Struct OllamaClient 

pub struct OllamaClient { /* private fields */ }

Implementations

impl OllamaClient

pub fn new(model: &str) -> Result<Self>

Creates a new OllamaClient with the default Ollama URL (http://localhost:11434). Checks that Ollama is reachable before returning.

pub fn new_with_url(base_url: &str, model: &str) -> Result<Self>

Creates a new OllamaClient with a custom base URL. Checks that Ollama is reachable before returning.

pub fn is_available(&self) -> bool

Quick health check – returns true if Ollama responds to GET /api/tags.

pub fn ensure_model(&self) -> Result<()>

Checks if the configured model is already pulled. If not, pulls it.

pub fn generate(&self, prompt: &str, system: Option<&str>) -> Result<String>

Generates a completion using the /api/chat endpoint (Ollama chat format). This is compatible with both Ollama and vMLX/OpenAI-compatible servers. Returns the response text.

pub fn expand_query(&self, query: &str) -> Result<Vec<String>>

Uses the LLM to expand a search query into additional search terms.

pub fn summarize_memories( &self, memories: &[(String, String)], ) -> Result<String>

Takes (title, content) pairs and returns a consolidated summary.

pub fn auto_tag(&self, title: &str, content: &str) -> Result<Vec<String>>

Generates suggested tags for a memory.

pub fn embed_text(&self, text: &str, embed_model: &str) -> Result<Vec<f32>>

Generate an embedding vector via Ollama’s /api/embed endpoint.

Used for nomic-embed-text-v1.5 on smart/autonomous tiers.

pub fn ensure_embed_model(&self, model: &str) -> Result<()>

Ensure an embedding model is pulled in Ollama.

pub fn detect_contradiction(&self, mem_a: &str, mem_b: &str) -> Result<bool>

Returns true if two memory contents contradict each other.

Trait Implementations

impl AutonomyLlm for OllamaClient

fn auto_tag(&self, title: &str, content: &str) -> Result<Vec<String>>

Generate tags for a memory.

fn detect_contradiction(&self, mem_a: &str, mem_b: &str) -> Result<bool>

Return true iff the two pieces of content contradict each other.

fn summarize_memories(&self, memories: &[(String, String)]) -> Result<String>

Produce a consolidated summary of N memories.