# Vectorizer for hybrid search

**URL:** <https://forum.weaviate.io/t/vectorizer-for-hybrid-search/1263>\
**Category:** Support\
**Created:** [January 19, 2024, 3:08pm UTC](https://forum.weaviate.io/t/vectorizer-for-hybrid-search/1263 "2024-01-19T15:08:31Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![llmwill](https://avatars.discourse-cdn.com/v4/letter/l/858c86/32.png) [@llmwill](https://forum.weaviate.io/u/llmwill)\
**Post date:** [January 19, 2024, 3:08pm UTC](https://forum.weaviate.io/t/vectorizer-for-hybrid-search/1263/1 "2024-01-19T15:08:31Z")

</div>

Hi, I am kind of new to large language models. My goal is to implement hybrid search in rag. I am not quite sure on what vectorizer to make use of , any suggestions? (I was reading on the internet that bm25 requires sparse vectors and sematic search requires dense vectors, so how can I narrow it down to one type of vectorizer?)

Thank you!!

---

<div class="post-metadata">

**Author:** ![DudaNogueira](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/dudanogueira/32/7846_2.png) [@DudaNogueira](https://forum.weaviate.io/u/DudaNogueira)\
**Post date:** [January 22, 2024, 9:36pm UTC](https://forum.weaviate.io/t/vectorizer-for-hybrid-search/1263/2 "2024-01-22T21:36:32Z")

</div>

Hi @llmwill !!

Welcome! I believe you are at the best place to put all this together 🙂

We have some [great recipes](https://github.com/weaviate/recipes) that can get you up and running in no time:

This for example, will guide you on how to do a Generative Search/RAG:

> <https://github.com/weaviate/recipes/blob/main/generative-search/generative_search_openai.ipynb>

Now, this other recipe, is about hybrid search (but not generating an answer)

> <https://github.com/weaviate/recipes/blob/main/hybrid-search/hybrid_search_openai.ipynb>

Combining both, you should end up with something like:

```auto
generateTask = "Explain why these Jeopardy questions are under the Animals category."

result = (
  client.query
  .get("JeopardyQuestion", ["question"])
  .with_generate(grouped_task = generateTask)
  #.with_near_text({
  # "concepts": ["Elephants"]
  #})
  .with_hybrid(
        query = "Elephants",
        properties = ["question"],
        alpha = 0.80
    )
  .with_limit(3)
).do()

print(json.dumps(result, indent=1))

```

By the way, check out our events page. We have some great free workshops that will help you.

> **[Events & Webinars | Weaviate - Vector Database](https://weaviate.io/community/events)**
>
> Join us at conferences, meetups, webinars or workshops

Let me know if that helps 🙂