phi-core 0.10.0

Simple, effective agent loop with tool execution and event streaming
Documentation
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//! Google Vertex AI provider.
//!
//! Similar to Google Generative AI but uses OAuth2 authentication
//! and a different base URL pattern with project/location.
//!
//! The API key in StreamConfig is expected to be an OAuth2 access token.
//! Callers are responsible for obtaining the token (e.g., via service account JWT).
/*
ARCHITECTURE: GoogleVertexProvider — enterprise Gemini via Vertex AI

Vertex AI is Google's enterprise AI platform. It hosts the same Gemini models
as Generative AI (`generativelanguage.googleapis.com`) but with:

  Different URL structure:
    GenAI:  https://generativelanguage.googleapis.com/v1beta/models/{model}:streamGenerateContent
    Vertex: https://{region}-aiplatform.googleapis.com/v1/projects/{project}/locations/{region}/
              publishers/google/models/{model}:streamGenerateContent

  Different authentication:
    GenAI:  `?key={api_key}` query parameter (simple API key)
    Vertex: `Authorization: Bearer {oauth2_access_token}` header

  Same API format:
    Both use identical request/response JSON shapes (Gemini content format).
    We re-use `build_vertex_request_body()` which is structurally the same as
    Google GenAI's `build_request_body()`.

ARCHITECTURE: Delegation pattern

`GoogleVertexProvider` doesn't re-implement the SSE event loop. Instead, it:
  1. Constructs the Vertex-specific URL (`vertex_url()` static method)
  2. Adds the OAuth2 Bearer token as a header
  3. Delegates to `super::google::stream_google_content()` (shared SSE logic)

This avoids duplicating the Google event parsing code. The only Vertex-specific
logic is URL construction and auth — everything else is identical to GenAI.

RUST QUIRK: `fn vertex_url(model_config: &ModelConfig, model: &str) -> String`
  An associated function on `GoogleVertexProvider` (no `self` parameter).
  Called as `Self::vertex_url(model_config, model)` or `GoogleVertexProvider::vertex_url(...)`.
  Python analogy: a `@staticmethod` on the class.
*/

use super::model::ModelConfig;
use super::traits::*;
use crate::types::*;
use async_trait::async_trait;
use tokio::sync::mpsc;

/// Unit struct — no state. All logic in the `StreamProvider` impl.
pub struct GoogleVertexProvider;

impl GoogleVertexProvider {
    /// Build the Vertex AI URL from model config.
    /// Expects base_url in format: `https://{region}-aiplatform.googleapis.com/v1/projects/{project}/locations/{region}/publishers/google/models`
    fn vertex_url(
        model_config: &ModelConfig, // CONFIG — carries base_url (Vertex endpoint) to construct full URL
        model: &str, // MODEL NAME — appended to base_url to get the per-model endpoint
    ) -> String {
        format!(
            "{}/{}:streamGenerateContent?alt=sse",
            model_config.base_url, model
        )
    }
}

#[async_trait]
impl StreamProvider for GoogleVertexProvider {
    fn provider_id(&self) -> &str {
        "vertex"
    }

    async fn stream(
        &self,
        config: StreamConfig, // REQUEST — api_key is OAuth2 Bearer token (not API key); base_url is Vertex endpoint
        tx: mpsc::UnboundedSender<StreamEvent>, // OBSERVER — delegates to GoogleProvider's stream logic
        cancel: tokio_util::sync::CancellationToken, // ABORT — forwarded to delegate
    ) -> Result<Message, ProviderError> {
        let model_config = &config.model_config;
        // Resolve via CredentialProvider when set, else use the static `api_key`.
        let api_key = model_config.resolve_api_key().await?;

        // Override the base_url to use Vertex format.
        // The GoogleProvider's stream will use model_config.base_url, but we need
        // a different URL pattern. We delegate to GoogleProvider with a modified config.
        let vertex_url = Self::vertex_url(model_config, &config.model_config.id);

        // Create a modified model config with the Vertex URL pattern
        let mut vertex_model = model_config.clone();
        // For Vertex, auth is via Bearer token (OAuth2), not API key in query param.
        // We need to add the Authorization header.
        vertex_model
            .headers
            .insert("authorization".to_string(), format!("Bearer {}", api_key));

        // Build request body same as Google (same content format)
        let body = build_vertex_request_body(&config);

        let client = reqwest::Client::new();
        let mut request = client
            .post(&vertex_url)
            .header("content-type", "application/json");

        for (k, v) in &vertex_model.headers {
            request = request.header(k, v);
        }

        let response = request
            .json(&body)
            .send()
            .await
            .map_err(|e| ProviderError::Network(e.to_string()))?;

        if !response.status().is_success() {
            let status = response.status();
            let body = response.text().await.unwrap_or_default();
            return Err(ProviderError::classify(
                status.as_u16(),
                &format!("Vertex AI error {}: {}", status, body),
            ));
        }

        // Delegate SSE parsing to the Google provider's streaming logic.
        // Since the response format is identical, we reuse GoogleProvider.
        // However, we already have the response, so we'll parse it inline.
        // Actually, let's just delegate to GoogleProvider. The key difference
        // is auth (Bearer vs API key in URL). We handle that by using a modified
        // model config. But GoogleProvider builds its own URL... so let's just
        // use GoogleProvider with a trick: empty api_key and auth in headers.
        // We can't easily reuse GoogleProvider because it constructs its own URL.
        // Instead, parse the SSE response directly (same format as Google GenAI).
        parse_google_sse_response(response, &config, &model_config.provider, tx, cancel).await
    }
}

/// Parse a Google-format SSE response stream. Shared between Google and Vertex.
async fn parse_google_sse_response(
    response: reqwest::Response,
    config: &StreamConfig,
    provider_name: &str,
    tx: mpsc::UnboundedSender<StreamEvent>,
    cancel: tokio_util::sync::CancellationToken,
) -> Result<Message, ProviderError> {
    use futures::StreamExt;
    use serde::Deserialize;
    use tracing::{debug, warn};

    let mut content: Vec<Content> = Vec::new();
    let mut usage = Usage::default();
    let mut stop_reason = StopReason::Stop;

    let _ = tx.send(StreamEvent::Start);

    let mut stream = response.bytes_stream();
    let mut buffer = String::new();

    loop {
        tokio::select! {
            _ = cancel.cancelled() => {
                return Err(ProviderError::Cancelled);
            }
            chunk = stream.next() => {
                match chunk {
                    None => break,
                    Some(Err(e)) => {
                        warn!("Vertex stream error: {}", e);
                        break;
                    }
                    Some(Ok(bytes)) => {
                        buffer.push_str(&String::from_utf8_lossy(&bytes));

                        while let Some(pos) = buffer.find("\n\n") {
                            let event_str = buffer[..pos].to_string();
                            buffer = buffer[pos + 2..].to_string();

                            let data = event_str
                                .lines()
                                .find(|l| l.starts_with("data: "))
                                .map(|l| &l[6..])
                                .unwrap_or("");

                            if data.is_empty() {
                                continue;
                            }

                            #[derive(Deserialize)]
                            struct Chunk {
                                #[serde(default)]
                                candidates: Option<Vec<Candidate>>,
                                #[serde(default, rename = "usageMetadata")]
                                usage_metadata: Option<UsageMeta>,
                            }
                            #[derive(Deserialize)]
                            struct Candidate {
                                #[serde(default)]
                                content: Option<CContent>,
                                #[serde(default, rename = "finishReason")]
                                finish_reason: Option<String>,
                            }
                            #[derive(Deserialize)]
                            struct CContent {
                                #[serde(default)]
                                parts: Vec<Part>,
                            }
                            #[derive(Deserialize)]
                            struct Part {
                                #[serde(default)]
                                text: Option<String>,
                                #[serde(default, rename = "functionCall")]
                                function_call: Option<FCall>,
                            }
                            #[derive(Deserialize)]
                            struct FCall {
                                name: String,
                                #[serde(default)]
                                args: Option<serde_json::Value>,
                            }
                            #[derive(Deserialize)]
                            struct UsageMeta {
                                #[serde(default, rename = "promptTokenCount")]
                                prompt_token_count: Option<u64>,
                                #[serde(default, rename = "candidatesTokenCount")]
                                candidates_token_count: Option<u64>,
                                #[serde(default, rename = "totalTokenCount")]
                                total_token_count: Option<u64>,
                            }

                            let parsed: Chunk = match serde_json::from_str(data) {
                                Ok(c) => c,
                                Err(e) => {
                                    debug!("Failed to parse Vertex chunk: {}", e);
                                    continue;
                                }
                            };

                            for candidate in parsed.candidates.unwrap_or_default() {
                                if let Some(c) = candidate.content {
                                    for part in c.parts {
                                        if let Some(text) = part.text {
                                            let idx = content.iter().position(|c| matches!(c, Content::Text { .. }));
                                            let idx = match idx {
                                                Some(i) => i,
                                                None => {
                                                    content.push(Content::Text { text: String::new() });
                                                    content.len() - 1
                                                }
                                            };
                                            if let Some(Content::Text { text: t }) = content.get_mut(idx) {
                                                t.push_str(&text);
                                            }
                                            let _ = tx.send(StreamEvent::TextDelta {
                                                content_index: idx,
                                                delta: text,
                                            });
                                        }
                                        if let Some(fc) = part.function_call {
                                            let id = format!("vertex-fc-{}", content.len());
                                            let args = fc.args.unwrap_or(serde_json::Value::Object(Default::default()));
                                            let idx = content.len();
                                            content.push(Content::ToolCall {
                                                id: id.clone(),
                                                name: fc.name.clone(),
                                                arguments: args,
                                            });
                                            let _ = tx.send(StreamEvent::ToolCallStart {
                                                content_index: idx,
                                                id,
                                                name: fc.name,
                                            });
                                            let _ = tx.send(StreamEvent::ToolCallEnd { content_index: idx });
                                            stop_reason = StopReason::ToolUse;
                                        }
                                    }
                                }
                                if let Some(reason) = candidate.finish_reason {
                                    stop_reason = match reason.as_str() {
                                        "STOP" => StopReason::Stop,
                                        "MAX_TOKENS" => StopReason::Length,
                                        _ => StopReason::Stop,
                                    };
                                }
                            }

                            if let Some(u) = parsed.usage_metadata {
                                usage.input = u.prompt_token_count.unwrap_or(0);
                                usage.output = u.candidates_token_count.unwrap_or(0);
                                usage.total_tokens = u.total_token_count.unwrap_or(0);
                            }
                        }
                    }
                }
            }
        }
    }

    let message = Message::Assistant {
        content,
        stop_reason,
        model: config.model_config.id.clone(),
        provider: provider_name.to_string(),
        usage,
        timestamp: now_ms(),
        error_message: None,
    };

    let _ = tx.send(StreamEvent::Done {
        message: message.clone(),
    });
    Ok(message)
}

/// Build the request body for Vertex AI (same format as Google GenAI).
fn build_vertex_request_body(config: &StreamConfig) -> serde_json::Value {
    // Same format as Google GenAI
    let mut contents: Vec<serde_json::Value> = Vec::new();

    for msg in &config.messages {
        match msg {
            Message::User { content, .. } => {
                let parts: Vec<serde_json::Value> = content
                    .iter()
                    .filter_map(|c| match c {
                        Content::Text { text } => Some(serde_json::json!({"text": text})),
                        Content::Image { data, mime_type } => Some(serde_json::json!({
                            "inlineData": {"mimeType": mime_type, "data": data},
                        })),
                        _ => None,
                    })
                    .collect();
                contents.push(serde_json::json!({"role": "user", "parts": parts}));
            }
            Message::Assistant { content, .. } => {
                let parts: Vec<serde_json::Value> = content
                    .iter()
                    .filter_map(|c| match c {
                        Content::Text { text } => Some(serde_json::json!({"text": text})),
                        Content::ToolCall {
                            name, arguments, ..
                        } => Some(serde_json::json!({
                            "functionCall": {"name": name, "args": arguments},
                        })),
                        _ => None,
                    })
                    .collect();
                contents.push(serde_json::json!({"role": "model", "parts": parts}));
            }
            Message::ToolResult {
                tool_name, content, ..
            } => {
                let text = content
                    .iter()
                    .find_map(|c| match c {
                        Content::Text { text } => Some(text.clone()),
                        _ => None,
                    })
                    .unwrap_or_default();

                let mut parts = vec![serde_json::json!({
                    "functionResponse": {"name": tool_name, "response": {"result": text}}
                })];

                for c in content {
                    if let Content::Image { data, mime_type } = c {
                        parts.push(serde_json::json!({
                            "inlineData": {"mimeType": mime_type, "data": data},
                        }));
                    }
                }

                contents.push(serde_json::json!({
                    "role": "user",
                    "parts": parts,
                }));
            }
        }
    }

    let mut body = serde_json::json!({"contents": contents});

    if !config.system_prompt.is_empty() {
        body["systemInstruction"] = serde_json::json!({"parts": [{"text": config.system_prompt}]});
    }

    let mut gen_config = serde_json::json!({});
    if let Some(max) = config.max_tokens {
        gen_config["maxOutputTokens"] = serde_json::json!(max);
    }
    if let Some(temp) = config.temperature {
        gen_config["temperature"] = serde_json::json!(temp);
    }
    // Vertex AI shares Gemini's structured-output shape (responseMimeType +
    // optional responseSchema inside generationConfig).
    match &config.response_format {
        ResponseFormat::Text => {}
        ResponseFormat::JsonObject => {
            gen_config["responseMimeType"] = serde_json::json!("application/json");
        }
        ResponseFormat::JsonSchema { schema, .. } => {
            gen_config["responseMimeType"] = serde_json::json!("application/json");
            gen_config["responseSchema"] = schema.clone();
        }
    }
    if gen_config != serde_json::json!({}) {
        body["generationConfig"] = gen_config;
    }

    if !config.tools.is_empty() {
        let declarations: Vec<serde_json::Value> = config
            .tools
            .iter()
            .map(|t| {
                serde_json::json!({
                    "name": t.name,
                    "description": t.description,
                    "parameters": t.parameters,
                })
            })
            .collect();
        body["tools"] = serde_json::json!([{"functionDeclarations": declarations}]);
    }

    body
}