mirror of
https://github.com/hwchase17/langchain
synced 2024-11-06 03:20:49 +00:00
68 lines
2.0 KiB
Markdown
68 lines
2.0 KiB
Markdown
# sql-research-assistant
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This package does research over a SQL database
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## Usage
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This package relies on multiple models, which have the following dependencies:
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- OpenAI: set the `OPENAI_API_KEY` environment variables
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- Ollama: [install and run Ollama](https://python.langchain.com/docs/integrations/chat/ollama)
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- llama2 (on Ollama): `ollama pull llama2` (otherwise you will get 404 errors from Ollama)
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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 sql-research-assistant
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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 sql-research-assistant
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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 sql_research_assistant import chain as sql_research_assistant_chain
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add_routes(app, sql_research_assistant_chain, path="/sql-research-assistant")
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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/sql-research-assistant/playground](http://127.0.0.1:8000/sql-research-assistant/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/sql-research-assistant")
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``` |