Implement Interview feature for agent interactions in simulations
- Added a new Interview module to facilitate interactions with agents post-simulation, allowing for single and batch interviews. - Introduced IPC communication mechanism for command and response handling between the Flask backend and simulation scripts. - Updated README.md to include detailed instructions on the new Interview functionality, including API endpoints and usage examples. - Enhanced simulation scripts to support waiting for commands after completion, improving user control over the simulation environment. - Implemented error handling and logging for interview processes, ensuring robust operation and traceability.
This commit is contained in:
666ghj
@@ -73,6 +73,11 @@
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启动模拟 → 运行OASIS脚本 → 实时监控 → 记录动作 → (可选)更新Zep图谱记忆 → 状态查询
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```
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4. **Interview采访流程**:
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```
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模拟完成 → 环境进入等待模式 → 发送Interview命令 → Agent回答 → 获取结果 → (可选)关闭环境
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```
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---
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## 技术栈
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@@ -152,6 +157,7 @@ backend/
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│ ├── simulation_config_generator.py # 配置生成
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│ ├── simulation_manager.py # 模拟管理
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│ ├── simulation_runner.py # 模拟运行
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│ ├── simulation_ipc.py # 模拟IPC通信（Interview功能）
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│ └── zep_graph_memory_updater.py # 图谱记忆动态更新
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└── utils/ # 工具类
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├── __init__.py
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@@ -211,12 +217,43 @@ backend/
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4. 解析动作日志(actions.jsonl)
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5. (可选)将Agent活动实时更新到Zep图谱
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6. 实时更新运行状态
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7. 支持停止/暂停/恢复
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7. 模拟完成后进入等待命令模式
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8. 支持停止/暂停/恢复
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**核心服务**:
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- `SimulationRunner`: 模拟运行器
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- `ZepGraphMemoryUpdater`: 图谱记忆动态更新器
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### 4. Agent采访(Interview)模块
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**功能**: 在模拟完成后对Agent进行采访
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**特点**:
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- **模拟状态持久化**: 模拟完成后环境不立即关闭，进入等待命令模式
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- **IPC通信机制**: 通过文件系统在Flask后端和模拟脚本之间通信
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- **单个采访**: 对指定Agent提问并获取回答
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- **批量采访**: 同时对多个Agent提不同问题
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- **全局采访**: 使用相同问题采访所有Agent
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- **采访历史**: 从数据库读取所有Interview记录
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**核心服务**:
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- `SimulationIPCClient`: IPC客户端（Flask端使用）
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- `SimulationIPCServer`: IPC服务器（模拟脚本端使用）
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**工作原理**:
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```
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Flask后端 模拟脚本
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│ │
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│ 写入命令文件 │
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│ ─────────────────────────→│
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│ │ 轮询命令目录
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│ │ 执行Interview
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│ │ 写入响应文件
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│←───────────────────────── │
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│ 读取响应文件 │
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│ │
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```
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---
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## API接口文档
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@@ -630,6 +667,290 @@ backend/
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---
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### Interview 采访接口
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> **注意**: 所有Interview接口的参数都通过请求体(JSON)传递，包括simulation_id。
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>
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> **双平台模式说明**: 当不指定`platform`参数时，双平台模拟会同时采访两个平台并返回整合结果。
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#### 1. 采访单个Agent
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**接口**: `POST /api/simulation/interview`
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**请求参数**:
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```json
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{
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"simulation_id": "sim_xxxx",
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"agent_id": 0,
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"prompt": "你对这件事有什么看法？",
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"platform": "reddit",
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"timeout": 60
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}
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```
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| 参数 | 类型 | 必填 | 默认值 | 说明 |
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|------|------|------|--------|------|
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| simulation_id | String | 是 | - | 模拟ID |
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| agent_id | Integer | 是 | - | Agent ID |
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| prompt | String | 是 | - | 采访问题 |
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| platform | String | 否 | null | 指定平台(twitter/reddit)，不指定则双平台同时采访 |
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| timeout | Integer | 否 | 60 | 超时时间（秒） |
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**返回示例（指定单平台）**:
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```json
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{
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"success": true,
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"data": {
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"success": true,
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"agent_id": 0,
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"prompt": "你对这件事有什么看法？",
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"result": {
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"agent_id": 0,
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"response": "我认为这件事反映了...",
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"platform": "reddit",
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"timestamp": "2025-12-08T10:00:00"
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},
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"timestamp": "2025-12-08T10:00:01"
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}
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}
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```
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**返回示例（不指定platform，双平台模式）**:
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```json
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{
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"success": true,
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"data": {
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"success": true,
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"agent_id": 0,
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"prompt": "你对这件事有什么看法？",
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"result": {
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"agent_id": 0,
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"prompt": "你对这件事有什么看法？",
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"platforms": {
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"twitter": {
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"agent_id": 0,
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"response": "从Twitter视角来看...",
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"platform": "twitter",
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"timestamp": "2025-12-08T10:00:00"
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},
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"reddit": {
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"agent_id": 0,
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"response": "作为Reddit用户，我认为...",
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"platform": "reddit",
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"timestamp": "2025-12-08T10:00:00"
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}
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}
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},
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"timestamp": "2025-12-08T10:00:01"
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}
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}
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```
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**注意**: 此功能需要模拟环境处于运行状态（完成模拟循环后进入等待命令模式）
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---
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#### 2. 批量采访多个Agent
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**接口**: `POST /api/simulation/interview/batch`
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**请求参数**:
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```json
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{
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"simulation_id": "sim_xxxx",
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"interviews": [
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{"agent_id": 0, "prompt": "你对A有什么看法？", "platform": "twitter"},
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{"agent_id": 1, "prompt": "你对B有什么看法？", "platform": "reddit"},
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{"agent_id": 2, "prompt": "你对C有什么看法？"}
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],
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"platform": "reddit",
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"timeout": 120
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}
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```
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| 参数 | 类型 | 必填 | 默认值 | 说明 |
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|------|------|------|--------|------|
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| simulation_id | String | 是 | - | 模拟ID |
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| interviews | Array | 是 | - | 采访列表，每项包含agent_id、prompt和可选的platform |
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| platform | String | 否 | null | 默认平台(被每项的platform覆盖)，不指定则双平台同时采访 |
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| timeout | Integer | 否 | 120 | 超时时间（秒） |
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**返回示例**:
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```json
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{
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"success": true,
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"data": {
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"success": true,
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"interviews_count": 3,
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"result": {
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"interviews_count": 6,
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"results": {
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"twitter_0": {"agent_id": 0, "response": "...", "platform": "twitter"},
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"reddit_1": {"agent_id": 1, "response": "...", "platform": "reddit"},
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"twitter_2": {"agent_id": 2, "response": "...", "platform": "twitter"},
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"reddit_2": {"agent_id": 2, "response": "...", "platform": "reddit"}
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}
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},
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"timestamp": "2025-12-08T10:00:01"
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}
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}
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```
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---
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#### 3. 全局采访（采访所有Agent）
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**接口**: `POST /api/simulation/interview/all`
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**请求参数**:
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```json
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{
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"simulation_id": "sim_xxxx",
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"prompt": "你对这件事整体有什么看法？",
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"platform": "reddit",
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"timeout": 180
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}
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```
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| 参数 | 类型 | 必填 | 默认值 | 说明 |
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|------|------|------|--------|------|
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| simulation_id | String | 是 | - | 模拟ID |
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| prompt | String | 是 | - | 采访问题（所有Agent使用相同问题） |
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| platform | String | 否 | null | 指定平台(twitter/reddit)，不指定则双平台同时采访 |
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| timeout | Integer | 否 | 180 | 超时时间（秒） |
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**返回示例**:
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```json
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{
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"success": true,
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"data": {
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"success": true,
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"interviews_count": 50,
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"result": {
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"interviews_count": 100,
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"results": {
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"twitter_0": {"agent_id": 0, "response": "...", "platform": "twitter"},
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"reddit_0": {"agent_id": 0, "response": "...", "platform": "reddit"},
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"twitter_1": {"agent_id": 1, "response": "...", "platform": "twitter"},
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"reddit_1": {"agent_id": 1, "response": "...", "platform": "reddit"},
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...
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}
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},
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"timestamp": "2025-12-08T10:00:01"
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}
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}
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```
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---
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#### 4. 获取Interview历史
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**接口**: `POST /api/simulation/interview/history`
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**请求参数**:
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```json
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{
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"simulation_id": "sim_xxxx",
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"platform": "reddit",
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"agent_id": 0,
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"limit": 100
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}
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```
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| 参数 | 类型 | 必填 | 默认值 | 说明 |
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|------|------|------|--------|------|
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| simulation_id | String | 是 | - | 模拟ID |
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| platform | String | 否 | reddit | 平台类型（reddit/twitter） |
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| agent_id | Integer | 否 | - | 过滤Agent ID |
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| limit | Integer | 否 | 100 | 返回数量限制 |
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**返回示例**:
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```json
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{
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"success": true,
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"data": {
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"count": 10,
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"history": [
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{
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"agent_id": 0,
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"response": "我认为...",
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"prompt": "你对这件事有什么看法？",
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"timestamp": "2025-12-08T10:00:00",
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"platform": "reddit"
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},
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...
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]
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}
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}
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```
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---
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#### 5. 获取模拟环境状态
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**接口**: `POST /api/simulation/env-status`
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**请求参数**:
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```json
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{
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"simulation_id": "sim_xxxx"
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}
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```
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| 参数 | 类型 | 必填 | 默认值 | 说明 |
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|------|------|------|--------|------|
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| simulation_id | String | 是 | - | 模拟ID |
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**返回示例**:
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```json
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{
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"success": true,
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"data": {
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"simulation_id": "sim_xxxx",
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"env_alive": true,
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"twitter_available": true,
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"reddit_available": true,
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"message": "环境正在运行，可以接收Interview命令"
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}
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}
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```
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---
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#### 6. 关闭模拟环境
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**接口**: `POST /api/simulation/close-env`
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**请求参数**:
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```json
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{
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"simulation_id": "sim_10b494550540",
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"timeout": 30
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}
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```
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| 参数 | 类型 | 必填 | 默认值 | 说明 |
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|------|------|------|--------|------|
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| simulation_id | String | 是 | - | 模拟ID |
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| timeout | Integer | 否 | 30 | 超时时间（秒） |
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**返回示例**:
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```json
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{
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"success": true,
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"data": {
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"success": true,
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"message": "环境关闭命令已发送",
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"result": {"message": "环境即将关闭"},
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"timestamp": "2025-12-08T10:00:01"
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}
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}
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```
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**注意**: 此接口与 `/stop` 不同：
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- `/stop`: 强制终止模拟进程
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- `/close-env`: 优雅地关闭环境，让模拟进程正常退出
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#### 6. 获取运行状态
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**接口**: `GET /api/simulation/{simulation_id}/run-status`
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@@ -1395,6 +1716,92 @@ POST /api/simulation/start
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---
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### 9. SimulationIPCClient/Server (IPC通信模块)
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**文件**: `app/services/simulation_ipc.py`
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**功能**: 实现Flask后端与模拟脚本之间的进程间通信
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**核心类**:
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```python
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class SimulationIPCClient:
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"""IPC客户端（Flask端使用）"""
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def send_interview(agent_id: int, prompt: str, timeout: float) -> IPCResponse:
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"""发送单个Agent采访命令"""
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def send_batch_interview(interviews: List[Dict], timeout: float) -> IPCResponse:
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"""发送批量采访命令"""
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def send_close_env(timeout: float) -> IPCResponse:
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"""发送关闭环境命令"""
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def check_env_alive() -> bool:
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"""检查模拟环境是否存活"""
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```
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```python
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class SimulationIPCServer:
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"""IPC服务器（模拟脚本端使用）"""
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def poll_commands() -> Optional[IPCCommand]:
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"""轮询获取待处理命令"""
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def send_response(response: IPCResponse):
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"""发送响应"""
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```
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**命令类型**:
|
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|
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| 命令类型 | 说明 |
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|----------|------|
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| interview | 单个Agent采访 |
|
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| batch_interview | 批量采访 |
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| close_env | 关闭环境 |
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**文件结构**:
|
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|
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```
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uploads/simulations/sim_xxx/
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├── ipc_commands/ # 命令文件目录
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│ └── {command_id}.json # 待处理命令
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├── ipc_responses/ # 响应文件目录
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│ └── {command_id}.json # 命令响应
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└── env_status.json # 环境状态文件
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```
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|
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**使用示例**:
|
||||
|
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```python
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# Flask端发送Interview命令
|
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from app.services import SimulationRunner
|
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|
||||
# 单个采访
|
||||
result = SimulationRunner.interview_agent(
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simulation_id="sim_xxx",
|
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agent_id=0,
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prompt="你对这件事有什么看法？"
|
||||
)
|
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# 批量采访
|
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result = SimulationRunner.interview_agents_batch(
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simulation_id="sim_xxx",
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interviews=[
|
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{"agent_id": 0, "prompt": "问题A"},
|
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{"agent_id": 1, "prompt": "问题B"}
|
||||
]
|
||||
)
|
||||
|
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# 全局采访
|
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result = SimulationRunner.interview_all_agents(
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simulation_id="sim_xxx",
|
||||
prompt="你认为事件会如何发展？"
|
||||
)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 工具类
|
||||
|
||||
### 1. FileParser (文件解析器)
|
||||
@@ -1661,7 +2068,35 @@ curl -X POST http://localhost:5001/api/simulation/start \
|
||||
# Step 8: 实时查询运行状态
|
||||
curl http://localhost:5001/api/simulation/{sim_xxx}/run-status
|
||||
|
||||
# Step 9: 停止模拟
|
||||
# Step 9: 检查环境状态（模拟完成后环境会进入等待命令模式）
|
||||
curl http://localhost:5001/api/simulation/{sim_xxx}/env-status
|
||||
|
||||
# Step 10: 采访单个Agent
|
||||
curl -X POST http://localhost:5001/api/simulation/{sim_xxx}/interview \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"agent_id": 0,
|
||||
"prompt": "你对这件事有什么看法？"
|
||||
}'
|
||||
|
||||
# Step 11: 全局采访（采访所有Agent）
|
||||
curl -X POST http://localhost:5001/api/simulation/{sim_xxx}/interview/all \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "你认为事件的后续发展会如何？"
|
||||
}'
|
||||
|
||||
# Step 12: 获取Interview历史
|
||||
curl http://localhost:5001/api/simulation/{sim_xxx}/interview/history
|
||||
|
||||
# Step 13: 关闭模拟环境（优雅退出）
|
||||
curl -X POST http://localhost:5001/api/simulation/close-env \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"simulation_id": "sim_xxx"
|
||||
}'
|
||||
|
||||
# 或者强制停止模拟
|
||||
curl -X POST http://localhost:5001/api/simulation/stop \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
@@ -1830,6 +2265,31 @@ MIT License
|
||||
|
||||
---
|
||||
|
||||
**最后更新**: 2025-12-05
|
||||
**版本**: v1.1.0
|
||||
**最后更新**: 2025-12-08
|
||||
**版本**: v1.2.0
|
||||
|
||||
### 更新日志
|
||||
|
||||
**v1.2.0 (2025-12-08)**:
|
||||
- 新增 Interview 采访功能
|
||||
- 支持单个Agent采访
|
||||
- 支持批量采访多个Agent
|
||||
- 支持全局采访（所有Agent使用相同问题）
|
||||
- 支持获取Interview历史记录
|
||||
- 新增模拟状态持久化
|
||||
- 模拟完成后环境不立即关闭，进入等待命令模式
|
||||
- 支持优雅关闭环境命令
|
||||
- 新增 IPC 通信机制
|
||||
- Flask后端与模拟脚本之间的进程间通信
|
||||
- 基于文件系统的命令/响应模式
|
||||
|
||||
**v1.1.0 (2025-12-05)**:
|
||||
- 新增图谱记忆动态更新功能
|
||||
- 支持 max_rounds 参数限制模拟轮数
|
||||
|
||||
**v1.0.0**:
|
||||
- 初始版本发布
|
||||
- 支持知识图谱构建
|
||||
- 支持Agent人设生成
|
||||
- 支持双平台模拟
|
||||
|
||||
|
||||
Reference in New Issue
Block a user