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Updated titles into a consistent format. Fixed links to the diagrams. Fixed typos. Note: The Templates menu in the navbar is now sorted by the file names. I'll try sorting the navbar menus by the page titles, not the page file names.
76 lines
2.2 KiB
Markdown
76 lines
2.2 KiB
Markdown
# Hypothetical Document Embeddings (HyDE)
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This template uses `HyDE` with RAG.
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`Hyde` is a retrieval method that stands for `Hypothetical Document Embeddings`. It is a method used to enhance retrieval by generating a hypothetical document for an incoming query.
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The document is then embedded, and that embedding is utilized to look up real documents that are similar to the hypothetical document.
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The underlying concept is that the hypothetical document may be closer in the embedding space than the query.
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For a more detailed description, see the[Precise Zero-Shot Dense Retrieval without Relevance Labels](https://arxiv.org/abs/2212.10496) paper.
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## Environment Setup
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Set the `OPENAI_API_KEY` environment variable to access the OpenAI models.
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## Usage
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To use this package, you should first have the LangChain CLI installed:
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```shell
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pip install -U langchain-cli
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```
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To create a new LangChain project and install this as the only package, you can do:
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```shell
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langchain app new my-app --package hyde
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```
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If you want to add this to an existing project, you can just run:
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```shell
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langchain app add hyde
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```
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And add the following code to your `server.py` file:
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```python
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from hyde.chain import chain as hyde_chain
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add_routes(app, hyde_chain, path="/hyde")
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```
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(Optional) Let's now configure LangSmith.
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LangSmith will help us trace, monitor and debug LangChain applications.
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You can sign up for LangSmith [here](https://smith.langchain.com/).
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If you don't have access, you can skip this section
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```shell
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export LANGCHAIN_TRACING_V2=true
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export LANGCHAIN_API_KEY=<your-api-key>
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export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
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```
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If you are inside this directory, then you can spin up a LangServe instance directly by:
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```shell
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langchain serve
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```
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This will start the FastAPI app with a server is running locally at
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[http://localhost:8000](http://localhost:8000)
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We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
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We can access the playground at [http://127.0.0.1:8000/hyde/playground](http://127.0.0.1:8000/hyde/playground)
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We can access the template from code with:
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```python
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from langserve.client import RemoteRunnable
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runnable = RemoteRunnable("http://localhost:8000/hyde")
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```
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