Add AstraDB tile (#109)

* add astradb-document-store.md

* add logo, license, and usage example

* add code examples

* remove unnecessary installations

* Update integrations/astradb-document-store.md

Co-authored-by: Tuana Çelik <[email protected]>

* add components and links to documentation

* rename file

* add retriever example

* white logo to make it visible on tile

* Update integrations/astradb.md

Co-authored-by: Tuana Çelik <[email protected]>

* Update integrations/astradb.md

Co-authored-by: Tuana Çelik <[email protected]>

* Update integrations/astradb.md

Co-authored-by: Tuana Çelik <[email protected]>

* remove DuplicatePolicy

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Co-authored-by: Tuana Çelik <[email protected]>

integrations/astradb.md

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+---
+layout: integration
+name: AstraDB
+description: A Document Store for storing and retrieval from AstraDB - built for Haystack 2.0.
+authors:
+  - name: Nicholas Brackley
+    socials:
+      github: hc33brackles
+  - name: deepset
+    socials:
+      github: deepset-ai
+      twitter: deepset_ai
+      linkedin: deepset-ai
+pypi: https://pypi.org/project/astra-haystack/
+repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/astra
+type: Document Store
+report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
+logo: /logos/astradb.png
+version: Haystack 2.0
+toc: true
+---
+
+### **Table of Contents**
+- [Overview](#overview)
+- [Installation](#installation)
+- [Usage](#usage)
+- [Note](#note)
+- [License](#license)
+
+## Overview
+
+
+DataStax Astra DB is a serverless vector database built on Apache Cassandra, and it supports vector-based search and auto-scaling. You can deploy it on AWS, GCP, or Azure and easily expand to one or more regions within those clouds for multi-region availability, low latency data access, data sovereignty, and to avoid cloud vendor lock-in. For more information, see the [DataStax documentation](https://docs.datastax.com/en/astra-serverless/docs/).
+
+
+This integration allows you to use AstraDB for document storage and retrieval in your Haystack 2.0 pipelines. This page provides instructions on how to initialize an AstraDB instance and connect with Haystack.
+
+## Components
+
+- [`AstraDocumentStore`](https://docs.haystack.deepset.ai/v2.0/docs/astradocumentstore). This component serves as a persistent data store for your Haystack documents, and supports a number of embedding models and vector dimensions.
+- [`AstraRetriever`](https://docs.haystack.deepset.ai/v2.0/docs/astraretriever) This is an embedding-based Retriever compatible with the Astra Document Store.
+
+
+## Initialization
+
+First you need to [sign up for a free DataStax account](https://astra.datastax.com/signup). Follow these instructions for [creating an AstraDB Database](https://docs.datastax.com/en/astra/astra-db-vector/databases/create-database.html#create-a-serverless-non-vector-database) in the Datastax console. Make sure you create a collection, a keyspace name, and an access token since you'll need those later.
+
+## Installation
+
+```console
+pip install astra-store
+```
+## Usage
+
+This package includes Astra Document Store and Astra Retriever classes that integrate with Haystack 2.0, allowing you to easily perform document retrieval or RAG with AstraDB, and include those functions in Haystack pipelines.
+
+In order to connect AstraDB with Haystack, you'll need these pieces of information from your Datastax console:
+- AstraDB ID
+- region
+- Astra collection name
+- Astra keyspace name
+- access token
+
+### how to use the `AstraDocumentStore`:
+
+```python
+from astra_haystack.document_store import AstraDocumentStore
+from haystack import Document
+
+astra_id = os.getenv("ASTRA_DB_ID", "")
+astra_region = os.getenv("ASTRA_DB_REGION", "us-east-2")
+astra_application_token = os.getenv("ASTRA_DB_APPLICATION_TOKEN", "")
+collection_name = os.getenv("COLLECTION_NAME", "haystack_integration")
+keyspace_name = os.getenv("KEYSPACE_NAME", "astra_haystack_test")
+
+document_store = AstraDocumentStore(
+    astra_id=astra_id,
+    astra_region=astra_region,
+    astra_collection=collection_name,
+    astra_keyspace=keyspace_name,
+    astra_application_token=astra_application_token,
+)
+
+document_store.write_documents([
+    Document(content="This is first"),
+    Document(content="This is second")
+    ])
+print(document_store.count_documents())
+```
+
+### How to use the `AstraRetriever`
+
+```python
+from astra_haystack.document_store import AstraDocumentStore
+from astra_haystack.retriever import AstraRetriever
+
+from haystack import Document, Pipeline
+from haystack.components.embedders import SentenceTransformersTextEmbedder, SentenceTransformersDocumentEmbedder
+
+astra_id = os.getenv("ASTRA_DB_ID", "")
+astra_region = os.getenv("ASTRA_DB_REGION", "us-east-2")
+astra_application_token = os.getenv("ASTRA_DB_APPLICATION_TOKEN", "")
+collection_name = os.getenv("COLLECTION_NAME", "haystack_integration")
+keyspace_name = os.getenv("KEYSPACE_NAME", "astra_haystack_test")
+
+document_store = AstraDocumentStore(
+    astra_id=astra_id,
+    astra_region=astra_region,
+    astra_collection=collection_name,
+    astra_keyspace=keyspace_name,
+    astra_application_token=astra_application_token,
+)
+
+model = "sentence-transformers/all-mpnet-base-v2"
+
+documents = [Document(content="There are over 7,000 languages spoken around the world today."),
+						Document(content="Elephants have been observed to behave in a way that indicates a high level of self-awareness, such as recognizing themselves in mirrors."),
+						Document(content="In certain parts of the world, like the Maldives, Puerto Rico, and San Diego, you can witness the phenomenon of bioluminescent waves.")]
+
+document_embedder = SentenceTransformersDocumentEmbedder(model=model_name_or_path)  
+document_embedder.warm_up()
+documents_with_embeddings = document_embedder.run(documents)
+
+document_store.write_documents(documents_with_embeddings.get("documents"))
+query_pipeline = Pipeline()
+query_pipeline.add_component("text_embedder", SentenceTransformersTextEmbedder(model=model_name_or_path))
+query_pipeline.add_component("retriever", AstraRetriever(document_store=document_store))
+query_pipeline.connect("text_embedder.embedding", "retriever.query_embedding")
+
+query = "How many languages are there?"
+
+result = query_pipeline.run({"text_embedder": {"text": query}})
+
+print(result['retriever']['documents'][0])
+```
+
+### Note:
+Please note that the current version of Astra JSON API does not support the following operators:
+$lt, $lte, $gt, $gte, $nin, $not, $neq 
+As well as filtering with none values (these won't be inserted as the result is stored as json document, and it doesn't store nones)
+
+### License
+
+`astra-store` is distributed under the terms of the [Apache-2.0](https://spdx.org/licenses/Apache-2.0.html) license.