Add Needle integration (#262)

* Add Needle integration

* Fix broken link

integrations/needle.md

@@ -0,0 +1,101 @@
+---
+layout: integration
+name: Needle
+description: Use Needle document store and retriever in Haystack.
+authors:
+    - name: Needle Team
+      socials:
+        twitter: needlexAI
+        linkedin: needlexai
+pypi: https://pypi.org/project/needle-haystack-ai
+repo: https://github.com/JANHMS/needle-haystack
+type: Document Store
+report_issue: https://github.com/JANHMS/needle-haystack/issues
+logo: /logos/needle.png
+version: Haystack 2.x
+---
+
+# Needle RAG tools for Haystack
+
+[![PyPI - Version](https://img.shields.io/pypi/v/needle-haystack-ai.svg)](https://pypi.org/project/needle-haystack-ai)
+[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/needle-haystack-ai.svg)](https://pypi.org/project/needle-haystack-ai)
+
+This package provides `NeedleDocumentStore` and `NeedleEmbeddingRetriever` component for use in Haystack projects.
+
+## Usage ⚡️
+
+Get started by installing the package via `pip`.
+
+```bash
+pip install needle-haystack-ai
+```
+
+### API Keys
+
+We will show you building a common RAG pipeline using Needle tools and OpenAI generator.
+For using these tools you must set your environment variables, `NEEDLE_API_KEY` and `OPENAI_API_KEY` respectively.
+
+You can get your Needle API key from from [Developer settings](https://needle-ai.com/dashboard/settings).
+
+### Example Pipeline 🧱
+
+In Needle document stores are called collections. For detailed information, see our [docs](https://docs.needle-ai.com).
+You can create a reference to your Needle collection using `NeedleDocumentStore` and use `NeedleEmbeddingRetriever` to retrieve documents from it.
+
+```python
+from needle_haystack import NeedleDocumentStore, NeedleEmbeddingRetriever
+
+document_store = NeedleDocumentStore(collection_id="<your-collection-id>")
+retriever = NeedleEmbeddingRetriever(document_store=document_store)
+```
+
+Use the retriever in a Haystack pipeline. Example:
+
+```python
+from haystack import Pipeline
+from haystack.components.generators import OpenAIGenerator
+from haystack.components.builders import PromptBuilder
+
+prompt_template = """
+Given the following retrieved documents, generate a concise and informative answer to the query:
+
+Query: {{query}}
+Documents:
+{% for doc in documents %}
+    {{ doc.content }}
+{% endfor %}
+
+Answer:
+"""
+
+prompt_builder = PromptBuilder(template=prompt_template)
+llm = OpenAIGenerator()
+
+# Add components to pipeline
+pipeline = Pipeline()
+pipeline.add_component("retriever", retriever)
+pipeline.add_component("prompt_builder", prompt_builder)
+pipeline.add_component("llm", llm)
+
+# Connect the components
+pipeline.connect("retriever", "prompt_builder.documents")
+pipeline.connect("prompt_builder", "llm")
+```
+
+Run your RAG pipeline:
+
+```python
+prompt = "What is the topic of the news?"
+
+result = basic_rag_pipeline.run({
+    "retriever": {"text": prompt},
+    "prompt_builder": {"query": prompt}
+})
+
+# Print final answer
+print(result['llm']['replies'][0])
+```
+
+# Support 📞
+
+For detailed guides, take a look at our [docs](https://docs.needle-ai.com). If you have questions or requests you can contact us in our [Discord channel](https://discord.gg/JzJcHgTyZx).