- harden URL/request handling for composio and whatsapp integrations - reduce cleartext logging exposure across providers/tools/gateway - hash and constant-time compare gateway webhook secrets - expand nested secret encryption coverage in config - align feature aliases and add regression tests for security paths - fix bubblewrap all-features test invocation surfaced during deep validation
440 lines
14 KiB
Rust
440 lines
14 KiB
Rust
use crate::providers::traits::{
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ChatMessage, ChatRequest as ProviderChatRequest, ChatResponse as ProviderChatResponse,
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Provider, ToolCall as ProviderToolCall,
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};
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use crate::tools::ToolSpec;
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use async_trait::async_trait;
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use reqwest::Client;
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use serde::{Deserialize, Serialize};
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pub struct OpenAiProvider {
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credential: Option<String>,
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client: Client,
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}
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#[derive(Debug, Serialize)]
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struct ChatRequest {
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model: String,
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messages: Vec<Message>,
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temperature: f64,
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}
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#[derive(Debug, Serialize)]
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struct Message {
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role: String,
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content: String,
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}
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#[derive(Debug, Deserialize)]
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struct ChatResponse {
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choices: Vec<Choice>,
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}
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#[derive(Debug, Deserialize)]
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struct Choice {
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message: ResponseMessage,
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}
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#[derive(Debug, Deserialize)]
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struct ResponseMessage {
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content: String,
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}
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#[derive(Debug, Serialize)]
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struct NativeChatRequest {
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model: String,
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messages: Vec<NativeMessage>,
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temperature: f64,
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#[serde(skip_serializing_if = "Option::is_none")]
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tools: Option<Vec<NativeToolSpec>>,
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#[serde(skip_serializing_if = "Option::is_none")]
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tool_choice: Option<String>,
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}
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#[derive(Debug, Serialize)]
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struct NativeMessage {
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role: String,
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#[serde(skip_serializing_if = "Option::is_none")]
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content: Option<String>,
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#[serde(skip_serializing_if = "Option::is_none")]
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tool_call_id: Option<String>,
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#[serde(skip_serializing_if = "Option::is_none")]
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tool_calls: Option<Vec<NativeToolCall>>,
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}
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#[derive(Debug, Serialize)]
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struct NativeToolSpec {
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#[serde(rename = "type")]
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kind: String,
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function: NativeToolFunctionSpec,
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}
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#[derive(Debug, Serialize)]
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struct NativeToolFunctionSpec {
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name: String,
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description: String,
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parameters: serde_json::Value,
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}
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#[derive(Debug, Serialize, Deserialize)]
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struct NativeToolCall {
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#[serde(skip_serializing_if = "Option::is_none")]
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id: Option<String>,
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#[serde(rename = "type", skip_serializing_if = "Option::is_none")]
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kind: Option<String>,
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function: NativeFunctionCall,
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}
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#[derive(Debug, Serialize, Deserialize)]
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struct NativeFunctionCall {
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name: String,
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arguments: String,
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}
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#[derive(Debug, Deserialize)]
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struct NativeChatResponse {
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choices: Vec<NativeChoice>,
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}
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#[derive(Debug, Deserialize)]
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struct NativeChoice {
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message: NativeResponseMessage,
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}
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#[derive(Debug, Deserialize)]
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struct NativeResponseMessage {
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#[serde(default)]
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content: Option<String>,
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#[serde(default)]
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tool_calls: Option<Vec<NativeToolCall>>,
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}
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impl OpenAiProvider {
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pub fn new(credential: Option<&str>) -> Self {
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Self {
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credential: credential.map(ToString::to_string),
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client: Client::builder()
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.timeout(std::time::Duration::from_secs(120))
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.connect_timeout(std::time::Duration::from_secs(10))
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.build()
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.unwrap_or_else(|_| Client::new()),
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}
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}
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fn convert_tools(tools: Option<&[ToolSpec]>) -> Option<Vec<NativeToolSpec>> {
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tools.map(|items| {
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items
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.iter()
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.map(|tool| NativeToolSpec {
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kind: "function".to_string(),
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function: NativeToolFunctionSpec {
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name: tool.name.clone(),
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description: tool.description.clone(),
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parameters: tool.parameters.clone(),
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},
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})
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.collect()
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})
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}
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fn convert_messages(messages: &[ChatMessage]) -> Vec<NativeMessage> {
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messages
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.iter()
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.map(|m| {
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if m.role == "assistant" {
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if let Ok(value) = serde_json::from_str::<serde_json::Value>(&m.content) {
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if let Some(tool_calls_value) = value.get("tool_calls") {
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if let Ok(parsed_calls) =
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serde_json::from_value::<Vec<ProviderToolCall>>(
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tool_calls_value.clone(),
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)
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{
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let tool_calls = parsed_calls
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.into_iter()
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.map(|tc| NativeToolCall {
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id: Some(tc.id),
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kind: Some("function".to_string()),
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function: NativeFunctionCall {
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name: tc.name,
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arguments: tc.arguments,
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},
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})
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.collect::<Vec<_>>();
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let content = value
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.get("content")
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.and_then(serde_json::Value::as_str)
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.map(ToString::to_string);
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return NativeMessage {
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role: "assistant".to_string(),
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content,
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tool_call_id: None,
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tool_calls: Some(tool_calls),
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};
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}
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}
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}
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}
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if m.role == "tool" {
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if let Ok(value) = serde_json::from_str::<serde_json::Value>(&m.content) {
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let tool_call_id = value
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.get("tool_call_id")
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.and_then(serde_json::Value::as_str)
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.map(ToString::to_string);
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let content = value
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.get("content")
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.and_then(serde_json::Value::as_str)
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.map(ToString::to_string);
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return NativeMessage {
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role: "tool".to_string(),
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content,
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tool_call_id,
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tool_calls: None,
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};
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}
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}
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NativeMessage {
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role: m.role.clone(),
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content: Some(m.content.clone()),
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tool_call_id: None,
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tool_calls: None,
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}
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})
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.collect()
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}
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fn parse_native_response(message: NativeResponseMessage) -> ProviderChatResponse {
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let tool_calls = message
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.tool_calls
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.unwrap_or_default()
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.into_iter()
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.map(|tc| ProviderToolCall {
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id: tc.id.unwrap_or_else(|| uuid::Uuid::new_v4().to_string()),
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name: tc.function.name,
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arguments: tc.function.arguments,
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})
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.collect::<Vec<_>>();
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ProviderChatResponse {
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text: message.content,
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tool_calls,
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}
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}
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}
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#[async_trait]
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impl Provider for OpenAiProvider {
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async fn chat_with_system(
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&self,
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system_prompt: Option<&str>,
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message: &str,
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model: &str,
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temperature: f64,
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) -> anyhow::Result<String> {
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let credential = self.credential.as_ref().ok_or_else(|| {
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anyhow::anyhow!("OpenAI API key not set. Set OPENAI_API_KEY or edit config.toml.")
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})?;
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let mut messages = Vec::new();
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if let Some(sys) = system_prompt {
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messages.push(Message {
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role: "system".to_string(),
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content: sys.to_string(),
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});
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}
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messages.push(Message {
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role: "user".to_string(),
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content: message.to_string(),
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});
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let request = ChatRequest {
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model: model.to_string(),
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messages,
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temperature,
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};
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let response = self
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.client
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.post("https://api.openai.com/v1/chat/completions")
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.header("Authorization", format!("Bearer {credential}"))
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.json(&request)
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.send()
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.await?;
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if !response.status().is_success() {
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return Err(super::api_error("OpenAI", response).await);
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}
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let chat_response: ChatResponse = response.json().await?;
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chat_response
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.choices
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.into_iter()
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.next()
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.map(|c| c.message.content)
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.ok_or_else(|| anyhow::anyhow!("No response from OpenAI"))
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}
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async fn chat(
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&self,
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request: ProviderChatRequest<'_>,
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model: &str,
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temperature: f64,
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) -> anyhow::Result<ProviderChatResponse> {
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let credential = self.credential.as_ref().ok_or_else(|| {
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anyhow::anyhow!("OpenAI API key not set. Set OPENAI_API_KEY or edit config.toml.")
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})?;
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let tools = Self::convert_tools(request.tools);
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let native_request = NativeChatRequest {
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model: model.to_string(),
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messages: Self::convert_messages(request.messages),
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temperature,
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tool_choice: tools.as_ref().map(|_| "auto".to_string()),
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tools,
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};
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let response = self
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.client
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.post("https://api.openai.com/v1/chat/completions")
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.header("Authorization", format!("Bearer {credential}"))
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.json(&native_request)
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.send()
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.await?;
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if !response.status().is_success() {
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return Err(super::api_error("OpenAI", response).await);
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}
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let native_response: NativeChatResponse = response.json().await?;
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let message = native_response
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.choices
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.into_iter()
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.next()
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.map(|c| c.message)
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.ok_or_else(|| anyhow::anyhow!("No response from OpenAI"))?;
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Ok(Self::parse_native_response(message))
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}
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fn supports_native_tools(&self) -> bool {
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true
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}
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn creates_with_key() {
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let p = OpenAiProvider::new(Some("openai-test-credential"));
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assert_eq!(p.credential.as_deref(), Some("openai-test-credential"));
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}
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#[test]
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fn creates_without_key() {
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let p = OpenAiProvider::new(None);
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assert!(p.credential.is_none());
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}
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#[test]
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fn creates_with_empty_key() {
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let p = OpenAiProvider::new(Some(""));
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assert_eq!(p.credential.as_deref(), Some(""));
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}
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#[tokio::test]
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async fn chat_fails_without_key() {
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let p = OpenAiProvider::new(None);
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let result = p.chat_with_system(None, "hello", "gpt-4o", 0.7).await;
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assert!(result.is_err());
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assert!(result.unwrap_err().to_string().contains("API key not set"));
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}
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#[tokio::test]
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async fn chat_with_system_fails_without_key() {
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let p = OpenAiProvider::new(None);
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let result = p
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.chat_with_system(Some("You are ZeroClaw"), "test", "gpt-4o", 0.5)
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.await;
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assert!(result.is_err());
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}
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#[test]
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fn request_serializes_with_system_message() {
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let req = ChatRequest {
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model: "gpt-4o".to_string(),
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messages: vec![
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Message {
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role: "system".to_string(),
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content: "You are ZeroClaw".to_string(),
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},
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Message {
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role: "user".to_string(),
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content: "hello".to_string(),
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},
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],
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temperature: 0.7,
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};
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let json = serde_json::to_string(&req).unwrap();
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assert!(json.contains("\"role\":\"system\""));
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assert!(json.contains("\"role\":\"user\""));
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assert!(json.contains("gpt-4o"));
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}
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#[test]
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fn request_serializes_without_system() {
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let req = ChatRequest {
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model: "gpt-4o".to_string(),
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messages: vec![Message {
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role: "user".to_string(),
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content: "hello".to_string(),
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}],
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temperature: 0.0,
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};
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let json = serde_json::to_string(&req).unwrap();
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assert!(!json.contains("system"));
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assert!(json.contains("\"temperature\":0.0"));
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}
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#[test]
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fn response_deserializes_single_choice() {
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let json = r#"{"choices":[{"message":{"content":"Hi!"}}]}"#;
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let resp: ChatResponse = serde_json::from_str(json).unwrap();
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assert_eq!(resp.choices.len(), 1);
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assert_eq!(resp.choices[0].message.content, "Hi!");
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}
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#[test]
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fn response_deserializes_empty_choices() {
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let json = r#"{"choices":[]}"#;
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let resp: ChatResponse = serde_json::from_str(json).unwrap();
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assert!(resp.choices.is_empty());
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}
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#[test]
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fn response_deserializes_multiple_choices() {
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let json = r#"{"choices":[{"message":{"content":"A"}},{"message":{"content":"B"}}]}"#;
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let resp: ChatResponse = serde_json::from_str(json).unwrap();
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assert_eq!(resp.choices.len(), 2);
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assert_eq!(resp.choices[0].message.content, "A");
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}
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#[test]
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fn response_with_unicode() {
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let json = r#"{"choices":[{"message":{"content":"こんにちは 🦀"}}]}"#;
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let resp: ChatResponse = serde_json::from_str(json).unwrap();
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assert_eq!(resp.choices[0].message.content, "こんにちは 🦀");
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}
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#[test]
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fn response_with_long_content() {
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let long = "x".repeat(100_000);
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let json = format!(r#"{{"choices":[{{"message":{{"content":"{long}"}}}}]}}"#);
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let resp: ChatResponse = serde_json::from_str(&json).unwrap();
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assert_eq!(resp.choices[0].message.content.len(), 100_000);
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}
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}
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