A minimalist, async-first Rust library for LLM interactions with streaming support.
- Guide (tutorials, patterns, custom providers): https://weavemindai.github.io/MiniLLMLibRS/
- API reference (every type and method): https://docs.rs/minillmlib
- Async-first: Built on Tokio for high-performance async operations
- Streaming Support: First-class SSE streaming for real-time responses
- Conversation Trees:
ChatNodeprovides 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)
Add to your Cargo.toml:
[dependencies]
minillmlib = "0.2"
tokio = { version = "1", features = ["rt-multi-thread", "macros"] }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-2.5-flash-lite");
// 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(())
}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-hereuse 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(¶ms)).await?;
println!("{}", response.text().unwrap());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);
}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"use minillmlib::{ChatNode, GeneratorInfo, ImageData, MessageContent, Message, Role};
let generator = GeneratorInfo::openrouter("google/gemini-2.5-flash-lite");
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?;use minillmlib::{AudioData, MessageContent};
let audio = AudioData::from_file("./audio.mp3")?;
let content = MessageContent::with_audio("Transcribe this audio.", &[audio]);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(¶ms)).await?;
// response.text() will contain valid, repaired JSONlet 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 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 completionOpenRouter routing is provider-specific, so it's attached via
with_openrouter_routing (which carries it under the request's provider key);
non-OpenRouter providers simply ignore it.
use minillmlib::{CompletionParameters, ProviderSettings};
let routing = 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_openrouter_routing(routing);Mark what to cache on the tree; the provider decides the wire (Anthropic emits
cache_control, OpenAI auto-caches). Switch the provider and the same code works.
let root = ChatNode::root(big_system_prompt);
root.cache_breakpoint(); // cache just the system prompt
// ...or NodeCompletionParameters::new().with_cache(true) to cache the whole prefix
// Warm the cache before an agent run (cheap to call repeatedly):
let warm_cost = some_node.ensure_cached(&generator, None).await?;
// Clear marks:
root.clear_cache_breakpoint(); // one node
root.clear_all_cache_breakpoints(); // whole treeCache tokens are priced with distinct read/write rates (cache reads are ~0.1× input; cache writes a ~1.25× premium):
let price = TokenPrice::new(1.0, 5.0) // $/Mtok input, output
.with_cache_rates(0.1, 1.25); // $/Mtok cache-read, cache-write// 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"}));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));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.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)?;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();use minillmlib::{ChatNode, GeneratorInfo, NodeCompletionParameters, CostInfo};
use std::sync::{Arc, Mutex};
let generator = GeneratorInfo::openrouter("google/gemini-2.5-flash-lite");
// 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_cost_tracking(true)
.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(¶ms)).await?;
println!("Total spent: {} credits", *total_cost.lock().unwrap());| 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 |
CostResolution |
Whether a reported cost is Resolved, Unpriced, or Unknown |
// Pre-configured providers
GeneratorInfo::openrouter(model) // OpenRouter (OpenAI wire, native USD cost)
GeneratorInfo::openai(model) // OpenAI (token-only; price via with_token_price)
GeneratorInfo::anthropic(model) // Native Anthropic /v1/messages, x-api-key auth
GeneratorInfo::claude_subscription(model)// Anthropic wire, Claude Pro/Max OAuth token
GeneratorInfo::custom(name, url, model) // Custom OpenAI-compatible endpoint
// Auth builder methods
.with_api_key(key) // provider chooses header (Bearer / x-api-key)
.with_api_key_from_env("ENV_VAR")
.with_bearer_token(token) // OAuth / subscription bearer token
.with_bearer_token_from_env("ENV_VAR")
// Other builder methods
.with_token_price(TokenPrice::new(in_per_mtok, out_per_mtok)) // cost estimate for token-only providers
.with_provider(Arc::new(MyProvider)) // swap the wire dialect
.with_header(name, value)
.with_vision()
.with_audio()
.with_max_context(length)
.with_default_params(params)A Claude Pro/Max subscription OAuth token authenticates against the native Anthropic API the same way an API key does, but draws on your subscription's rolling quota (the 5-hour / 7-day window) instead of pay-as-you-go API billing.
claude_subscription resolves the token in this order:
- the
ANTHROPIC_AUTH_TOKENenv var, if set (explicit override, e.g. fromclaude setup-token; you keep it fresh); - otherwise the live Claude Code credential at
~/.claude/.credentials.json(claudeAiOauth.accessToken), which Claude Code keeps refreshed, so if you're logged into Claude Code with your subscription, it just works.
use minillmlib::{ChatNode, GeneratorInfo, TokenPrice};
// Anthropic returns token counts but no dollar cost, so set a price for a
// resolved cost ESTIMATE (otherwise tracking reports `Unpriced`).
let generator = GeneratorInfo::claude_subscription("claude-haiku-4-5")
.with_token_price(TokenPrice::new(1.0, 5.0)); // $/Mtok in, $/Mtok out
let root = ChatNode::root("You are helpful.");
let response = root.chat("Hello!", &generator).await?;Subscription vs Console. A subscription token (from Claude Code) bills your Pro/Max plan. A Console/API OAuth token (e.g. from the
antCLI) bills your API account, not the subscription; for Console use an API key viaGeneratorInfo::anthropic(model). Verify which bucket you're hitting by the response's rate-limit headers: subscription returnsanthropic-ratelimit-unified-5h-*; the API tier returnsanthropic-ratelimit-input-tokens-limit.
| 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 |
response_format |
Option<ResponseFormat> |
None |
Force JSON output |
reasoning |
Option<ReasoningConfig> |
None |
Extended-thinking effort/budget |
extra |
Option<HashMap> |
None |
Provider-specific keys (incl. OpenRouter routing) |
| 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 |
track_cost |
bool |
false |
Request and report usage/cost |
token_price |
Option<TokenPrice> |
None |
Per-request price override (token-only providers) |
cost_callback |
Option<CostCallback> |
None |
Callback for cost info |
| 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 |
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# Default: all offline tests (unit + offline integration). No API calls, free.
cargo test
# Unit tests only (fast)
cargo test --lib
# Live integration tests (REAL, billed API calls): opt in with the `live` feature.
# Reads OPENROUTER_API_KEY, ANTHROPIC_API_KEY, ANTHROPIC_AUTH_TOKEN from the env
# (or a .env); each live test skips gracefully if its key is absent.
cargo test --features live
# Run with output
cargo test -- --nocaptureWithout --features live, every network test skips, so cargo test is free,
offline, and deterministic even when real keys are present in your environment.
MIT License - see LICENSE for details.
Contributions are welcome! Please feel free to submit a Pull Request.