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Python: Migrate to new Google GenAI SDK (#13371)
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> Closes #12970, #13352 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> 1. Migrate Google AI connector to use the new Google AI SDK. 2. This PR also marks the VertexAI connector as deprecated in favor of the Google AI connector. With this update, if users wants to connect to a VertexAI project instead of a Google AI endpoint, they can do so with the Google AI connector. 3. This PR also adds the ability for users to provide a custom client to the Google AI connector (#13352). 4. This PR also marks `AzureTextCompletion` deprecated. ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [x] All unit tests pass, and I have added new tests where possible - [ ] I didn't break anyone 😄
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‎.github/workflows/python-integration-tests.yml‎

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@@ -67,6 +67,7 @@ env:
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GOOGLE_AI_GEMINI_MODEL_ID: ${{ vars.GOOGLE_AI_GEMINI_MODEL_ID }}
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GOOGLE_AI_EMBEDDING_MODEL_ID: ${{ vars.GOOGLE_AI_EMBEDDING_MODEL_ID }}
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GOOGLE_AI_API_KEY: ${{ secrets.GOOGLE_AI_API_KEY }}
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GOOGLE_AI_CLOUD_PROJECT_ID: ${{ vars.GOOGLE_AI_CLOUD_PROJECT_ID }}
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VERTEX_AI_PROJECT_ID: ${{ vars.VERTEX_AI_PROJECT_ID }}
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VERTEX_AI_GEMINI_MODEL_ID: ${{ vars.VERTEX_AI_GEMINI_MODEL_ID }}
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VERTEX_AI_EMBEDDING_MODEL_ID: ${{ vars.VERTEX_AI_EMBEDDING_MODEL_ID }}

‎python/README.md‎

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@@ -4,7 +4,7 @@ Highlights
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- Flexible Agent Framework: build, orchestrate, and deploy AI agents and multi-agent systems
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- Multi-Agent Systems: Model workflows and collaboration between AI specialists
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- Plugin Ecosystem: Extend with Python, OpenAPI, Model Context Protocol (MCP), and more
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- LLM Support: OpenAI, Azure OpenAI, Hugging Face, Mistral, Vertex AI, ONNX, Ollama, NVIDIA NIM, and others
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- LLM Support: OpenAI, Azure OpenAI, Hugging Face, Mistral, Google AI, ONNX, Ollama, NVIDIA NIM, and others
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- Vector DB Support: Azure AI Search, Elasticsearch, Chroma, and more
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- Process Framework: Build structured business processes with workflow modeling
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- Multimodal: Text, vision, audio

‎python/pyproject.toml‎

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]
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dependencies = [
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# azure agents
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"azure-ai-projects >= 1.0.0b12",
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"azure-ai-projects ~= 1.0.0b12",
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"azure-ai-agents >= 1.2.0b3",
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"aiohttp ~= 3.8",
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"cloudevents ~=1.0",
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]
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google = [
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"google-cloud-aiplatform ~= 1.114.0",
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"google-generativeai ~= 0.8"
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"google-genai ~= 1.51.0"
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]
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hugging_face = [
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"transformers[torch] ~= 4.28",

‎python/samples/concepts/plugins/plugins_from_dir.py‎

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import asyncio
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import os
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from azure.identity import AzureCliCredential
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from semantic_kernel import Kernel
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from semantic_kernel.connectors.ai.open_ai import AzureTextCompletion, OpenAITextCompletion
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from semantic_kernel.connectors.ai.open_ai import OpenAITextCompletion
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from semantic_kernel.functions import KernelArguments
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async def main():
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kernel = Kernel()
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useAzureOpenAI = False
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model = "gpt-35-turbo-instruct" if useAzureOpenAI else "gpt-3.5-turbo-instruct"
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model = "gpt-3.5-turbo-instruct"
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service_id = model
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# Configure AI service used by the kernel
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if useAzureOpenAI:
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kernel.add_service(
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AzureTextCompletion(service_id=service_id, credential=AzureCliCredential()),
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)
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else:
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kernel.add_service(
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OpenAITextCompletion(service_id=service_id, ai_model_id=model),
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)
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kernel.add_service(
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OpenAITextCompletion(service_id=service_id, ai_model_id=model),
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)
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# note: using plugins from the samples folder
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plugins_directory = os.path.join(__file__, "../../../../../prompt_template_samples/")

‎python/samples/concepts/setup/ALL_SETTINGS.md‎

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| | [OpenAITextToAudio](../../../semantic_kernel/connectors/ai/open_ai/services/open_ai_text_to_audio.py) | ai_model_id, <br> api_key, <br> org_id | OPENAI_TEXT_TO_AUDIO_MODEL_ID, <br> OPENAI_API_KEY, <br> OPENAI_ORG_ID | Yes, <br> Yes, <br> No | |
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| | [OpenAIAudioToText](../../../semantic_kernel/connectors/ai/open_ai/services/open_ai_audio_to_text.py) | ai_model_id, <br> api_key, <br> org_id | OPENAI_AUDIO_TO_TEXT_MODEL_ID, <br> OPENAI_API_KEY, <br> OPENAI_ORG_ID | Yes, <br> Yes, <br> No | |
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| Azure OpenAI | [AzureChatCompletion](../../../semantic_kernel/connectors/ai/open_ai/services/azure_chat_completion.py) | deployment_name, <br> api_key, <br> endpoint, <br> api_version, <br> base_url | AZURE_OPENAI_CHAT_DEPLOYMENT_NAME, <br> AZURE_OPENAI_API_KEY, <br> AZURE_OPENAI_ENDPOINT, <br> AZURE_OPENAI_API_VERSION, <br> AZURE_OPENAI_BASE_URL | Yes, <br> No, <br> Yes, <br> Yes, <br> Yes | [AzureOpenAISettings](../../../semantic_kernel/connectors/ai/open_ai/settings/azure_open_ai_settings.py) |
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| | [AzureTextCompletion](../../../semantic_kernel/connectors/ai/open_ai/services/azure_text_completion.py) | deployment_name, <br> api_key, <br> endpoint, <br> api_version, <br> base_url | AZURE_OPENAI_TEXT_DEPLOYMENT_NAME, <br> AZURE_OPENAI_API_KEY, <br> AZURE_OPENAI_ENDPOINT, <br> AZURE_OPENAI_API_VERSION, <br> AZURE_OPENAI_BASE_URL | Yes, <br> No, <br> Yes, <br> Yes, <br> Yes | |
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| | [AzureTextEmbedding](../../../semantic_kernel/connectors/ai/open_ai/services/azure_text_embedding.py) | deployment_name, <br> api_key, <br> endpoint, <br> api_version, <br> base_url | AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME, <br> AZURE_OPENAI_API_KEY, <br> AZURE_OPENAI_ENDPOINT, <br> AZURE_OPENAI_API_VERSION, <br> AZURE_OPENAI_BASE_URL | Yes, <br> No, <br> Yes, <br> Yes, <br> Yes | |
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| | [AzureTextToImage](../../../semantic_kernel/connectors/ai/open_ai/services/azure_text_to_image.py) | deployment_name, <br> api_key, <br> endpoint | AZURE_OPENAI_TEXT_TO_IMAGE_DEPLOYMENT_NAME, <br> AZURE_OPENAI_API_KEY, <br> AZURE_OPENAI_ENDPOINT | Yes, <br> No, <br> Yes | |
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| | [AzureTextToAudio](../../../semantic_kernel/connectors/ai/open_ai/services/azure_text_to_audio.py) | deployment_name, <br> api_key, <br> endpoint | AZURE_OPENAI_TEXT_TO_AUDIO_DEPLOYMENT_NAME, <br> AZURE_OPENAI_API_KEY, <br> AZURE_OPENAI_ENDPOINT | Yes, <br> No, <br> Yes | |
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| Google AI | [GoogleAIChatCompletion](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_chat_completion.py) | gemini_model_id, <br> api_key | GOOGLE_AI_GEMINI_MODEL_ID, <br> GOOGLE_AI_API_KEY | Yes, <br> Yes | [GoogleAISettings](../../../semantic_kernel/connectors/ai/google/google_ai/google_ai_settings.py) |
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| | [GoogleAITextCompletion](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_text_completion.py) | gemini_model_id, <br> api_key | GOOGLE_AI_GEMINI_MODEL_ID, <br> GOOGLE_AI_API_KEY | Yes, <br> Yes | |
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| | [GoogleAITextEmbedding](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_text_embedding.py) | embedding_model_id, <br> api_key | GOOGLE_AI_EMBEDDING_MODEL_ID, <br> GOOGLE_AI_API_KEY | Yes, <br> Yes | |
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| Vertex AI | [VertexAIChatCompletion](../../../semantic_kernel/connectors/ai/google/vertex_ai/services/vertex_ai_chat_completion.py) | project_id, <br> region, <br> gemini_model_id | VERTEX_AI_PROJECT_ID, <br> VERTEX_AI_REGION, <br> VERTEX_AI_GEMINI_MODEL_ID | Yes, <br> No, <br> Yes | [VertexAISettings](../../../semantic_kernel/connectors/ai/google/vertex_ai/vertex_ai_settings.py) |
29-
| | [VertexAITextCompletion](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_text_completion.py) | project_id, <br> region, <br> gemini_model_id | VERTEX_AI_PROJECT_ID, <br> VERTEX_AI_REGION, <br> VERTEX_AI_GEMINI_MODEL_ID | Yes, <br> No, <br> Yes | |
30-
| | [VertexAITextEmbedding](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_text_embedding.py) | project_id, <br> region, <br> embedding_model_id | VERTEX_AI_PROJECT_ID, <br> VERTEX_AI_REGION, <br> VERTEX_AI_EMBEDDING_MODEL_ID | Yes, <br> No, <br> Yes | |
27+
| Vertex AI | [GoogleAIChatCompletion](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_chat_completion.py) | project_id, <br> region, <br> gemini_model_id | GOOGLE_AI_CLOUD_PROJECT_ID, <br> GOOGLE_AI_CLOUD_REGION, <br> GOOGLE_AI_GEMINI_MODEL_ID, <br> GOOGLE_AI_USE_VERTEXAI | Yes, <br> No, <br> Yes, <br> Yes (must set to true) | [GoogleAISettings](../../../semantic_kernel/connectors/ai/google/google_ai/google_ai_settings.py) |
28+
| | [GoogleAITextCompletion](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_text_completion.py) | project_id, <br> region, <br> gemini_model_id | GOOGLE_AI_CLOUD_PROJECT_ID, <br> GOOGLE_AI_CLOUD_REGION, <br> GOOGLE_AI_GEMINI_MODEL_ID, <br> GOOGLE_AI_USE_VERTEXAI | Yes, <br> No, <br> Yes, <br> Yes (must set to true) | |
29+
| | [GoogleAITextEmbedding](../../../semantic_kernel/connectors/ai/google/google_ai/services/google_ai_text_embedding.py) | project_id, <br> region, <br> embedding_model_id | GOOGLE_AI_CLOUD_PROJECT_ID, <br> GOOGLE_AI_CLOUD_REGION, <br> GOOGLE_AI_EMBEDDING_MODEL_ID, <br> GOOGLE_AI_USE_VERTEXAI | Yes, <br> No, <br> Yes, <br> Yes (must set to true) | |
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| HuggingFace | [HuggingFaceTextCompletion](../../../semantic_kernel/connectors/ai/hugging_face/services/hf_text_completion.py) | ai_model_id | N/A | Yes | |
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| | [HuggingFaceTextEmbedding](../../../semantic_kernel/connectors/ai/hugging_face/services/hf_text_embedding.py) | ai_model_id | N/A | Yes | |
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| NVIDIA NIM | [NvidiaChatCompletion](../../../semantic_kernel/connectors/ai/nvidia/services/nvidia_chat_completion.py) | ai_model_id, <br> api_key, <br> base_url | NVIDIA_CHAT_MODEL_ID, <br> NVIDIA_API_KEY, <br> NVIDIA_BASE_URL | Yes (default: meta/llama-3.1-8b-instruct), <br> Yes, <br> No | [NvidiaAISettings](../../../semantic_kernel/connectors/ai/nvidia/settings/nvidia_settings.py) |

‎python/samples/concepts/setup/chat_completion_services.py‎

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Please refer to the Semantic Kernel Python documentation for more information:
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https://learn.microsoft.com/en-us/python/api/semantic-kernel/semantic_kernel?view=semantic-kernel
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"""
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from semantic_kernel.connectors.ai.google.google_ai import (
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GoogleAIChatCompletion,
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GoogleAIChatPromptExecutionSettings,
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)
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from semantic_kernel.connectors.ai.google import GoogleAIChatCompletion, GoogleAIChatPromptExecutionSettings
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chat_service = GoogleAIChatCompletion(service_id=service_id)
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request_settings = GoogleAIChatPromptExecutionSettings(service_id=service_id)
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Please refer to the Semantic Kernel Python documentation for more information:
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https://learn.microsoft.com/en-us/python/api/semantic-kernel/semantic_kernel?view=semantic-kernel
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"""
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from semantic_kernel.connectors.ai.google.vertex_ai import (
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VertexAIChatCompletion,
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VertexAIChatPromptExecutionSettings,
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)
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from semantic_kernel.connectors.ai.google import GoogleAIChatCompletion, GoogleAIChatPromptExecutionSettings
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chat_service = VertexAIChatCompletion(service_id=service_id)
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request_settings = VertexAIChatPromptExecutionSettings(service_id=service_id)
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chat_service = GoogleAIChatCompletion(service_id=service_id, use_vertexai=True)
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request_settings = GoogleAIChatPromptExecutionSettings(service_id=service_id)
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return chat_service, request_settings
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‎python/samples/concepts/setup/text_completion_services.py‎

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"""
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OPENAI = "openai"
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AZURE_OPENAI = "azure_openai"
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BEDROCK = "bedrock"
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GOOGLE_AI = "google_ai"
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HUGGING_FACE = "huggingface"
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# Use lambdas or functions to delay instantiation
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text_services = {
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Services.OPENAI: lambda: get_openai_text_completion_service_and_request_settings(),
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Services.AZURE_OPENAI: lambda: get_azure_openai_text_completion_service_and_request_settings(),
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Services.BEDROCK: lambda: get_bedrock_text_completion_service_and_request_settings(),
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Services.GOOGLE_AI: lambda: get_google_ai_text_completion_service_and_request_settings(),
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Services.HUGGING_FACE: lambda: get_hugging_face_text_completion_service_and_request_settings(),
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return text_service, request_settings
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def get_azure_openai_text_completion_service_and_request_settings() -> tuple[
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"TextCompletionClientBase", "PromptExecutionSettings"
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]:
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"""Return Azure OpenAI text completion service and request settings.
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The service credentials can be read by 3 ways:
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1. Via the constructor
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2. Via the environment variables
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3. Via an environment file
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The request settings control the behavior of the service. The default settings are sufficient to get started.
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However, you can adjust the settings to suit your needs.
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Note: Some of the settings are NOT meant to be set by the user.
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Please refer to the Semantic Kernel Python documentation for more information:
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https://learn.microsoft.com/en-us/python/api/semantic-kernel/semantic_kernel?view=semantic-kernel
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"""
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from azure.identity import AzureCliCredential
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from semantic_kernel.connectors.ai.open_ai import AzureTextCompletion, OpenAITextPromptExecutionSettings
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text_service = AzureTextCompletion(credential=AzureCliCredential())
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request_settings = OpenAITextPromptExecutionSettings()
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return text_service, request_settings
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def get_bedrock_text_completion_service_and_request_settings() -> tuple[
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"TextCompletionClientBase", "PromptExecutionSettings"
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]:
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Please refer to the Semantic Kernel Python documentation for more information:
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https://learn.microsoft.com/en-us/python/api/semantic-kernel/semantic_kernel?view=semantic-kernel
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"""
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from semantic_kernel.connectors.ai.google.vertex_ai import (
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VertexAITextCompletion,
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VertexAITextPromptExecutionSettings,
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)
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from semantic_kernel.connectors.ai.google import GoogleAITextCompletion, GoogleAITextPromptExecutionSettings
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text_service = VertexAITextCompletion()
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request_settings = VertexAITextPromptExecutionSettings()
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text_service = GoogleAITextCompletion()
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request_settings = GoogleAITextPromptExecutionSettings()
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return text_service, request_settings

‎python/samples/concepts/setup/text_embedding_services.py‎

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Please refer to the Semantic Kernel Python documentation for more information:
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https://learn.microsoft.com/en-us/python/api/semantic-kernel/semantic_kernel?view=semantic-kernel
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"""
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from semantic_kernel.connectors.ai.google.vertex_ai import (
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VertexAIEmbeddingPromptExecutionSettings,
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VertexAITextEmbedding,
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)
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from semantic_kernel.connectors.ai.google import GoogleAIEmbeddingPromptExecutionSettings, GoogleAITextEmbedding
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embedding_service = VertexAITextEmbedding()
301+
embedding_service = GoogleAITextEmbedding()
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# Note: not all models support specifying the dimensions or there may be constraints on the dimensions
306-
request_settings = VertexAIEmbeddingPromptExecutionSettings(output_dimensionality=768)
303+
request_settings = GoogleAIEmbeddingPromptExecutionSettings(output_dimensionality=768)
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return embedding_service, request_settings

‎python/samples/concepts/text_completion/text_completion.py‎

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# You can select from the following text embedding services:
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# - Services.OPENAI
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# - Services.AZURE_OPENAI
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# - Services.BEDROCK
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# - Services.GOOGLE_AI
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# - Services.HUGGING_FACE

‎python/samples/concepts/text_completion/text_completion_streaming.py‎

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# You can select from the following text embedding services:
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# - Services.OPENAI
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# - Services.AZURE_OPENAI
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# - Services.BEDROCK
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# - Services.GOOGLE_AI
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# - Services.HUGGING_FACE

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