feat: Gemini openai compatibility

examples/gemini-openai-compatibility/Cargo.toml

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+[package]
+name = "gemini-openai-compatibility"
+version = "0.1.0"
+edition = "2021"
+rust-version.workspace = true
+
+[dependencies]
+async-openai = {path = "../../async-openai", features = ["byot"]}
+tokio = { version = "1.43.0", features = ["full"] }
+tracing-subscriber = { version =  "0.3.19",  features = ["env-filter"]}
+dotenv = "0.15.0"
+futures = "0.3.31"
+serde_json = "1.0.100"
+serde = { version = "1.0", features = ["derive"] }
+base64 = "0.22.1"

examples/gemini-openai-compatibility/README.md

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+# Gemini's OpenAI Compatibility Example
+
+This example demonstrates how to use OpenAI's `async_openai` Rust library with Google's Gemini API. By modifying a few lines of configuration, you can integrate Gemini models while maintaining OpenAI compatibility.
+
+## Features
+- **List Available Models**: Fetch a list of supported Gemini models.
+- **Retrieve Model Details**: Get detailed information about the `gemini-1.5-flash` model.
+- **Chat Completion**: Perform chat completions using Gemini's API.
+- **Stream Chat Messages**: Receive streaming responses for chat queries in real-time.
+- **Generate Images**: Leverage Gemini's image generation capabilities.
+- **Understand Images**: Analyze and extract information from images.
+- **Understand Audio**: Process and interpret audio inputs.
+- **Structured Output Response**: Generate structured outputs for complex queries.
+- **Function Calling**: Invoke functions dynamically based on input prompts.
+- **Create Embeddings**: Generate embeddings for text or other data types.
+- **Bring Your Own Type (BYOT)**: Use custom Gemini response types defined in `gemini_type.rs`.
+
+## Prerequisites
+- Rust installed (`rustc` and `cargo`)
+- Set up your Google Gemini API key from [Google AI Studio](https://aistudio.google.com/)
+- Create a `.env` file with:
+  ```plaintext
+  GEMINI_API_KEY=your_api_key_here
+  ```
+- Install dependencies:
+  ```sh
+  cargo add async-openai dotenv futures tokio
+  ```
+
+## Enabling BYOT Feature
+To enable the BYOT (Bring Your Own Type) feature in `async-openai`, modify your `Cargo.toml` as follows:
+```toml
+async-openai = {version = '{{version}}', features = ["byot"]}
+```
+
+## Usage
+This example now uses the `byot` (Bring Your Own Type) feature to define custom types for Gemini responses. The Gemini types are defined in `gemini_type.rs`, and methods using these types have the `_byot` suffix.
+
+### Running the Example
+To run the example:
+```sh
+cargo run
+```
+This will:
+1. List available models
+2. Retrieve details of `gemini-1.5-flash`
+3. Generate chat completion responses
+4. Stream chat messages
+5. Generate an image
+6. Understanding an image
+7. Understanding an audio
+8. Structured output response
+9. Function calling
+10. Create Embeddings
+
+
+## References
+- [Google Gemini's OpenAI compatibility](https://ai.google.dev/gemini-api/docs/openai)
+

examples/gemini-openai-compatibility/src/gemini_types.rs

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+use std::pin::Pin;
+
+/// Gemini types (Generally user defined types) for Gemini API
+use async_openai::{
+    error::OpenAIError,
+    types::{ChatChoice, ChatChoiceStream, CompletionUsage, Image},
+};
+use futures::Stream;
+use serde::{Deserialize, Serialize};
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct GeminiModel {
+    pub id: String,
+    pub object: String,
+    pub owned_by: String,
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct ListGeminiModelResponse {
+    pub data: Vec<GeminiModel>,
+    pub object: String,
+}
+
+#[derive(Debug, Deserialize, Clone, PartialEq, Serialize)]
+/// Represents a streamed chunk of a chat completion response returned by model, based on the provided input.
+pub struct GeminiCreateChatCompletionStreamResponse {
+    /// A list of chat completion choices. Can contain more than one elements if `n` is greater than 1. Can also be empty for the last chunk if you set `stream_options: {"include_usage": true}`.
+    pub choices: Vec<ChatChoiceStream>,
+
+    /// The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same timestamp.
+    pub created: u32,
+    /// The model to generate the completion.
+    pub model: String,
+
+    /// The object type, which is always `chat.completion.chunk`.
+    pub object: String,
+
+    /// An optional field that will only be present when you set `stream_options: {"include_usage": true}` in your request.
+    /// When present, it contains a null value except for the last chunk which contains the token usage statistics for the entire request.
+    pub usage: Option<CompletionUsage>,
+}
+
+/// A stream of chat completion responses.
+pub type GeminiChatCompletionResponseStream = Pin<
+    Box<dyn Stream<Item = Result<GeminiCreateChatCompletionStreamResponse, OpenAIError>> + Send>,
+>;
+
+/// Represents a chat completion response returned by model, based on the provided input.
+#[derive(Debug, Deserialize, Clone, PartialEq, Serialize)]
+pub struct GeminiCreateChatCompletionResponse {
+    /// A list of chat completion choices. Can be more than one if `n` is greater than 1.
+    pub choices: Vec<ChatChoice>,
+    /// The Unix timestamp (in seconds) of when the chat completion was created.
+    pub created: u32,
+    /// The model used for the chat completion.
+    pub model: String,
+    /// The object type, which is always `chat.completion`.
+    pub object: String,
+    /// usage statistics for the entire request.
+    pub usage: Option<CompletionUsage>,
+}
+
+#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
+pub struct GeminiImagesResponse {
+    pub data: Vec<std::sync::Arc<Image>>,
+}
+
+/// Represents an embedding vector returned by embedding endpoint.
+#[derive(Debug, Deserialize, Serialize, Clone, PartialEq)]
+pub struct GeminiEmbedding {
+    /// The object type, which is always "embedding".
+    pub object: String,
+    /// The embedding vector, which is a list of floats. The length of vector
+    pub embedding: Vec<f32>,
+}
+
+#[derive(Debug, Deserialize, Clone, PartialEq, Serialize)]
+pub struct GeminiCreateEmbeddingResponse {
+    pub object: String,
+    /// The name of the model used to generate the embedding.
+    pub model: String,
+    /// The list of embeddings generated by the model.
+    pub data: Vec<GeminiEmbedding>,
+}