use crate::traits::{ChatMessage, ChatRequest, ChatResponse, ModelProvider, TokenUsage, ToolCall};
use async_trait::async_trait;
use nenjo_tools::ToolSpec;
use reqwest::Client;
use serde::{Deserialize, Serialize};
pub struct OpenAiProvider {
api_key: Option<String>,
client: Client,
}
#[derive(Debug, Serialize)]
struct NativeChatRequest {
model: String,
messages: Vec<NativeMessage>,
temperature: f64,
#[serde(skip_serializing_if = "Option::is_none")]
tools: Option<Vec<NativeToolSpec>>,
#[serde(skip_serializing_if = "Option::is_none")]
tool_choice: Option<String>,
}
#[derive(Debug, Serialize)]
struct NativeMessage {
role: String,
#[serde(skip_serializing_if = "Option::is_none")]
content: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
tool_call_id: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
tool_calls: Option<Vec<NativeToolCall>>,
}
#[derive(Debug, Serialize)]
struct NativeToolSpec {
#[serde(rename = "type")]
kind: String,
function: NativeToolFunctionSpec,
}
#[derive(Debug, Serialize)]
struct NativeToolFunctionSpec {
name: String,
description: String,
parameters: serde_json::Value,
}
#[derive(Debug, Serialize, Deserialize)]
struct NativeToolCall {
#[serde(skip_serializing_if = "Option::is_none")]
id: Option<String>,
#[serde(rename = "type", skip_serializing_if = "Option::is_none")]
kind: Option<String>,
function: NativeFunctionCall,
}
#[derive(Debug, Serialize, Deserialize)]
struct NativeFunctionCall {
name: String,
arguments: String,
}
#[derive(Debug, Deserialize)]
struct NativeUsage {
#[serde(default)]
prompt_tokens: u64,
#[serde(default)]
completion_tokens: u64,
}
#[derive(Debug, Deserialize)]
struct NativeChatResponse {
choices: Vec<NativeChoice>,
#[serde(default)]
usage: Option<NativeUsage>,
}
#[derive(Debug, Deserialize)]
struct NativeChoice {
message: NativeResponseMessage,
}
#[derive(Debug, Deserialize)]
struct NativeResponseMessage {
#[serde(default)]
content: Option<String>,
#[serde(default)]
tool_calls: Option<Vec<NativeToolCall>>,
}
impl OpenAiProvider {
pub fn new(api_key: Option<&str>) -> Self {
Self {
api_key: api_key.map(ToString::to_string),
client: Client::builder()
.timeout(std::time::Duration::from_secs(120))
.connect_timeout(std::time::Duration::from_secs(10))
.build()
.unwrap_or_else(|_| Client::new()),
}
}
fn convert_tools(tools: Option<&[ToolSpec]>) -> Option<Vec<NativeToolSpec>> {
tools.map(|items| {
items
.iter()
.map(|tool| NativeToolSpec {
kind: "function".to_string(),
function: NativeToolFunctionSpec {
name: tool.name.clone(),
description: tool.description.clone(),
parameters: tool.parameters.clone(),
},
})
.collect()
})
}
fn convert_messages(messages: &[ChatMessage]) -> Vec<NativeMessage> {
messages
.iter()
.map(|m| {
if m.role == "assistant"
&& let Ok(value) = serde_json::from_str::<serde_json::Value>(&m.content)
&& let Some(tool_calls_value) = value.get("tool_calls")
&& let Ok(parsed_calls) =
serde_json::from_value::<Vec<ToolCall>>(tool_calls_value.clone())
{
let tool_calls = parsed_calls
.into_iter()
.map(|tc| NativeToolCall {
id: Some(tc.id),
kind: Some("function".to_string()),
function: NativeFunctionCall {
name: tc.name,
arguments: tc.arguments,
},
})
.collect::<Vec<_>>();
let content = value
.get("content")
.and_then(serde_json::Value::as_str)
.map(ToString::to_string);
return NativeMessage {
role: "assistant".to_string(),
content,
tool_call_id: None,
tool_calls: Some(tool_calls),
};
}
if m.role == "tool"
&& let Ok(value) = serde_json::from_str::<serde_json::Value>(&m.content)
{
let tool_call_id = value
.get("tool_call_id")
.and_then(serde_json::Value::as_str)
.map(ToString::to_string);
let content = value
.get("content")
.and_then(serde_json::Value::as_str)
.map(ToString::to_string);
return NativeMessage {
role: "tool".to_string(),
content,
tool_call_id,
tool_calls: None,
};
}
NativeMessage {
role: m.role.clone(),
content: Some(m.content.clone()),
tool_call_id: None,
tool_calls: None,
}
})
.collect()
}
fn parse_native_response(message: NativeResponseMessage) -> ChatResponse {
let tool_calls = message
.tool_calls
.unwrap_or_default()
.into_iter()
.map(|tc| ToolCall {
id: tc.id.unwrap_or_else(|| uuid::Uuid::new_v4().to_string()),
name: tc.function.name,
arguments: tc.function.arguments,
})
.collect::<Vec<_>>();
ChatResponse {
text: message.content,
tool_calls,
usage: TokenUsage::default(),
}
}
}
#[async_trait]
impl ModelProvider for OpenAiProvider {
async fn chat(
&self,
request: ChatRequest<'_>,
model: &str,
temperature: f64,
) -> anyhow::Result<ChatResponse> {
let api_key = self.api_key.as_ref().ok_or_else(|| {
anyhow::anyhow!("OpenAI API key not set. Set OPENAI_API_KEY or edit config.toml.")
})?;
let tools = Self::convert_tools(request.tools);
let native_request = NativeChatRequest {
model: model.to_string(),
messages: Self::convert_messages(request.messages),
temperature,
tool_choice: tools.as_ref().map(|_| "auto".to_string()),
tools,
};
let response = self
.client
.post("https://api.openai.com/v1/chat/completions")
.header("Authorization", format!("Bearer {api_key}"))
.json(&native_request)
.send()
.await?;
if !response.status().is_success() {
return Err(crate::api_error("OpenAI", response).await);
}
let native_response: NativeChatResponse = response.json().await?;
let usage = native_response
.usage
.map(|u| TokenUsage {
input_tokens: u.prompt_tokens,
output_tokens: u.completion_tokens,
})
.unwrap_or_default();
let message = native_response
.choices
.into_iter()
.next()
.map(|c| c.message)
.ok_or_else(|| anyhow::anyhow!("No response from OpenAI"))?;
let mut result = Self::parse_native_response(message);
result.usage = usage;
Ok(result)
}
fn context_window(&self, model: &str) -> Option<usize> {
let m = model.to_lowercase();
Some(if m.contains("gpt-5") {
1_000_000
} else if m.contains("o1") || m.contains("o3") || m.contains("o4") {
200_000
} else if m.contains("gpt-4o") {
128_000
} else {
128_000
})
}
fn supports_native_tools(&self) -> bool {
true
}
fn supports_developer_role(&self, model: &str) -> bool {
let m = model.to_lowercase();
m.starts_with("o1") || m.starts_with("o3") || m.starts_with("o4")
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn creates_with_key() {
let p = OpenAiProvider::new(Some("sk-proj-abc123"));
assert_eq!(p.api_key.as_deref(), Some("sk-proj-abc123"));
}
#[test]
fn creates_without_key() {
let p = OpenAiProvider::new(None);
assert!(p.api_key.is_none());
}
#[test]
fn creates_with_empty_key() {
let p = OpenAiProvider::new(Some(""));
assert_eq!(p.api_key.as_deref(), Some(""));
}
#[tokio::test]
async fn chat_fails_without_key() {
let p = OpenAiProvider::new(None);
let messages = vec![ChatMessage::user("hello")];
let request = ChatRequest {
messages: &messages,
tools: None,
};
let result = p.chat(request, "gpt-4o", 0.7).await;
assert!(result.is_err());
assert!(result.unwrap_err().to_string().contains("API key not set"));
}
#[tokio::test]
async fn chat_with_system_fails_without_key() {
let p = OpenAiProvider::new(None);
let messages = vec![
ChatMessage::system("You are Nenjo"),
ChatMessage::user("test"),
];
let request = ChatRequest {
messages: &messages,
tools: None,
};
let result = p.chat(request, "gpt-4o", 0.5).await;
assert!(result.is_err());
}
}