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https://github.com/hwchase17/langchain
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- **Description:** Added integration instructions for Remembrall.
- **Tag maintainer:** @hwchase17
- **Twitter handle:** @raunakdoesdev
Fun fact, this project originated at the Modal Hackathon in NYC where it
won the Best LLM App prize sponsored by Langchain. Thanks for your
support 🦜
54 lines
2.6 KiB
Markdown
54 lines
2.6 KiB
Markdown
# Remembrall
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This page covers how to use the [Remembrall](https://remembrall.dev) ecosystem within LangChain.
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## What is Remembrall?
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Remembrall gives your language model long-term memory, retrieval augmented generation, and complete observability with just a few lines of code.
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It works as a light-weight proxy on top of your OpenAI calls and simply augments the context of the chat calls at runtime with relevant facts that have been collected.
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## Setup
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To get started, [sign in with Github on the Remembrall platform](https://remembrall.dev/login) and copy your [API key from the settings page](https://remembrall.dev/dashboard/settings).
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Any request that you send with the modified `openai_api_base` (see below) and Remembrall API key will automatically be tracked in the Remembrall dashboard. You **never** have to share your OpenAI key with our platform and this information is **never** stored by the Remembrall systems.
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### Enable Long Term Memory
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In addition to setting the `openai_api_base` and Remembrall API key via `x-gp-api-key`, you should specify a UID to maintain memory for. This will usually be a unique user identifier (like email).
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```python
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from langchain.chat_models import ChatOpenAI
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chat_model = ChatOpenAI(openai_api_base="https://remembrall.dev/api/openai/v1",
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model_kwargs={
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"headers":{
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"x-gp-api-key": "remembrall-api-key-here",
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"x-gp-remember": "user@email.com",
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}
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})
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chat_model.predict("My favorite color is blue.")
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import time; time.sleep(5) # wait for system to save fact via auto save
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print(chat_model.predict("What is my favorite color?"))
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```
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### Enable Retrieval Augmented Generation
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First, create a document context in the [Remembrall dashboard](https://remembrall.dev/dashboard/spells). Paste in the document texts or upload documents as PDFs to be processed. Save the Document Context ID and insert it as shown below.
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```python
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from langchain.chat_models import ChatOpenAI
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chat_model = ChatOpenAI(openai_api_base="https://remembrall.dev/api/openai/v1",
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model_kwargs={
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"headers":{
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"x-gp-api-key": "remembrall-api-key-here",
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"x-gp-context": "document-context-id-goes-here",
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}
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})
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print(chat_model.predict("This is a question that can be answered with my document."))
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```
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