Benign python Download

openinference-instrumentation-pipecat 2.0.2

“OpenInference Pipecat Instrumentation”

Accesses Python class base or MROTar extraction guards member paths

SHA-256a1c36d7be057e20ef88f4a610ba71579bd59f161dfa01bb7bdadfb431ecf69b6

URLhttps://files.pythonhosted.org/packages/93/bf/c0e46303eefa7e414adb7f7fe5cca8352882c44d02116f0cc41101cbe72c/openinference_instrumentation_pipecat-2.0.2-py3-none-any.whl

MaleculeH₂(Db₂F)

Evidence

Python module-level function call syntax lines 1–48

1"""OpenInference observer for Pipecat pipelines."""
2
3import logging
4import time
5from contextvars import Token
6from datetime import datetime
7from typing import Any, Dict, List, Optional, Set, TextIO
8
9from opentelemetry import trace as trace_api
10from opentelemetry.context import Context
11from opentelemetry.trace import Span
12
13from openinference.instrumentation import OITracer, TraceConfig
14from openinference.instrumentation.helpers import safe_json_dumps
15from openinference.semconv.trace import (
16    OpenInferenceSpanKindValues,
17    SpanAttributes,
18)
19from pipecat.frames.frames import (
20    Frame,
21    FunctionCallResultFrame,
22    LLMContextFrame,
23    LLMFullResponseEndFrame,
24    LLMFullResponseStartFrame,
25    LLMTextFrame,
26    MetricsFrame,
27    StartFrame,
28    STTMuteFrame,
29    TranscriptionFrame,
30    TTSStartedFrame,
31    TTSTextFrame,
32    VADUserStartedSpeakingFrame,
33    VADUserStoppedSpeakingFrame,
34)
35from pipecat.observers.base_observer import FramePushed
36from pipecat.observers.turn_tracking_observer import TurnTrackingObserver
37from pipecat.observers.user_bot_latency_observer import UserBotLatencyObserver
38from pipecat.processors.frame_processor import FrameProcessor
39from pipecat.services.ai_service import AIService
40from pipecat.services.llm_service import LLMService
41from pipecat.services.stt_service import STTService
42from pipecat.services.tts_service import TTSService
43from pipecat.transports.base_output import BaseOutputTransport
44
45from ._attributes import (  # noqa: F401
46    detect_service_type,
47    detect_service_type_from_class_string,
48    extract_attributes_from_frame,

Python file opened for write or append lines 118–127

14… bug_log_filename:
          # Write log to current working directory (where the script is running)
          try:
              self._debug_log_file = open(debug_log_filename, "w")
              self._log_debug(f"=== Observer initialized for conversation {conversation_id} ===")
              self._log_debug(f"=== Log file: {debug_log_filename} ===")
          except Exception as e:
              logger.error(f"Could not open debug log file: {e}")
126
      self._active_spans: Dict[int | str, Dict[str, Any] …

Explicit LLM or language-model reference lines 282–287

40… }, service_type: {service_type}")
283
      if service_type in ("llm", "stt", "tts"):
          # only these frame types will start a span:
          ## LLMContextFrame (LLM)
          ## ST …

Text refers to LLM/model calls lines 403–406

36… ted_output:
                      # No text output means this LLM call likely triggered tool calls
                      # Store a reference to this span so tool calls can be parented under it
  …

LLM response or output reference lines 406–409

10…                self._log_debug(
                          f"  LLM response ended with no text output - "
                          f"storing span {service_id} as potential tool call parent"
         …

No evidence locations were recorded for this file. Raw result