cohere-ai/cohere-azure-workshops

cohere-ai/cohere-azure-workshops

Language: Jupyter Notebook

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Created: 2026-05-01T21:40:24Z

Pushed: 2026-06-09T12:51:12Z

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README:

Cohere Azure Workshops

Hands-on labs for using Cohere embed-v4.0 and Cohere rerank-v4.0 via Microsoft Foundry to build semantic search and reranking applications.

Labs

| Lab | Notebook | Description | | ------------------------------ | -------------------------------------------- | ------------------------------------------------------------------ | | lab-2a-embed-getting-started | lab-2a-embed.ipynb | Introduction to text embeddings with Cohere on Azure | | lab-2b-embed-business-graphs | lab-2b-embed.ipynb | Multimodal semantic search — index and query business graph images | | lab-2c-rerank | lab-2c-rerank-getting-started.ipynb | Semantic reranking — improve search relevance with Cohere Rerank | | lab-2c-rerank (optional) | optional-lab-rerank_wikipedia_search.ipynb | Reranking over Wikipedia search results | | lab-2c-rerank (optional) | optional-lab-rerank_structured_data.ipynb | Reranking structured data |

> All notebooks use cohere.ClientV2 and connect to Microsoft Foundry via the /providers/cohere endpoint path.

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Setup

Option A — Local (Windows — Command Prompt or PowerShell)

git clone https://github.com/cohere-ai/cohere-azure-workshops.git
cd cohere-azure-workshops
pip install -r requirements.txt
copy .env.example .env
# edit .env with your Azure credentials

> Lab 2b note (Windows): Open lab-2b-embed.ipynb directly from the lab-2b-embed-business-graphs\ folder in VS Code so the Jupyter kernel's working directory is set to that folder. This ensures relative paths like ./dataset/ and ./chroma_db resolve correctly.

Option B — Local (macOS / Linux)

git clone https://github.com/cohere-ai/cohere-azure-workshops.git
cd cohere-azure-workshops
pip install -r requirements.txt
cp .env.example .env
# edit .env with your Azure credentials

Option C — GitHub Codespaces

1. Click Code → Codespaces → Create codespace on main 2. Wait for the container to build and pip install to complete (~2 min) 3. Copy the env file and fill in your Azure credentials:

cp .env.example .env
# edit .env with your Azure endpoint URLs and API keys

Microsoft Foundry — Endpoint URL Format

The correct base_url for each model uses the **/providers/cohere path (visible on the deployment's Details page in the Microsoft Foundry portal under Target URI**):

| Model type | Target URI pattern | SDK base_url | | ---------- | ------------------------------ | ----------------------------------------------------------- | | Embed | …/providers/cohere/v2/embed | https://.services.ai.azure.com/providers/cohere | | Rerank | …/providers/cohere/v2/rerank | https://.services.ai.azure.com/providers/cohere |

> Note: cohere.ClientV2 automatically appends /v2/embed or /v2/rerank to the base_url.

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Environment Variables

| Variable | Description | | ----------------- | -------------------------------------------------------- | | EMBED_MODEL | Cohere embed model name (e.g. embed-v-4-0) | | EMBED_BASE_URL | Microsoft Foundry endpoint — up to /providers/cohere | | EMBED_API_KEY | Azure API key for the embed deployment | | RERANK_MODEL | Cohere rerank model name (e.g. Cohere-rerank-v4.0-pro) | | RERANK_BASE_URL | Microsoft Foundry endpoint — up to /providers/cohere | | RERANK_API_KEY | Azure API key for the rerank deployment | | CHROMA_DB_PATH | Path to ChromaDB storage (default: ./chroma_db) |