Add Scavio integration

[scavio-ai]

Adds a listing for the Scavio integration, following up on deepset-ai/haystack-core-integrations#3486 (we published the component as a standalone package per the maintainer's recommendation).

• Component: ScavioWebSearch — web search returning Haystack Documents and source links, mirroring TavilyWebSearch/ExaWebSearch.
• PyPI: https://pypi.org/project/scavio-haystack (pip install scavio-haystack)
• Repo: https://github.com/scavio-ai/haystack-scavio

Adds integrations/scavio.md and logos/scavio.png.

[vercel]

@scavio-ai is attempting to deploy a commit to the deepset Team on Vercel.

A member of the Team first needs to authorize it.

[scavio-ai]

Hi @bogdankostic, following up on deepset-ai/haystack-core-integrations#3486 — we published the integration ourselves per your suggestion.

• PyPI: https://pypi.org/project/scavio-haystack (pip install scavio-haystack, tested live against the API)
• Repo (from the custom-component template): https://github.com/scavio-ai/haystack-scavio

This PR just adds the listing (integrations/scavio.md + logos/scavio.png). The only failing check is the Vercel preview, which needs authorization since this is a fork PR. Thanks for the pointer!

[bilgeyucel]

Thanks for the PR! Left a comment

[bilgeyucel]

We dont need this section as the first part clearly shows how to use the component

Suggested change

	#### In a Pipeline
	```python
	from haystack import Pipeline
	from haystack.components.builders import PromptBuilder
	from haystack.components.generators import OpenAIGenerator
	from haystack_integrations.components.websearch.scavio import ScavioWebSearch
	template = """
	Given the following web search results, answer the question.
	Results:
	{% for doc in documents %}{{ doc.content }}
	{% endfor %}
	Question: {{ query }}
	Answer:
	"""
	pipe = Pipeline()
	pipe.add_component("search", ScavioWebSearch(top_k=5))
	pipe.add_component("prompt_builder", PromptBuilder(template=template))
	pipe.add_component("llm", OpenAIGenerator())
	pipe.connect("search.documents", "prompt_builder.documents")
	pipe.connect("prompt_builder", "llm")
	query = "What is Haystack by deepset?"
	result = pipe.run(data={"search": {"query": query}, "prompt_builder": {"query": query}})
	print(result["llm"]["replies"][0])
	```

[scavio-ai]

Good call — removed the "In a Pipeline" section. Thanks for the review!