1use anyhow::{anyhow, Result};
2use assistant_slash_command::{
3 ArgumentCompletion, SlashCommand, SlashCommandOutput, SlashCommandOutputSection,
4 SlashCommandResult,
5};
6use feature_flags::FeatureFlag;
7use futures::StreamExt;
8use gpui::{AppContext, AsyncAppContext, Task, WeakView};
9use language::{CodeLabel, LspAdapterDelegate};
10use language_model::{
11 LanguageModelCompletionEvent, LanguageModelRegistry, LanguageModelRequest,
12 LanguageModelRequestMessage, Role,
13};
14use semantic_index::{FileSummary, SemanticDb};
15use smol::channel;
16use std::sync::{atomic::AtomicBool, Arc};
17use ui::{BorrowAppContext, WindowContext};
18use util::ResultExt;
19use workspace::Workspace;
20
21use crate::slash_command::create_label_for_command;
22
23pub struct AutoSlashCommandFeatureFlag;
24
25impl FeatureFlag for AutoSlashCommandFeatureFlag {
26 const NAME: &'static str = "auto-slash-command";
27}
28
29pub(crate) struct AutoCommand;
30
31impl SlashCommand for AutoCommand {
32 fn name(&self) -> String {
33 "auto".into()
34 }
35
36 fn description(&self) -> String {
37 "Automatically infer what context to add".into()
38 }
39
40 fn menu_text(&self) -> String {
41 self.description()
42 }
43
44 fn label(&self, cx: &AppContext) -> CodeLabel {
45 create_label_for_command("auto", &["--prompt"], cx)
46 }
47
48 fn complete_argument(
49 self: Arc<Self>,
50 _arguments: &[String],
51 _cancel: Arc<AtomicBool>,
52 workspace: Option<WeakView<Workspace>>,
53 cx: &mut WindowContext,
54 ) -> Task<Result<Vec<ArgumentCompletion>>> {
55 // There's no autocomplete for a prompt, since it's arbitrary text.
56 // However, we can use this opportunity to kick off a drain of the backlog.
57 // That way, it can hopefully be done resummarizing by the time we've actually
58 // typed out our prompt. This re-runs on every keystroke during autocomplete,
59 // but in the future, we could instead do it only once, when /auto is first entered.
60 let Some(workspace) = workspace.and_then(|ws| ws.upgrade()) else {
61 log::warn!("workspace was dropped or unavailable during /auto autocomplete");
62
63 return Task::ready(Ok(Vec::new()));
64 };
65
66 let project = workspace.read(cx).project().clone();
67 let Some(project_index) =
68 cx.update_global(|index: &mut SemanticDb, cx| index.project_index(project, cx))
69 else {
70 return Task::ready(Err(anyhow!("No project indexer, cannot use /auto")));
71 };
72
73 let cx: &mut AppContext = cx;
74
75 cx.spawn(|cx: gpui::AsyncAppContext| async move {
76 let task = project_index.read_with(&cx, |project_index, cx| {
77 project_index.flush_summary_backlogs(cx)
78 })?;
79
80 cx.background_executor().spawn(task).await;
81
82 anyhow::Ok(Vec::new())
83 })
84 }
85
86 fn requires_argument(&self) -> bool {
87 true
88 }
89
90 fn run(
91 self: Arc<Self>,
92 arguments: &[String],
93 _context_slash_command_output_sections: &[SlashCommandOutputSection<language::Anchor>],
94 _context_buffer: language::BufferSnapshot,
95 workspace: WeakView<Workspace>,
96 _delegate: Option<Arc<dyn LspAdapterDelegate>>,
97 cx: &mut WindowContext,
98 ) -> Task<SlashCommandResult> {
99 let Some(workspace) = workspace.upgrade() else {
100 return Task::ready(Err(anyhow::anyhow!("workspace was dropped")));
101 };
102 if arguments.is_empty() {
103 return Task::ready(Err(anyhow!("missing prompt")));
104 };
105 let argument = arguments.join(" ");
106 let original_prompt = argument.to_string();
107 let project = workspace.read(cx).project().clone();
108 let Some(project_index) =
109 cx.update_global(|index: &mut SemanticDb, cx| index.project_index(project, cx))
110 else {
111 return Task::ready(Err(anyhow!("no project indexer")));
112 };
113
114 let task = cx.spawn(|cx: gpui::AsyncWindowContext| async move {
115 let summaries = project_index
116 .read_with(&cx, |project_index, cx| project_index.all_summaries(cx))?
117 .await?;
118
119 commands_for_summaries(&summaries, &original_prompt, &cx).await
120 });
121
122 // As a convenience, append /auto's argument to the end of the prompt
123 // so you don't have to write it again.
124 let original_prompt = argument.to_string();
125
126 cx.background_executor().spawn(async move {
127 let commands = task.await?;
128 let mut prompt = String::new();
129
130 log::info!(
131 "Translating this response into slash-commands: {:?}",
132 commands
133 );
134
135 for command in commands {
136 prompt.push('/');
137 prompt.push_str(&command.name);
138 prompt.push(' ');
139 prompt.push_str(&command.arg);
140 prompt.push('\n');
141 }
142
143 prompt.push('\n');
144 prompt.push_str(&original_prompt);
145
146 Ok(SlashCommandOutput {
147 text: prompt,
148 sections: Vec::new(),
149 run_commands_in_text: true,
150 })
151 })
152 }
153}
154
155const PROMPT_INSTRUCTIONS_BEFORE_SUMMARY: &str = include_str!("prompt_before_summary.txt");
156const PROMPT_INSTRUCTIONS_AFTER_SUMMARY: &str = include_str!("prompt_after_summary.txt");
157
158fn summaries_prompt(summaries: &[FileSummary], original_prompt: &str) -> String {
159 let json_summaries = serde_json::to_string(summaries).unwrap();
160
161 format!("{PROMPT_INSTRUCTIONS_BEFORE_SUMMARY}\n{json_summaries}\n{PROMPT_INSTRUCTIONS_AFTER_SUMMARY}\n{original_prompt}")
162}
163
164/// The slash commands that the model is told about, and which we look for in the inference response.
165const SUPPORTED_SLASH_COMMANDS: &[&str] = &["search", "file"];
166
167#[derive(Debug, Clone)]
168struct CommandToRun {
169 name: String,
170 arg: String,
171}
172
173/// Given the pre-indexed file summaries for this project, as well as the original prompt
174/// string passed to `/auto`, get a list of slash commands to run, along with their arguments.
175///
176/// The prompt's output does not include the slashes (to reduce the chance that it makes a mistake),
177/// so taking one of these returned Strings and turning it into a real slash-command-with-argument
178/// involves prepending a slash to it.
179///
180/// This function will validate that each of the returned lines begins with one of SUPPORTED_SLASH_COMMANDS.
181/// Any other lines it encounters will be discarded, with a warning logged.
182async fn commands_for_summaries(
183 summaries: &[FileSummary],
184 original_prompt: &str,
185 cx: &AsyncAppContext,
186) -> Result<Vec<CommandToRun>> {
187 if summaries.is_empty() {
188 log::warn!("Inferring no context because there were no summaries available.");
189 return Ok(Vec::new());
190 }
191
192 // Use the globally configured model to translate the summaries into slash-commands,
193 // because Qwen2-7B-Instruct has not done a good job at that task.
194 let Some(model) = cx.update(|cx| LanguageModelRegistry::read_global(cx).active_model())? else {
195 log::warn!("Can't infer context because there's no active model.");
196 return Ok(Vec::new());
197 };
198 // Only go up to 90% of the actual max token count, to reduce chances of
199 // exceeding the token count due to inaccuracies in the token counting heuristic.
200 let max_token_count = (model.max_token_count() * 9) / 10;
201
202 // Rather than recursing (which would require this async function use a pinned box),
203 // we use an explicit stack of arguments and answers for when we need to "recurse."
204 let mut stack = vec![summaries];
205 let mut final_response = Vec::new();
206 let mut prompts = Vec::new();
207
208 // TODO We only need to create multiple Requests because we currently
209 // don't have the ability to tell if a CompletionProvider::complete response
210 // was a "too many tokens in this request" error. If we had that, then
211 // we could try the request once, instead of having to make separate requests
212 // to check the token count and then afterwards to run the actual prompt.
213 let make_request = |prompt: String| LanguageModelRequest {
214 messages: vec![LanguageModelRequestMessage {
215 role: Role::User,
216 content: vec![prompt.into()],
217 // Nothing in here will benefit from caching
218 cache: false,
219 }],
220 tools: Vec::new(),
221 stop: Vec::new(),
222 temperature: None,
223 };
224
225 while let Some(current_summaries) = stack.pop() {
226 // The split can result in one slice being empty and the other having one element.
227 // Whenever that happens, skip the empty one.
228 if current_summaries.is_empty() {
229 continue;
230 }
231
232 log::info!(
233 "Inferring prompt context using {} file summaries",
234 current_summaries.len()
235 );
236
237 let prompt = summaries_prompt(¤t_summaries, original_prompt);
238 let start = std::time::Instant::now();
239 // Per OpenAI, 1 token ~= 4 chars in English (we go with 4.5 to overestimate a bit, because failed API requests cost a lot of perf)
240 // Verifying this against an actual model.count_tokens() confirms that it's usually within ~5% of the correct answer, whereas
241 // getting the correct answer from tiktoken takes hundreds of milliseconds (compared to this arithmetic being ~free).
242 // source: https://help.openai.com/en/articles/4936856-what-are-tokens-and-how-to-count-them
243 let token_estimate = prompt.len() * 2 / 9;
244 let duration = start.elapsed();
245 log::info!(
246 "Time taken to count tokens for prompt of length {:?}B: {:?}",
247 prompt.len(),
248 duration
249 );
250
251 if token_estimate < max_token_count {
252 prompts.push(prompt);
253 } else if current_summaries.len() == 1 {
254 log::warn!("Inferring context for a single file's summary failed because the prompt's token length exceeded the model's token limit.");
255 } else {
256 log::info!(
257 "Context inference using file summaries resulted in a prompt containing {token_estimate} tokens, which exceeded the model's max of {max_token_count}. Retrying as two separate prompts, each including half the number of summaries.",
258 );
259 let (left, right) = current_summaries.split_at(current_summaries.len() / 2);
260 stack.push(right);
261 stack.push(left);
262 }
263 }
264
265 let all_start = std::time::Instant::now();
266
267 let (tx, rx) = channel::bounded(1024);
268
269 let completion_streams = prompts
270 .into_iter()
271 .map(|prompt| {
272 let request = make_request(prompt.clone());
273 let model = model.clone();
274 let tx = tx.clone();
275 let stream = model.stream_completion(request, &cx);
276
277 (stream, tx)
278 })
279 .collect::<Vec<_>>();
280
281 cx.background_executor()
282 .spawn(async move {
283 let futures = completion_streams
284 .into_iter()
285 .enumerate()
286 .map(|(ix, (stream, tx))| async move {
287 let start = std::time::Instant::now();
288 let events = stream.await?;
289 log::info!("Time taken for awaiting /await chunk stream #{ix}: {:?}", start.elapsed());
290
291 let completion: String = events
292 .filter_map(|event| async {
293 if let Ok(LanguageModelCompletionEvent::Text(text)) = event {
294 Some(text)
295 } else {
296 None
297 }
298 })
299 .collect()
300 .await;
301
302 log::info!("Time taken for all /auto chunks to come back for #{ix}: {:?}", start.elapsed());
303
304 for line in completion.split('\n') {
305 if let Some(first_space) = line.find(' ') {
306 let command = &line[..first_space].trim();
307 let arg = &line[first_space..].trim();
308
309 tx.send(CommandToRun {
310 name: command.to_string(),
311 arg: arg.to_string(),
312 })
313 .await?;
314 } else if !line.trim().is_empty() {
315 // All slash-commands currently supported in context inference need a space for the argument.
316 log::warn!(
317 "Context inference returned a non-blank line that contained no spaces (meaning no argument for the slash command): {:?}",
318 line
319 );
320 }
321 }
322
323 anyhow::Ok(())
324 })
325 .collect::<Vec<_>>();
326
327 let _ = futures::future::try_join_all(futures).await.log_err();
328
329 let duration = all_start.elapsed();
330 eprintln!("All futures completed in {:?}", duration);
331 })
332 .await;
333
334 drop(tx); // Close the channel so that rx.collect() won't hang. This is safe because all futures have completed.
335 let results = rx.collect::<Vec<_>>().await;
336 eprintln!(
337 "Finished collecting from the channel with {} results",
338 results.len()
339 );
340 for command in results {
341 // Don't return empty or duplicate commands
342 if !command.name.is_empty()
343 && !final_response
344 .iter()
345 .any(|cmd: &CommandToRun| cmd.name == command.name && cmd.arg == command.arg)
346 {
347 if SUPPORTED_SLASH_COMMANDS
348 .iter()
349 .any(|supported| &command.name == supported)
350 {
351 final_response.push(command);
352 } else {
353 log::warn!(
354 "Context inference returned an unrecognized slash command: {:?}",
355 command
356 );
357 }
358 }
359 }
360
361 // Sort the commands by name (reversed just so that /search appears before /file)
362 final_response.sort_by(|cmd1, cmd2| cmd1.name.cmp(&cmd2.name).reverse());
363
364 Ok(final_response)
365}