minillmlib

Crates.iominillmlib
lib.rsminillmlib
version0.2.2
created_at2025-12-13 20:37:57.217199+00
updated_at2026-01-24 00:14:17.642116+00
descriptionA minimalist, async-first Rust library for LLM interactions with streaming support
homepagehttps://github.com/qfeuilla/MiniLLMLibRS
repositoryhttps://github.com/qfeuilla/MiniLLMLibRS
max_upload_size
id1983387
size356,606
Quentin FEUILLADE--MONTIXI (qfeuilla)

documentation

https://docs.rs/minillmlib

README

MiniLLMLib-RS

A minimalist, async-first Rust library for LLM interactions with streaming support.

Crates.io Documentation CI License: MIT

Features

  • Async-first: Built on Tokio for high-performance async operations
  • Streaming Support: First-class SSE streaming for real-time responses
  • Conversation Trees: ChatNode provides tree-based conversation structure with branching
  • Tree Manipulation: detach(), merge(), tree iterators (depth-first, breadth-first, leaves)
  • Template Substitution: Format kwargs with {placeholders} in messages
  • Thread Serialization: Save/load conversation threads to/from JSON files
  • Cost Tracking: OpenRouter usage accounting with callbacks
  • Multimodal: Support for images and audio in messages
  • JSON Repair: Robust handling of malformed JSON from LLM outputs
  • OpenRouter Compatible: Works with OpenRouter, OpenAI, and any OpenAI-compatible API
  • Retry with Backoff: Built-in exponential backoff and retry logic
  • Provider Routing: OpenRouter provider settings (sort, ignore, data collection)

Installation

Add to your Cargo.toml:

[dependencies]
minillmlib = "0.2"
tokio = { version = "1", features = ["rt-multi-thread", "macros"] }

Quick Start

use minillmlib::{ChatNode, GeneratorInfo};

#[tokio::main]
async fn main() -> minillmlib::Result<()> {
    // Load .env and configure logging
    minillmlib::init();

    // Create a generator for OpenRouter
    let generator = GeneratorInfo::openrouter("google/gemini-2.0-flash-lite-001");

    // Start a conversation
    let root = ChatNode::root("You are a helpful assistant.");
    let response = root.chat("Hello!", &generator).await?;

    println!("Assistant: {}", response.text().unwrap_or_default());
    Ok(())
}

Environment Variables

Set your API key in a .env file or environment:

OPENROUTER_API_KEY=sk-or-v1-your-key-here
# Or for direct OpenAI:
OPENAI_API_KEY=sk-your-key-here

Usage Examples

Basic Completion

use minillmlib::{ChatNode, GeneratorInfo, CompletionParameters, NodeCompletionParameters};

let generator = GeneratorInfo::openrouter("anthropic/claude-3.5-sonnet");
let root = ChatNode::root("You are helpful.");
let user = root.add_user("What is 2+2?");

// With custom parameters
let params = NodeCompletionParameters::new()
    .with_params(
        CompletionParameters::new()
            .with_temperature(0.0)
            .with_max_tokens(100)
    );

let response = user.complete(&generator, Some(&params)).await?;
println!("{}", response.text().unwrap());

Streaming

let root = ChatNode::root("You are helpful.");
let user = root.add_user("Tell me a story.");

let mut stream = user.complete_streaming(&generator, None).await?;

while let Some(chunk) = stream.next_chunk().await {
    print!("{}", chunk?.delta);
}

Multi-turn Conversation

let root = ChatNode::root("You are helpful.");

// First turn
let response1 = root.chat("My name is Alice.", &generator).await?;

// Second turn - context is preserved
let response2 = response1.chat("What's my name?", &generator).await?;
// Response will mention "Alice"

Image Input

use minillmlib::{ChatNode, GeneratorInfo, ImageData, MessageContent, Message, Role};

let generator = GeneratorInfo::openrouter("google/gemini-2.0-flash-lite-001");
let image = ImageData::from_file("./image.jpg")?;

let content = MessageContent::with_images("Describe this image.", &[image]);
let root = ChatNode::root("You are helpful.");
let user = root.add_child(ChatNode::new(Message {
    role: Role::User,
    content,
    name: None,
    tool_call_id: None,
    tool_calls: None,
}));

let response = user.complete(&generator, None).await?;

Audio Input

use minillmlib::{AudioData, MessageContent};

let audio = AudioData::from_file("./audio.mp3")?;
let content = MessageContent::with_audio("Transcribe this audio.", &[audio]);

JSON Response with Repair

let params = NodeCompletionParameters::new()
    .with_parse_json(true)           // Enable JSON repair
    .with_crash_on_refusal(true)     // Retry if no valid JSON
    .with_retry(3);                  // Number of retries

let response = user.complete(&generator, Some(&params)).await?;
// response.text() will contain valid, repaired JSON

Retry with Exponential Backoff

let params = NodeCompletionParameters::new()
    .with_retry(5)
    .with_exp_back_off(true)
    .with_back_off_time(1.0)    // Start with 1 second
    .with_max_back_off(30.0)    // Max 30 seconds
    .with_crash_on_empty(true); // Retry on empty responses

Force Prepend (Constrained Generation)

// Force the model to start its response with specific text
let params = NodeCompletionParameters::new()
    .with_force_prepend("Score: ");

// Response will start with "Score: " followed by the model's completion

OpenRouter Provider Settings

use minillmlib::{CompletionParameters, ProviderSettings};

let provider = ProviderSettings::new()
    .sort_by_throughput()                              // or .sort_by_price()
    .deny_data_collection()
    .with_ignore(vec!["SambaNova".to_string()]);       // Exclude providers

let params = CompletionParameters::new()
    .with_provider(provider);

Custom/Extra Parameters

// Pass arbitrary parameters to the API
let params = CompletionParameters::new()
    .with_extra("custom_param", serde_json::json!(42))
    .with_extra("another", serde_json::json!({"nested": "value"}));

Pretty Print Conversations

use minillmlib::{pretty_messages, format_conversation, PrettyPrintConfig};

let root = ChatNode::root("You are helpful.");
let user = root.add_user("Hello");
let assistant = user.add_assistant("Hi there!");

// Default formatting
let pretty = format_conversation(&assistant);
// Output: "SYSTEM: You are helpful.\n\nUSER: Hello\n\nASSISTANT: Hi there!"

// Custom formatting
let config = PrettyPrintConfig::new("[SYS] ", "\n[USR] ", "\n[AST] ");
let pretty = pretty_messages(&assistant, Some(&config));

Template Substitution (Format Kwargs)

use minillmlib::ChatNode;

// Create a reusable prompt template
let root = ChatNode::root("You are {bot_name}, a {style} assistant.");
root.set_format_kwarg("bot_name", "Claude");
root.set_format_kwarg("style", "helpful");

let user = root.add_user("Hi {bot_name}!");

// Get formatted messages with placeholders replaced
let formatted = user.formatted_thread();
// Messages now contain "You are Claude, a helpful assistant." etc.

Save and Load Conversation Threads

use minillmlib::ChatNode;

// Build a conversation
let root = ChatNode::root("You are helpful.");
root.set_format_kwarg("name", "Alice");
let user = root.add_user("Hello {name}!");
let assistant = user.add_assistant("Hi there!");

// Save to JSON file
assistant.save_thread("conversation.json")?;

// Load from JSON file (returns root and leaf)
let (loaded_root, loaded_leaf) = ChatNode::from_thread_file("conversation.json")?;

// Or load from JSON string
let json = r#"{"prompts": [{"role": "system", "content": "Hello"}], "required_kwargs": {}}"#;
let (root, leaf) = ChatNode::from_thread_json(json)?;

Tree Manipulation

use minillmlib::ChatNode;

// Navigate to root from any node
let root = some_deep_node.get_root();

// Detach a subtree
let subtree = node.detach();  // node is now a new root

// Merge trees
let merged = tree1_leaf.merge(&tree2_leaf);  // tree2's root becomes child of tree1_leaf

// Iterate over tree
for node in root.iter_depth_first() {
    println!("{}", node.text().unwrap_or_default());
}

// Get all leaves
let leaves = root.iter_leaves();

// Count nodes
let count = root.node_count();

Cost Tracking (OpenRouter)

use minillmlib::{ChatNode, GeneratorInfo, NodeCompletionParameters, CostInfo};
use std::sync::{Arc, Mutex};

let generator = GeneratorInfo::openrouter("google/gemini-2.0-flash-lite-001");

// Track costs across multiple requests
let total_cost = Arc::new(Mutex::new(0.0));
let cost_tracker = total_cost.clone();

let params = NodeCompletionParameters::new()
    .with_openrouter_cost_tracking()
    .with_cost_callback(move |info: CostInfo| {
        *cost_tracker.lock().unwrap() += info.cost;
        println!("Request cost: {} credits", info.cost);
        println!("Tokens: {} prompt, {} completion", 
            info.prompt_tokens, info.completion_tokens);
    });

let root = ChatNode::root("You are helpful.");
let user = root.add_user("Hello!");
let response = user.complete(&generator, Some(&params)).await?;

println!("Total spent: {} credits", *total_cost.lock().unwrap());

API Reference

Core Types

Type Description
ChatNode A node in the conversation tree
GeneratorInfo LLM provider configuration
CompletionParameters Generation parameters (temperature, max_tokens, etc.)
NodeCompletionParameters Per-request settings (retry, JSON parsing, cost tracking, etc.)
Message A single message with role and content
MessageContent Text or multimodal content
ThreadData Serializable conversation thread with format kwargs
CostInfo Cost and token usage information from completions
CostTrackingType Cost tracking mode (None, OpenRouter)

GeneratorInfo Methods

// Pre-configured providers
GeneratorInfo::openrouter(model)    // OpenRouter API
GeneratorInfo::openai(model)        // OpenAI API
GeneratorInfo::anthropic(model)     // Anthropic API
GeneratorInfo::custom(name, url, model)  // Custom endpoint

// Builder methods
.with_api_key(key)
.with_api_key_from_env("ENV_VAR")
.with_header(name, value)
.with_vision()
.with_audio()
.with_max_context(length)
.with_default_params(params)

CompletionParameters

Parameter Type Default Description
max_tokens Option<u32> 4096 Maximum tokens to generate
temperature Option<f32> 0.7 Sampling temperature
top_p Option<f32> None Nucleus sampling
top_k Option<u32> None Top-k sampling
stop Option<Vec<String>> None Stop sequences
seed Option<u64> None Random seed
provider Option<ProviderSettings> None OpenRouter provider routing
extra Option<HashMap> None Custom parameters

NodeCompletionParameters

Parameter Type Default Description
system_prompt Option<String> None Override system prompt
parse_json bool false Parse/repair JSON response
force_prepend Option<String> None Force response prefix
retry u32 4 Retry attempts
exp_back_off bool false Exponential backoff
back_off_time f64 1.0 Initial backoff (seconds)
max_back_off f64 15.0 Max backoff (seconds)
crash_on_refusal bool false Error if no JSON
crash_on_empty_response bool false Error if empty
cost_tracking CostTrackingType None Enable cost tracking
cost_callback Option<CostCallback> None Callback for cost info

ProviderSettings (OpenRouter)

Parameter Description
order Ordered list of providers to try
sort Sort by: "price", "throughput", "latency"
ignore Providers to exclude
data_collection "allow" or "deny"
allow_fallbacks Allow fallback providers

CLI Tool

The library includes a CLI for JSON repair:

# Repair JSON from file
minillmlib-cli input.json

# Repair JSON from stdin
echo '{"key": "value",}' | minillmlib-cli

Running Tests

# Run all tests (unit + integration)
cargo test

# Run only unit tests (fast, no API calls)
cargo test --lib

# Run integration tests (requires API key)
cargo test --test integration_tests

# Run with output
cargo test -- --nocapture

License

MIT License - see LICENSE for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Commit count: 0

cargo fmt