Metadata-Version: 2.1
Name: zeitkapsel-api
Version: 0.1.0
Summary: 
Author: Your Name
Author-email: you@example.com
Requires-Python: >=3.11,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: aiosqlite (>=0.20.0,<0.21.0)
Requires-Dist: langchain (>=0.2.11,<0.3.0)
Requires-Dist: langchain-cli (>=0.0.22,<0.0.23)
Requires-Dist: langchain-openai (>=0.1.6,<0.2.0)
Requires-Dist: langgraph (==0.1.15)
Requires-Dist: langserve[server] (>=0.0.30)
Requires-Dist: psycopg (>=3.2.1,<4.0.0)
Requires-Dist: psycopg2-binary (>=2.9.9,<3.0.0)
Requires-Dist: pydantic (>=2.7.4,<3.0.0)
Requires-Dist: python-dotenv (>=1.0.1,<2.0.0)
Requires-Dist: uvicorn (>=0.23.2,<0.24.0)
Description-Content-Type: text/markdown

# my-app

## Installation

Install the LangChain CLI if you haven't yet

```bash
pip install -U langchain-cli
```

## Adding packages

```bash
# adding packages from 
# https://github.com/langchain-ai/langchain/tree/master/templates
langchain app add $PROJECT_NAME

# adding custom GitHub repo packages
langchain app add --repo $OWNER/$REPO
# or with whole git string (supports other git providers):
# langchain app add git+https://github.com/hwchase17/chain-of-verification

# with a custom api mount point (defaults to `/{package_name}`)
langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag
```

Note: you remove packages by their api path

```bash
langchain app remove my/custom/path/rag
```

## Setup LangSmith (Optional)
LangSmith will help us trace, monitor and debug LangChain applications. 
LangSmith is currently in private beta, you can sign up [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"
```

## Launch LangServe

```bash
langchain serve
```

## Running in Docker

This project folder includes a Dockerfile that allows you to easily build and host your LangServe app.

### Building the Image

To build the image, you simply:

```shell
docker build . -t my-langserve-app
```

If you tag your image with something other than `my-langserve-app`,
note it for use in the next step.

### Running the Image Locally

To run the image, you'll need to include any environment variables
necessary for your application.

In the below example, we inject the `OPENAI_API_KEY` environment
variable with the value set in my local environment
(`$OPENAI_API_KEY`)

We also expose port 8080 with the `-p 8080:8080` option.

```shell
docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app
```

