Add analysis feature

backend/routes/assistants.py

@@ -277,6 +277,17 @@ async def _validate_vision_model(
             raise HTTPException(400, "视觉模型必须支持图片输入")
 
 
+async def _validate_analysis_model(
+    session: AsyncSession, body: AssistantUpsert
+) -> None:
+    config = body.analysis_config
+    if not config.enabled:
+        return
+    resource = await session.get(ModelResource, config.model_resource_id)
+    if not resource or not resource.enabled or resource.capability != "LLM":
+        raise HTTPException(400, "分析模型必须引用已启用的 LLM 模型资源")
+
+
 async def _validate_knowledge_base(session: AsyncSession, body: AssistantUpsert) -> None:
     if body.runtime_mode != "pipeline" or body.type not in {"prompt", "workflow"}:
         body.knowledge_base_id = None
@@ -384,6 +395,7 @@ async def _to_out(session: AsyncSession, assistant: Assistant) -> AssistantOut:
         tool_ids=await _tool_ids(session, assistant.id),
         prompt=assistant.prompt,
         dynamic_variable_definitions=assistant.dynamic_variable_definitions or {},
+        analysis_config=assistant.analysis_config or {},
         api_url=assistant.api_url,
         api_key=mask(assistant.api_key),
         app_id=assistant.app_id,
@@ -413,6 +425,7 @@ async def create_assistant(
     await _validate_system_tool_selection(session, body)
     await _validate_startup_actions(session, body)
     await _validate_vision_model(session, body)
+    await _validate_analysis_model(session, body)
     await _validate_knowledge_base(session, body)
     data = body.model_dump()
     resource_ids = data.pop("model_resource_ids")
@@ -459,6 +472,7 @@ async def duplicate_assistant(
         knowledge_retrieval_config=dict(source.knowledge_retrieval_config or {}),
         prompt=source.prompt,
         dynamic_variable_definitions=dict(source.dynamic_variable_definitions or {}),
+        analysis_config=dict(source.analysis_config or {}),
         api_url=source.api_url,
         api_key=source.api_key,
         app_id=source.app_id,
@@ -489,6 +503,7 @@ async def update_assistant(
     await _validate_system_tool_selection(session, body)
     await _validate_startup_actions(session, body)
     await _validate_vision_model(session, body)
+    await _validate_analysis_model(session, body)
     await _validate_knowledge_base(session, body)
     data = body.model_dump()
     resource_ids = data.pop("model_resource_ids")

backend/routes/conversations.py

@@ -8,6 +8,8 @@ from fastapi import APIRouter, Depends, HTTPException, Query, Response
 from loguru import logger
 from schemas import (
     ConversationArtifactOut,
+    ConversationAnalysisFieldOut,
+    ConversationAnalysisOut,
     ConversationDetailOut,
     ConversationListOut,
     ConversationMessageOut,
@@ -40,6 +42,33 @@ def _session_out(row: ConversationSession) -> ConversationOut:
     )
 
 
+def _analysis_out(row: ConversationSession) -> ConversationAnalysisOut:
+    data = row.analysis_data or {}
+    plan = data.get("plan") if isinstance(data.get("plan"), dict) else {}
+    definitions = plan.get("fields") if isinstance(plan.get("fields"), list) else []
+    result = data.get("result") if isinstance(data.get("result"), dict) else {}
+    fields = []
+    for definition in definitions:
+        if not isinstance(definition, dict):
+            continue
+        name = str(definition.get("name") or "")
+        if not name:
+            continue
+        fields.append(
+            ConversationAnalysisFieldOut(
+                name=name,
+                type=str(definition.get("type") or "string"),
+                value=result.get(name),
+            )
+        )
+    return ConversationAnalysisOut(
+        status=row.analysis_status or "none",
+        fields=fields,
+        error=row.analysis_error or "",
+        completed_at=data.get("completedAt"),
+    )
+
+
 @router.get("", response_model=ConversationListOut)
 async def list_conversations(
     page: int = Query(1, ge=1),
@@ -119,6 +148,7 @@ async def get_conversation(
     return ConversationDetailOut(
         **_session_out(conversation).model_dump(),
         extra=conversation.extra or {},
+        analysis=_analysis_out(conversation),
         messages=[
             ConversationMessageOut(
                 id=message.id,