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* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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# Run with: uv run samples/02-agents/embeddings/openai_embeddings.py
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import asyncio
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from agent_framework.openai import OpenAIEmbeddingClient
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from dotenv import load_dotenv
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load_dotenv()
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"""OpenAI Embedding Client Example
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This sample demonstrates how to generate embeddings using the OpenAI embedding client.
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It shows single and batch embedding generation, as well as custom dimensions.
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Prerequisites:
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Set the OPENAI_API_KEY environment variable or add it to a .env file.
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"""
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async def main() -> None:
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"""Generate embeddings with OpenAI."""
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client = OpenAIEmbeddingClient(model="text-embedding-3-small")
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# 1. Generate a single embedding.
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result = await client.get_embeddings(["Hello, world!"])
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print(f"Single embedding dimensions: {result[0].dimensions}")
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print(f"First 5 values: {result[0].vector[:5]}")
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print(f"Model: {result[0].model_id}")
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print(f"Usage: {result.usage}")
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print()
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# 2. Generate embeddings for multiple inputs.
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texts = [
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"The weather is sunny today.",
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"It is raining outside.",
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"Machine learning is fascinating.",
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]
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result = await client.get_embeddings(texts)
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print(f"Batch of {len(result)} embeddings, each with {result[0].dimensions} dimensions")
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print(f"First embedding vector: {result[0].vector[:5]}") # Print first 5 values of the first embedding
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print()
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# 3. Generate embeddings with custom dimensions.
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result = await client.get_embeddings(["Custom dimensions example"], options={"dimensions": 256})
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print(f"Custom dimensions: {result[0].dimensions}")
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print(f"First 5 values: {result[0].vector[:5]}")
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if __name__ == "__main__":
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asyncio.run(main())
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"""
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Sample output:
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Single embedding dimensions: 1536
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First 5 values: [0.012, -0.034, 0.056, -0.078, 0.090]
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Model: text-embedding-3-small
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Usage: {'prompt_tokens': 4, 'total_tokens': 4}
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Batch of 3 embeddings, each with 1536 dimensions
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Custom dimensions: 256
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"""
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