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# Jina
This page covers how to use the Jina ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific Jina wrappers.
## Installation and Setup
- Install the Python SDK with `pip install jina`
- Get a Jina AI Cloud auth token from [here](https://cloud.jina.ai/settings/tokens) and set it as an environment variable (`JINA_AUTH_TOKEN`)
## Wrappers
### Embeddings
There exists a Jina Embeddings wrapper, which you can access with
```python
from langchain.embeddings import JinaEmbeddings
```
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For a more detailed walkthrough of this, see [this notebook](/docs/modules/data_connection/text_embedding/integrations/jina.html)
docs: update Jina ecosystem (#7149)
Documentation update for [Jina
ecosystem](https://python.langchain.com/docs/ecosystem/integrations/jina)
and `langchain-serve` in the deployments section to latest features.
@hwchase17
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## Deployment
[Langchain-serve](https://github.com/jina-ai/langchain-serve), powered by Jina, helps take LangChain apps to production with easy to use REST/WebSocket APIs and Slack bots.
### Usage
Install the package from PyPI.
```bash
pip install langchain-serve
```
Wrap your LangChain app with the `@serving` decorator.
```python
# app.py
from lcserve import serving
@serving
def ask(input: str) -> str:
from langchain import LLMChain, OpenAI
from langchain.agents import AgentExecutor, ZeroShotAgent
tools = [...] # list of tools
prompt = ZeroShotAgent.create_prompt(
tools, input_variables=["input", "agent_scratchpad"],
)
llm_chain = LLMChain(llm=OpenAI(temperature=0), prompt=prompt)
agent = ZeroShotAgent(
llm_chain=llm_chain, allowed_tools=[tool.name for tool in tools]
)
agent_executor = AgentExecutor.from_agent_and_tools(
agent=agent,
tools=tools,
verbose=True,
)
return agent_executor.run(input)
```
Deploy on Jina AI Cloud with `lc-serve deploy jcloud app`. Once deployed, we can send a POST request to the API endpoint to get a response.
```bash
curl -X 'POST' 'https://<your-app>.wolf.jina.ai/ask' \
-d '{
"input": "Your Quesion here?",
"envs": {
"OPENAI_API_KEY": "sk-***"
}
}'
```
You can also self-host the app on your infrastructure with Docker-compose or Kubernetes. See [here](https://github.com/jina-ai/langchain-serve#-self-host-llm-apps-with-docker-compose-or-kubernetes) for more details.
Langchain-serve also allows to deploy the apps with WebSocket APIs and Slack Bots both on [Jina AI Cloud](https://cloud.jina.ai/) or self-hosted infrastructure.