auto_command.rs

  1use super::create_label_for_command;
  2use super::{SlashCommand, SlashCommandOutput};
  3use anyhow::{anyhow, Result};
  4use assistant_slash_command::ArgumentCompletion;
  5use feature_flags::FeatureFlag;
  6use futures::StreamExt;
  7use gpui::{AppContext, AsyncAppContext, Task, WeakView};
  8use language::{CodeLabel, LspAdapterDelegate};
  9use language_model::{
 10    LanguageModelCompletionEvent, LanguageModelRegistry, LanguageModelRequest,
 11    LanguageModelRequestMessage, Role,
 12};
 13use semantic_index::{FileSummary, SemanticDb};
 14use smol::channel;
 15use std::sync::{atomic::AtomicBool, Arc};
 16use ui::{BorrowAppContext, WindowContext};
 17use util::ResultExt;
 18use workspace::Workspace;
 19
 20pub struct AutoSlashCommandFeatureFlag;
 21
 22impl FeatureFlag for AutoSlashCommandFeatureFlag {
 23    const NAME: &'static str = "auto-slash-command";
 24}
 25
 26pub(crate) struct AutoCommand;
 27
 28impl SlashCommand for AutoCommand {
 29    fn name(&self) -> String {
 30        "auto".into()
 31    }
 32
 33    fn description(&self) -> String {
 34        "Automatically infer what context to add, based on your prompt".into()
 35    }
 36
 37    fn menu_text(&self) -> String {
 38        "Automatically Infer Context".into()
 39    }
 40
 41    fn label(&self, cx: &AppContext) -> CodeLabel {
 42        create_label_for_command("auto", &["--prompt"], cx)
 43    }
 44
 45    fn complete_argument(
 46        self: Arc<Self>,
 47        _arguments: &[String],
 48        _cancel: Arc<AtomicBool>,
 49        workspace: Option<WeakView<Workspace>>,
 50        cx: &mut WindowContext,
 51    ) -> Task<Result<Vec<ArgumentCompletion>>> {
 52        // There's no autocomplete for a prompt, since it's arbitrary text.
 53        // However, we can use this opportunity to kick off a drain of the backlog.
 54        // That way, it can hopefully be done resummarizing by the time we've actually
 55        // typed out our prompt. This re-runs on every keystroke during autocomplete,
 56        // but in the future, we could instead do it only once, when /auto is first entered.
 57        let Some(workspace) = workspace.and_then(|ws| ws.upgrade()) else {
 58            log::warn!("workspace was dropped or unavailable during /auto autocomplete");
 59
 60            return Task::ready(Ok(Vec::new()));
 61        };
 62
 63        let project = workspace.read(cx).project().clone();
 64        let Some(project_index) =
 65            cx.update_global(|index: &mut SemanticDb, cx| index.project_index(project, cx))
 66        else {
 67            return Task::ready(Err(anyhow!("No project indexer, cannot use /auto")));
 68        };
 69
 70        let cx: &mut AppContext = cx;
 71
 72        cx.spawn(|cx: gpui::AsyncAppContext| async move {
 73            let task = project_index.read_with(&cx, |project_index, cx| {
 74                project_index.flush_summary_backlogs(cx)
 75            })?;
 76
 77            cx.background_executor().spawn(task).await;
 78
 79            anyhow::Ok(Vec::new())
 80        })
 81    }
 82
 83    fn requires_argument(&self) -> bool {
 84        true
 85    }
 86
 87    fn run(
 88        self: Arc<Self>,
 89        arguments: &[String],
 90        workspace: WeakView<Workspace>,
 91        _delegate: Option<Arc<dyn LspAdapterDelegate>>,
 92        cx: &mut WindowContext,
 93    ) -> Task<Result<SlashCommandOutput>> {
 94        let Some(workspace) = workspace.upgrade() else {
 95            return Task::ready(Err(anyhow::anyhow!("workspace was dropped")));
 96        };
 97        if arguments.is_empty() {
 98            return Task::ready(Err(anyhow!("missing prompt")));
 99        };
100        let argument = arguments.join(" ");
101        let original_prompt = argument.to_string();
102        let project = workspace.read(cx).project().clone();
103        let Some(project_index) =
104            cx.update_global(|index: &mut SemanticDb, cx| index.project_index(project, cx))
105        else {
106            return Task::ready(Err(anyhow!("no project indexer")));
107        };
108
109        let task = cx.spawn(|cx: gpui::AsyncWindowContext| async move {
110            let summaries = project_index
111                .read_with(&cx, |project_index, cx| project_index.all_summaries(cx))?
112                .await?;
113
114            commands_for_summaries(&summaries, &original_prompt, &cx).await
115        });
116
117        // As a convenience, append /auto's argument to the end of the prompt
118        // so you don't have to write it again.
119        let original_prompt = argument.to_string();
120
121        cx.background_executor().spawn(async move {
122            let commands = task.await?;
123            let mut prompt = String::new();
124
125            log::info!(
126                "Translating this response into slash-commands: {:?}",
127                commands
128            );
129
130            for command in commands {
131                prompt.push('/');
132                prompt.push_str(&command.name);
133                prompt.push(' ');
134                prompt.push_str(&command.arg);
135                prompt.push('\n');
136            }
137
138            prompt.push('\n');
139            prompt.push_str(&original_prompt);
140
141            Ok(SlashCommandOutput {
142                text: prompt,
143                sections: Vec::new(),
144                run_commands_in_text: true,
145            })
146        })
147    }
148}
149
150const PROMPT_INSTRUCTIONS_BEFORE_SUMMARY: &str = include_str!("prompt_before_summary.txt");
151const PROMPT_INSTRUCTIONS_AFTER_SUMMARY: &str = include_str!("prompt_after_summary.txt");
152
153fn summaries_prompt(summaries: &[FileSummary], original_prompt: &str) -> String {
154    let json_summaries = serde_json::to_string(summaries).unwrap();
155
156    format!("{PROMPT_INSTRUCTIONS_BEFORE_SUMMARY}\n{json_summaries}\n{PROMPT_INSTRUCTIONS_AFTER_SUMMARY}\n{original_prompt}")
157}
158
159/// The slash commands that the model is told about, and which we look for in the inference response.
160const SUPPORTED_SLASH_COMMANDS: &[&str] = &["search", "file"];
161
162#[derive(Debug, Clone)]
163struct CommandToRun {
164    name: String,
165    arg: String,
166}
167
168/// Given the pre-indexed file summaries for this project, as well as the original prompt
169/// string passed to `/auto`, get a list of slash commands to run, along with their arguments.
170///
171/// The prompt's output does not include the slashes (to reduce the chance that it makes a mistake),
172/// so taking one of these returned Strings and turning it into a real slash-command-with-argument
173/// involves prepending a slash to it.
174///
175/// This function will validate that each of the returned lines begins with one of SUPPORTED_SLASH_COMMANDS.
176/// Any other lines it encounters will be discarded, with a warning logged.
177async fn commands_for_summaries(
178    summaries: &[FileSummary],
179    original_prompt: &str,
180    cx: &AsyncAppContext,
181) -> Result<Vec<CommandToRun>> {
182    if summaries.is_empty() {
183        log::warn!("Inferring no context because there were no summaries available.");
184        return Ok(Vec::new());
185    }
186
187    // Use the globally configured model to translate the summaries into slash-commands,
188    // because Qwen2-7B-Instruct has not done a good job at that task.
189    let Some(model) = cx.update(|cx| LanguageModelRegistry::read_global(cx).active_model())? else {
190        log::warn!("Can't infer context because there's no active model.");
191        return Ok(Vec::new());
192    };
193    // Only go up to 90% of the actual max token count, to reduce chances of
194    // exceeding the token count due to inaccuracies in the token counting heuristic.
195    let max_token_count = (model.max_token_count() * 9) / 10;
196
197    // Rather than recursing (which would require this async function use a pinned box),
198    // we use an explicit stack of arguments and answers for when we need to "recurse."
199    let mut stack = vec![summaries];
200    let mut final_response = Vec::new();
201    let mut prompts = Vec::new();
202
203    // TODO We only need to create multiple Requests because we currently
204    // don't have the ability to tell if a CompletionProvider::complete response
205    // was a "too many tokens in this request" error. If we had that, then
206    // we could try the request once, instead of having to make separate requests
207    // to check the token count and then afterwards to run the actual prompt.
208    let make_request = |prompt: String| LanguageModelRequest {
209        messages: vec![LanguageModelRequestMessage {
210            role: Role::User,
211            content: vec![prompt.into()],
212            // Nothing in here will benefit from caching
213            cache: false,
214        }],
215        tools: Vec::new(),
216        stop: Vec::new(),
217        temperature: 1.0,
218    };
219
220    while let Some(current_summaries) = stack.pop() {
221        // The split can result in one slice being empty and the other having one element.
222        // Whenever that happens, skip the empty one.
223        if current_summaries.is_empty() {
224            continue;
225        }
226
227        log::info!(
228            "Inferring prompt context using {} file summaries",
229            current_summaries.len()
230        );
231
232        let prompt = summaries_prompt(&current_summaries, original_prompt);
233        let start = std::time::Instant::now();
234        // 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)
235        // Verifying this against an actual model.count_tokens() confirms that it's usually within ~5% of the correct answer, whereas
236        // getting the correct answer from tiktoken takes hundreds of milliseconds (compared to this arithmetic being ~free).
237        // source: https://help.openai.com/en/articles/4936856-what-are-tokens-and-how-to-count-them
238        let token_estimate = prompt.len() * 2 / 9;
239        let duration = start.elapsed();
240        log::info!(
241            "Time taken to count tokens for prompt of length {:?}B: {:?}",
242            prompt.len(),
243            duration
244        );
245
246        if token_estimate < max_token_count {
247            prompts.push(prompt);
248        } else if current_summaries.len() == 1 {
249            log::warn!("Inferring context for a single file's summary failed because the prompt's token length exceeded the model's token limit.");
250        } else {
251            log::info!(
252                "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.",
253            );
254            let (left, right) = current_summaries.split_at(current_summaries.len() / 2);
255            stack.push(right);
256            stack.push(left);
257        }
258    }
259
260    let all_start = std::time::Instant::now();
261
262    let (tx, rx) = channel::bounded(1024);
263
264    let completion_streams = prompts
265        .into_iter()
266        .map(|prompt| {
267            let request = make_request(prompt.clone());
268            let model = model.clone();
269            let tx = tx.clone();
270            let stream = model.stream_completion(request, &cx);
271
272            (stream, tx)
273        })
274        .collect::<Vec<_>>();
275
276    cx.background_executor()
277        .spawn(async move {
278            let futures = completion_streams
279                .into_iter()
280                .enumerate()
281                .map(|(ix, (stream, tx))| async move {
282                    let start = std::time::Instant::now();
283                    let events = stream.await?;
284                    log::info!("Time taken for awaiting /await chunk stream #{ix}: {:?}", start.elapsed());
285
286                    let completion: String = events
287                        .filter_map(|event| async {
288                            if let Ok(LanguageModelCompletionEvent::Text(text)) = event {
289                                Some(text)
290                            } else {
291                                None
292                            }
293                        })
294                        .collect()
295                        .await;
296
297                    log::info!("Time taken for all /auto chunks to come back for #{ix}: {:?}", start.elapsed());
298
299                    for line in completion.split('\n') {
300                        if let Some(first_space) = line.find(' ') {
301                            let command = &line[..first_space].trim();
302                            let arg = &line[first_space..].trim();
303
304                            tx.send(CommandToRun {
305                                name: command.to_string(),
306                                arg: arg.to_string(),
307                            })
308                            .await?;
309                        } else if !line.trim().is_empty() {
310                            // All slash-commands currently supported in context inference need a space for the argument.
311                            log::warn!(
312                                "Context inference returned a non-blank line that contained no spaces (meaning no argument for the slash command): {:?}",
313                                line
314                            );
315                        }
316                    }
317
318                    anyhow::Ok(())
319                })
320                .collect::<Vec<_>>();
321
322            let _ = futures::future::try_join_all(futures).await.log_err();
323
324            let duration = all_start.elapsed();
325            eprintln!("All futures completed in {:?}", duration);
326        })
327        .await;
328
329    drop(tx); // Close the channel so that rx.collect() won't hang. This is safe because all futures have completed.
330    let results = rx.collect::<Vec<_>>().await;
331    eprintln!(
332        "Finished collecting from the channel with {} results",
333        results.len()
334    );
335    for command in results {
336        // Don't return empty or duplicate commands
337        if !command.name.is_empty()
338            && !final_response
339                .iter()
340                .any(|cmd: &CommandToRun| cmd.name == command.name && cmd.arg == command.arg)
341        {
342            if SUPPORTED_SLASH_COMMANDS
343                .iter()
344                .any(|supported| &command.name == supported)
345            {
346                final_response.push(command);
347            } else {
348                log::warn!(
349                    "Context inference returned an unrecognized slash command: {:?}",
350                    command
351                );
352            }
353        }
354    }
355
356    // Sort the commands by name (reversed just so that /search appears before /file)
357    final_response.sort_by(|cmd1, cmd2| cmd1.name.cmp(&cmd2.name).reverse());
358
359    Ok(final_response)
360}