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# Basic Chat
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This example shows how to create a basic chat flow. It demonstrates how to create a chatbot that can remember previous interactions and use the conversation history to generate next message.
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Tools used in this flow:
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- `llm` tool
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## Prerequisites
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Install promptflow sdk and other dependencies in this folder:
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```bash
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pip install -r requirements.txt
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```
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## What you will learn
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In this flow, you will learn
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- how to compose a chat flow.
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- prompt template format of LLM tool chat api. Message delimiter is a separate line containing "#", role name and colon: "# system:", "# user:", "# assistant:".
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See <a href="https://platform.openai.com/docs/api-reference/chat/create#chat/create-role" target="_blank">OpenAI Chat</a> for more about message role.
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```jinja
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# system:
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You are a chatbot having a conversation with a human.
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# user:
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{{question}}
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```
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- how to consume chat history in prompt.
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```jinja
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{% for item in chat_history %}
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# user:
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{{item.inputs.question}}
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# assistant:
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{{item.outputs.answer}}
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{% endfor %}
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```
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## Getting started
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### 1 Create connection for LLM tool to use
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Go to "Prompt flow" "Connections" tab. Click on "Create" button, select one of LLM tool supported connection types and fill in the configurations.
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Currently, there are two connection types supported by LLM tool: "AzureOpenAI" and "OpenAI". If you want to use "AzureOpenAI" connection type, you need to create an Azure OpenAI service first. Please refer to [Azure OpenAI Service](https://azure.microsoft.com/en-us/products/cognitive-services/openai-service/) for more details. If you want to use "OpenAI" connection type, you need to create an OpenAI account first. Please refer to [OpenAI](https://platform.openai.com/) for more details.
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```bash
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# Override keys with --set to avoid yaml file changes
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pf connection create --file ../../../connections/azure_openai.yml --set api_key=<your_api_key> api_base=<your_api_base> --name open_ai_connection
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```
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Note in [flow.dag.yaml](flow.dag.yaml) we are using connection named `open_ai_connection`.
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```bash
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# show registered connection
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pf connection show --name open_ai_connection
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```
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### 2 Start chatting
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```bash
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# run chat flow with default question in flow.dag.yaml
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pf flow test --flow .
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# run chat flow with new question
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pf flow test --flow . --inputs question="What's Azure Machine Learning?"
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# start a interactive chat session in CLI
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pf flow test --flow . --interactive
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# start a interactive chat session in CLI with verbose info
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pf flow test --flow . --interactive --verbose
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```
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