Begin by ensuring you have access to your Azure Blob Storage account. Obtain the necessary credentials such as the Account Name and Account Key. These credentials will be used to authenticate and access the blobs programmatically.

On your local machine or server, install the Azure SDK for Python and the Typesense client using pip. These libraries will provide the necessary functions to interact with Azure Blob Storage and Typesense.

```bash
pip install azure-storage-blob typesense
```

Write a Python script to connect to Azure Blob Storage and list the blobs in your container. Then, download the blobs that contain the data you want to move to Typesense.

```python
from azure.storage.blob import BlobServiceClient

blob_service_client = BlobServiceClient.from_connection_string("your_connection_string")
container_client = blob_service_client.get_container_client("your_container_name")

blobs_list = container_client.list_blobs()
for blob in blobs_list:
blob_client = container_client.get_blob_client(blob)
with open(blob.name, "wb") as download_file:
download_file.write(blob_client.download_blob().readall())
```

Once downloaded, parse and prepare your data in a format that Typesense accepts. Typesense typically requires data in JSON format. Ensure each document is structured according to your Typesense schema.

```python
import json

# Example of transforming data
with open("your_blob_data.json", "r") as file:
data = json.load(file)

formatted_data = [{"id": str(i), "field1": item["field1"], "field2": item["field2"]} for i, item in enumerate(data)]
```

Ensure you have a running Typesense server. If not, you can start one using Docker:

```bash
docker run -p 8108:8108 -v/tmp/data:/data typesense/typesense:0.23.1 \
--data-dir /data --api-key=xyz
```

Replace `xyz` with a secure API key of your choice.

Use the Typesense client to create a collection with the appropriate schema to hold your data. This includes defining fields and their types.

```python
import typesense

client = typesense.Client({
'nodes': [{
'host': 'localhost',
'port': '8108',
'protocol': 'http'
}],
'api_key': 'xyz',
'connection_timeout_seconds': 2
})

schema = {
'name': 'your_collection_name',
'fields': [
{'name': 'id', 'type': 'string'},
{'name': 'field1', 'type': 'string'},
{'name': 'field2', 'type': 'string'}
]
}

client.collections.create(schema)
```

Finally, index the prepared data into the Typesense collection. Use batch indexing for efficiency if you have a large dataset.

```python
client.collections['your_collection_name'].documents.import_(formatted_data)
```

By following these steps, you will have successfully moved your data from Azure Blob Storage to Typesense without relying on third-party connectors or integrations.