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Josh SorefandCopybara-Service
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Merge https://github.com/google/adk-python/pull/3394 This PR corrects misspellings identified by the [check-spelling action](https://github.com/marketplace/actions/check-spelling) Note: while I use tooling to identify errors, the tooling doesn't _actually_ provide the corrections, I'm picking them on my own. I'm a human, and I may make mistakes. ### Testing Plan The misspellings have been reported at https://github.com/jsoref/adk-python/actions/runs/19056081305/attempts/1#summary-54426435973 The action reports that the changes in this PR would make it happy: https://github.com/jsoref/adk-python/actions/runs/19056081446/attempts/1#summary-54426436321 **Unit Tests:** - [ ] I have added or updated unit tests for my change. - [ ] All unit tests pass locally. _Please include a summary of passed `pytest` results._ **Manual End-to-End (E2E) Tests:** _Please provide instructions on how to manually test your changes, including any necessary setup or configuration. Please provide logs or screenshots to help reviewers better understand the fix._ ### Checklist - [x] I have read the [CONTRIBUTING.md](https://github.com/google/adk-python/blob/main/CONTRIBUTING.md) document. - [x] I have performed a self-review of my own code. - [ ] I have commented my code, particularly in hard-to-understand areas. - [ ] I have added tests that prove my fix is effective or that my feature works. - [ ] New and existing unit tests pass locally with my changes. - [ ] I have manually tested my changes end-to-end. - [ ] Any dependent changes have been merged and published in downstream modules. ### Additional context - https://github.com/google/adk-python/pull/3382#issuecomment-3488654110 COPYBARA_INTEGRATE_REVIEW=https://github.com/google/adk-python/pull/3394 from jsoref:spelling-contributing c3d5e342c4350f7cae9f8f0c6638b176f2e30e80 PiperOrigin-RevId: 828659867
85 lines
3.1 KiB
Markdown
85 lines
3.1 KiB
Markdown
# Hello World with Apigee LLM
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This sample demonstrates how to use the Agent Development Kit (ADK) with an LLM fronted by an Apigee proxy. It showcases the flexibility of the `ApigeeLlm` class in configuring the target LLM provider (Gemini or Vertex AI) and API version through the model string.
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## Setup
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Before running the sample, you need to configure your environment with the necessary credentials.
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1. **Create a `.env` file:**
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Copy the sample environment file to a new file named `.env` in the same directory.
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```bash
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cp .env-sample .env
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```
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2. **Set Environment Variables:**
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Open the `.env` file and provide values for the following variables:
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- `GOOGLE_API_KEY`: Your API key for the Google AI services (Gemini).
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- `APIGEE_PROXY_URL`: The full URL of your Apigee proxy endpoint.
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Example `.env` file:
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```
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GOOGLE_API_KEY="your-google-api-key"
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APIGEE_PROXY_URL="https://your-apigee-proxy.net/basepath"
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```
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The `main.py` script will automatically load these variables when it runs.
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## Run the Sample
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Once your `.env` file is configured, you can run the sample with the following command:
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```bash
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python main.py
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```
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## Configuring the Apigee LLM
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The `ApigeeLlm` class is configured using a special model string format in `agent.py`. This string determines which backend provider (Vertex AI or Gemini) and which API version to use.
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### Model String Format
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The supported format is:
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`apigee/[<provider>/][<version>/]<model_id>`
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- **`provider`** (optional): Can be `vertex_ai` or `gemini`.
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- If specified, it forces the use of that provider.
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- If omitted, the provider is determined by the `GOOGLE_GENAI_USE_VERTEXAI` environment variable. If this variable is set to `true` or `1`, Vertex AI is used; otherwise, `gemini` is used by default.
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- **`version`** (optional): The API version to use (e.g., `v1`, `v1beta`).
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- If omitted, the default version for the selected provider is used.
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- **`model_id`** (required): The identifier for the model you want to use (e.g., `gemini-2.5-flash`).
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### Configuration Examples
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Here are some examples of how to configure the model string in `agent.py` to achieve different behaviors:
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1. **Implicit Provider (determined by environment variable):**
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- `model="apigee/gemini-2.5-flash"`
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- Uses the default API version.
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- Provider is Vertex AI if `GOOGLE_GENAI_USE_VERTEXAI` is true; otherwise, Gemini.
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- `model="apigee/v1/gemini-2.5-flash"`
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- Uses API version `v1`.
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- Provider is determined by the environment variable.
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2. **Explicit Provider (ignores environment variable):**
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- `model="apigee/vertex_ai/gemini-2.5-flash"`
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- Uses Vertex AI with the default API version.
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- `model="apigee/gemini/gemini-2.5-flash"`
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- Uses Gemini with the default API version.
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- `model="apigee/gemini/v1/gemini-2.5-flash"`
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- Uses Gemini with API version `v1`.
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- `model="apigee/vertex_ai/v1beta/gemini-2.5-flash"`
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- Uses Vertex AI with API version `v1beta`.
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By modifying the `model` string in `agent.py`, you can test various configurations without changing the core logic of the agent.
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