edgequake-llm 0.10.0

Multi-provider LLM abstraction library with caching, rate limiting, and cost tracking
Documentation
//! Gemini (Google AI) discovery — DYNAMIC strategy.
//!
//! `GET /v1beta/models` returns inputTokenLimit, outputTokenLimit,
//! supportedGenerationMethods, and thinking: bool.
//!
//! Source: <https://ai.google.dev/gemini-api/docs/models>

use async_trait::async_trait;
use chrono::Utc;

use crate::discovery::registry::gemini_models;
use crate::discovery::traits::ModelDiscoveryProvider;
use crate::discovery::types::{DiscoveredModel, DiscoverySource, DiscoveryStrategy};
use crate::model_config::{ModelCapabilities, ModelType};

pub struct GeminiDiscovery {
    api_key: Option<String>,
}

impl Default for GeminiDiscovery {
    fn default() -> Self {
        Self::new()
    }
}

impl GeminiDiscovery {
    pub fn new() -> Self {
        Self {
            api_key: std::env::var("GEMINI_API_KEY")
                .or_else(|_| std::env::var("GOOGLE_API_KEY"))
                .ok(),
        }
    }

    pub fn with_api_key(api_key: String) -> Self {
        Self {
            api_key: Some(api_key),
        }
    }

    async fn fetch_from_api(&self) -> Option<Vec<DiscoveredModel>> {
        let key = self.api_key.as_ref()?;
        let url = format!(
            "https://generativelanguage.googleapis.com/v1beta/models?key={}",
            key
        );
        let client = reqwest::Client::new();
        let resp = client
            .get(&url)
            .timeout(std::time::Duration::from_secs(10))
            .send()
            .await
            .ok()?;

        if !resp.status().is_success() {
            return None;
        }

        let body: serde_json::Value = resp.json().await.ok()?;
        let models_arr = body["models"].as_array()?;

        let now = Utc::now();
        let models: Vec<DiscoveredModel> = models_arr
            .iter()
            .filter_map(|m| {
                let full_name = m["name"].as_str()?;
                let id = full_name.strip_prefix("models/").unwrap_or(full_name);
                let display = m["displayName"].as_str().unwrap_or(id);
                let ctx = m["inputTokenLimit"].as_u64().unwrap_or(0) as usize;
                let max_out = m["outputTokenLimit"].as_u64().unwrap_or(0) as usize;
                let thinking = m["thinking"].as_bool().unwrap_or(false);

                let methods: Vec<String> = m["supportedGenerationMethods"]
                    .as_array()
                    .map(|a| {
                        a.iter()
                            .filter_map(|v| v.as_str().map(String::from))
                            .collect()
                    })
                    .unwrap_or_default();

                let is_embedding = methods.iter().any(|m| m == "embedContent")
                    && !methods.iter().any(|m| m == "generateContent");

                if ctx == 0 && !is_embedding {
                    return None;
                }

                Some(DiscoveredModel {
                    id: id.to_string(),
                    name: display.to_string(),
                    provider: "gemini".into(),
                    context_length: ctx,
                    max_output_tokens: max_out,
                    capabilities: ModelCapabilities {
                        context_length: ctx,
                        max_output_tokens: max_out,
                        supports_vision: true,
                        supports_function_calling: methods.iter().any(|m| m == "generateContent"),
                        supports_json_mode: true,
                        supports_streaming: true,
                        supports_thinking: thinking,
                        supports_system_message: true,
                        ..Default::default()
                    },
                    source: DiscoverySource::DynamicApi,
                    discovered_at: now,
                    available: true,
                    model_type: if is_embedding {
                        ModelType::Embedding
                    } else {
                        ModelType::Llm
                    },
                    ..Default::default()
                })
            })
            .collect();
        Some(models)
    }
}

#[async_trait]
impl ModelDiscoveryProvider for GeminiDiscovery {
    fn provider_id(&self) -> &str {
        "gemini"
    }

    fn discovery_strategy(&self) -> DiscoveryStrategy {
        DiscoveryStrategy::Dynamic
    }

    async fn discover_models(&self) -> crate::error::Result<Vec<DiscoveredModel>> {
        match self.fetch_from_api().await {
            Some(models) if !models.is_empty() => Ok(models),
            _ => {
                tracing::info!("Gemini API unavailable, using static registry");
                Ok(gemini_models())
            }
        }
    }
}