feat: implement session-based architecture for OPRO

- Add session layer above runs to group related optimization tasks
- Sessions use first task description as name instead of 'Session 1'
- Simplified sidebar: show sessions without expansion
- Add '+ 新建任务' button in header to create runs within session
- Fix: reload sessions after creating new run
- Add debugging logs for candidate generation
- Backend: auto-update session name with first task description

_qwen_xinference_demo/api.py

@@ -14,6 +14,7 @@ from .opro.session_state import USER_FEEDBACK_LOG
 
 # True OPRO session management
 from .opro.session_state import (
+    create_opro_session, get_opro_session, list_opro_sessions,
     create_opro_run, get_opro_run, update_opro_iteration,
     add_opro_evaluation, get_opro_trajectory, set_opro_test_cases,
     complete_opro_run, list_opro_runs
@@ -122,6 +123,7 @@ class CreateOPRORunReq(BaseModel):
     task_description: str
     test_cases: Optional[List[TestCase]] = None
     model_name: Optional[str] = None
+    session_id: Optional[str] = None  # Optional session to associate with
 
 
 class OPROIterateReq(BaseModel):
@@ -360,12 +362,62 @@ def set_model(req: SetModelReq):
 # TRUE OPRO ENDPOINTS (System Instruction Optimization)
 # ============================================================================
 
+# Session Management
+
+@app.post("/opro/session/create", tags=["opro-true"])
+def opro_create_session(session_name: str = None):
+    """
+    Create a new OPRO session that can contain multiple runs.
+    """
+    session_id = create_opro_session(session_name=session_name)
+    session = get_opro_session(session_id)
+
+    return ok({
+        "session_id": session_id,
+        "session_name": session["session_name"],
+        "num_runs": len(session["run_ids"])
+    })
+
+
+@app.get("/opro/sessions", tags=["opro-true"])
+def opro_list_sessions():
+    """
+    List all OPRO sessions.
+    """
+    sessions = list_opro_sessions()
+    return ok({"sessions": sessions})
+
+
+@app.get("/opro/session/{session_id}", tags=["opro-true"])
+def opro_get_session(session_id: str):
+    """
+    Get detailed information about an OPRO session.
+    """
+    session = get_opro_session(session_id)
+    if not session:
+        raise AppException(404, "Session not found", "SESSION_NOT_FOUND")
+
+    # Get all runs in this session
+    runs = list_opro_runs(session_id=session_id)
+
+    return ok({
+        "session_id": session_id,
+        "session_name": session["session_name"],
+        "created_at": session["created_at"],
+        "num_runs": len(session["run_ids"]),
+        "runs": runs
+    })
+
+
+# Run Management
+
 @app.post("/opro/create", tags=["opro-true"])
 def opro_create_run(req: CreateOPRORunReq):
     """
     Create a new OPRO optimization run.
 
     This starts a new system instruction optimization process for a given task.
+    Optionally can be associated with a session.
     """
     # Convert test cases from Pydantic models to tuples
     test_cases = None
@@ -375,7 +427,8 @@ def opro_create_run(req: CreateOPRORunReq):
     run_id = create_opro_run(
         task_description=req.task_description,
         test_cases=test_cases,
-        model_name=req.model_name
+        model_name=req.model_name,
+        session_id=req.session_id
     )
 
     run = get_opro_run(run_id)
@@ -385,7 +438,8 @@ def opro_create_run(req: CreateOPRORunReq):
         "task_description": run["task_description"],
         "num_test_cases": len(run["test_cases"]),
         "iteration": run["iteration"],
-        "status": run["status"]
+        "status": run["status"],
+        "session_id": run.get("session_id")
     })