SQLite v2 API source connector (#300)

Author: Paul-Cornell

api-reference/ingest/source-connectors/sqlite.mdx

@@ -0,0 +1,23 @@
+---
+title: SQLite
+---
+
+import NewDocument from '/snippets/general-shared-text/new-document.mdx';
+
+<NewDocument />
+
+import SharedContentSQLite from '/snippets/sc-shared-text/sqlite-cli-api.mdx';
+import SharedAPIKeyURL from '/snippets/general-shared-text/api-key-url.mdx';
+
+<SharedContentSQLite/>
+<SharedAPIKeyURL/>
+
+Now call the Unstructured Ingest CLI or the Unstructured Ingest Python library. The destination connector can be any of the ones supported. This example uses the local destination connector:
+
+import SQLiteAPISh from '/snippets/source_connectors/sqlite.sh.mdx';
+import SQLiteAPIPyV2 from '/snippets/source_connectors/sqlite.v2.py.mdx';
+
+<CodeGroup>
+  <SQLiteAPISh />
+  <SQLiteAPIPyV2 />
+</CodeGroup>

mint.json

@@ -176,6 +176,7 @@
               "open-source/ingest/source-connectors/sharepoint",
               "open-source/ingest/source-connectors/slack",
               "open-source/ingest/source-connectors/snowflake",
+              "open-source/ingest/source-connectors/sqlite",
               "open-source/ingest/source-connectors/wikipedia"
             ]
           },
@@ -331,6 +332,7 @@
               "api-reference/ingest/source-connectors/sharepoint",
               "api-reference/ingest/source-connectors/slack",
               "api-reference/ingest/source-connectors/snowflake",
+              "api-reference/ingest/source-connectors/sqlite",
               "api-reference/ingest/source-connectors/wikipedia"
             ]
           },

open-source/ingest/source-connectors/sqlite.mdx

@@ -0,0 +1,27 @@
+---
+title: SQLite
+---
+
+import NewDocument from '/snippets/general-shared-text/new-document.mdx';
+
+<NewDocument />
+
+import SharedContentSQLite from '/snippets/sc-shared-text/sqlite-cli-api.mdx';
+
+<SharedContentSQLite/>
+
+Now call the Unstructured Ingest CLI or the Unstructured Ingest Python library. The destination connector can be any of the ones supported. This example uses the local destination connector.
+
+This example sends data to Unstructured API services for processing by default. To process data locally instead, see the instructions at the end of this page.
+
+import SQLiteSh from '/snippets/source_connectors/sqlite.sh.mdx';
+import SQLitePyV2 from '/snippets/source_connectors/sqlite.v2.py.mdx';
+
+<CodeGroup>
+  <SQLiteSh />
+  <SQLitePyV2 />
+</CodeGroup>
+
+import SharedPartitionByAPIOSS from '/snippets/ingest-configuration-shared/partition-by-api-oss.mdx';
+
+<SharedPartitionByAPIOSS/>

snippets/sc-shared-text/sqlite-cli-api.mdx

@@ -0,0 +1,9 @@
+Connect SQLite to your preprocessing pipeline, and use the Unstructured Ingest CLI or the Unstructured Ingest Python library to batch process all your documents and store structured outputs locally on your filesystem.
+
+You will need: 
+
+import SharedSQLite from '/snippets/general-shared-text/sqlite.mdx';
+import SharedSQLiteCLIAPI from '/snippets/general-shared-text/sqlite-cli-api.mdx';
+
+<SharedSQLite />
+<SharedSQLiteCLIAPI />

snippets/source_connectors/sqlite.sh.mdx

@@ -0,0 +1,18 @@
+```bash CLI
+#!/usr/bin/env bash
+
+# Chunking and embedding are optional.
+
+unstructured-ingest \
+  sqlite \
+    --database-path $SQLITE_DB_PATH \
+    --table-name elements \
+    --id-column id \
+    --download-dir $LOCAL_FILE_DOWNLOAD_DIR \
+    --chunking-strategy by_title \
+    --embedding-provider huggingface \
+    --output-dir $LOCAL_FILE_OUTPUT_DIR \
+    --partition-by-api \
+    --api-key $UNSTRUCTURED_API_KEY \
+    --partition-endpoint $UNSTRUCTURED_API_URL
+```

snippets/source_connectors/sqlite.v2.py.mdx

@@ -0,0 +1,52 @@
+```python Python Ingest v2
+import os
+
+from unstructured_ingest.v2.pipeline.pipeline import Pipeline
+from unstructured_ingest.v2.interfaces import ProcessorConfig
+
+from unstructured_ingest.v2.processes.connectors.sql.sqlite import (
+    SQLiteIndexerConfig,
+    SQLiteDownloaderConfig,
+    SQLiteConnectionConfig,
+    SQLiteAccessConfig
+)
+
+from unstructured_ingest.v2.processes.partitioner import PartitionerConfig
+from unstructured_ingest.v2.processes.chunker import ChunkerConfig
+from unstructured_ingest.v2.processes.embedder import EmbedderConfig
+
+from unstructured_ingest.v2.processes.connectors.local import (
+    LocalConnectionConfig,
+    LocalUploaderConfig
+)
+
+# Chunking and embedding are optional.
+
+if __name__ == "__main__":
+    Pipeline.from_configs(
+        context=ProcessorConfig(),
+        indexer_config=SQLiteIndexerConfig(
+            table_name="elements",
+            id_column="id"
+        ),
+        downloader_config=SQLiteDownloaderConfig(download_dir=os.getenv("LOCAL_FILE_DOWNLOAD_DIR")),
+        source_connection_config=SQLiteConnectionConfig(
+            access_config=SQLiteAccessConfig(),
+            database_path=os.getenv("SQLITE_DB_PATH")
+        ),
+        partitioner_config=PartitionerConfig(
+            partition_by_api=True,
+            api_key=os.getenv("UNSTRUCTURED_API_KEY"),
+            partition_endpoint=os.getenv("UNSTRUCTURED_API_URL"),
+            additional_partition_args={
+                "split_pdf_page": True,
+                "split_pdf_allow_failed": True,
+                "split_pdf_concurrency_level": 15
+            }
+        ),
+        chunker_config=ChunkerConfig(chunking_strategy="by_title"),
+        embedder_config=EmbedderConfig(embedding_provider="huggingface"),
+        destination_connection_config=LocalConnectionConfig(),
+        uploader_config=LocalUploaderConfig(output_dir=os.getenv("LOCAL_FILE_OUTPUT_DIR"))
+    ).run()
+```