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README.md
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title: Chatbot AI
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emoji:
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colorFrom:
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colorTo: purple
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sdk: docker
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pinned: false
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license: mit
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app_port: 8080
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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# app
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## Installation
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Install the LangChain CLI if you haven't yet
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```bash
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pip install -U langchain-cli
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```
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## Adding packages
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```bash
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# adding packages from
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# https://github.com/langchain-ai/langchain/tree/master/templates
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langchain app add $PROJECT_NAME
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# adding custom GitHub repo packages
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langchain app add --repo $OWNER/$REPO
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# or with whole git string (supports other git providers):
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# langchain app add git+https://github.com/hwchase17/chain-of-verification
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# with a custom api mount point (defaults to `/{package_name}`)
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langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag
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```
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Note: you remove packages by their api path
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```bash
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langchain app remove my/custom/path/rag
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```
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## Setup LangSmith (Optional)
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LangSmith will help us trace, monitor and debug LangChain applications.
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LangSmith is currently in private beta, you can sign up [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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## Launch LangServe
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```bash
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langchain serve
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```
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## Running in Docker
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This project folder includes a Dockerfile that allows you to easily build and host your LangServe app.
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### Building the Image
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To build the image, you simply:
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```shell
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docker build . -t my-langserve-app
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```
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If you tag your image with something other than `my-langserve-app`,
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note it for use in the next step.
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### Running the Image Locally
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To run the image, you'll need to include any environment variables
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necessary for your application.
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In the below example, we inject the `OPENAI_API_KEY` environment
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variable with the value set in my local environment
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(`$OPENAI_API_KEY`)
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We also expose port 8080 with the `-p 8080:8080` option.
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```shell
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docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app
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```
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---
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title: Chatbot AI
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emoji: 💬
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colorFrom: blue
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colorTo: purple
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sdk: docker
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pinned: false
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license: mit
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app_port: 8080
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---
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+
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+
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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# app
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+
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+
## Installation
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+
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+
Install the LangChain CLI if you haven't yet
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+
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+
```bash
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pip install -U langchain-cli
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```
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+
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+
## Adding packages
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24 |
+
|
25 |
+
```bash
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+
# adding packages from
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+
# https://github.com/langchain-ai/langchain/tree/master/templates
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28 |
+
langchain app add $PROJECT_NAME
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+
|
30 |
+
# adding custom GitHub repo packages
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+
langchain app add --repo $OWNER/$REPO
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+
# or with whole git string (supports other git providers):
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33 |
+
# langchain app add git+https://github.com/hwchase17/chain-of-verification
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34 |
+
|
35 |
+
# with a custom api mount point (defaults to `/{package_name}`)
|
36 |
+
langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag
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37 |
+
```
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38 |
+
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39 |
+
Note: you remove packages by their api path
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40 |
+
|
41 |
+
```bash
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+
langchain app remove my/custom/path/rag
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43 |
+
```
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44 |
+
|
45 |
+
## Setup LangSmith (Optional)
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46 |
+
LangSmith will help us trace, monitor and debug LangChain applications.
|
47 |
+
LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
|
48 |
+
If you don't have access, you can skip this section
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49 |
+
|
50 |
+
|
51 |
+
```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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+
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+
## Launch LangServe
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+
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+
```bash
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langchain serve
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+
```
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+
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+
## Running in Docker
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64 |
+
|
65 |
+
This project folder includes a Dockerfile that allows you to easily build and host your LangServe app.
|
66 |
+
|
67 |
+
### Building the Image
|
68 |
+
|
69 |
+
To build the image, you simply:
|
70 |
+
|
71 |
+
```shell
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+
docker build . -t my-langserve-app
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+
```
|
74 |
+
|
75 |
+
If you tag your image with something other than `my-langserve-app`,
|
76 |
+
note it for use in the next step.
|
77 |
+
|
78 |
+
### Running the Image Locally
|
79 |
+
|
80 |
+
To run the image, you'll need to include any environment variables
|
81 |
+
necessary for your application.
|
82 |
+
|
83 |
+
In the below example, we inject the `OPENAI_API_KEY` environment
|
84 |
+
variable with the value set in my local environment
|
85 |
+
(`$OPENAI_API_KEY`)
|
86 |
+
|
87 |
+
We also expose port 8080 with the `-p 8080:8080` option.
|
88 |
+
|
89 |
+
```shell
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+
docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app
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```
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