Sweep: Add chat_logger logs to context_pruning.py similarly to how assistant_wrapper.py handles it

[wwzeng1]

we want to update the chat_logger logs after the entire run is complete

Checklist

• Modify sweepai/core/context_pruning.py ✓ d3a5011 Edit
• Running GitHub Actions for sweepai/core/context_pruning.py ✓ Edit

[sweep-nightly]

Here's the PR! #2724. See Sweep's process at dashboard.

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Sandbox logs for 338fc3c

Checking sweepai/core/context_pruning.py for syntax errors... ✅ sweepai/core/context_pruning.py has no syntax errors! 1/1 ✓

Checking sweepai/core/context_pruning.py for syntax errors...
✅ sweepai/core/context_pruning.py has no syntax errors!

Sandbox passed on the latest main, so sandbox checks will be enabled for this issue.

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Step 1: 🔎 Searching

I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.

Some code snippets I think are relevant in decreasing order of relevance (click to expand). If some file is missing from here, you can mention the path in the ticket description.

sweep/sweepai/agents/assistant_wrapper.py

Lines 193 to 217 in 338fc3c

	]
	if message_strings != current_message_strings and current_message_strings:
	logger.info(run.status)
	logger.info(current_message_strings[0])
	message_strings = current_message_strings
	json_messages = get_json_messages(
	thread_id=thread_id,
	run_id=run_id,
	assistant_id=assistant_id,
	)
	if chat_logger is not None:
	chat_logger.add_chat(
	{
	"model": model,
	"messages": json_messages,
	"output": message_strings[0],
	"thread_id": thread_id,
	"run_id": run_id,
	"max_tokens": 1000,
	"temperature": 0,
	}
	)
	else:
	if i % 5 == 0:
	logger.info(run.status)

sweep/sweepai/agents/assistant_wrapper.py

Lines 143 to 156 in 338fc3c

	)
	return messages_json
	def run_until_complete(
	thread_id: str,
	run_id: str,
	assistant_id: str,
	model: str = "gpt-4-1106-preview",
	chat_logger: ChatLogger | None = None,
	sleep_time: int = 3,
	max_iterations: int = 200,
	save_ticket_progress: save_ticket_progress_type | None = None,
	):

sweep/sweepai/agents/assistant_wrapper.py

Lines 287 to 302 in 338fc3c

	)
	run_until_complete(
	thread_id=thread.id,
	run_id=run.id,
	model=model,
	chat_logger=chat_logger,
	assistant_id=assistant.id,
	sleep_time=sleep_time,
	save_ticket_progress=save_ticket_progress,
	)
	for file_id in file_ids:
	client.files.delete(file_id=file_id)
	return (
	assistant.id,
	run.id,
	thread.id,

sweep/sweepai/core/context_pruning.py

Lines 1 to 20 in 338fc3c

	import json
	import re
	import time
	from copy import deepcopy
	from attr import dataclass
	from loguru import logger
	from openai.types.beta.thread import Thread
	from openai.types.beta.threads.run import Run
	from sweepai.agents.assistant_wrapper import client, openai_retry_with_timeout
	from sweepai.core.entities import Snippet
	from sweepai.logn.cache import file_cache
	from sweepai.utils.chat_logger import ChatLogger
	from sweepai.utils.github_utils import ClonedRepo
	from sweepai.utils.progress import AssistantConversation, TicketProgress
	from sweepai.utils.tree_utils import DirectoryTree
	ASSISTANT_MAX_CHARS = 4096 * 4 * 0.95 # ~95% of 4k tokens

sweep/sweepai/core/context_pruning.py

Lines 200 to 210 in 338fc3c

	if can_add_snippet(snippet, self.current_top_snippets):
	self.current_top_snippets.append(snippet)
	@file_cache(ignore_params=["repo_context_manager", "ticket_progress", "chat_logger"])
	def get_relevant_context(
	query: str,
	repo_context_manager: RepoContextManager,
	ticket_progress: TicketProgress | None = None,
	chat_logger: ChatLogger = None,
	):

sweep/sweepai/core/context_pruning.py

Lines 403 to 469 in 338fc3c

	tool_outputs=tool_outputs,
	)
	else:
	logger.warning(
	f"Context pruning iteration taking too long. Status: {run.status}"
	)
	assistant_conversation = AssistantConversation.from_ids(
	assistant_id=run.assistant_id,
	run_id=run.id,
	thread_id=thread.id,
	)
	if ticket_progress:
	if assistant_conversation:
	ticket_progress.search_progress.pruning_conversation = (
	assistant_conversation
	)
	ticket_progress.save()
	logger.info(
	f"Context Management End:\npaths_to_keep: {paths_to_keep}\npaths_to_add: {paths_to_add}\ndirectories_to_expand: {directories_to_expand}"
	)
	if paths_to_keep or paths_to_add:
	repo_context_manager.remove_all_non_kept_paths(paths_to_keep + paths_to_add)
	if directories_to_expand:
	repo_context_manager.expand_all_directories(directories_to_expand)
	logger.info(
	f"Context Management End:\ncurrent snippet paths: {repo_context_manager.top_snippet_paths}"
	)
	paths_changed = set(initial_file_paths) != set(
	repo_context_manager.top_snippet_paths
	)
	# if the paths have not changed or all tools were empty, we are done
	return not (
	paths_changed and (paths_to_keep or directories_to_expand or paths_to_add)
	)
	if __name__ == "__main__":
	import os
	from sweepai.utils.ticket_utils import prep_snippets
	installation_id = os.environ["INSTALLATION_ID"]
	cloned_repo = ClonedRepo("sweepai/sweep", installation_id, "main")
	query = "create a new search query filtering agent that will be used in ticket_utils.py. The agent should filter unnecessary terms out of the search query to be sent into lexical search. Use a prompt to do this, using name_agent.py as a reference."
	ticket_progress = TicketProgress(
	tracking_id="test",
	)
	import linecache
	import sys
	def trace_lines(frame, event, arg):
	if event == "line":
	filename = frame.f_code.co_filename
	if "context_pruning" in filename:
	lineno = frame.f_lineno
	line = linecache.getline(filename, lineno)
	print(f"Executing {filename}:line {lineno}:{line.rstrip()}")
	return trace_lines
	sys.settrace(trace_lines)
	repo_context_manager = prep_snippets(cloned_repo, query, ticket_progress)
	rcm = get_relevant_context(
	query,
	repo_context_manager,
	ticket_progress,
	chat_logger=ChatLogger({"username": "wwzeng1"}),
	)

sweep/sweepai/core/context_pruning.py

Lines 210 to 216 in 338fc3c

	):
	modify_iterations: int = 2
	model = (
	"gpt-3.5-turbo-1106"
	if (chat_logger and chat_logger.use_faster_model())
	else "gpt-4-1106-preview"
	)

sweep/sweepai/utils/chat_logger.py

Lines 67 to 111 in 338fc3c

	def add_chat(self, additional_data):
	if self.chat_collection is None:
	logger.error("Chat collection is not initialized")
	return
	document = {
	**self.data,
	**additional_data,
	"expiration": self.expiration,
	"index": self.index,
	}
	self.index += 1
	self.chat_collection.insert_one(document)
	def add_successful_ticket(self, gpt3=False):
	if self.ticket_collection is None:
	logger.error("Ticket Collection Does Not Exist")
	return
	username = self.data.get("assignee", self.data["username"])
	update_fields = {self.current_month: 1, self.current_date: 1}
	if gpt3:
	key = f"{self.current_month}_gpt3"
	update_fields = {key: 1}
	self.ticket_collection.update_one(
	{"username": username}, {"$inc": update_fields}, upsert=True
	)
	ticket_count = self.get_ticket_count()
	should_decrement = (self.is_paying_user() and ticket_count >= 500) or (
	self.is_consumer_tier() and ticket_count >= 20
	)
	if should_decrement:
	self.ticket_collection.update_one(
	{"username": username}, {"$inc": {"purchased_tickets": -1}}, upsert=True
	)
	logger.info(f"Added Successful Ticket for {username}")
	def _cache_key(self, username, field, metadata=""):
	return f"{username}_{field}_{metadata}"

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Step 2: ⌨️ Coding

• Modify sweepai/core/context_pruning.py ✓ d3a5011 Edit

Modify sweepai/core/context_pruning.py with contents:
• At the end of the get_relevant_context function, after the context pruning process is complete, add a call to the add_chat method of the chat_logger object.
• The add_chat method should be called with a dictionary that contains the relevant data. This data might include the query, the repo_context_manager object, the ticket_progress object, and any other data that is relevant to the context pruning process.
• For example, the code might look like this: ```python chat_logger.add_chat( { "query": query, "repo_context_manager": repo_context_manager, "ticket_progress": ticket_progress, # add any other relevant data here } ) ```
• Make sure to handle the case where the chat_logger object is None. In this case, the add_chat method should not be called. You can do this by adding a condition before the call to the add_chat method, like this: ```python if chat_logger is not None: chat_logger.add_chat( { "query": query, "repo_context_manager": repo_context_manager, "ticket_progress": ticket_progress, # add any other relevant data here } ) ```

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+++
@@ -1,3 +1,4 @@
+from sweepai.api import chat_logger
import json
import re
import time
@@ -431,9 +432,18 @@
repo_context_manager.top_snippet_paths
)
# if the paths have not changed or all tools were empty, we are done

• return not (

•    paths_changed and (paths_to_keep or directories_to_expand or paths_to_add)
  

• )

• finished = not (paths_changed and (paths_to_keep or directories_to_expand or paths_to_add))
• if chat_logger is not None:

•    chat_logger.add_chat(
  

•        {
  

•            "query": query,
  

•            "repo_context_manager": repo_context_manager,
  

•            "ticket_progress": ticket_progress,
  

•            # add any other relevant data here
  

•        }
  

•    )
  

• return finished

if name == "main":

• Running GitHub Actions for sweepai/core/context_pruning.py ✓ Edit

Check sweepai/core/context_pruning.py with contents:

Ran GitHub Actions for d3a50112db4d73a8c62906d62f51f86dad9afba3:
• black: ✓
• Vercel Preview Comments: ✓

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Step 3: 🔁 Code Review

I have finished reviewing the code for completeness. I did not find errors for sweep/add-chat-logger-to-context-pruning.

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