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 # Templates
 
-A list of all template repos
+Highlighting a few different categories of templates
 
-⭐Retrieval Augmented Generation Chatbot: Build a chatbot over your data. Uses OpenAI and Pinecone.
+## ⭐ Popular
 
-⭐Extraction with OpenAI Functions: Do extraction of structured data from unstructured data. Uses OpenAI function calling.
+These are some of the more popular templates to get started with.
 
-⭐Local Retrieval Augmented Generation: Build a chatbot over your data. Uses only local tooling: Ollama, GPT4all, Chroma.
+- [Retrieval Augmented Generation Chatbot](../rag-conversation): Build a chatbot over your data. Defaults to OpenAI and Pinecone.
+- [Extraction with OpenAI Functions](../extraction-openai-functions): Do extraction of structured data from unstructured data. Uses OpenAI function calling.
+- [Local Retrieval Augmented Generation](../rag-chroma-private): Build a chatbot over your data. Uses only local tooling: Ollama, GPT4all, Chroma.
+- [OpenAI Functions Agent](../openai-functions-agent): Build a chatbot that can take actions. Uses OpenAI function calling and Tavily.
+- [XML Agent](../xml-agent): Build a chatbot that can take actions. Uses Anthropic and You.com.
 
-⭐OpenAI Functions Agent: Build a chatbot that can take actions. Uses OpenAI function calling and Tavily.
 
-⭐XML Agent: Build a chatbot that can take actions. Uses Anthropic and You.com.
+## 📥 Advanced Retrieval
+
+These templates cover advanced retrieval techniques.
+
+- [Reranking](../rag-pinecone-rerank): This retrieval technique uses Cohere's reranking endpoint to rerank documents from an initial retrieval step.
+- [Anthropic Iterative Search](../anthropic-iterative-search): This retrieval technique uses iterative prompting to determine what to retrieve and whether the retriever documents are good enough.
+- [Neo4j Parent Document Retrieval](../neo4j-parent): This retrieval technique stores embeddings for smaller chunks, but then returns larger chunks to pass to the model for generation.
+- [Semi-Structured RAG](../rag-semi-structured): The template shows how to do retrieval over semi-structured data (e.g. data that involves both text and tables).
+
+## 🔍Advanced Retrieval - Query Transformation
+
+A selection of advanced retrieval methods that involve transforming the original user query.
+
+- [Hypothetical Document Embeddings](../hyde): A retrieval technique that generates a hypothetical document for a given query, and then uses the embedding of that document to do semantic search. [Paper](https://arxiv.org/abs/2212.10496).
+- [Rewrite-Retrieve-Read](../rewrite-retrieve-read): A retrieval technique that rewrites a given query before passing it to a search engine. [Paper](https://arxiv.org/abs/2305.14283).
+- [Step-back QA Prompting](../stepback-qa-prompting): A retrieval technique that generates a "step-back" question and then retrieves documents relevant to both that question and the original question. [Paper](https://arxiv.org/abs//2310.06117).
+- [RAG-Fusion](../rag-fusion): A retrieval technique that generates multiple queries and then reranks the retrieved documents using reciprocal rank fusion. [Article](https://towardsdatascience.com/forget-rag-the-future-is-rag-fusion-1147298d8ad1).
+- [Multi-Query Retriever](../rag-pinecone-multi-query): This retrieval technique uses an LLM to generate multiple queries and then fetches documents for all queries.
+
+
+## 🧠Advanced Retrieval - Query Construction
+
+A selection of advanced retrieval methods that involve constructing a query in a separate DSL from natural language.
+
+- [Elastic Query Generator](../elastic-query-generator): Generate elastic search queries from natural language.
+- [Neo4j Cypher Generation](../neo4j-cypher): Generate cypher statements from natural language. Available with a ["full text" option](../neo4j-cypher-ft) as well.
+- [Supabase Self Query](../self-query-supabase): Parse a natural language query into a semantic query as well as a metadata filter for Supabase.
+
+
+## 🦙 OSS Models
+
+These templates use OSS models.
+
+- [Local Retrieval Augmented Generation](../rag-chroma-private): Build a chatbot over your data. Uses only local tooling: Ollama, GPT4all, Chroma.
+- [SQL Question Answering (Replicate)](../sql-llama2): Question answering over a SQL database, using Llama2 hosted on [Replicate](https://replicate.com/).
+- [SQL Question Answering (LlamaCpp)](../sql-llamacpp): Question answering over a SQL database, using Llama2 through [LlamaCpp](https://github.com/ggerganov/llama.cpp).
+- [SQL Question Answering (Ollama)](../sql-ollama): Question answering over a SQL database, using Llama2 through [Ollama](https://github.com/jmorganca/ollama).
+
+## ⛏️ Extraction
+
+Extract data in a structured format
+- [Extraction Using OpenAI Functions](../extraction-openai-functions): Extract information from text using OpenAI Function Calling.
+- [Extraction Using Anthropic Functions](../extraction-anthropic-functions): Extract information from text using a LangChain wrapper around the Anthropic endpoints intended to simulate function calling.
+- [Extract BioTech Plate Data](../plate-chain): Extract plate data from messy Excel spreadsheets into a more normalized format.
+
+## 🤖 Agents
+- [OpenAI Functions Agent](../openai-functions-agent): Build a chatbot that can take actions. Uses OpenAI function calling and Tavily.
+- [XML Agent](../xml-agent): Build a chatbot that can take actions. Uses Anthropic and You.com.
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