use super::OpenAIEngine;
use crate::error::{AmbiError, Result};
use crate::types::message::Message;
use crate::types::LLMRequest;
use crate::ContentPart;
use async_openai::types::chat::{
ChatCompletionRequestAssistantMessageArgs, ChatCompletionRequestMessage,
ChatCompletionRequestMessageContentPartImageArgs,
ChatCompletionRequestMessageContentPartTextArgs, ChatCompletionRequestSystemMessageArgs,
ChatCompletionRequestUserMessageArgs, ChatCompletionRequestUserMessageContentPart,
ChatCompletionTool, ChatCompletionTools, CreateChatCompletionRequest,
CreateChatCompletionRequestArgs, FunctionObjectArgs, ImageUrlArgs,
};
impl OpenAIEngine {
pub(super) fn get_request(
&self,
model_name: String,
request: LLMRequest,
stream: bool,
) -> Result<CreateChatCompletionRequest> {
let mut messages: Vec<ChatCompletionRequestMessage> = Vec::new();
if !request.system_prompt.is_empty() {
messages.push(
ChatCompletionRequestSystemMessageArgs::default()
.content(request.system_prompt.clone())
.build()
.map_err(|e| AmbiError::EngineError(e.to_string()))?
.into(),
);
}
for msg in &request.history {
let api_msg: ChatCompletionRequestMessage = match &**msg {
Message::User { content } => {
let mut parts = Vec::new();
for part in content {
match part {
ContentPart::Text { text } => {
parts.push(ChatCompletionRequestUserMessageContentPart::Text(
ChatCompletionRequestMessageContentPartTextArgs::default()
.text(text.clone())
.build()
.map_err(|e| AmbiError::EngineError(e.to_string()))?,
));
}
ContentPart::Image { url } => {
parts.push(ChatCompletionRequestUserMessageContentPart::ImageUrl(
ChatCompletionRequestMessageContentPartImageArgs::default()
.image_url(
ImageUrlArgs::default()
.url(url.clone())
.build()
.map_err(|e| {
AmbiError::EngineError(e.to_string())
})?,
)
.build()
.map_err(|e| AmbiError::EngineError(e.to_string()))?,
));
}
}
}
ChatCompletionRequestUserMessageArgs::default()
.content(parts)
.build()
.map_err(|e| AmbiError::EngineError(e.to_string()))?
.into()
}
Message::Assistant { .. } => ChatCompletionRequestAssistantMessageArgs::default()
.content(msg.to_string())
.build()
.map_err(|e| AmbiError::EngineError(e.to_string()))?
.into(),
Message::Tool { .. } => ChatCompletionRequestUserMessageArgs::default()
.content(format!("Tool result: {}", msg))
.build()
.map_err(|e| AmbiError::EngineError(e.to_string()))?
.into(),
Message::System { .. } => continue,
};
messages.push(api_msg);
}
let mut request_builder = CreateChatCompletionRequestArgs::default();
request_builder
.model(model_name)
.messages(messages)
.temperature(self.cfg.temp)
.top_p(self.cfg.top_p)
.stream(stream);
if !request.tools.is_empty() {
let mut api_tools = Vec::new();
for t in &request.tools {
let func = FunctionObjectArgs::default()
.name(&t.name)
.description(&t.description)
.parameters(t.parameters.clone())
.build()
.map_err(|e| AmbiError::EngineError(e.to_string()))?;
let tool = ChatCompletionTool { function: func };
api_tools.push(ChatCompletionTools::Function(tool));
}
request_builder.tools(api_tools);
}
request_builder.build().map_err(|e| {
AmbiError::EngineError(format!("Failed to build OpenAI API request: {}", e))
})
}
}