add ocr

docs.md

@@ -0,0 +1,167 @@
+# vlite Documentation
+
+vlite is a simple(and blazing fast) vector database. It allows you to store and retrieve data semantically using embeddings.
+
+## Installation
+
+```bash
+pip install vlite
+```
+
+### Installation with PDF OCR Support
+
+To enable PDF OCR support, you need to install the `vlite[ocr]` extra:
+
+```bash  
+pip install vlite[ocr]
+```
+
+## Usage
+
+### Importing VLite
+
+```python
+from vlite import VLite
+```
+
+### Creating a VLite Instance
+
+
+```python
+vlite = VLite(collection="my_collection")
+```
+
+- `collection` (optional): The name of the collection file. If not provided, a default name will be generated based on the current timestamp.
+- `device` (optional): The device to use for embedding ('cpu' or 'cuda'). Default is 'cpu'.
+- `model_name` (optional): The name of the embedding model to use. Default is 'mixedbread-ai/mxbai-embed-large-v1'.
+
+### Data types supported
+
+- `text`: A string containing the text data.
+- `.txt`: A path to a text file locally.
+- `.pdf/.docx`: A path to a PDF file locally.
+- `.csv`: A path to a CSV file locally.
+- `.pptx`: A path to a PPTX file locally.
+- `webpage`: A URL to a webpage.
+
+
+### Adding Text to the Collection
+
+To add text to the collection, use the `add` method:
+
+```python
+vlite.add(data, metadata=None)
+```
+
+- `data`: The text data to be added. It can be a string, a dictionary containing text, id, and/or metadata, or a list of strings or dictionaries.
+- `metadata` (optional): Additional metadata to be appended to each text entry.
+
+The `add` method returns a list of tuples, each containing the ID of the added text, the updated vectors array, and the metadata.
+
+### Retrieving Similar Texts
+
+To retrieve similar texts from the collection, use the `retrieve` method:
+
+```python
+vlite.retrieve(text=None, top_k=5, metadata=None)
+```
+
+- `text` (optional): The query text for finding similar texts.
+- `top_k` (optional): The number of top similar texts to retrieve. Default is 5.
+- `metadata` (optional): Metadata to filter the retrieved texts.
+
+The `retrieve` method returns a tuple containing a list of similar texts, their similarity scores, and metadata (if applicable).
+
+### Deleting Items
+
+To delete items from the collection, use the `delete` method:
+
+```python
+vlite.delete(ids)
+```
+
+- `ids`: A single ID or a list of IDs of the items to delete.
+
+The `delete` method returns the number of items deleted from the collection.
+
+### Updating Items
+
+To update an item in the collection, use the `update` method:
+
+```python
+vlite.update(id, text=None, metadata=None, vector=None)
+```
+
+- `id`: The ID of the item to update.
+- `text` (optional): The updated text content of the item.
+- `metadata` (optional): The updated metadata of the item.
+- `vector` (optional): The updated embedding vector of the item.
+
+The `update` method returns `True` if the item was successfully updated, `False` otherwise.
+
+### Retrieving Items
+
+To retrieve items from the collection based on IDs and/or metadata, use the `get` method:
+
+```python
+vlite.get(ids=None, where=None)
+```
+
+- `ids` (optional): List of IDs to retrieve. If provided, only items with the specified IDs will be returned.
+- `where` (optional): Metadata filter to apply. Items matching the filter will be returned.
+
+The `get` method returns a list of retrieved items, each item being a tuple of (text, metadata).
+
+### Counting Items
+
+To get the number of items in the collection, use the `count` method:
+
+```python
+vlite.count()
+```
+
+The `count` method returns the count of items in the collection.
+
+### Saving the Collection
+
+To save the current state of the collection to a file, use the `save` method:
+
+```python
+vlite.save()
+```
+
+The `save` method saves the collection to the specified file.
+
+### Clearing the Collection
+
+To clear the entire collection, removing all items and resetting the attributes, use the `clear` method:
+
+```python
+vlite.clear()
+```
+
+The `clear` method clears the collection and saves the changes.
+
+### Getting Collection Information
+
+To print information about the collection, including the number of items, collection file path, and the embedding model used, use the `info` method:
+
+```python
+vlite.info()
+```
+
+The `info` method prints the collection information.
+
+### Dumping Collection Data
+
+To dump the collection data to a dictionary for serialization, use the `dump` method:
+
+```python
+vlite.dump()
+```
+
+The `dump` method returns a dictionary containing the collection data.
+
+## License
+
+AGPL-3.0 License

requirements.txt

@@ -13,6 +13,7 @@ setuptools==65.3.0
 tiktoken==0.4.0
 torch==2.2.2
 tqdm==4.65.0
-transformers==4.37.0
+transformers==4.36.2
 chromadb==0.4.24
 qdrant-client
+git+https://github.com/sdan/surya.git

setup.py

@@ -17,5 +17,9 @@
         'usearch',
         'PyPDF2',
         'docx2txt',
+        'surya-ocr'
     ],
+    # extras_require={
+    #     'ocr': ['surya-ocr']
+    # },
 )