Conversational graph package

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  • Requires: Python >=3.9
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Project description

Conversational Graph

Build deterministic, multi-turn voice and chat AI agents as directed graphs : where you control the flow and the LLM handles natural conversation.

Installation

pip install videosdk-conversational-graph

Features

Capability How It Works
Predictable flows Conversations follow the exact path you define. No hallucinated detours.
Structured data collection Extract and validate user data with Pydantic models : types, constraints, custom validators.
Conditional branching Route to different paths based on collected data (e.g., credit score -> approve/reject/review).
Human-in-the-loop Pause the conversation, wait for external input (payment callback, human review), then resume.
Checkpointing Save conversation state after every step. Resume interrupted calls. Time-travel to any past point.
Parallel tool execution Run multiple nodes or tool calls concurrently with fan-out/fan-in transitions.
Provider agnostic Works with any STT, LLM, TTS via the VideoSDK pipeline.

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  • Requires: Python >=3.9

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1.0.1

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1.0.0

0.0.6

0.0.5

0.0.4

0.0.3

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0.0.1

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videosdk_conversational_graph-1.0.0-cp313-cp313-win_amd64.whl (776.0 kB view details)

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videosdk_conversational_graph-1.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (6.1 MB view details)

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videosdk_conversational_graph-1.0.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl (6.0 MB view details)

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videosdk_conversational_graph-1.0.0-cp312-cp312-macosx_11_0_arm64.whl (897.4 kB view details)

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