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ChangeLog

All notable changes to SDialog will be documented here.

[0.4.6] 2026-03-12 🧠

Added

  • sdialog.agents:
    • New @final_response_tool decorator to return tool output directly as the final agent response (bypassing post-tool LLM synthesis for non-empty outputs).
    • Example: 
      from sdialog.agents import Agent, final_response_tool

@final_response_tool
def get_table(callsign: str) -> str:
    return "| Timestamp | Transcription |\n|---|---|\n| ... | ... |"

agent = Agent(tools=[get_table])

Changed

  • sdialog.evaluation:
    • KDEDistanceEvaluator now supports multiple values per dialog.
    • Improved placeholder handling in STAR response generation.
    • Implemented Laplace smoothing in dialog log-likelihood computation.

[0.4.5] 2026-02-18 🎙️

Added

  • sdialog.audio:
    • Voice cloning support in voice databases.
    • New TTS classes: Qwen3TTS, Qwen3TTSVoiceClone, and BaseVoiceCloneTTS.
    • Persona-based dynamic voice generation and customizable voice descriptions.
    • Improved speaker name / role mapping for voice assignment.

Changed

  • sdialog.audio:
    • Dialog.to_audio() supports output path as positional argument.
    • Audio pipeline now supports more flexible voice assignment.
    • Qwen3-TTS voice cloning set as default dynamic voice creation path.

Fixed

  • sdialog.agents:
    • Restored orchestration behavior when agent is served.
  • sdialog.audio:
    • Fixed speaker-role mapping and case-sensitivity edge cases.
    • Fixed optional audio path handling in Dialog.to_audio().
    • Fixed label assignment and default keep_duplicate handling.
  • sdialog.evaluation:
    • Fixed division-by-zero / log(0) edge cases in divergence computations.
    • Added jitter handling for KL/CS divergence when variance is zero.
    • Fixed fallback behavior for unknown edges in flow score computation.

[0.4.3] 2025-11-30 📊

Added

  • sdialog.evaluation:
    • New readability and conversational metrics.
    • New scoring classes for individual linguistic features.
    • Added Dialog.from_folder() to load dialogs from directories.
    • Added ToolSequenceValidator for validating tool usage order in dialogs.

Changed

  • sdialog.evaluation:
    • Enhanced plotting support with customizable titles and labels.
  • sdialog.interpretability:
    • Improved top-k visualization and steering defaults.

Fixed

  • sdialog.agents:
    • Improved tool invocation error handling.
  • sdialog:
    • Updated dialog prompt formatting.

[0.4.2] 2025-11-21 🛠️

Changed

  • sdialog.agents:
    • Improved progress bar behavior during dialog generation.
  • sdialog.audio:
    • Updated dependencies and dscaper integration behavior.

Documentation

  • Added clearer Kokoro TTS installation instructions.

[0.4.1] 2025-11-20 🔧

Fixed

  • sdialog.audio:
    • Fixed dscaper timeline generation bug and test updates around deleted directories.

Documentation

  • Updated audio tutorials and README installation instructions (including sox/ffmpeg and setup guidance).

[0.4.0] 2025-10-30 🔊

Added

  • sdialog.audio: New audio generation module to transform text dialogs into audio conversations
    • Dialog.to_audio(): Convert any text dialog to audio with a single method call
    • Text-to-Speech (TTS): Support for multiple TTS engines including Kokoro and Hugging Face models
    • Voice databases: Automatic or manual voice assignment from Hugging Face, local storage, or on-the-fly generation based on persona attributes (age, gender, language)
    • Acoustic simulation: Realistic room acoustics simulation with ray tracing technology for spatial audio
    • Microphone simulation: Professional microphone impulse responses from brands like Shure, Sennheiser, and Sony
    • Room generation: Define and generate diverse room types with customizable properties (dimensions, wall materials, furniture placement)
    • Multiple formats: Export to WAV, MP3, or FLAC with custom sampling rates
    • Background/foreground effects: Add environmental sounds and acoustic variations
    • 7 comprehensive tutorials covering audio generation, acoustic simulation, rooms, voice databases, and impulse responses
  • sdialog.interpretability:
    • Support for inspecting layer and component inputs with Inspector(target="model.layers.15", inspect_input=True)
    • Support for inspecting and steering input tokens (tokens given as input, not only generated ones), e.g., inspector.input[i][j].act where i is turn index and j is input token index
  • sdialog.config:
    • Support for Anthropic backend (#100)
    • Support for Azure OpenAI backend (#100)

Fixed

  • sdialog.agents: Agent memory reset when no prompt system and no persona is given

[0.3.3] 2025-10-30 🚀

Added

  • sdialog.server:
    • New module to serve agents via an Ollama/OpenAI-compatible REST API (works with UIs like Open WebUI) (#92)
  • sdialog:
    • Dialog.from_huggingface() to load/download dialogues directly from Hugging Face datasets (#59)

Changed

  • sdialog.evaluation:
    • LLM judge methods now accept additional user-defined template arguments (e.g., like document in this example) (#86)
  • sdialog.agents:
    • Improved Agent initialization so agents can act as a proxy for external conversational systems (#90, fa1d8f3)

Fixed

  • sdialog.evaluation:
    • Corrected Flesch Reading Ease and Gunning Fog score calculations (d1d4260)

[0.3.0] 2025-10-03 ✨

Added

  • sdialog:
    • Context: new class class to explicitly model the common/shared context of conversations (#73)
    • Dialog: merge functionality - Added option to merge consecutive turns of the same speaker when loading a dialog (#77)
    • Dialog: built-in string support - Added support to built-in str functions for Dialog class (#83)
  • sdialog.agents: Added new sdialog.agents module and moved Agent class inside (#81)
    • Agent: thinking capabilities - Agents can now handle internal thinking processes (#95)
    • Agent: tools support - Added tools capabilities to Agents (e.g. RAG or any other function) (#84)
      • New tutorial for agents with tools and thoughts.
  • sdialog.generators:
    • ContextGenerator: new class added to explicitly model the common/shared context of conversations (#73)
    • Paraphraser: new class class to paraphrase dialogues (#76)
  • sdialog.evaluation:
    • LinguisticFeatureScore: new class added to compute Flesch reading ease, Gunning fog, Hesitation rate, and/or Mean turn length (#63)
  • sdialog.personas:
    • Customer and SupportAgent: new personas added for customer service dialogues (#85)
    • Persona: Added static method to get the list of all attributes in Persona class (#79)

Changed

  • sdialog: Improved metadata handling (#66)
  • sdialog.interpretability: Improved and simplified the way inspection targets are defined in interpretability submodule (#78)
  • sdialog.evaluation.base:
    • LLMJudgeYesNoOutput: Renamed attribute yes to positive (#86)
    • LLMJudgeScoreOutput: Renamed attribute feedback to reason (#86)

Fixed

  • sdialog.generators: Fixed potential bug in PersonaDialogGenerator class (#67)

Enhanced

  • sdialog.agents: Added base_model attribute to Agent to direclty access the LLM's underlying model for mechanistic interpretability (#74)
  • sdialog.config: Added clear_cache() method to config (#75)

Documentation

  • API Documentation: Refactored/cleaned all components and added docstrings with examples (#82, #88)
  • Updated all tutorials to work with new code and added "Open in Colab" badges
  • Completed API documentation for initial official release (#87)
  • Automatic generation of llm.txt from API documentation (24f6ee6)

[0.1.0] 2025-08-05 🌱

Added

  • Multi-backend support (Hugging Face, Ollama, OpenAI, AWS)
  • Enhanced persona generation (beyond initial PersonaDialogGenerator)
  • Interpretability module (sdialog.interpretability): inspectors, steerers, hooks, intruders
  • Evaluation module (sdialog.evaluation): metrics, LLM-as-a-judge scoring, evaluators, dataset comparators

Changed

  • Standardized / improved dialog format

Notes

  • 500 commits since 0.0.2 (post-JSALT 2025 consolidation)

Pending

  • Audio module (sdialog.audio) integration
  • Documentation updates

[0.0.2] 2025-06-03 🔧

Added

  • language attribute to Persona class
  • PersonaDialogGenerator to generators module to support persona-based dialogue generatin with single LLM: 
    from sdialog.generators import PersonaDialogGenerator

dialog_generator = PersonaDialogGenerator(
    model=MODEL_NAME,
    persona_a=bob_persona,
    persona_b=alice_persona,
)

dialog_generator.generate().print()

Fixed

  • Python 2 and 3 compatibility problem with scikit-learn (using version 0.20.1 from now on)
  • PyPi: setup.py: long_description_content_type set to 'text/markdown'

[0.0.1] 2025-05-22 🎉

(initial release)