Merge branch 'Azure-Samples:main' into main

.env.sample

@@ -22,9 +22,8 @@ AZURE_SEARCH_DATASOURCE_NAME=
 # Azure OpenAI for generating the answer and computing the embedding of the documents
 AZURE_OPENAI_RESOURCE=
 AZURE_OPENAI_API_KEY=
-AZURE_OPENAI_MODEL=gpt-35-turbo
-AZURE_OPENAI_MODEL_NAME=gpt-35-turbo
-AZURE_OPENAI_EMBEDDING_MODEL=text-embedding-ada-002
+AZURE_OPENAI_MODEL_INFO="{\"model\":\"gpt-35-turbo-16k\",\"modelName\":\"gpt-35-turbo-16k\",\"modelVersion\":\"0613\"}"
+AZURE_OPENAI_EMBEDDING_MODEL_INFO="{\"model\":\"text-embedding-ada-002\",\"modelName\":\"text-embedding-ada-002\",\"modelVersion\":\"2\"}"
 AZURE_OPENAI_TEMPERATURE=0
 AZURE_OPENAI_TOP_P=1.0
 AZURE_OPENAI_MAX_TOKENS=1000
@@ -63,3 +62,7 @@ USE_KEY_VAULT=true
 AZURE_KEY_VAULT_ENDPOINT=
 # Chat conversation type to decide between custom or byod (bring your own data) conversation type
 CONVERSATION_FLOW=
+# Chat History CosmosDB Integration Settings
+AZURE_COSMOSDB_INFO="{\"accountName\":\"cosmos-abc123\",\"databaseName\":\"db_conversation_history\",\"containerName\":\"conversations\"}"
+AZURE_COSMOSDB_ACCOUNT_KEY=
+AZURE_COSMOSDB_ENABLE_FEEDBACK=

.flake8

@@ -2,3 +2,4 @@
 max-line-length = 88
 extend-ignore = E501
 exclude = .venv
+ignore = E203, W503

.gitignore

@@ -426,3 +426,5 @@ tests/integration/ui/cypress/screenshots/
 
 #JetBrains IDE
 .idea/
+Pipfile
+Pipfile.lock

README.md

@@ -114,11 +114,18 @@ In this scenario, a financial advisor is preparing for a meeting with a potentia
 
 Now that the financial advisor is more informed about Woodgrove’s Emerging Markets Funds, they're better equipped to respond to questions about this fund from their client.
 
-#### Legal Review and Summarization Assistant scenario
-Additionally, we have implemented a Legal Review and Summarization Assistant scenario to demonstrate how this accelerator can be utilized in any industry. The Legal Review and Summarization Assistant helps professionals manage and interact with a large collection of documents efficiently. For more details, refer to the [Legal Review and Summarization Assistant README](docs/contract_assistance.md).
+#### Contract Review and Summarization Assistant scenario
+Additionally, we have implemented a Legal Review and Summarization Assistant scenario to demonstrate how this accelerator can be utilized in any industry. The Legal Review and Summarization Assistant helps professionals manage and interact with a large collection of documents efficiently. For more details, refer to the [Contract Review and Summarization Assistant README](docs/contract_assistance.md).
 
 Note: Some of the sample data included with this accelerator was generated using AI and is for illustrative purposes only.
 
+
+#### Employee Onboarding Scenario
+The sample data illustrates how this accelerator could be used for an employee onboarding scenario in across industries.
+
+In this scenario, a newly hired employee is in the process of onboarding to their organization. Leveraging the solution accelerator, she navigates through the extensive offerings of her organization’s health and retirement benefits. With the newly integrated chat history capabilities, they can revisit previous conversations, ensuring continuity and context across multiple days of research. This functionality allows the new employee to efficiently gather and consolidate information, streamlining their onboarding experience. [For more details, refer to the README](docs/employee_assistance.md).
+
+
 ---
 
 ![One-click Deploy](/docs/images/oneClickDeploy.png)
@@ -138,6 +145,7 @@ Note: Some of the sample data included with this accelerator was generated using
 - Azure Search Service
 - Azure Storage Account
 - Azure Speech Service
+- Azure CosmosDB
 - Teams (optional: Teams extension only)
 
 ### Required licenses

azure.yaml

@@ -46,7 +46,7 @@ services:
       prepackage:
         windows:
           shell: pwsh
-          run: poetry install; poetry export -o requirements.txt
+          run: poetry export -o requirements.txt; pip install -r requirements.txt
         posix:
           shell: sh
-          run: poetry install; poetry export -o requirements.txt
+          run: poetry export -o requirements.txt; pip install -r requirements.txt

code/backend/Admin.py

@@ -51,6 +51,7 @@ def load_css(file_path):
     """
          * If you want to ingest data (pdf, websites, etc.), then use the `Ingest Data` tab
          * If you want to explore how your data was chunked, check the `Explore Data` tab
+         * If you want to delete your data, check the `Delete Data` tab
          * If you want to adapt the underlying prompts, logging settings and others, use the `Configuration` tab
          """
 )