feat(embedded): add GLM tool format adapter for code fence stripping

GLM-4 models wrap tool calls in markdown code fences and inline backticks,
which prevents the streaming parser from detecting them. This adapter:

- Strips ```json and ``` code fence markers during streaming
- Strips inline backticks from tool call JSON
- Handles chunked streaming correctly (buffers potential fence lines)
- Transforms GLM native format (<|assistant|>tool_name) to g3 JSON format

Also refactors embedded provider into module structure:
- embedded/mod.rs - module exports
- embedded/provider.rs - main EmbeddedProvider (moved from embedded.rs)
- embedded/adapters/mod.rs - ToolFormatAdapter trait
- embedded/adapters/glm.rs - GLM-specific adapter

Includes 22 unit tests covering edge cases like nested JSON in strings,
chunk boundary handling, and false pattern detection.

Updates README to show GLM-4 9B now works () for agentic tasks.
This commit is contained in:
Dhanji R. Prasanna
2026-01-29 12:52:09 +11:00
parent 457ba35f80
commit 8191a5e8e6
5 changed files with 871 additions and 4 deletions

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@@ -133,7 +133,7 @@ g3 supports local models via llama.cpp with Metal acceleration on macOS. Here's
|-------|------|-------|---------------|-------| |-------|------|-------|---------------|-------|
| ~~Qwen3-32B~~ (Dense) | 18 GB | Slow | ❌ | Good reasoning, but flails on execution and crashes | | ~~Qwen3-32B~~ (Dense) | 18 GB | Slow | ❌ | Good reasoning, but flails on execution and crashes |
| Qwen3-14B | 8.4 GB | Medium | ⭐⭐ | Understands tasks but makes implementation errors | | Qwen3-14B | 8.4 GB | Medium | ⭐⭐ | Understands tasks but makes implementation errors |
| ~~GLM-4 9B~~ | 5.7 GB | Fast | | Uses incompatible native tool format, not JSON | | GLM-4 9B | 5.7 GB | Fast | ⭐⭐ | Works with adapter (strips code fences) |
| Qwen3-4B | 2.3 GB | Very Fast | ❌ | Generates malformed tool calls - not for agentic use | | Qwen3-4B | 2.3 GB | Very Fast | ❌ | Generates malformed tool calls - not for agentic use |
| ~~Qwen3-30B-A3B~~ (MoE) | 17 GB | Very Fast | ❌ | **Avoid** - loops infinitely on tool calls | | ~~Qwen3-30B-A3B~~ (MoE) | 17 GB | Very Fast | ❌ | **Avoid** - loops infinitely on tool calls |

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@@ -0,0 +1,733 @@
//! GLM/Z-AI tool format adapter
//!
//! GLM models can use two tool calling formats:
//!
//! 1. Native format:
//! ```text
//! <|assistant|>tool_name
//! {"arg": "value"}
//! ```
//!
//! 2. Code-fenced JSON (when following system prompt instructions):
//! ```text
//! ```json
//! {"tool": "shell", "args": {"command": "ls"}}
//! ```
//! ```
//!
//! This adapter handles both formats and strips code fences when present.
use super::{AdapterOutput, ToolFormatAdapter};
/// Safety limits to prevent unbounded buffering
const MAX_PATTERN_BUFFER: usize = 20; // `<|assistant|>` is 13 chars
const MAX_TOOL_NAME: usize = 64;
const MAX_JSON_BUFFER: usize = 65536; // 64KB
const MAX_NEWLINES_BEFORE_JSON: usize = 2;
/// The pattern that indicates a tool call in GLM format
const ASSISTANT_PATTERN: &str = "<|assistant|>";
/// Parser state for the main state machine
#[derive(Debug, Clone, PartialEq)]
enum ParseState {
/// Normal prose, watching for `<|assistant|>`
Prose,
/// Saw start of potential pattern (e.g., "<|"), buffering to confirm
MaybePattern,
/// Confirmed `<|assistant|>`, now reading tool name until newline
InToolName,
/// Got tool name, waiting for `{` to start JSON (allowing whitespace/newlines)
AwaitingJson { tool_name: String, newline_count: usize },
/// Inside JSON body, tracking depth to find end
InToolJson { tool_name: String },
}
/// State for JSON parsing (to handle strings correctly)
#[derive(Debug, Clone, Copy, PartialEq)]
enum JsonState {
/// Normal JSON, counting braces
Normal,
/// Inside a string literal, ignore braces
InString,
/// Just saw backslash in string, next char is escaped
InStringEscape,
}
/// Adapter for GLM/Z-AI model tool calling format
#[derive(Debug)]
pub struct GlmToolAdapter {
/// Buffer for accumulating content
buffer: String,
/// Buffer for current line (to detect code fences)
line_buffer: String,
/// Whether we're currently inside a code fence
in_code_fence: bool,
/// Current parse state
state: ParseState,
/// JSON parsing state (when in InToolJson)
json_state: JsonState,
/// Brace depth for JSON parsing
json_depth: i32,
/// Content to emit that's been confirmed as prose
pending_emit: String,
}
impl GlmToolAdapter {
pub fn new() -> Self {
Self {
buffer: String::new(),
line_buffer: String::new(),
in_code_fence: false,
state: ParseState::Prose,
json_state: JsonState::Normal,
json_depth: 0,
pending_emit: String::new(),
}
}
/// Process a character for code fence detection (streaming-safe)
/// Returns the string to emit (empty if content should be suppressed)
fn process_for_code_fence(&mut self, c: char) -> String {
if c == '\n' {
// End of line - check if it's a code fence
let trimmed = self.line_buffer.trim();
if trimmed.starts_with("```") {
let after_fence = trimmed.trim_start_matches('`').trim();
if after_fence.is_empty() || after_fence.chars().all(|c| c.is_ascii_alphanumeric()) {
// This is a code fence marker line - suppress it
self.line_buffer.clear();
return String::new(); // Don't emit anything for fence lines
}
}
// Not a fence line - just emit the newline
// (buffered content was already emitted char-by-char)
self.line_buffer.clear();
c.to_string()
} else {
self.line_buffer.push(c);
// Only suppress output if the line looks like it could be a code fence
// A code fence line starts with optional whitespace then ```
let trimmed = self.line_buffer.trim_start();
if trimmed.starts_with('`') && trimmed.len() <= 10 {
// Potentially a fence marker - buffer until we see newline
String::new()
} else {
// Not a fence - emit the entire buffer (which includes current char)
// and clear it since we've emitted everything
let result = std::mem::take(&mut self.line_buffer);
result
}
}
}
/// Strip markdown code fence markers from output
///
/// GLM models sometimes wrap tool calls in code fences like:
/// ```json
/// {"tool": "shell", ...}
/// ```
///
/// This strips those markers so the JSON can be parsed as a tool call.
fn strip_code_fences(text: &str) -> String {
text.lines()
.filter_map(|line| {
let trimmed = line.trim();
// Filter out lines that are just code fence markers (with optional language)
if trimmed.starts_with("```") {
// Check if there's content after the fence marker on the same line
let after_fence = trimmed.trim_start_matches('`').trim();
if after_fence.is_empty() || after_fence.chars().all(|c| c.is_ascii_alphanumeric()) {
// Just a fence marker (possibly with language like "json"), skip it
return None;
}
}
Some(line)
})
.collect::<Vec<_>>()
.join("\n")
}
/// Strip inline code backticks from text
///
/// GLM models sometimes wrap tool calls in inline backticks like:
/// `{"tool": "shell", ...}`
fn strip_inline_backticks(text: &str) -> String {
let trimmed = text.trim();
if trimmed.starts_with('`') && trimmed.ends_with('`') && !trimmed.starts_with("```") {
trimmed[1..trimmed.len()-1].to_string()
} else {
text.to_string()
}
}
/// Check if a string is a valid tool name
/// Pattern: starts with letter or underscore, followed by alphanumeric or underscore
fn is_valid_tool_name(name: &str) -> bool {
if name.is_empty() || name.len() > MAX_TOOL_NAME {
return false;
}
let mut chars = name.chars();
match chars.next() {
Some(c) if c.is_ascii_alphabetic() || c == '_' => {}
_ => return false,
}
chars.all(|c| c.is_ascii_alphanumeric() || c == '_')
}
/// Process a single character in Prose state
fn process_prose_char(&mut self, c: char) {
// First, filter through code fence detection
let filtered = self.process_for_code_fence(c);
for filtered_c in filtered.chars() {
if filtered_c == '<' {
// Potential start of pattern
self.buffer.push(filtered_c);
self.state = ParseState::MaybePattern;
} else {
self.pending_emit.push(filtered_c);
}
}
// If empty string, the character is being buffered for code fence detection
}
/// Process a single character in MaybePattern state
fn process_maybe_pattern_char(&mut self, c: char) {
self.buffer.push(c);
// Check if buffer matches start of pattern
if ASSISTANT_PATTERN.starts_with(&self.buffer) {
// Still could be the pattern
if self.buffer == ASSISTANT_PATTERN {
// Complete pattern match!
self.buffer.clear();
self.state = ParseState::InToolName;
}
// else: keep buffering
} else {
// Not the pattern, emit buffer as prose
self.pending_emit.push_str(&self.buffer);
self.buffer.clear();
self.state = ParseState::Prose;
}
// Safety: if buffer gets too long, it's not our pattern
if self.buffer.len() > MAX_PATTERN_BUFFER {
self.pending_emit.push_str(&self.buffer);
self.buffer.clear();
self.state = ParseState::Prose;
}
}
/// Process a single character in InToolName state
fn process_tool_name_char(&mut self, c: char) {
if c == '\n' {
// End of tool name
let tool_name = self.buffer.trim().to_string();
self.buffer.clear();
if Self::is_valid_tool_name(&tool_name) {
self.state = ParseState::AwaitingJson {
tool_name,
newline_count: 1,
};
} else {
// Invalid tool name, emit as prose
self.pending_emit.push_str(ASSISTANT_PATTERN);
self.pending_emit.push_str(&tool_name);
self.pending_emit.push(c);
self.state = ParseState::Prose;
}
} else if c.is_whitespace() && self.buffer.is_empty() {
// Skip leading whitespace after <|assistant|>
} else {
self.buffer.push(c);
// Safety: tool name too long
if self.buffer.len() > MAX_TOOL_NAME {
self.pending_emit.push_str(ASSISTANT_PATTERN);
self.pending_emit.push_str(&self.buffer);
self.buffer.clear();
self.state = ParseState::Prose;
}
}
}
/// Process a single character in AwaitingJson state
fn process_awaiting_json_char(&mut self, c: char, tool_name: String, newline_count: usize) {
if c == '{' {
// Start of JSON!
self.buffer.push(c);
self.json_depth = 1;
self.json_state = JsonState::Normal;
self.state = ParseState::InToolJson { tool_name };
} else if c == '\n' {
let new_count = newline_count + 1;
if new_count > MAX_NEWLINES_BEFORE_JSON {
// Too many newlines, not a tool call
self.pending_emit.push_str(ASSISTANT_PATTERN);
self.pending_emit.push_str(&tool_name);
for _ in 0..new_count {
self.pending_emit.push('\n');
}
self.state = ParseState::Prose;
} else {
self.state = ParseState::AwaitingJson {
tool_name,
newline_count: new_count,
};
}
} else if c.is_whitespace() {
// Skip whitespace while waiting for JSON
self.state = ParseState::AwaitingJson {
tool_name,
newline_count,
};
} else {
// Non-JSON character, not a tool call
self.pending_emit.push_str(ASSISTANT_PATTERN);
self.pending_emit.push_str(&tool_name);
self.pending_emit.push('\n');
self.pending_emit.push(c);
self.state = ParseState::Prose;
}
}
/// Process a single character in InToolJson state
fn process_json_char(&mut self, c: char, tool_name: String) -> Option<String> {
self.buffer.push(c);
// Update JSON state machine
match self.json_state {
JsonState::Normal => {
match c {
'{' => self.json_depth += 1,
'}' => {
self.json_depth -= 1;
if self.json_depth == 0 {
// JSON complete!
let json_args = self.buffer.clone();
self.buffer.clear();
self.state = ParseState::Prose;
// Transform to g3 format
let transformed = format!(
"{{\"tool\": \"{}\", \"args\": {}}}",
tool_name, json_args
);
return Some(transformed);
}
}
'"' => self.json_state = JsonState::InString,
_ => {}
}
}
JsonState::InString => {
match c {
'\\' => self.json_state = JsonState::InStringEscape,
'"' => self.json_state = JsonState::Normal,
_ => {}
}
}
JsonState::InStringEscape => {
// Any character after backslash, return to InString
self.json_state = JsonState::InString;
}
}
// Safety: JSON buffer too large
if self.buffer.len() > MAX_JSON_BUFFER {
// Emit as malformed - let downstream handle it
self.pending_emit.push_str(ASSISTANT_PATTERN);
self.pending_emit.push_str(&tool_name);
self.pending_emit.push('\n');
self.pending_emit.push_str(&self.buffer);
self.buffer.clear();
self.state = ParseState::Prose;
self.json_state = JsonState::Normal;
self.json_depth = 0;
}
// Keep state for next iteration
self.state = ParseState::InToolJson { tool_name };
None
}
}
impl Default for GlmToolAdapter {
fn default() -> Self {
Self::new()
}
}
impl ToolFormatAdapter for GlmToolAdapter {
fn handles(&self, model_type: &str) -> bool {
model_type.contains("glm")
}
fn process_chunk(&mut self, chunk: &str) -> AdapterOutput {
let mut has_tool_call = false;
for c in chunk.chars() {
match self.state.clone() {
ParseState::Prose => {
self.process_prose_char(c);
}
ParseState::MaybePattern => {
self.process_maybe_pattern_char(c);
}
ParseState::InToolName => {
self.process_tool_name_char(c);
}
ParseState::AwaitingJson { tool_name, newline_count } => {
self.process_awaiting_json_char(c, tool_name, newline_count);
}
ParseState::InToolJson { tool_name } => {
if let Some(transformed) = self.process_json_char(c, tool_name) {
self.pending_emit.push('\n');
self.pending_emit.push_str(&transformed);
has_tool_call = true;
}
}
}
}
// Return accumulated emit content, stripping any code fence markers
let raw_emit = std::mem::take(&mut self.pending_emit);
let stripped_fences = Self::strip_code_fences(&raw_emit);
let emit = Self::strip_inline_backticks(&stripped_fences);
AdapterOutput {
emit: emit.to_string(),
has_tool_call,
}
}
fn flush(&mut self) -> AdapterOutput {
let mut emit = std::mem::take(&mut self.pending_emit);
// Emit any buffered content as-is
match &self.state {
ParseState::Prose => {
// Nothing extra to emit
}
ParseState::MaybePattern => {
emit.push_str(&self.buffer);
}
ParseState::InToolName => {
emit.push_str(ASSISTANT_PATTERN);
emit.push_str(&self.buffer);
}
ParseState::AwaitingJson { tool_name, newline_count } => {
emit.push_str(ASSISTANT_PATTERN);
emit.push_str(tool_name);
for _ in 0..*newline_count {
emit.push('\n');
}
}
ParseState::InToolJson { tool_name } => {
emit.push_str(ASSISTANT_PATTERN);
emit.push_str(tool_name);
emit.push('\n');
emit.push_str(&self.buffer);
}
}
// Flush any remaining line buffer content (if not a code fence)
if !self.line_buffer.is_empty() {
let trimmed = self.line_buffer.trim();
let is_fence = trimmed.starts_with("```") &&
(trimmed.trim_start_matches('`').trim().is_empty() ||
trimmed.trim_start_matches('`').trim().chars().all(|c| c.is_ascii_alphanumeric()));
if !is_fence {
emit.push_str(&self.line_buffer);
}
}
self.reset();
// Strip code fences and inline backticks from final output
let stripped_fences = Self::strip_code_fences(&emit);
let stripped = Self::strip_inline_backticks(&stripped_fences);
AdapterOutput {
emit: stripped,
has_tool_call: false,
}
}
fn reset(&mut self) {
self.buffer.clear();
self.line_buffer.clear();
self.in_code_fence = false;
self.state = ParseState::Prose;
self.json_state = JsonState::Normal;
self.json_depth = 0;
self.pending_emit.clear();
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_handles_glm_models() {
let adapter = GlmToolAdapter::new();
assert!(adapter.handles("glm4"));
assert!(adapter.handles("glm"));
assert!(adapter.handles("some-glm-variant"));
assert!(!adapter.handles("qwen"));
assert!(!adapter.handles("llama"));
}
#[test]
fn test_valid_tool_names() {
assert!(GlmToolAdapter::is_valid_tool_name("shell"));
assert!(GlmToolAdapter::is_valid_tool_name("read_file"));
assert!(GlmToolAdapter::is_valid_tool_name("_private"));
assert!(GlmToolAdapter::is_valid_tool_name("tool123"));
assert!(!GlmToolAdapter::is_valid_tool_name(""));
assert!(!GlmToolAdapter::is_valid_tool_name("123tool"));
assert!(!GlmToolAdapter::is_valid_tool_name("tool-name"));
assert!(!GlmToolAdapter::is_valid_tool_name("tool name"));
}
#[test]
fn test_basic_tool_call() {
let mut adapter = GlmToolAdapter::new();
let input = "Let me list files.<|assistant|>shell\n{\"command\": \"ls\"}";
let output = adapter.process_chunk(input);
assert!(output.has_tool_call);
assert!(output.emit.contains("Let me list files."));
assert!(output.emit.contains(r#"{"tool": "shell", "args": {"command": "ls"}}"#));
}
#[test]
fn test_tool_call_chunked() {
let mut adapter = GlmToolAdapter::new();
// Simulate chunked input
let chunks = vec![
"Let me ",
"list.<|assis",
"tant|>shell\n{\"co",
"mmand\": \"ls\"}",
];
let mut full_output = String::new();
let mut found_tool = false;
for chunk in chunks {
let output = adapter.process_chunk(chunk);
full_output.push_str(&output.emit);
if output.has_tool_call {
found_tool = true;
}
}
let final_output = adapter.flush();
full_output.push_str(&final_output.emit);
assert!(found_tool);
assert!(full_output.contains("Let me list."));
assert!(full_output.contains(r#"{"tool": "shell", "args": {"command": "ls"}}"#));
}
#[test]
fn test_nested_json_in_string() {
let mut adapter = GlmToolAdapter::new();
let input = r#"<|assistant|>shell
{"command": "echo '{\"nested\": true}'"}
Done."#;
let output = adapter.process_chunk(input);
let final_output = adapter.flush();
assert!(output.has_tool_call);
let full = format!("{}{}", output.emit, final_output.emit);
assert!(full.contains(r#""args": {"command": "echo '{\"nested\": true}'"}}"#));
}
#[test]
fn test_escaped_quotes_in_string() {
let mut adapter = GlmToolAdapter::new();
let input = r#"<|assistant|>shell
{"command": "echo \"hello\""}
Done."#;
let output = adapter.process_chunk(input);
assert!(output.has_tool_call);
assert!(output.emit.contains(r#""args": {"command": "echo \"hello\""}"#));
}
#[test]
fn test_false_pattern_in_prose() {
let mut adapter = GlmToolAdapter::new();
let input = "The format is <|assistant|>tool_name for GLM models.";
let output = adapter.process_chunk(input);
let final_output = adapter.flush();
// Should not detect as tool call since no JSON follows
assert!(!output.has_tool_call);
let full = format!("{}{}", output.emit, final_output.emit);
assert!(full.contains("<|assistant|>"));
}
#[test]
fn test_multiple_tool_calls() {
let mut adapter = GlmToolAdapter::new();
let input = r#"First:<|assistant|>shell
{"command": "ls"}
Second:<|assistant|>read_file
{"path": "test.txt"}"#;
let output = adapter.process_chunk(input);
assert!(output.has_tool_call);
assert!(output.emit.contains(r#"{"tool": "shell"#));
assert!(output.emit.contains(r#"{"tool": "read_file"#));
}
#[test]
fn test_whitespace_before_json() {
let mut adapter = GlmToolAdapter::new();
let input = "<|assistant|>shell\n {\"command\": \"ls\"}";
let output = adapter.process_chunk(input);
assert!(output.has_tool_call);
}
#[test]
fn test_extra_newline_before_json() {
let mut adapter = GlmToolAdapter::new();
let input = "<|assistant|>shell\n\n{\"command\": \"ls\"}";
let output = adapter.process_chunk(input);
assert!(output.has_tool_call);
}
#[test]
fn test_too_many_newlines_before_json() {
let mut adapter = GlmToolAdapter::new();
let input = "<|assistant|>shell\n\n\n{\"command\": \"ls\"}";
let output = adapter.process_chunk(input);
let final_output = adapter.flush();
// Should not detect as tool call - too many newlines
assert!(!output.has_tool_call);
let full = format!("{}{}", output.emit, final_output.emit);
assert!(full.contains("<|assistant|>shell"));
}
#[test]
fn test_invalid_tool_name() {
let mut adapter = GlmToolAdapter::new();
let input = "<|assistant|>123invalid\n{\"command\": \"ls\"}";
let output = adapter.process_chunk(input);
let final_output = adapter.flush();
// Should not detect as tool call - invalid name
assert!(!output.has_tool_call);
let full = format!("{}{}", output.emit, final_output.emit);
assert!(full.contains("<|assistant|>123invalid"));
}
#[test]
fn test_stream_ends_mid_pattern() {
let mut adapter = GlmToolAdapter::new();
let output = adapter.process_chunk("text<|assis");
let final_output = adapter.flush();
assert!(!output.has_tool_call);
let full = format!("{}{}", output.emit, final_output.emit);
assert_eq!(full, "text<|assis");
}
#[test]
fn test_stream_ends_mid_json() {
let mut adapter = GlmToolAdapter::new();
let output = adapter.process_chunk("<|assistant|>shell\n{\"command\": \"ls");
let final_output = adapter.flush();
assert!(!output.has_tool_call);
let full = format!("{}{}", output.emit, final_output.emit);
// Should emit the incomplete content
assert!(full.contains("<|assistant|>shell"));
assert!(full.contains("{\"command\": \"ls"));
}
#[test]
fn test_prose_with_angle_brackets() {
let mut adapter = GlmToolAdapter::new();
let input = "Use <html> tags and <|other|> patterns.";
let output = adapter.process_chunk(input);
let final_output = adapter.flush();
assert!(!output.has_tool_call);
let full = format!("{}{}", output.emit, final_output.emit);
assert_eq!(full, input);
}
#[test]
fn test_reset() {
let mut adapter = GlmToolAdapter::new();
// Start processing but don't finish
adapter.process_chunk("<|assistant|>shell\n{\"cmd");
// Reset
adapter.reset();
// Should be back to clean state
let output = adapter.process_chunk("Normal text");
assert_eq!(output.emit, "Normal text");
assert!(!output.has_tool_call);
}
}
#[test]
fn test_strip_code_fences() {
assert_eq!(
GlmToolAdapter::strip_code_fences("```json\n{\"tool\": \"shell\"}\n```"),
"{\"tool\": \"shell\"}"
);
assert_eq!(
GlmToolAdapter::strip_code_fences("```\n{\"tool\": \"shell\"}\n```"),
"{\"tool\": \"shell\"}"
);
assert_eq!(
GlmToolAdapter::strip_code_fences("normal text"),
"normal text"
);
assert_eq!(
GlmToolAdapter::strip_code_fences("```json\ncode\n```\nmore text"),
"code\nmore text"
);
}
#[test]
fn test_code_fenced_tool_call() {
let mut adapter = GlmToolAdapter::new();
let input = "```json\n{\"tool\": \"shell\", \"args\": {\"command\": \"ls\"}}\n```";
let output = adapter.process_chunk(input);
let final_output = adapter.flush();
let full = format!("{}{}", output.emit, final_output.emit);
// Should strip the code fences
assert!(!full.contains("```"));
assert!(full.contains("{\"tool\": \"shell\""));
}

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@@ -0,0 +1,98 @@
//! Tool format adapters for embedded models
//!
//! Different model families use different formats for tool calling.
//! Adapters transform model-specific formats to g3's standard JSON format:
//! `{"tool": "name", "args": {...}}`
//!
//! This module provides:
//! - `ToolFormatAdapter` trait for implementing format transformations
//! - `GlmToolAdapter` for GLM/Z-AI models that use `<|assistant|>tool_name` format
mod glm;
pub use glm::GlmToolAdapter;
/// Output from processing a chunk through an adapter
#[derive(Debug, Clone, Default)]
pub struct AdapterOutput {
/// Text safe to emit downstream (prose and/or complete tool calls)
pub emit: String,
/// True if a complete tool call was detected and transformed
pub has_tool_call: bool,
}
impl AdapterOutput {
pub fn new() -> Self {
Self::default()
}
pub fn with_emit(emit: String) -> Self {
Self {
emit,
has_tool_call: false,
}
}
pub fn with_tool_call(emit: String) -> Self {
Self {
emit,
has_tool_call: true,
}
}
}
/// Trait for adapting model-specific tool call formats to g3's standard format
///
/// Adapters are stateful to handle streaming - they buffer incomplete patterns
/// and emit complete chunks as soon as they're ready.
pub trait ToolFormatAdapter: Send + Sync {
/// Check if this adapter handles the given model type
fn handles(&self, model_type: &str) -> bool;
/// Process a chunk of model output
///
/// The adapter may buffer content if it's in the middle of a potential pattern.
/// Returns content that's safe to emit downstream.
fn process_chunk(&mut self, chunk: &str) -> AdapterOutput;
/// Flush any remaining buffered content (call at end of stream)
///
/// This should emit any buffered content, even if incomplete.
fn flush(&mut self) -> AdapterOutput;
/// Reset the adapter state (call between conversations)
fn reset(&mut self);
}
/// Create an adapter for the given model type, if one exists
pub fn create_adapter_for_model(model_type: &str) -> Option<Box<dyn ToolFormatAdapter>> {
let glm_adapter = GlmToolAdapter::new();
if glm_adapter.handles(model_type) {
return Some(Box::new(glm_adapter));
}
// Add other adapters here as needed:
// let mistral_adapter = MistralToolAdapter::new();
// if mistral_adapter.handles(model_type) { ... }
None
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_create_adapter_for_glm() {
assert!(create_adapter_for_model("glm4").is_some());
assert!(create_adapter_for_model("glm").is_some());
assert!(create_adapter_for_model("some-glm-variant").is_some());
}
#[test]
fn test_no_adapter_for_unknown() {
assert!(create_adapter_for_model("qwen").is_none());
assert!(create_adapter_for_model("llama").is_none());
assert!(create_adapter_for_model("mistral").is_none());
}
}

View File

@@ -0,0 +1,12 @@
//! Embedded LLM provider using llama.cpp
//!
//! This module provides local model inference via llama.cpp with Metal acceleration.
pub mod adapters;
mod provider;
// Re-export adapter types
pub use adapters::{create_adapter_for_model, AdapterOutput, ToolFormatAdapter};
// Re-export the main provider
pub use provider::EmbeddedProvider;

View File

@@ -82,6 +82,8 @@ fn suppress_llama_logging() {
// Provider Struct // Provider Struct
// ============================================================================ // ============================================================================
use super::adapters::create_adapter_for_model;
pub struct EmbeddedProvider { pub struct EmbeddedProvider {
name: String, name: String,
model: Arc<LlamaModel>, model: Arc<LlamaModel>,
@@ -540,8 +542,12 @@ impl LLMProvider for EmbeddedProvider {
let backend = self.backend.clone(); let backend = self.backend.clone();
let context_length = self.context_length; let context_length = self.context_length;
let threads = self.threads; let threads = self.threads;
let model_type = self.model_type.clone();
tokio::task::spawn_blocking(move || { tokio::task::spawn_blocking(move || {
// Create adapter for model-specific tool format transformation (e.g., GLM)
let mut adapter = create_adapter_for_model(&model_type);
let mut prepared = match prepare_context( let mut prepared = match prepare_context(
&model, &model,
&backend, &backend,
@@ -584,10 +590,18 @@ impl LLMProvider for EmbeddedProvider {
break; break;
} }
// Stream the token // Stream the token (through adapter if present)
if tx.blocking_send(Ok(make_text_chunk(token_str))).is_err() { let output_text = if let Some(ref mut adapt) = adapter {
let output = adapt.process_chunk(&token_str);
output.emit
} else {
token_str
};
if !output_text.is_empty() {
if tx.blocking_send(Ok(make_text_chunk(output_text))).is_err() {
return; // Receiver dropped return; // Receiver dropped
} }
}
if token_count >= params.max_tokens { if token_count >= params.max_tokens {
debug!("Reached max token limit: {}", params.max_tokens); debug!("Reached max token limit: {}", params.max_tokens);
@@ -609,6 +623,16 @@ impl LLMProvider for EmbeddedProvider {
} }
} }
// Flush any remaining content from the adapter
if let Some(ref mut adapt) = adapter {
let final_output = adapt.flush();
if !final_output.emit.is_empty() {
if tx.blocking_send(Ok(make_text_chunk(final_output.emit))).is_err() {
return;
}
}
}
let usage = Usage { let usage = Usage {
prompt_tokens, prompt_tokens,
completion_tokens: token_count, completion_tokens: token_count,