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64bit64bit
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refactors (64bit#91)
* cargo fmt * remove colon * add function call stream in makefile
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Diff for: ‎async-openai/README.md

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Original file line numberDiff line numberDiff line change
@@ -105,7 +105,7 @@ Thank you for your time to contribute and improve the project, I'd be happy to h
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A good starting point would be existing [open issues](https://github.com/64bit/async-openai/issues).
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## Complimentary Crates:
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## Complimentary Crates
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- [openai-func-enums](https://github.com/frankfralick/openai-func-enums) provides procedural macros that make it easier to use this library with OpenAI API's function calling feature. It also provides derive macros you can add to existing [clap](https://github.com/clap-rs/clap) application subcommands for natural language use of command line tools.
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## License

Diff for: ‎examples/Makefile.toml

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Original file line numberDiff line numberDiff line change
@@ -15,6 +15,7 @@ cd create-image-edit && cargo run && cd -
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cd create-image-variation && cargo run && cd -
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cd embeddings && cargo run && cd -
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cd function-call && cargo run && cd -
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cd function-call-stream && cargo run && cd -
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cd models && cargo run && cd -
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cd moderations && cargo run && cd -
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#cd rate-limit-completions && cargo run && cd -

Diff for: ‎examples/function-call-stream/src/main.rs

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Original file line numberDiff line numberDiff line change
@@ -1,6 +1,6 @@
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use std::io::{stdout, Write};
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use std::collections::HashMap;
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use std::error::Error;
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use std::io::{stdout, Write};
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use async_openai::{
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types::{
@@ -13,7 +13,6 @@ use async_openai::{
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use futures::StreamExt;
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use serde_json::json;
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#[tokio::main]
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async fn main() -> Result<(), Box<dyn Error>> {
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let client = Client::new();
@@ -44,80 +43,80 @@ async fn main() -> Result<(), Box<dyn Error>> {
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.build()?;
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// the first response from GPT is just the json response containing the function that was called
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// and the model-generated arguments for that function (don't stream this)
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// and the model-generated arguments for that function (don't stream this)
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let response = client
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.chat()
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.create(request)
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.await?
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.choices
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.get(0)
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.unwrap()
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.message
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.clone();
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if let Some(function_call) = response.function_call {
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let mut available_functions: HashMap<&str, fn(&str, &str) -> serde_json::Value> =
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HashMap::new();
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available_functions.insert("get_current_weather", get_current_weather);
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let function_name = function_call.name;
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let function_args: serde_json::Value = function_call.arguments.parse().unwrap();
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.chat()
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.create(request)
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.await?
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.choices
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.get(0)
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.unwrap()
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.message
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.clone();
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let location = function_args["location"].as_str().unwrap();
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let unit = "fahrenheit"; // why doesn't the model return a unit argument?
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let function = available_functions.get(function_name.as_str()).unwrap();
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if let Some(function_call) = response.function_call {
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let mut available_functions: HashMap<&str, fn(&str, &str) -> serde_json::Value> =
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HashMap::new();
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available_functions.insert("get_current_weather", get_current_weather);
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let function_name = function_call.name;
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let function_args: serde_json::Value = function_call.arguments.parse().unwrap();
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let location = function_args["location"].as_str().unwrap();
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let unit = "fahrenheit"; // why doesn't the model return a unit argument?
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let function = available_functions.get(function_name.as_str()).unwrap();
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let function_response = function(location, unit); // call the function
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let message = vec![
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ChatCompletionRequestMessageArgs::default()
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.role(Role::User)
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.content("What's the weather like in Boston?")
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.build()?,
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ChatCompletionRequestMessageArgs::default()
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.role(Role::Function)
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.content(function_response.to_string())
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.name(function_name)
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.build()?
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];
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let message = vec![
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ChatCompletionRequestMessageArgs::default()
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.role(Role::User)
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.content("What's the weather like in Boston?")
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.build()?,
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ChatCompletionRequestMessageArgs::default()
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.role(Role::Function)
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.content(function_response.to_string())
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.name(function_name)
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.build()?,
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];
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let request = CreateChatCompletionRequestArgs::default()
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.max_tokens(512u16)
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.model("gpt-3.5-turbo-0613")
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.messages(message)
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.build()?;
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let request = CreateChatCompletionRequestArgs::default()
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.max_tokens(512u16)
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.model("gpt-3.5-turbo-0613")
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.messages(message)
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.build()?;
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// Now stream received response from model, which essentially formats the function response
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let mut stream = client.chat().create_stream(request).await?;
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// Now stream received response from model, which essentially formats the function response
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let mut stream = client.chat().create_stream(request).await?;
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let mut lock = stdout().lock();
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while let Some(result) = stream.next().await {
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match result {
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Ok(response) => {
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response.choices.iter().for_each(|chat_choice| {
97-
if let Some(ref content) = chat_choice.delta.content {
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write!(lock, "{}", content).unwrap();
99-
}
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});
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}
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Err(err) => {
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writeln!(lock, "error: {err}").unwrap();
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}
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}
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stdout().flush()?;
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}
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println!("{}", "\n");
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}
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let mut lock = stdout().lock();
92+
while let Some(result) = stream.next().await {
93+
match result {
94+
Ok(response) => {
95+
response.choices.iter().for_each(|chat_choice| {
96+
if let Some(ref content) = chat_choice.delta.content {
97+
write!(lock, "{}", content).unwrap();
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}
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});
100+
}
101+
Err(err) => {
102+
writeln!(lock, "error: {err}").unwrap();
103+
}
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}
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stdout().flush()?;
106+
}
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println!("{}", "\n");
108+
}
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Ok(())
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}
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fn get_current_weather(location: &str, unit: &str) -> serde_json::Value {
115-
let weather_info = json!({
116-
"location": location,
117-
"temperature": "72",
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"unit": unit,
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"forecast": ["sunny", "windy"]
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});
114+
let weather_info = json!({
115+
"location": location,
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"temperature": "72",
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"unit": unit,
118+
"forecast": ["sunny", "windy"]
119+
});
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122-
weather_info
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weather_info
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}

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