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Merge branch 'main' into chat-data-suggestion-styling
2 parents e33f8df + c5d9b9b commit 0eb8dc3

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-54
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‎js/chat/chat.scss‎

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@@ -93,6 +93,8 @@ shiny-chat-message {
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// images and avatars are full-bleed
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height: 100%;
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width: 100%;
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max-width: 100%;
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max-height: 100%;
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margin: 0 !important;
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object-fit: contain;
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}
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max-height: 66%;
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max-width: 66%;
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}
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// Provide .border-0 as a way to opt-out of border container
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&:has(> .border-0) {
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border: none;
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border-radius: unset;
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overflow: unset;
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}
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}
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/* Vertically center the 2nd column (message content) */

‎shiny/templates/chat/llm-enterprise/aws-bedrock-anthropic/_template.json‎

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{
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"type": "app",
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"id": "chat-ai-anthropic-aws",
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"title": "Chat AI using Anthropic via AWS Bedrock"
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"title": "Chat AI using Anthropic via AWS Bedrock",
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"next_steps": [
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"Put your Bedrock credentials in the `template.env` file and rename it to `.env`.",
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"Run the app with `shiny run app.py`."
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],
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"follow_up": [
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{
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"type": "info",
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"text": "Need help connecting to Bedrock?"
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},
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{
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"type": "action",
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"text": "Learn more at https://posit-dev.github.io/chatlas/reference/ChatBedrockAnthropic.html"
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}
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]
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}

‎shiny/templates/chat/llm-enterprise/aws-bedrock-anthropic/app.py‎

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load_dotenv()
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chat_model = ChatBedrockAnthropic(
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model="anthropic.claude-3-sonnet-20240229-v1:0",
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# aws_secret_key=os.getenv("AWS_SECRET_KEY"),
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# aws_access_key=os.getenv("AWS_ACCESS_KEY"),
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# aws_region=os.getenv("AWS_REGION"),
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# aws_account_id=os.getenv("AWS_ACCOUNT_ID"),
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)
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# Set some Shiny page options
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# Define a callback to run when the user submits a message
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@chat.on_user_submit
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async def handle_user_input(user_input: str):
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response = chat_model.stream(user_input)
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response = await chat_model.stream_async(user_input)
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await chat.append_message_stream(response)

‎shiny/templates/chat/llm-enterprise/aws-bedrock-anthropic/requirements.txt‎

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shiny
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python-dotenv
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tokenizers
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chatlas
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anthropic[bedrock]

‎shiny/templates/chat/llm-enterprise/aws-bedrock-anthropic/template.env‎

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# Once you provided your API key, rename this file to .env
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# The load_dotenv() in the app.py will then load this env variable
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AWS_SECRET_KEY=<Your AWS info here>
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AWS_ACCESS_KEY=<Your AWS info here>
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AWS_REGION=<Your AWS info here>
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AWS_ACCOUNT_ID=<Your AWS info here>

‎shiny/templates/chat/llm-enterprise/azure-openai/_template.json‎

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{
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"type": "app",
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"id": "chat-ai-azure-openai",
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"title": "Chat AI using OpenAI via Azure"
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"title": "Chat AI using OpenAI via Azure",
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"next_steps": [
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"Put your Azure credentials in the `template.env` file and rename it to `.env`.",
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"Run the app with `shiny run app.py`."
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],
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"follow_up": [
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{
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"type": "info",
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"text": "Need help connecting to Azure?"
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},
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{
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"type": "action",
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"text": "Learn more at https://posit-dev.github.io/chatlas/reference/ChatAzureOpenAI.html"
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}
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]
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}

‎shiny/templates/chat/llm-enterprise/azure-openai/app.py‎

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# Define a callback to run when the user submits a message
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@chat.on_user_submit
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async def handle_user_input(user_input: str):
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response = chat_model.stream(user_input)
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response = await chat_model.stream_async(user_input)
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await chat.append_message_stream(response)

‎shiny/templates/chat/llm-enterprise/azure-openai/requirements.txt‎

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shiny
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python-dotenv
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tokenizers
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chatlas
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openai

‎shiny/templates/chat/llm-enterprise/azure-openai/template.env‎

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# Once you provided your API key, rename this file to .env
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# The load_dotenv() in the app.py will then load this env variable
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AZURE_OPENAI_API_KEY=<Your Azure OpenAI API key>

‎shiny/templates/chat/llms/anthropic/_template.json‎

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{
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"type": "app",
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"id": "chat-ai-anthropic",
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"title": "Chat AI using Anthropic"
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"title": "Chat AI using Anthropic",
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"next_steps": [
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"Put your Anthropic API key in the `template.env` file and rename it to `.env`.",
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"Run the app with `shiny run app.py`."
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],
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"follow_up": [
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{
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"type": "info",
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"text": "Need help obtaining an API key?"
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},
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{
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"type": "action",
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"text": "Learn how to obtain one at https://posit-dev.github.io/chatlas/reference/ChatAnthropic.html"
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}
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]
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}

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