aither_core/llm/
mod.rs

1//! # Language Models and Conversation Management
2//!
3//! This module provides everything you need to work with language models in a provider-agnostic way.
4//! Build chat applications, generate structured output, and integrate tools without being tied to any specific AI service.
5//!
6//! ## Core Components
7//!
8//! - **[`LanguageModel`]** - The main trait for text generation and conversation
9//! - **[`LLMRequest`]** - Encapsulates messages, tools, and parameters for model calls
10//! - **[`Event`]** - Stream events from the model (text, reasoning, tool calls)
11//! - **[`Message`]** - Represents individual messages in a conversation
12//! - **[`Tool`]** - Function calling interface for extending model capabilities
13//!
14//! ## Design Philosophy
15//!
16//! The core crate provides a **low-level API** that emits events without executing tools.
17//! Tool execution is the responsibility of higher-level abstractions like `aither-agent`.
18//!
19//! This design allows:
20//! - Full control over tool execution flow
21//! - Hooks for intercepting and modifying tool calls
22//! - Proper context management between turns
23//! - Clean separation between LLM communication and agent logic
24//!
25//! ## Quick Start
26//!
27//! ### Basic Conversation
28//!
29//! ```rust,ignore
30//! use aither::llm::{LanguageModel, Event, oneshot};
31//! use futures_lite::StreamExt;
32//!
33//! async fn chat_with_model(model: impl LanguageModel) -> Result<String, Box<dyn std::error::Error>> {
34//!     let request = oneshot("You are a helpful assistant", "What's the capital of Japan?");
35//!     let mut stream = model.respond(request);
36//!     let mut full_text = String::new();
37//!
38//!     while let Some(event) = stream.next().await {
39//!         match event? {
40//!             Event::Text(chunk) => full_text.push_str(&chunk),
41//!             Event::Reasoning(thought) => eprintln!("[thinking] {}", thought),
42//!             Event::ToolCall(call) => {
43//!                 // Handle tool call (typically done by agent crate)
44//!                 println!("Tool requested: {}", call.name);
45//!             }
46//!             _ => {}
47//!         }
48//!     }
49//!
50//!     Ok(full_text)
51//! }
52//! ```
53//!
54//! ### With Tools (Agent-Controlled)
55//!
56//! ```rust,ignore
57//! use aither::llm::{LanguageModel, Event, LLMRequest, Message};
58//!
59//! // The core crate does NOT execute tools - it emits ToolCall events.
60//! // Tool execution should be handled by the agent crate.
61//! let request = LLMRequest::new([Message::user("What's the weather?")])
62//!     .with_tool_definitions(vec![weather_tool_definition()]);
63//!
64//! let mut stream = model.respond(request);
65//! while let Some(event) = stream.next().await {
66//!     match event? {
67//!         Event::ToolCall(call) => {
68//!             // Execute tool and continue conversation
69//!             let result = my_tool_executor.execute(&call).await;
70//!             // Add result to messages and send another request...
71//!         }
72//!         _ => {}
73//!     }
74//! }
75//! ```
76
77/// Assistant module for managing assistant-related functionality.
78pub mod assistant;
79/// Event types for streaming responses.
80pub mod event;
81/// Message types and conversation handling.
82pub mod message;
83/// Model profiles and capabilities.
84pub mod model;
85/// Provider module for managing language model providers and their configurations.
86pub mod provider;
87/// Provider-opaque reasoning state carried across turns.
88pub mod reasoning;
89/// Deep research workflows and agent capabilities.
90pub mod researcher;
91/// Tool system for function calling.
92pub mod tool;
93
94use crate::llm::{model::Parameters, tool::Tools};
95use alloc::{
96    boxed::Box,
97    string::{String, ToString},
98    sync::Arc,
99    vec,
100    vec::Vec,
101};
102use core::{any::TypeId, future::Future};
103pub use event::{Event, ToolCall, Usage};
104use futures_core::Stream;
105use futures_lite::{StreamExt, pin};
106pub use message::{Attachment, Message, Role};
107pub use provider::LanguageModelProvider;
108pub use reasoning::ReasoningState;
109pub use researcher::{
110    ResearchCitation, ResearchEvent, ResearchFinding, ResearchOptions, ResearchReport,
111    ResearchRequest, ResearchSource, ResearchStage, Researcher, ResearcherProfile,
112};
113use schemars::{JsonSchema, schema_for};
114use serde::de::DeserializeOwned;
115pub use tool::{IntoToolResult, Tool, ToolResult};
116
117use crate::llm::model::Profile;
118
119/// Why a structured-output call failed.
120///
121/// [`LanguageModel::respond`] reports provider failures through the model's own
122/// [`LanguageModel::Error`]. Structured output adds a second, separate way to
123/// fail — the model answered, but not with the requested shape — so this keeps
124/// the two distinguishable instead of flattening both into one opaque error.
125/// Callers need that distinction: a rate limit is worth retrying, a schema
126/// mismatch is worth re-prompting, and an auth failure is worth neither.
127#[derive(Debug)]
128pub enum GenerateError<E> {
129    /// The provider itself failed: transport, rate limit, auth, and so on.
130    Provider(E),
131
132    /// The provider answered, but the response did not match the schema.
133    ///
134    /// Carries the text that could not be parsed so callers can log or retry.
135    Parse {
136        /// The underlying deserialization failure.
137        source: serde_json::Error,
138        /// The response text that failed to parse, truncated for logging.
139        response: String,
140    },
141}
142
143impl<E: core::fmt::Display> core::fmt::Display for GenerateError<E> {
144    fn fmt(&self, f: &mut core::fmt::Formatter<'_>) -> core::fmt::Result {
145        match self {
146            Self::Provider(err) => write!(f, "language model request failed: {err}"),
147            Self::Parse { source, response } => {
148                write!(
149                    f,
150                    "structured output did not match the requested schema: {source}; response: {response}"
151                )
152            }
153        }
154    }
155}
156
157impl<E: core::error::Error + 'static> core::error::Error for GenerateError<E> {
158    fn source(&self) -> Option<&(dyn core::error::Error + 'static)> {
159        match self {
160            Self::Provider(err) => Some(err),
161            Self::Parse { source, .. } => Some(source),
162        }
163    }
164}
165
166/// Builder-style request passed into [`LanguageModel::respond`].
167///
168/// Wraps the full conversation, model parameters, and tool definitions a provider
169/// needs in order to execute a call.
170#[derive(Debug, Clone)]
171pub struct LLMRequest {
172    messages: Vec<Message>,
173    parameters: Parameters,
174    tool_definitions: Vec<tool::ToolDefinition>,
175}
176
177impl LLMRequest {
178    /// Creates a request from the provided messages using default parameters.
179    pub fn new(messages: impl Into<Vec<Message>>) -> Self {
180        Self {
181            messages: messages.into(),
182            parameters: Parameters::default(),
183            tool_definitions: Vec::new(),
184        }
185    }
186
187    /// Adds tool definitions to the request.
188    ///
189    /// These define what tools the model can request. The model will emit
190    /// [`Event::ToolCall`] events when it wants to use a tool.
191    #[must_use]
192    pub fn with_tool_definitions(mut self, definitions: Vec<tool::ToolDefinition>) -> Self {
193        self.tool_definitions = definitions;
194        self
195    }
196
197    /// Adds a single tool definition.
198    #[must_use]
199    pub fn with_tool<T: Tool>(mut self, tool: &T) -> Self {
200        self.tool_definitions.push(tool::ToolDefinition::new(tool));
201        self
202    }
203
204    /// Overrides the sampling parameters used for this call.
205    #[must_use]
206    pub fn with_parameters(mut self, parameters: Parameters) -> Self {
207        self.parameters = parameters;
208        self
209    }
210
211    /// Returns the current conversation messages.
212    #[must_use]
213    pub fn messages(&self) -> &[Message] {
214        &self.messages
215    }
216
217    /// Returns a mutable reference to messages for modification.
218    pub const fn messages_mut(&mut self) -> &mut Vec<Message> {
219        &mut self.messages
220    }
221
222    /// Returns the current parameter snapshot.
223    #[must_use]
224    pub const fn parameters(&self) -> &Parameters {
225        &self.parameters
226    }
227
228    /// Returns the tool definitions.
229    #[must_use]
230    pub fn tool_definitions(&self) -> &[tool::ToolDefinition] {
231        &self.tool_definitions
232    }
233
234    /// Breaks the request into owned components.
235    #[must_use]
236    pub fn into_parts(self) -> (Vec<Message>, Parameters, Vec<tool::ToolDefinition>) {
237        (self.messages, self.parameters, self.tool_definitions)
238    }
239}
240
241/// Legacy request builder that supports mutable tool registry.
242///
243/// This is provided for backwards compatibility with providers that
244/// handle tool execution internally (built-in tools).
245#[derive(Debug)]
246pub struct LLMRequestWithTools<'tools> {
247    inner: LLMRequest,
248    tools: &'tools mut Tools,
249}
250
251impl LLMRequest {
252    /// Attaches a mutable tool registry to the request.
253    ///
254    /// This is for providers that execute tools internally (e.g., built-in tools).
255    /// For agent-controlled tool execution, use `with_tool_definitions` instead.
256    pub fn with_tools(self, tools: &mut Tools) -> LLMRequestWithTools<'_> {
257        let definitions = tools.definitions();
258        LLMRequestWithTools {
259            inner: self.with_tool_definitions(definitions),
260            tools,
261        }
262    }
263}
264
265impl<'tools> LLMRequestWithTools<'tools> {
266    /// Returns the inner request.
267    #[must_use]
268    pub const fn request(&self) -> &LLMRequest {
269        &self.inner
270    }
271
272    /// Returns the tool registry.
273    #[must_use]
274    pub const fn tools(&mut self) -> &mut Tools {
275        self.tools
276    }
277
278    /// Breaks into components.
279    #[must_use]
280    pub fn into_parts(self) -> (LLMRequest, &'tools mut Tools) {
281        (self.inner, self.tools)
282    }
283
284    /// Invokes a registered tool by name.
285    ///
286    /// # Errors
287    /// Returns an error if tool is not found or the tool call fails.
288    pub async fn call_tool(&mut self, name: &str, args_json: &str) -> crate::Result<ToolResult> {
289        self.tools.call(name, args_json).await
290    }
291}
292
293/// Language models for text generation and conversation.
294///
295/// The `respond` method returns a stream of [`Event`]s. Tool calls are emitted
296/// as events and are NOT automatically executed - this allows higher-level
297/// abstractions (like agents) to control tool execution.
298///
299/// See the [module documentation](crate::llm) for examples and usage patterns.
300pub trait LanguageModel: Sized + Send + Sync {
301    /// The error type returned by this language model.
302    type Error: core::error::Error + Send + Sync + 'static;
303
304    /// Generates a streaming response to a conversation.
305    ///
306    /// Returns a stream of [`Event`]s including:
307    /// - `Event::Text` - Visible text chunks
308    /// - `Event::Reasoning` - Internal reasoning (for reasoning models)
309    /// - `Event::ToolCall` - Requests to execute tools (NOT auto-executed)
310    /// - `Event::BuiltInToolResult` - Results from provider's built-in tools
311    fn respond(&self, request: LLMRequest)
312    -> impl Stream<Item = Result<Event, Self::Error>> + Send;
313
314    /// Generates a streaming response with a mutable tool registry.
315    ///
316    /// This is for providers that support built-in tool execution.
317    /// The default implementation ignores the tools and delegates to `respond`.
318    fn respond_with_tools(
319        &self,
320        request: LLMRequestWithTools<'_>,
321    ) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
322        let (inner, _tools) = request.into_parts();
323        self.respond(inner)
324    }
325
326    /// Generates structured output conforming to JSON schema.
327    ///
328    /// # Note for Implementors
329    /// By default, we use a system prompt to instruct the model to generate structured output based on the provided JSON schema.
330    /// However, that is not efficient enough, if supported, provider should override this method to provide native structured generation support.
331    /// Native structured generation can apply decode rules in token-level, ensuring the output is always valid JSON, and reducing parsing errors.
332    fn generate<T: JsonSchema + DeserializeOwned + 'static>(
333        &self,
334        request: LLMRequest,
335    ) -> impl Future<Output = Result<T, GenerateError<Self::Error>>> + Send {
336        async { structured_generate(self, request).await }
337    }
338
339    /// Completes given text prefix.
340    fn complete(&self, prefix: &str) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
341        self.respond(oneshot("Please complete the following text:", prefix))
342    }
343
344    /// Summarizes text.
345    ///
346    /// # Note for Implementors
347    /// By default, we provide a generic summarization prompt. However, some model provider, like Apple Intelligence, may have native summarization support.
348    /// It would load a summarization-specific lora at runtime, providing better quality.
349    fn summarize(&self, text: &str) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
350        summarize(self, text)
351    }
352
353    /// Categorizes text.
354    ///
355    /// # Note for Implementors
356    /// By default, we use a system prompt to instruct the model to categorize text based on the provided JSON schema.
357    /// However, that is not efficient enough, if supported, provider should override this method to provide native categorization support.
358    fn categorize<T: JsonSchema + DeserializeOwned + 'static>(
359        &self,
360        text: &str,
361    ) -> impl Future<Output = Result<T, GenerateError<Self::Error>>> + Send {
362        async { categorize_text(self, text).await }
363    }
364
365    /// Returns model profile and capabilities.
366    ///
367    /// See [`Profile`] for details on model metadata.
368    fn profile(&self) -> impl Future<Output = Profile> + Send;
369}
370
371macro_rules! impl_language_model {
372    ($($name:ident),*) => {
373        $(
374            impl<T: LanguageModel> LanguageModel for $name<T> {
375                type Error = T::Error;
376
377                fn respond(
378                    &self,
379                    request: LLMRequest,
380                ) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
381                    T::respond(self, request)
382                }
383
384                fn respond_with_tools(
385                    &self,
386                    request: LLMRequestWithTools<'_>,
387                ) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
388                    T::respond_with_tools(self, request)
389                }
390
391                fn generate<U: JsonSchema + DeserializeOwned + 'static>(
392                    &self,
393                    request: LLMRequest,
394                ) -> impl Future<Output = Result<U, GenerateError<Self::Error>>> + Send {
395                    T::generate(self, request)
396                }
397
398                fn complete(
399                    &self,
400                    prefix: &str,
401                ) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
402                    T::complete(self, prefix)
403                }
404
405                fn summarize(
406                    &self,
407                    text: &str,
408                ) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
409                    T::summarize(self, text)
410                }
411
412                fn categorize<U: JsonSchema + DeserializeOwned + 'static>(
413                    &self,
414                    text: &str,
415                ) -> impl Future<Output = Result<U, GenerateError<Self::Error>>> + Send {
416                    T::categorize(self, text)
417                }
418
419                fn profile(&self) -> impl Future<Output = Profile> + Send {
420                    T::profile(self)
421                }
422            }
423        )*
424    };
425}
426
427impl<T: LanguageModel> LanguageModel for &T {
428    type Error = T::Error;
429
430    fn respond(
431        &self,
432        request: LLMRequest,
433    ) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
434        T::respond(self, request)
435    }
436
437    fn respond_with_tools(
438        &self,
439        request: LLMRequestWithTools<'_>,
440    ) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
441        T::respond_with_tools(self, request)
442    }
443
444    fn generate<U: JsonSchema + DeserializeOwned + 'static>(
445        &self,
446        request: LLMRequest,
447    ) -> impl Future<Output = Result<U, GenerateError<Self::Error>>> + Send {
448        T::generate(self, request)
449    }
450
451    fn complete(&self, prefix: &str) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
452        T::complete(self, prefix)
453    }
454
455    fn summarize(&self, text: &str) -> impl Stream<Item = Result<Event, Self::Error>> + Send {
456        T::summarize(self, text)
457    }
458
459    fn categorize<U: JsonSchema + DeserializeOwned + 'static>(
460        &self,
461        text: &str,
462    ) -> impl Future<Output = Result<U, GenerateError<Self::Error>>> + Send {
463        T::categorize(self, text)
464    }
465
466    fn profile(&self) -> impl Future<Output = Profile> + Send {
467        T::profile(self)
468    }
469}
470
471mod prompts;
472
473impl_language_model!(Arc, Box);
474
475/// Collects text from an event stream.
476///
477/// # Errors
478///
479/// Returns the first stream error encountered while collecting text chunks.
480pub async fn collect_text<S, E>(stream: S) -> Result<String, E>
481where
482    S: Stream<Item = Result<Event, E>>,
483{
484    pin!(stream);
485    let mut result = String::new();
486    while let Some(event) = stream.next().await {
487        if let Event::Text(text) = event? {
488            result.push_str(&text);
489        }
490    }
491    Ok(result)
492}
493
494async fn structured_generate<T: JsonSchema + DeserializeOwned + 'static, M: LanguageModel>(
495    model: &M,
496    mut request: LLMRequest,
497) -> Result<T, GenerateError<M::Error>> {
498    let schema = schema_for!(T);
499
500    // If it is a string, we are not required to set up structured generation and JSON schema.
501    let json = if schema.as_value().is_string() {
502        let stream = model.respond(request);
503        let response = collect_text(stream)
504            .await
505            .map_err(GenerateError::Provider)?;
506        // Let's encode it as JSON string. Serializing a String cannot fail.
507        serde_json::to_string(&response).map_err(|source| GenerateError::Parse {
508            source,
509            response: response.clone(),
510        })?
511    } else {
512        // Serializing a `Schema` is infallible in practice, but keep the error
513        // typed rather than unwrapping.
514        let schema =
515            serde_json::to_string_pretty(&schema).map_err(|source| GenerateError::Parse {
516                source,
517                response: String::new(),
518            })?;
519        let prompt = prompts::generate(&schema);
520        request.messages.push(Message::system(prompt));
521        request.parameters.structured_outputs = true;
522
523        let stream = model.respond(request);
524        collect_text(stream)
525            .await
526            .map_err(GenerateError::Provider)?
527    };
528
529    parse_json_with_recovery(&json).map_err(|source| GenerateError::Parse {
530        source,
531        response: truncate_for_error(&json),
532    })
533}
534
535/// Keeps a failed response short enough to log without dumping a whole context.
536fn truncate_for_error(response: &str) -> String {
537    const LIMIT: usize = 500;
538    response.chars().take(LIMIT).collect()
539}
540
541/// Convenience helper that creates a single system + user [`LLMRequest`].
542pub fn oneshot(system: impl Into<String>, user: impl Into<String>) -> LLMRequest {
543    let messages = vec![Message::system(system.into()), Message::user(user.into())];
544    LLMRequest::new(messages)
545}
546
547fn summarize<M: LanguageModel>(
548    model: &M,
549    text: &str,
550) -> impl Stream<Item = Result<Event, M::Error>> + Send {
551    let messages = oneshot("Summarize text:", text);
552    model.respond(messages)
553}
554
555async fn categorize_text<T: JsonSchema + DeserializeOwned + 'static, M: LanguageModel>(
556    model: &M,
557    text: &str,
558) -> Result<T, GenerateError<M::Error>> {
559    let request = oneshot("Categorize text by provided schema", text);
560    model.generate(request).await
561}
562
563fn parse_json_with_recovery<T: DeserializeOwned + 'static>(
564    json: &str,
565) -> Result<T, serde_json::Error> {
566    use serde::de::Error as _;
567
568    let trimmed = json.trim();
569    let mut last_error: Option<serde_json::Error> = None;
570    let mut last_candidate: Option<String> = None;
571
572    for candidate in build_json_candidates(trimmed) {
573        match serde_json::from_str::<T>(&candidate) {
574            Ok(value) => return Ok(value),
575            Err(err) => {
576                last_error = Some(err);
577                last_candidate = Some(candidate);
578            }
579        }
580    }
581
582    // A model asked for a plain string will often answer with an object or a
583    // bare word instead. Re-encode whatever it did produce as a JSON string.
584    if is_string_type::<T>()
585        && let Some(candidate) = last_candidate
586        && let Ok(value) = serde_json::from_str::<serde_json::Value>(&candidate)
587    {
588        let text = match value {
589            serde_json::Value::String(s) => s,
590            other => other.to_string(),
591        };
592        let encoded = serde_json::to_string(&text)?;
593        if let Ok(value) = serde_json::from_str::<T>(&encoded) {
594            return Ok(value);
595        }
596    }
597
598    Err(last_error.unwrap_or_else(|| {
599        serde_json::Error::custom("structured output was empty or missing a JSON block")
600    }))
601}
602
603fn strip_code_fences(raw: &str) -> Option<String> {
604    let trimmed = raw.trim();
605    let fence_start = trimmed.find("```")?;
606    let after_fence = &trimmed[fence_start + 3..];
607    let mut lines = after_fence.lines();
608    let _maybe_lang = lines.next();
609    let body = lines.collect::<Vec<_>>().join("\n");
610    let content = body.rfind("```").map_or(body.as_str(), |end| &body[..end]);
611
612    let cleaned = content.trim();
613    if cleaned.is_empty() {
614        None
615    } else {
616        Some(cleaned.to_string())
617    }
618}
619
620fn extract_json_block(raw: &str) -> Option<String> {
621    if let (Some(start), Some(end)) = (raw.find('{'), raw.rfind('}'))
622        && end >= start
623    {
624        let candidate = &raw[start..=end];
625        if !candidate.trim().is_empty() {
626            return Some(candidate.trim().to_string());
627        }
628    }
629    if let (Some(start), Some(end)) = (raw.find('['), raw.rfind(']'))
630        && end >= start
631    {
632        let candidate = &raw[start..=end];
633        if !candidate.trim().is_empty() {
634            return Some(candidate.trim().to_string());
635        }
636    }
637    None
638}
639
640fn build_json_candidates(raw: &str) -> Vec<String> {
641    let mut candidates = Vec::new();
642
643    if !raw.is_empty() {
644        candidates.push(raw.to_string());
645    }
646
647    if let Some(fenced) = strip_code_fences(raw) {
648        candidates.push(fenced);
649    }
650
651    if let Some(block) = extract_json_block(raw) {
652        candidates.push(block);
653    }
654
655    if let Some(dequoted) = dequote_json_string(raw) {
656        candidates.push(dequoted);
657    }
658
659    if let Some(stripped) = strip_leading_label(raw, "json") {
660        candidates.push(stripped);
661    }
662
663    let mut deduped = Vec::new();
664    for candidate in candidates {
665        if deduped.iter().all(|seen| seen != &candidate) {
666            deduped.push(candidate);
667        }
668    }
669    deduped
670}
671
672fn dequote_json_string(raw: &str) -> Option<String> {
673    let trimmed = raw.trim();
674    if !(trimmed.starts_with('"') && trimmed.ends_with('"')) {
675        return None;
676    }
677    let inner: String = serde_json::from_str(trimmed).ok()?;
678    if inner.trim().is_empty() {
679        None
680    } else {
681        Some(inner)
682    }
683}
684
685fn strip_leading_label(raw: &str, label: &str) -> Option<String> {
686    let trimmed = raw.trim_start();
687    if !trimmed.to_ascii_lowercase().starts_with(label) {
688        return None;
689    }
690    let stripped = trimmed[label.len()..]
691        .trim_start_matches(|c: char| c.is_whitespace() || c == ':' || c == '-')
692        .trim();
693    if stripped.is_empty() {
694        None
695    } else {
696        Some(stripped.to_string())
697    }
698}
699
700fn is_string_type<T: 'static>() -> bool {
701    TypeId::of::<T>() == TypeId::of::<String>()
702}
703
704#[cfg(test)]
705mod tests {
706    use super::parse_json_with_recovery;
707    use alloc::string::String;
708    use serde::Deserialize;
709
710    #[derive(Debug, Deserialize, PartialEq, Eq)]
711    struct Foo {
712        a: u8,
713    }
714
715    #[test]
716    fn parses_plain_json() {
717        let foo: Foo = parse_json_with_recovery(r#"{"a":1}"#).unwrap();
718        assert_eq!(foo, Foo { a: 1 });
719    }
720
721    #[test]
722    fn parses_code_fence_json() {
723        let foo: Foo = parse_json_with_recovery("```json\n{\"a\":2}\n```").unwrap();
724        assert_eq!(foo, Foo { a: 2 });
725    }
726
727    #[test]
728    fn parses_embedded_block() {
729        let foo: Foo = parse_json_with_recovery("noise {\"a\":3} trailing").unwrap();
730        assert_eq!(foo, Foo { a: 3 });
731    }
732
733    #[test]
734    fn parses_quoted_json_string() {
735        let foo: Foo = parse_json_with_recovery(r#""{\"a\":4}""#).unwrap();
736        assert_eq!(foo, Foo { a: 4 });
737    }
738
739    #[test]
740    fn parses_labeled_json() {
741        let foo: Foo = parse_json_with_recovery("json {\"a\":5}").unwrap();
742        assert_eq!(foo, Foo { a: 5 });
743    }
744
745    #[test]
746    fn coerces_object_to_string() {
747        let value: String =
748            parse_json_with_recovery(r#"{"title":"summary","type":"content"}"#).unwrap();
749        assert!(
750            value.contains("\"title\":\"summary\"") && value.contains("\"type\":\"content\""),
751            "unexpected value: {value}"
752        );
753    }
754}
aither_core/llm/mod.rs

aither_core/llm/
mod.rs
