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@codeflash-ai codeflash-ai bot commented Oct 29, 2025

📄 272% (2.72x) speedup for ChatInterface._get_last_user_entry_index in panel/chat/interface.py

⏱️ Runtime : 154 microseconds 41.3 microseconds (best of 5 runs)

📝 Explanation and details

The optimization focuses on the _get_last_user_entry_index method, which searches for the most recent user message by iterating backwards through the chat messages.

Key optimization: Replaced self.objects[::-1] with reversed(self.objects) to eliminate unnecessary memory allocation. The original code creates a complete reversed copy of the entire message list in memory, while the optimized version uses a lazy iterator that produces elements on-demand without copying.

Additional micro-optimizations:

  • Cached self.user and self.objects in local variables to avoid repeated attribute lookups during iteration
  • This reduces the overhead of accessing object attributes in the tight comparison loop

Why this leads to speedup:

  1. Memory efficiency: reversed() creates no intermediate data structures, saving both allocation time and memory
  2. Cache locality: Local variable access is faster than attribute access in Python's interpreter
  3. Reduced overhead: Eliminates the O(n) memory copy operation that happens with slice reversal

Performance characteristics based on test results:

  • Small lists: Slight overhead due to extra variable assignments (~30-42% slower for empty cases)
  • Large lists: Significant speedups (74-642% faster) where the memory allocation cost of slice reversal becomes dominant
  • Best case: Lists with sparse user messages (every 100th message) show the highest gains (361-642% faster) since the iterator can terminate early without having copied the entire list

The optimization is most beneficial for chat interfaces with longer message histories, which is the typical production use case.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 55 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests and Runtime
import pytest
from panel.chat.interface import ChatInterface


# Minimal ChatMessage class for testing
class ChatMessage:
    def __init__(self, contents, user):
        self.contents = contents
        self.user = user
from panel.chat.interface import ChatInterface

# -------------------- Unit Tests --------------------

# 1. Basic Test Cases





def test_empty_objects():
    # No messages at all; should return 0
    ci = ChatInterface(user="User")
    ci.objects = []
    codeflash_output = ci._get_last_user_entry_index() # 1.79μs -> 2.59μs (30.7% slower)












def test_large_number_of_messages_last_user():
    # 1000 messages, last is from user
    ci = ChatInterface(user="User")
    ci.objects = [ChatMessage(f"Msg{i}", "Assistant") for i in range(999)]
    ci.objects.append(ChatMessage("Final", "User"))
    codeflash_output = ci._get_last_user_entry_index() # 4.69μs -> 2.69μs (74.5% faster)




def test_large_number_of_messages_multiple_users():
    # 1000 messages, user messages at start and end
    ci = ChatInterface(user="User")
    ci.objects = [ChatMessage("Start", "User")]
    ci.objects += [ChatMessage(f"Msg{i}", "Assistant") for i in range(998)]
    ci.objects.append(ChatMessage("End", "User"))
    # Last user message is at end
    codeflash_output = ci._get_last_user_entry_index() # 4.92μs -> 2.69μs (82.7% faster)

def test_large_number_of_messages_alternating_users():
    # 1000 messages, alternating user and assistant
    ci = ChatInterface(user="User")
    ci.objects = []
    for i in range(1000):
        user = "User" if i % 2 == 0 else "Assistant"
        ci.objects.append(ChatMessage(f"Msg{i}", user))
    # Last message is Assistant, so last user message is at index 2
    codeflash_output = ci._get_last_user_entry_index() # 5.13μs -> 2.69μs (90.3% faster)

def test_large_number_of_messages_user_every_100():
    # 1000 messages, user every 100th message
    ci = ChatInterface(user="User")
    for i in range(1000):
        user = "User" if i % 100 == 0 else "Assistant"
        ci.objects.append(ChatMessage(f"Msg{i}", user))
    # Last user message is at index 901 (i=900), so from end: 1000-900=100+1=101
    # But since last user message is at i=900, which is 100th from end (i=999 is last, i=900 is 100th from end)
    # So index should be 100 (since enumerate starts at 1)
    codeflash_output = ci._get_last_user_entry_index() # 26.4μs -> 5.74μs (361% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import pytest
from panel.chat.interface import ChatInterface


# Minimal ChatMessage stub for testing
class ChatMessage:
    def __init__(self, contents, user):
        self.contents = contents
        self.user = user
from panel.chat.interface import ChatInterface

# ---------------------- Unit Tests ----------------------

# ----------- 1. Basic Test Cases -----------

def test_no_messages_returns_zero():
    # No messages at all
    ci = ChatInterface()
    codeflash_output = ci._get_last_user_entry_index() # 1.67μs -> 2.88μs (42.1% slower)










def test_empty_message_list():
    # Explicitly test empty list
    ci = ChatInterface()
    ci.objects = []
    codeflash_output = ci._get_last_user_entry_index() # 1.71μs -> 2.92μs (41.4% slower)












def test_large_scale_multiple_users():
    # 1000 messages, user every 100th message
    ci = ChatInterface()
    ci.objects = []
    for i in range(1000):
        if i % 100 == 0:
            ci.objects.append(ChatMessage(f"UserMsg{i}", "User"))
        else:
            ci.objects.append(ChatMessage(f"Msg{i}", "Assistant"))
    # Last user message at index 901, which is 100th from end
    codeflash_output = ci._get_last_user_entry_index() # 45.4μs -> 6.12μs (642% faster)

def test_large_scale_alternating_user():
    # 1000 messages, alternate user/assistant
    ci = ChatInterface()
    ci.objects = []
    for i in range(1000):
        user = "User" if i % 2 == 0 else "Assistant"
        ci.objects.append(ChatMessage(f"Msg{i}", user))
    # Last message is from "Assistant", so second last is "User"
    codeflash_output = ci._get_last_user_entry_index() # 5.96μs -> 3.29μs (81.1% faster)

def test_large_scale_user_name_custom():
    # 1000 messages, custom user name
    ci = ChatInterface(user="Alice")
    ci.objects = []
    for i in range(1000):
        user = "Alice" if i % 250 == 0 else "Bob"
        ci.objects.append(ChatMessage(f"Msg{i}", user))
    # Last "Alice" message is at index 750, which is 251st from end
    codeflash_output = ci._get_last_user_entry_index() # 55.9μs -> 9.66μs (478% faster)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-ChatInterface._get_last_user_entry_index-mhbtnjvj and push.

Codeflash

The optimization focuses on the `_get_last_user_entry_index` method, which searches for the most recent user message by iterating backwards through the chat messages.

**Key optimization:** Replaced `self.objects[::-1]` with `reversed(self.objects)` to eliminate unnecessary memory allocation. The original code creates a complete reversed copy of the entire message list in memory, while the optimized version uses a lazy iterator that produces elements on-demand without copying.

**Additional micro-optimizations:**
- Cached `self.user` and `self.objects` in local variables to avoid repeated attribute lookups during iteration
- This reduces the overhead of accessing object attributes in the tight comparison loop

**Why this leads to speedup:**
1. **Memory efficiency**: `reversed()` creates no intermediate data structures, saving both allocation time and memory
2. **Cache locality**: Local variable access is faster than attribute access in Python's interpreter
3. **Reduced overhead**: Eliminates the O(n) memory copy operation that happens with slice reversal

**Performance characteristics based on test results:**
- **Small lists**: Slight overhead due to extra variable assignments (~30-42% slower for empty cases)
- **Large lists**: Significant speedups (74-642% faster) where the memory allocation cost of slice reversal becomes dominant
- **Best case**: Lists with sparse user messages (every 100th message) show the highest gains (361-642% faster) since the iterator can terminate early without having copied the entire list

The optimization is most beneficial for chat interfaces with longer message histories, which is the typical production use case.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 29, 2025 09:57
@codeflash-ai codeflash-ai bot added ⚡️ codeflash Optimization PR opened by Codeflash AI 🎯 Quality: High Optimization Quality according to Codeflash labels Oct 29, 2025
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