Merge branch 'main' into cforce-2065

Author: cforce

.github/workflows/python-test.yaml

@@ -26,13 +26,21 @@ jobs:
       matrix:
         os: ["ubuntu-20.04", "windows-latest"]
         python_version: ["3.9", "3.10", "3.11", "3.12"]
+    env:
+      UV_SYSTEM_PYTHON: 1
     steps:
         - uses: actions/checkout@v4
         - name: Setup python
           uses: actions/setup-python@v5
           with:
             python-version: ${{ matrix.python_version }}
             architecture: x64
+        - name: Install uv
+          uses: astral-sh/setup-uv@v3
+          with:
+            enable-cache: true
+            version: "0.4.20"
+            cache-dependency-glob: "requirements**.txt"
         - name: Setup node
           uses: actions/setup-node@v4
           with:
@@ -44,8 +52,7 @@ jobs:
             npm run build
         - name: Install dependencies
           run: |
-            python -m pip install --upgrade pip
-            pip install -r requirements-dev.txt
+            uv pip install -r requirements-dev.txt
         - name: Lint with ruff
           run: ruff check .
         - name: Check types with mypy

.pre-commit-config.yaml

@@ -1,17 +1,17 @@
 exclude: '^tests/snapshots/'
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.5.0
+    rev: v5.0.0
     hooks:
     -   id: check-yaml
     -   id: end-of-file-fixer
     -   id: trailing-whitespace
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.14
+    rev: v0.7.2
     hooks:
     -   id: ruff
 -   repo: https://github.com/psf/black
-    rev: 24.1.0
+    rev: 24.10.0
     hooks:
     -   id: black
 -   repo: https://github.com/pre-commit/mirrors-prettier

.vscode/tasks.json

@@ -3,14 +3,6 @@
     "tasks": [
         {
             "label": "Start App",
-            "type": "dotenv",
-            "targetTasks": [
-                "Start App (Script)"
-            ],
-            "file": "${input:dotEnvFilePath}"
-        },
-        {
-            "label": "Start App (Script)",
             "type": "shell",
             "command": "${workspaceFolder}/app/start.sh",
             "windows": {
@@ -24,12 +16,5 @@
             },
             "problemMatcher": []
         }
-    ],
-    "inputs": [
-        {
-            "id": "dotEnvFilePath",
-            "type": "command",
-            "command": "azure-dev.commands.getDotEnvFilePath"
-        }
     ]
 }

README.md

@@ -288,11 +288,11 @@ Here are the most common failure scenarios and solutions:
 ### Resources
 
 - [Additional documentation for this app](docs/README.md)
-- [📖 Revolutionize your Enterprise Data with ChatGPT: Next-gen Apps w/ Azure OpenAI and AI Search](https://aka.ms/entgptsearchblog)
+- [📖 Revolutionize your Enterprise Data with ChatGPT: Next-gen Apps w/ Azure OpenAI and AI Search](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/revolutionize-your-enterprise-data-with-chatgpt-next-gen-apps-w-azure-openai-and/3762087)
 - [📖 Azure AI Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search)
 - [📖 Azure OpenAI Service](https://learn.microsoft.com/azure/cognitive-services/openai/overview)
 - [📖 Comparing Azure OpenAI and OpenAI](https://learn.microsoft.com/azure/cognitive-services/openai/overview#comparing-azure-openai-and-openai/)
-- [📖 Access Control in Generative AI applications with Azure Cognitive Search](https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/access-control-in-generative-ai-applications-with-azure/ba-p/3956408)
+- [📖 Access Control in Generative AI applications with Azure AI Search](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/access-control-in-generative-ai-applications-with-azure-ai-search/3956408)
 - [📺 Quickly build and deploy OpenAI apps on Azure, infused with your own data](https://www.youtube.com/watch?v=j8i-OM5kwiY)
 - [📺 AI Chat App Hack series](https://www.youtube.com/playlist?list=PL5lwDBUC0ag6_dGZst5m3G72ewfwXLcXV)
 

app/frontend/src/assets/github.svg

@@ -134,4 +134,4 @@
         "useOidSecurityFilter": "Filtrér søgeresultater baseret på den godkendte brugers OID.",
         "useGroupsSecurityFilter": "Filtrér søgeresultater baseret på den godkendte brugers adgangsgrupper."
     }
-}
+}

app/frontend/src/assets/search.svg

@@ -81,7 +81,7 @@
         "minimumSearchScore": "Minimale zoekscore",
         "minimumRerankerScore": "Minimale reranker score",
         "retrieveCount": "Dit aantal zoekresultaten ophalen:",
-        "includeCategory": "Categorie opnemen", 
+        "includeCategory": "Categorie opnemen",
         "includeCategoryOptions": {
             "all": "Alle"
         },
@@ -151,4 +151,4 @@
         "useOidSecurityFilter": "Filtert zoekresultaten op basis van de OID van de geauthenticeerde gebruiker.",
         "useGroupsSecurityFilter": "Filtert zoekresultaten op basis van de groepen van de geauthenticeerde gebruiker."
     }
-}
+}

app/frontend/src/locales/da/translation.json

@@ -117,7 +117,7 @@ You can also try changing the ChatCompletion parameters, like temperature, to se
 
 ### Improving Azure AI Search results
 
-If the problem is with Azure AI Search (step 2 above), the first step is to check what search parameters you're using. Generally, the best results are found with hybrid search (text + vectors) plus the additional semantic re-ranking step, and that's what we've enabled by default. There may be some domains where that combination isn't optimal, however. Check out this blog post which [evaluates AI search strategies](https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/azure-ai-search-outperforming-vector-search-with-hybrid/ba-p/3929167) for a better understanding of the differences.
+If the problem is with Azure AI Search (step 2 above), the first step is to check what search parameters you're using. Generally, the best results are found with hybrid search (text + vectors) plus the additional semantic re-ranking step, and that's what we've enabled by default. There may be some domains where that combination isn't optimal, however. Check out this blog post which [evaluates AI search strategies](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/azure-ai-search-outperforming-vector-search-with-hybrid-retrieval-and-ranking-ca/3929167) for a better understanding of the differences.
 
 #### Configuring parameters in the app
 

app/frontend/src/locales/nl/translation.json

@@ -57,7 +57,7 @@ If needed, you can modify the chunking algorithm in `scripts/prepdocslib/textspl
 
 To enhance search functionality, categorize data during the ingestion process with the `--category` argument, for example `scripts/prepdocs.ps1 --category ExampleCategoryName`. This argument specifies the category to which the data belongs, enabling you to filter search results based on these categories.
 
-After running the script with the desired category, ensure these categories are added to the 'Include Category' dropdown list. This can be found in the developer settings in [`Settings.tsx`](/app/frontend/src/components/settings/Settings.tsx). The default option for this dropdown is "All". By including specific categories, you can refine your search results more effectively.
+After running the script with the desired category, ensure these categories are added to the 'Include Category' dropdown list. This can be found in the developer settings in [`Settings.tsx`](https://github.com/Azure-Samples/azure-search-openai-demo/blob/main/app/frontend/src/components/Settings/Settings.tsx). The default option for this dropdown is "All". By including specific categories, you can refine your search results more effectively.
 
 ### Indexing additional documents
 
@@ -75,7 +75,7 @@ You can also remove individual documents by using the `--remove` flag. Open eith
 
 ## Integrated Vectorization
 
-Azure AI Search includes an [integrated vectorization feature](https://techcommunity.microsoft.com/t5/ai-azure-ai-services-blog/announcing-the-public-preview-of-integrated-vectorization-in/ba-p/3960809#:~:text=Integrated%20vectorization%20is%20a%20new%20feature%20of%20Azure,pull-indexers%2C%20and%20vectorization%20of%20text%20queries%20through%20vectorizers), a cloud-based approach to data ingestion. Integrated vectorization takes care of document format cracking, data extraction, chunking, vectorization, and indexing, all with Azure technologies.
+Azure AI Search includes an [integrated vectorization feature](https://techcommunity.microsoft.com/blog/azure-ai-services-blog/announcing-the-public-preview-of-integrated-vectorization-in-azure-ai-search/3960809), a cloud-based approach to data ingestion. Integrated vectorization takes care of document format cracking, data extraction, chunking, vectorization, and indexing, all with Azure technologies.
 
 See [this notebook](https://github.com/Azure/azure-search-vector-samples/blob/main/demo-python/code/integrated-vectorization/azure-search-integrated-vectorization-sample.ipynb) to understand the process of setting up integrated vectorization.
 We have integrated that code into our `prepdocs` script, so you can use it without needing to understand the details.