> For the complete documentation index, see [llms.txt](https://genaistack.aiplanet.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://genaistack.aiplanet.com/components/retriever/quickstart.md).

# Quickstart

Currently we have support only for **LangChain Retriever**.

LangChainRetriever doesn't require any specific configuration from user

```py
from genai_stack.retriever import LangChainRetriever

retriever = LangChainRetriever.from_kwargs()

response = retriever.retrieve(query)
```

**Important Note**: A Retriever component is never used alone because it is depended on prompt engine, model and atleast any one of these two components vectordb or memory.

You can look more into prompt engine component to know why do you have to provide atleast any one of the component vectordb or memory. In short, The prompt engine component decides which prompt template to be used based on the availability of components.

Here is a small example of retriever along with its dependent components.

```py
from genai_stack.stack.stack import Stack
from genai_stack.prompt_engine.engine import PromptEngine
from genai_stack.model import OpenAIGpt35Model
from genai_stack.memory import ConversationBufferMemory
from genai_stack.retriever import LangChainRetriever

promptengine = PromptEngine.from_kwargs(should_validate = False)
model = OpenAIGpt35Model.from_kwargs(parameters={"openai_api_key": openai_api_key})
memory = ConversationBufferMemory.from_kwargs()
retriever = LangChainRetriever.from_kwargs()
Stack(model=model, prompt_engine=promptengine, retriever=retriever, memory=memory)

response = retriever.retrieve("Your query")
```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://genaistack.aiplanet.com/components/retriever/quickstart.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
