mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
163ef35dd1
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.
75 lines
2.0 KiB
Markdown
75 lines
2.0 KiB
Markdown
# Research assistant
|
|
|
|
This template implements a version of
|
|
[GPT Researcher](https://github.com/assafelovic/gpt-researcher) that you can use
|
|
as a starting point for a research agent.
|
|
|
|
## Environment Setup
|
|
|
|
The default template relies on `ChatOpenAI` and `DuckDuckGo`, so you will need the
|
|
following environment variable:
|
|
|
|
- `OPENAI_API_KEY`
|
|
|
|
And to use the `Tavily` LLM-optimized search engine, you will need:
|
|
|
|
- `TAVILY_API_KEY`
|
|
|
|
## Usage
|
|
|
|
To use this package, you should first have the LangChain CLI installed:
|
|
|
|
```shell
|
|
pip install -U langchain-cli
|
|
```
|
|
|
|
To create a new LangChain project and install this as the only package, you can do:
|
|
|
|
```shell
|
|
langchain app new my-app --package research-assistant
|
|
```
|
|
|
|
If you want to add this to an existing project, you can just run:
|
|
|
|
```shell
|
|
langchain app add research-assistant
|
|
```
|
|
|
|
And add the following code to your `server.py` file:
|
|
```python
|
|
from research_assistant import chain as research_assistant_chain
|
|
|
|
add_routes(app, research_assistant_chain, path="/research-assistant")
|
|
```
|
|
|
|
(Optional) Let's now configure LangSmith.
|
|
LangSmith will help us trace, monitor and debug LangChain applications.
|
|
You can sign up for LangSmith [here](https://smith.langchain.com/).
|
|
If you don't have access, you can skip this section
|
|
|
|
|
|
```shell
|
|
export LANGCHAIN_TRACING_V2=true
|
|
export LANGCHAIN_API_KEY=<your-api-key>
|
|
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
|
|
```
|
|
|
|
If you are inside this directory, then you can spin up a LangServe instance directly by:
|
|
|
|
```shell
|
|
langchain serve
|
|
```
|
|
|
|
This will start the FastAPI app with a server is running locally at
|
|
[http://localhost:8000](http://localhost:8000)
|
|
|
|
We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
|
|
We can access the playground at [http://127.0.0.1:8000/research-assistant/playground](http://127.0.0.1:8000/research-assistant/playground)
|
|
|
|
We can access the template from code with:
|
|
|
|
```python
|
|
from langserve.client import RemoteRunnable
|
|
|
|
runnable = RemoteRunnable("http://localhost:8000/research-assistant")
|
|
``` |