# Cohere Cookbooks: Build AI Agents and Solutions

In order to help developers get up and running on using Cohere's functionality, we've put together [some cookbooks](/guides/cookbooks-cookbooks) that work through common use cases.

They're organized by categories like "Agents," "Cloud," and "Summarization" to allow you to quickly find what you're looking for. To jump to a particular use-case category, click one of the links below:

- [Agents](/guides/cookbooks-cookbooks#agents)
- [Open Source Software Integrations](/guides/cookbooks-cookbooks#oss)
- [Search and Embeddings](/guides/cookbooks-cookbooks#search)
- [Cloud](/guides/cookbooks-cookbooks#cloud)
- [RAG](/guides/cookbooks-cookbooks#rag)
- [Summarization](/guides/cookbooks-cookbooks#summarization)

:::callout{intent="info" title="Note"}
The code examples in this section use the Cohere v1 API. The v2 API counterparts will be published at a later time.
:::

Here are some of the ones we think are most exciting!

- [A Data Analyst Agent Built with Cohere and Langchain](/guides/cookbooks-data-analyst-agent) - Build a data analyst agent with Python and Cohere's Command R+ mode and Langchain.
- [Creating a QA Bot From Technical Documentation](/guides/cookbooks-creating-a-qa-bot) - Create a chatbot that answers user questions based on technical documentation using Cohere embeddings and LlamaIndex.
- [Multilingual Search with Cohere and Langchain](/guides/cookbooks-multilingual-search) - Perform searches across a corpus of mixed-language documents with Cohere and Langchain.
- [Using Redis with Cohere](/guides/integrations-redis-and-cohere#building-a-retrieval-pipeline-with-cohere-and-redis) - Learn how to use Cohere's text vectorizer with Redis to create a semantic search index.
- [Wikipedia Semantic Search with Cohere + Weaviate](/guides/cookbooks-wikipedia-search-with-weaviate) - Search 10 million Wikipedia vectors with Cohere's multilingual model and Weaviate's public dataset.
- [Long Form General Strategies](/guides/cookbooks-long-form-general-strategies) - Techniques to address lengthy documents exceeding the context window of LLMs.

## Related pages

- [Changelog](../changelog.md)
- [Cohere](../index.md)
- [Cohere API](./cohere-api-index.md)
- [Cohere Labs](./cohere-labs-index.md)
- [Cohere Platform](./cohere-platform-index.md)
- [Cookbooks](./cookbooks-index.md)
- [Deployment Options](./deployment-options-index.md)
- [Embeddings (Vectors, Search, Retrieval)](./embeddings-vectors-search-retrieval-index.md)
- [Get Started](./get-started-index.md)
- [Going to Production](./going-to-production-index.md)

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