 
 
+def parse_pdf(data: bytes) -> str:
+    # For PDF and DOC/DOCX files, we can't reliably convert to string
+    pdf_bytes = io.BytesIO(data)
+    pdf_reader = PdfReader(pdf_bytes)
+    return "\n".join([page.extract_text() for page in pdf_reader.pages])
+
+
 def parse_data_url(data_url: str):
     data_url_pattern = re.compile(
         r"^"
@@ -88,10 +95,7 @@ def content_from_data(data_url: str) -> str:
         return data.decode(encoding)
 
     elif mime_type == "application/pdf":
-        # For PDF and DOC/DOCX files, we can't reliably convert to string)
-        pdf_bytes = io.BytesIO(data)
-        pdf_reader = PdfReader(pdf_bytes)
-        return "\n".join([page.extract_text() for page in pdf_reader.pages])
+        return parse_pdf(data)
 
     else:
         log.error("Could not extract content from data_url properly.")
@@ -105,6 +109,9 @@ async def content_from_doc(doc: MemoryBankDocument) -> str:
         else:
             async with httpx.AsyncClient() as client:
                 r = await client.get(doc.content.uri)
+            if doc.mime_type == "application/pdf":
+                return parse_pdf(r.content)
+            else:
                 return r.text
 
     pattern = re.compile("^(https?://|file://|data:)")
@@ -114,6 +121,9 @@ async def content_from_doc(doc: MemoryBankDocument) -> str:
         else:
             async with httpx.AsyncClient() as client:
                 r = await client.get(doc.content)
+            if doc.mime_type == "application/pdf":
+                return parse_pdf(r.content)
+            else:
                 return r.text
 
     return interleaved_text_media_as_str(doc.content)