Update README.md

README.md

@@ -1,91 +1,91 @@
----
-title: Chatbot AI
-emoji: 🐠
-colorFrom: purple
-colorTo: purple
-sdk: docker
-pinned: false
-license: mit
-app_port: 8080
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
-# 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
-```
+---
+title: Chatbot AI
+emoji: 💬
+colorFrom: blue
+colorTo: purple
+sdk: docker
+pinned: false
+license: mit
+app_port: 8080
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 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
+```