use super::{
catch_error, message::*, sse_stream, Client, CompletionData, CompletionOutput, ExtraConfig,
Model, ModelData, ModelPatches, OpenAIClient, PromptAction, PromptKind, SseHandler,
SseMmessage, ToolCall,
};
use anyhow::{bail, Result};
use reqwest::{Client as ReqwestClient, RequestBuilder};
use serde::Deserialize;
use serde_json::{json, Value};
const API_BASE: &str = "https://api.openai.com/v1";
#[derive(Debug, Clone, Deserialize, Default)]
pub struct OpenAIConfig {
pub name: Option<String>,
pub api_key: Option<String>,
pub api_base: Option<String>,
pub organization_id: Option<String>,
#[serde(default)]
pub models: Vec<ModelData>,
pub patches: Option<ModelPatches>,
pub extra: Option<ExtraConfig>,
}
impl OpenAIClient {
config_get_fn!(api_key, get_api_key);
config_get_fn!(api_base, get_api_base);
pub const PROMPTS: [PromptAction<'static>; 1] =
[("api_key", "API Key:", true, PromptKind::String)];
fn request_builder(
&self,
client: &ReqwestClient,
data: CompletionData,
) -> Result<RequestBuilder> {
let api_key = self.get_api_key()?;
let api_base = self.get_api_base().unwrap_or_else(|_| API_BASE.to_string());
let mut body = openai_build_body(data, &self.model);
self.patch_request_body(&mut body);
let url = format!("{api_base}/chat/completions");
debug!("OpenAI Request: {url} {body}");
let mut builder = client.post(url).bearer_auth(api_key).json(&body);
if let Some(organization_id) = &self.config.organization_id {
builder = builder.header("OpenAI-Organization", organization_id);
}
Ok(builder)
}
}
pub async fn openai_send_message(builder: RequestBuilder) -> Result<CompletionOutput> {
let res = builder.send().await?;
let status = res.status();
let data: Value = res.json().await?;
if !status.is_success() {
catch_error(&data, status.as_u16())?;
}
debug!("non-stream-data: {data}");
openai_extract_completion(&data)
}
pub async fn openai_send_message_streaming(
builder: RequestBuilder,
handler: &mut SseHandler,
) -> Result<()> {
let mut function_index = 0;
let mut function_name = String::new();
let mut function_arguments = String::new();
let mut function_id = String::new();
let handle = |message: SseMmessage| -> Result<bool> {
if message.data == "[DONE]" {
if !function_name.is_empty() {
handler.tool_call(ToolCall::new(
function_name.clone(),
json!(function_arguments),
Some(function_id.clone()),
))?;
}
return Ok(true);
}
let data: Value = serde_json::from_str(&message.data)?;
debug!("stream-data: {data}");
if let Some(text) = data["choices"][0]["delta"]["content"].as_str() {
handler.text(text)?;
} else if let (Some(function), index, id) = (
data["choices"][0]["delta"]["tool_calls"][0]["function"].as_object(),
data["choices"][0]["delta"]["tool_calls"][0]["index"].as_u64(),
data["choices"][0]["delta"]["tool_calls"][0]["id"].as_str(),
) {
let index = index.unwrap_or_default();
if index != function_index {
if !function_name.is_empty() {
handler.tool_call(ToolCall::new(
function_name.clone(),
json!(function_arguments),
Some(function_id.clone()),
))?;
}
function_name.clear();
function_arguments.clear();
function_id.clear();
function_index = index;
}
if let Some(name) = function.get("name").and_then(|v| v.as_str()) {
function_name = name.to_string();
}
if let Some(arguments) = function.get("arguments").and_then(|v| v.as_str()) {
function_arguments.push_str(arguments);
}
if let Some(id) = id {
function_id = id.to_string();
}
}
Ok(false)
};
sse_stream(builder, handle).await
}
pub fn openai_build_body(data: CompletionData, model: &Model) -> Value {
let CompletionData {
messages,
temperature,
top_p,
functions,
stream,
} = data;
let messages: Vec<Value> = messages
.into_iter()
.flat_map(|message| {
let Message { role, content } = message;
match content {
MessageContent::ToolResults((tool_call_results, text)) => {
let tool_calls: Vec<_> = tool_call_results.iter().map(|tool_call_result| {
json!({
"id": tool_call_result.call.id,
"type": "function",
"function": {
"name": tool_call_result.call.name,
"arguments": tool_call_result.call.arguments,
},
})
}).collect();
let mut messages = vec![
json!({ "role": MessageRole::Assistant, "content": text, "tool_calls": tool_calls })
];
for tool_call_result in tool_call_results {
messages.push(
json!({
"role": "tool",
"content": tool_call_result.output.to_string(),
"tool_call_id": tool_call_result.call.id,
})
);
}
messages
},
_ => vec![json!({ "role": role, "content": content })]
}
})
.collect();
let mut body = json!({
"model": &model.name(),
"messages": messages,
});
if let Some(v) = model.max_tokens_param() {
body["max_tokens"] = v.into();
}
if let Some(v) = temperature {
body["temperature"] = v.into();
}
if let Some(v) = top_p {
body["top_p"] = v.into();
}
if stream {
body["stream"] = true.into();
}
if let Some(functions) = functions {
body["tools"] = functions
.iter()
.map(|v| {
json!({
"type": "function",
"function": v,
})
})
.collect();
body["tool_choice"] = "auto".into();
}
body
}
pub fn openai_extract_completion(data: &Value) -> Result<CompletionOutput> {
let text = data["choices"][0]["message"]["content"]
.as_str()
.unwrap_or_default();
let mut tool_calls = vec![];
if let Some(tools_call) = data["choices"][0]["message"]["tool_calls"].as_array() {
tool_calls = tools_call
.iter()
.filter_map(|call| {
if let (Some(name), Some(arguments), Some(id)) = (
call["function"]["name"].as_str(),
call["function"]["arguments"].as_str(),
call["id"].as_str(),
) {
Some(ToolCall::new(
name.to_string(),
json!(arguments),
Some(id.to_string()),
))
} else {
None
}
})
.collect()
};
if text.is_empty() && tool_calls.is_empty() {
bail!("Invalid response data: {data}");
}
let output = CompletionOutput {
text: text.to_string(),
tool_calls,
id: data["id"].as_str().map(|v| v.to_string()),
input_tokens: data["usage"]["prompt_tokens"].as_u64(),
output_tokens: data["usage"]["completion_tokens"].as_u64(),
};
Ok(output)
}
impl_client_trait!(
OpenAIClient,
openai_send_message,
openai_send_message_streaming
);