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fix: in rust ast, allow ModelBlock model to be an expr #911

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Merged
starpit merged 1 commit into from
Apr 13, 2025
Merged

fix: in rust ast, allow ModelBlock model to be an expr #911

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19 changes: 18 additions & 1 deletion pdl-live-react/src-tauri/src/pdl/ast.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -274,7 +274,7 @@ pub struct PdlUsage {
#[serde(tag = "kind", rename = "model")]
#[builder(setter(into, strip_option), default)]
pub struct ModelBlock {
pub model: String,
pub model: EvalsTo<String, String>,
#[serde(skip_serializing_if = "Option::is_none")]
pub parameters: Option<HashMap<String, Value>>,
#[serde(skip_serializing_if = "Option::is_none")]
Expand Down Expand Up @@ -468,6 +468,23 @@ pub enum EvalsTo<S, T> {
Expr(Expr<S, T>),
}

impl Default for EvalsTo<String, String> {
fn default() -> Self {
EvalsTo::Const("".to_string())
}
}

impl From<&str> for EvalsTo<String, String> {
fn from(s: &str) -> Self {
EvalsTo::Const(s.to_string())
}
}
impl From<String> for EvalsTo<String, String> {
fn from(s: String) -> Self {
EvalsTo::Const(s)
}
}

/// Conditional control structure.
///
/// Example:
Expand Down
29 changes: 27 additions & 2 deletions pdl-live-react/src-tauri/src/pdl/extract.rs
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Original file line number Diff line number Diff line change
@@ -1,4 +1,6 @@
use crate::pdl::ast::{Block, Body::*, Metadata, PdlBlock, PdlBlock::Advanced};
use crate::pdl::ast::{
Block, Body::*, EvalsTo, Expr, Metadata, ModelBlock, PdlBlock, PdlBlock::Advanced,
};

/// Extract models referenced by the programs
pub fn extract_models(program: &PdlBlock) -> Vec<String> {
Expand Down Expand Up @@ -28,7 +30,30 @@ fn extract_values_iter(program: &PdlBlock, field: &str, values: &mut Vec<String>
PdlBlock::Function(b) => {
extract_values_iter(&b.return_, field, values);
}
Advanced(Block { body: Model(b), .. }) => values.push(b.model.clone()),
Advanced(Block {
body:
Model(ModelBlock {
model: EvalsTo::<String, String>::Const(m),
..
}),
..
}) => values.push(m.clone()),
Advanced(Block {
body:
Model(ModelBlock {
model: EvalsTo::<String, String>::Jinja(m),
..
}),
..
}) => values.push(m.clone()),
Advanced(Block {
body:
Model(ModelBlock {
model: EvalsTo::<String, String>::Expr(Expr { pdl_expr: m, .. }),
..
}),
..
}) => values.push(m.clone()),
Advanced(Block {
body: Repeat(b), ..
}) => {
Expand Down
263 changes: 142 additions & 121 deletions pdl-live-react/src-tauri/src/pdl/interpreter.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -261,6 +261,18 @@ impl<'a> Interpreter<'a> {
}
}

// TODO how can we better cope with the expected String return?
fn eval_string_to_string(
&self,
expr: &EvalsTo<String, String>,
state: &State,
) -> Result<PdlResult, PdlError> {
match expr {
EvalsTo::Const(s) | EvalsTo::Jinja(s) => self.eval(s, state),
EvalsTo::Expr(e) => self.eval(&e.pdl_expr, state),
}
}

/// Evaluate an Expr to a bool
fn eval_to_bool(
&self,
Expand Down Expand Up @@ -722,140 +734,149 @@ impl<'a> Interpreter<'a> {
})
}

/// Run a PdlBlock::Model
async fn run_model(
async fn run_ollama_model(
&mut self,
pdl_model: String,
block: &ModelBlock,
metadata: &Metadata,
state: &mut State,
) -> BodyInterpretation {
match &block.model {
pdl_model
if pdl_model.starts_with("ollama/") || pdl_model.starts_with("ollama_chat/") =>
{
let mut ollama = Ollama::default();
let model = if pdl_model.starts_with("ollama/") {
&pdl_model[7..]
} else {
&pdl_model[12..]
};
let mut ollama = Ollama::default();
let model = if pdl_model.starts_with("ollama/") {
&pdl_model[7..]
} else {
&pdl_model[12..]
};

let (options, tools) = self.to_ollama_model_options(&block.parameters);
if self.options.debug {
eprintln!("Model options {:?} {:?}", metadata.description, options);
eprintln!("Model tools {:?} {:?}", metadata.description, tools);
}
let (options, tools) = self.to_ollama_model_options(&block.parameters);
if self.options.debug {
eprintln!("Model options {:?} {:?}", metadata.description, options);
eprintln!("Model tools {:?} {:?}", metadata.description, tools);
}

// The input messages to the model is either:
// a) block.input, if given
// b) the current state's accumulated messages
let input_messages = match &block.input {
Some(input) => {
// TODO ignoring result, trace
let (_result, messages, _trace) = self.run_quiet(&*input, state).await?;
messages
}
None => state.messages.clone(),
};
let (prompt, history_slice): (&ChatMessage, &[ChatMessage]) =
match input_messages.split_last() {
Some(x) => x,
None => (&ChatMessage::user("".into()), &[]),
};
let mut history = Vec::from(history_slice);
if self.options.debug {
eprintln!(
"Ollama {:?} model={:?} prompt={:?} history={:?}",
metadata.description, block.model, prompt, history
);
}
// The input messages to the model is either:
// a) block.input, if given
// b) the current state's accumulated messages
let input_messages = match &block.input {
Some(input) => {
// TODO ignoring result, trace
let (_result, messages, _trace) = self.run_quiet(&*input, state).await?;
messages
}
None => state.messages.clone(),
};
let (prompt, history_slice): (&ChatMessage, &[ChatMessage]) =
match input_messages.split_last() {
Some(x) => x,
None => (&ChatMessage::user("".into()), &[]),
};
let mut history = Vec::from(history_slice);
if self.options.debug {
eprintln!(
"Ollama {:?} model={:?} prompt={:?} history={:?}",
metadata.description, block.model, prompt, history
);
}

//if state.emit {
//println!("{}", pretty_print(&input_messages));
//}

let req = ChatMessageRequest::new(model.into(), vec![prompt.clone()])
.options(options)
.tools(tools);

let (last_res, response_string) = if !self.options.stream {
let res = ollama
.send_chat_messages_with_history(&mut history, req)
.await?;
let response_string = res.message.content.clone();
print!("{}", response_string);
(Some(res), response_string)
} else {
let mut stream = ollama
.send_chat_messages_with_history_stream(
::std::sync::Arc::new(::std::sync::Mutex::new(history)),
req,
//ollama.generate(GenerationRequest::new(model.into(), prompt),
)
.await?;
// dbg!("Model result {:?}", &res);

let emit = if let Some(_) = &block.model_response {
false
} else {
true
};

let mut last_res: Option<ChatMessageResponse> = None;
let mut response_string = String::new();
let mut stdout = stdout();
if emit {
stdout.write_all(b"\x1b[1mAssistant: \x1b[0m").await?;
}
while let Some(Ok(res)) = stream.next().await {
if emit {
stdout.write_all(b"\x1b[32m").await?; // green
stdout.write_all(res.message.content.as_bytes()).await?;
stdout.flush().await?;
stdout.write_all(b"\x1b[0m").await?; // reset color
}
response_string += res.message.content.as_str();
last_res = Some(res);
}
if emit {
stdout.write_all(b"\n").await?;
}
//if state.emit {
//println!("{}", pretty_print(&input_messages));
//}

let req = ChatMessageRequest::new(model.into(), vec![prompt.clone()])
.options(options)
.tools(tools);

let (last_res, response_string) = if !self.options.stream {
let res = ollama
.send_chat_messages_with_history(&mut history, req)
.await?;
let response_string = res.message.content.clone();
print!("{}", response_string);
(Some(res), response_string)
} else {
let mut stream = ollama
.send_chat_messages_with_history_stream(
::std::sync::Arc::new(::std::sync::Mutex::new(history)),
req,
//ollama.generate(GenerationRequest::new(model.into(), prompt),
)
.await?;
// dbg!("Model result {:?}", &res);

(last_res, response_string)
};

if let Some(_) = &block.model_response {
if let Some(ref res) = last_res {
self.def(
&block.model_response,
&resultify_as_litellm(&from_str(&to_string(&res)?)?),
&None,
state,
true,
)?;
}
}
let emit = if let Some(_) = &block.model_response {
false
} else {
true
};

let mut trace = block.clone();
if let Some(res) = last_res {
if let Some(usage) = res.final_data {
trace.pdl_usage = Some(PdlUsage {
prompt_tokens: usage.prompt_eval_count,
prompt_nanos: Some(usage.prompt_eval_duration),
completion_tokens: usage.eval_count,
completion_nanos: Some(usage.eval_duration),
});
}
let output_messages = vec![ChatMessage::assistant(response_string)];
Ok((res.message.content.into(), output_messages, Model(trace)))
} else {
// nothing came out of the model
Ok(("".into(), vec![], Model(trace)))
let mut last_res: Option<ChatMessageResponse> = None;
let mut response_string = String::new();
let mut stdout = stdout();
if emit {
stdout.write_all(b"\x1b[1mAssistant: \x1b[0m").await?;
}
while let Some(Ok(res)) = stream.next().await {
if emit {
stdout.write_all(b"\x1b[32m").await?; // green
stdout.write_all(res.message.content.as_bytes()).await?;
stdout.flush().await?;
stdout.write_all(b"\x1b[0m").await?; // reset color
}
// dbg!(history);
response_string += res.message.content.as_str();
last_res = Some(res);
}
if emit {
stdout.write_all(b"\n").await?;
}

(last_res, response_string)
};

if let Some(_) = &block.model_response {
if let Some(ref res) = last_res {
self.def(
&block.model_response,
&resultify_as_litellm(&from_str(&to_string(&res)?)?),
&None,
state,
true,
)?;
}
_ => Err(Box::from(format!("Unsupported model {}", block.model))),
}

let mut trace = block.clone();
if let Some(res) = last_res {
if let Some(usage) = res.final_data {
trace.pdl_usage = Some(PdlUsage {
prompt_tokens: usage.prompt_eval_count,
prompt_nanos: Some(usage.prompt_eval_duration),
completion_tokens: usage.eval_count,
completion_nanos: Some(usage.eval_duration),
});
}
let output_messages = vec![ChatMessage::assistant(response_string)];
Ok((res.message.content.into(), output_messages, Model(trace)))
} else {
// nothing came out of the model
Ok(("".into(), vec![], Model(trace)))
}
// dbg!(history);
}

/// Run a PdlBlock::Model
async fn run_model(
&mut self,
block: &ModelBlock,
metadata: &Metadata,
state: &mut State,
) -> BodyInterpretation {
if let PdlResult::String(s) = self.eval_string_to_string(&block.model, state)? {
if s.starts_with("ollama/") || s.starts_with("ollama_chat/") {
return self.run_ollama_model(s, block, metadata, state).await;
}
}

Err(Box::from(format!("Unsupported model {:?}", block.model)))
}

/// Run a PdlBlock::Data
Expand Down
20 changes: 20 additions & 0 deletions pdl-live-react/src-tauri/src/pdl/interpreter_tests.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -79,6 +79,26 @@ mod tests {
Ok(())
}

#[test]
fn single_model_via_text_chain_expr() -> Result<(), Box<dyn Error>> {
let (_, messages, _) = run_json(
json!({
"text": [
"hello",
{"model": { "pdl__expr": DEFAULT_MODEL }}
]
}),
streaming(),
initial_scope(),
)?;
assert_eq!(messages.len(), 2);
assert_eq!(messages[0].role, MessageRole::User);
assert_eq!(messages[0].content, "hello");
assert_eq!(messages[1].role, MessageRole::Assistant);
assert!(messages[1].content.contains("Hello!"));
Ok(())
}

#[test]
fn single_model_via_text_chain() -> Result<(), Box<dyn Error>> {
let (_, messages, _) = run_json(
Expand Down