mirror of
https://github.com/agentscope-ai/ReMe.git
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c1a25e9ff4
* feat(agent): add Codex wrapper integration * feat(agent): enhance agent wrapper functionality and add comprehensive testing - Implement structured output schema normalization across all wrappers - Add Claude Code system prompt mode support with append/replace options - Introduce Codex agent wrapper with streaming, tool context isolation, and skill management - Enhance skill linking with validation and conflict resolution - Add approval event streaming support for Codex wrapper - Implement output schema validation and normalize function - Create dedicated test suites for Claude Code and Codex integration - Update README documentation for Codex wrapper capabilities - Refactor kwargs merging with proper schema handling - Add tool context validation when resuming sessions - Implement proper cleanup and session management for Codex wrapper * test(cc-agent): add test coverage for structured output scenarios - Add docstring for empty schema validation in build_options - Document falsy structured output preservation behavior - Add docstring for streaming wrapper schema rejection - Include lambda function reference for wrapper factory consistency - Add test documentation for live Codex wrapper contract exercise * docs: revert README changes * fix(agent): interrupt abandoned Codex turns
48 lines
2.5 KiB
Python
48 lines
2.5 KiB
Python
"""Stream chunk schema for incremental responses (e.g. LLM streaming)."""
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from typing import Any
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from pydantic import BaseModel, Field
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from ..enumeration import ChunkEnum
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class StreamChunk(BaseModel):
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"""A single chunk in a unified streaming response sequence.
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Carries full information from AgentScope, Claude Code SDK, and Codex
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backends. Optional fields are ``None`` by default so that simple
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text-only streams (e.g. plain CONTENT deltas) stay lightweight.
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Fields:
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chunk_type: Category of this chunk (see ChunkEnum).
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chunk: Payload, typically a text delta, but can be
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dict/list for structured data (tool-call JSON,
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usage stats, etc.).
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done: Terminal marker. True only for the final DONE chunk.
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session_id: Backend session identifier (Codex uses its thread id).
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block_id: Content-block identifier for matching start/delta/end
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sequences (both backends assign block IDs).
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tool_call_id: Tool-call identifier for correlating call deltas
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with their start event and result.
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tool_call_name: Name of the tool being invoked.
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media_type: MIME type for DATA blocks (e.g. ``"image/png"``).
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input_tokens: Prompt tokens consumed (populated on USAGE chunks).
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output_tokens: Completion tokens generated (populated on USAGE chunks).
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metadata: Backend-specific extras that don't warrant a dedicated
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field.
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"""
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chunk_type: ChunkEnum = Field(default=ChunkEnum.CONTENT, description="Type of chunk content")
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chunk: str | dict | list = Field(default="", description="Chunk payload")
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done: bool = Field(default=False, description="Whether this is the final chunk")
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session_id: str | None = Field(default=None, description="Session identifier")
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block_id: str | None = Field(default=None, description="Content block identifier")
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tool_call_id: str | None = Field(default=None, description="Tool call identifier")
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tool_call_name: str | None = Field(default=None, description="Tool call name")
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media_type: str | None = Field(default=None, description="MIME type for data blocks")
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input_tokens: int | None = Field(default=None, description="Prompt tokens consumed")
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output_tokens: int | None = Field(default=None, description="Completion tokens generated")
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metadata: dict[str, Any] = Field(default_factory=dict, description="Chunk metadata")
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