Conversational graph package
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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