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This commit is contained in:
João Moura
2025-05-27 00:33:26 -07:00
parent 42dacb2862
commit 4e0ce9adfe
2 changed files with 63 additions and 22 deletions

View File

@@ -67,33 +67,72 @@ class FilteredStream(io.TextIOBase):
self._lock = threading.Lock()
with self._lock:
# Filter out extraneous messages from LiteLLM
lower_s = s.lower()
# Skip common noisy LiteLLM banners and any other lines that contain "litellm"
if (
"Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new"
in s
or "LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()`"
in s
"give feedback / get help" in lower_s
or "litellm.info:" in lower_s
or "litellm" in lower_s
or "Consider using a smaller input or implementing a text splitting strategy" in lower_s
):
return 0
return self._original_stream.write(s)
def flush(self):
with self._lock:
return self._original_stream.flush()
def __getattr__(self, name):
"""Delegate attribute access to the wrapped original stream.
This ensures compatibility with libraries (e.g., Rich) that rely on
attributes such as `encoding`, `isatty`, `buffer`, etc., which may not
be explicitly defined on this proxy class.
"""
return getattr(self._original_stream, name)
# Delegate common properties/methods explicitly so they aren't shadowed by
# the TextIOBase defaults (e.g., .encoding returns None by default, which
# confuses Rich). These explicit pass-throughs ensure the wrapped Console
# still sees a fully-featured stream.
@property
def encoding(self):
return getattr(self._original_stream, "encoding", "utf-8")
def isatty(self):
return self._original_stream.isatty()
def fileno(self):
return self._original_stream.fileno()
def writable(self):
return True
# Apply the filtered stream globally so that any subsequent writes containing the filtered
# keywords (e.g., "litellm") are hidden from terminal output. We guard against double
# wrapping to ensure idempotency in environments where this module might be reloaded.
if not isinstance(sys.stdout, FilteredStream):
sys.stdout = FilteredStream(sys.stdout)
if not isinstance(sys.stderr, FilteredStream):
sys.stderr = FilteredStream(sys.stderr)
LLM_CONTEXT_WINDOW_SIZES = {
# openai
"gpt-4": 8192,
"gpt-4o": 128000,
"gpt-4o-mini": 128000,
"gpt-4o-mini": 200000,
"gpt-4-turbo": 128000,
"gpt-4.1": 1047576, # Based on official docs
"gpt-4.1-mini-2025-04-14": 1047576,
"gpt-4.1-nano-2025-04-14": 1047576,
"o1-preview": 128000,
"o1-mini": 128000,
"o3-mini": 200000, # Based on official o3-mini specifications
"o3-mini": 200000,
"o4-mini": 200000,
# gemini
"gemini-2.0-flash": 1048576,
"gemini-2.0-flash-thinking-exp-01-21": 32768,
@@ -208,7 +247,7 @@ LLM_CONTEXT_WINDOW_SIZES = {
}
DEFAULT_CONTEXT_WINDOW_SIZE = 8192
CONTEXT_WINDOW_USAGE_RATIO = 0.75
CONTEXT_WINDOW_USAGE_RATIO = 0.85
@contextmanager
@@ -219,12 +258,7 @@ def suppress_warnings():
"ignore", message="open_text is deprecated*", category=DeprecationWarning
)
# Redirect stdout and stderr
with (
redirect_stdout(FilteredStream(sys.stdout)),
redirect_stderr(FilteredStream(sys.stderr)),
):
yield
yield
class Delta(TypedDict):

View File

@@ -44,7 +44,7 @@ def render_text_description_and_args(
tools: Sequence[Union[CrewStructuredTool, BaseTool]],
) -> str:
"""Render the tool name, description, and args in plain text.
search: This tool is used for search, args: {"query": {"type": "string"}}
calculator: This tool is used for math, \
args: {"expression": {"type": "string"}}
@@ -309,7 +309,7 @@ def handle_context_length(
"""
if respect_context_window:
printer.print(
content="Context length exceeded. Summarizing content to fit the model context window.",
content="Context length exceeded. Summarizing content to fit the model context window. Might take a while...",
color="yellow",
)
summarize_messages(messages, llm, callbacks, i18n)
@@ -337,15 +337,22 @@ def summarize_messages(
callbacks: List of callbacks for LLM
i18n: I18N instance for messages
"""
messages_string = " ".join([message["content"] for message in messages])
messages_groups = []
for message in messages:
content = message["content"]
cut_size = llm.get_context_window_size()
for i in range(0, len(content), cut_size):
messages_groups.append({"content": content[i : i + cut_size]})
cut_size = llm.get_context_window_size()
for i in range(0, len(messages_string), cut_size):
messages_groups.append({"content": messages_string[i : i + cut_size]})
summarized_contents = []
for group in messages_groups:
total_groups = len(messages_groups)
for idx, group in enumerate(messages_groups, 1):
Printer().print(
content=f"Summarizing {idx}/{total_groups}...",
color="yellow",
)
summary = llm.call(
[
format_message_for_llm(