fix: 修复数据传递问题
This commit is contained in:
parent
39fb220cf2
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6ffbb29ec7
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@ -96,7 +96,16 @@ class Message(db.Model):
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role = db.Column(db.String(16), nullable=False) # user, assistant, system, tool
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# Unified JSON structure:
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# User: {"text": "...", "attachments": [{"name": "a.py", "extension": "py", "content": "..."}]}
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# Assistant: {"text": "...", "thinking": "...", "tool_calls": [{"id": "...", "name": "...", "arguments": "...", "result": "..."}]}
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# Assistant: {
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# "text": "...",
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# "tool_calls": [...], // legacy flat structure
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# "steps": [ // ordered steps for rendering (primary source of truth)
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# {"id": "step-0", "index": 0, "type": "thinking", "content": "..."},
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# {"id": "step-1", "index": 1, "type": "text", "content": "..."},
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# {"id": "step-2", "index": 2, "type": "tool_call", "id_ref": "call_xxx", "name": "...", "arguments": "..."},
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# {"id": "step-3", "index": 3, "type": "tool_result", "id_ref": "call_xxx", "name": "...", "content": "..."},
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# ]
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# }
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content = db.Column(LongText, default="")
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token_count = db.Column(db.Integer, default=0)
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created_at = db.Column(db.DateTime, default=lambda: datetime.now(timezone.utc), index=True)
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@ -224,7 +224,7 @@ def upload_project_folder():
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# Create project record
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project = Project(
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id=str(uuid.uuid4()),
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user_id=user_id,
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user_id=user.id,
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name=project_name,
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path=relative_path,
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description=description
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@ -53,8 +53,9 @@ class ChatService:
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messages = list(initial_messages)
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all_tool_calls = []
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all_tool_results = []
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all_steps = [] # Collect all ordered steps for DB storage (thinking/text/tool_call/tool_result)
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step_index = 0 # Track global step index for ordering
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for iteration in range(self.MAX_ITERATIONS):
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full_content = ""
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full_thinking = ""
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@ -62,10 +63,10 @@ class ChatService:
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prompt_tokens = 0
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msg_id = str(uuid.uuid4())
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tool_calls_list = []
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# Send thinking_start event to clear previous thinking in frontend
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yield f"event: thinking_start\ndata: {{}}\n\n"
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try:
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with app.app_context():
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active_conv = db.session.get(Conversation, conv_id)
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@ -79,7 +80,8 @@ class ChatService:
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stream=True,
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)
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resp.raise_for_status()
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# Stream LLM response chunk by chunk
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for line in resp.iter_lines():
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if not line:
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continue
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@ -93,76 +95,109 @@ class ChatService:
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chunk = json.loads(data_str)
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except json.JSONDecodeError:
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continue
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delta = chunk["choices"][0].get("delta", {})
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# Process thinking - send as process_step
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# Accumulate thinking content for this iteration
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reasoning = delta.get("reasoning_content", "")
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if reasoning:
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full_thinking += reasoning
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# Still send thinking event for backward compatibility
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yield f"event: thinking\ndata: {json.dumps({'content': reasoning}, ensure_ascii=False)}\n\n"
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# Process text
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# Accumulate text content for this iteration
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text = delta.get("content", "")
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if text:
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full_content += text
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yield f"event: message\ndata: {json.dumps({'content': text}, ensure_ascii=False)}\n\n"
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# Process tool calls
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# Accumulate tool calls from streaming deltas
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tool_calls_list = self._process_tool_calls_delta(delta, tool_calls_list)
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usage = chunk.get("usage", {})
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if usage:
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token_count = usage.get("completion_tokens", 0)
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prompt_tokens = usage.get("prompt_tokens", 0)
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except Exception as e:
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yield f"event: error\ndata: {json.dumps({'content': str(e)}, ensure_ascii=False)}\n\n"
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return
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# Tool calls exist - execute and continue
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# --- Tool calls exist: emit finalized steps, execute tools, continue loop ---
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if tool_calls_list:
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all_tool_calls.extend(tool_calls_list)
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# Send thinking as a complete step if exists
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# Record thinking as a finalized step (preserves order)
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if full_thinking:
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yield f"event: process_step\ndata: {json.dumps({'index': step_index, 'type': 'thinking', 'content': full_thinking}, ensure_ascii=False)}\n\n"
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step_data = {
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'id': f'step-{step_index}',
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'index': step_index,
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'type': 'thinking',
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'content': full_thinking,
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}
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all_steps.append(step_data)
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yield f"event: process_step\ndata: {json.dumps(step_data, ensure_ascii=False)}\n\n"
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step_index += 1
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# Send text as a step if exists (text before tool calls)
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# Record text as a finalized step (text that preceded tool calls)
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if full_content:
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yield f"event: process_step\ndata: {json.dumps({'index': step_index, 'type': 'text', 'content': full_content}, ensure_ascii=False)}\n\n"
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step_data = {
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'id': f'step-{step_index}',
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'index': step_index,
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'type': 'text',
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'content': full_content,
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}
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all_steps.append(step_data)
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yield f"event: process_step\ndata: {json.dumps(step_data, ensure_ascii=False)}\n\n"
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step_index += 1
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# Also send legacy tool_calls event for backward compatibility
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# Legacy tool_calls event for backward compatibility
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yield f"event: tool_calls\ndata: {json.dumps({'calls': tool_calls_list}, ensure_ascii=False)}\n\n"
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# Process each tool call one by one, send result immediately
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# Execute each tool call, emit tool_call + tool_result as paired steps
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tool_results = []
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for tc in tool_calls_list:
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# Send tool call step
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yield f"event: process_step\ndata: {json.dumps({'index': step_index, 'type': 'tool_call', 'id': tc['id'], 'name': tc['function']['name'], 'arguments': tc['function']['arguments']}, ensure_ascii=False)}\n\n"
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# Emit tool_call step (before execution)
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call_step = {
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'id': f'step-{step_index}',
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'index': step_index,
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'type': 'tool_call',
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'id_ref': tc['id'],
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'name': tc['function']['name'],
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'arguments': tc['function']['arguments'],
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}
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all_steps.append(call_step)
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yield f"event: process_step\ndata: {json.dumps(call_step, ensure_ascii=False)}\n\n"
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step_index += 1
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# Execute this single tool call (needs app context for db access)
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# Execute the tool
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with app.app_context():
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single_result = self.executor.process_tool_calls([tc], context)
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tool_results.extend(single_result)
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# Send tool result step immediately
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# Emit tool_result step (after execution)
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tr = single_result[0]
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try:
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result_content = json.loads(tr["content"])
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skipped = result_content.get("skipped", False)
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except:
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skipped = False
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yield f"event: process_step\ndata: {json.dumps({'index': step_index, 'type': 'tool_result', 'id': tr['tool_call_id'], 'name': tr['name'], 'content': tr['content'], 'skipped': skipped}, ensure_ascii=False)}\n\n"
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result_step = {
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'id': f'step-{step_index}',
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'index': step_index,
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'type': 'tool_result',
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'id_ref': tr['tool_call_id'],
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'name': tr['name'],
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'content': tr['content'],
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'skipped': skipped,
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}
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all_steps.append(result_step)
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yield f"event: process_step\ndata: {json.dumps(result_step, ensure_ascii=False)}\n\n"
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step_index += 1
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# Also send legacy tool_result event
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# Legacy tool_result event for backward compatibility
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yield f"event: tool_result\ndata: {json.dumps({'id': tr['tool_call_id'], 'name': tr['name'], 'content': tr['content'], 'skipped': skipped}, ensure_ascii=False)}\n\n"
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# Append assistant message + tool results for the next iteration
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messages.append({
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"role": "assistant",
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"content": full_content or None,
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@ -171,28 +206,41 @@ class ChatService:
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messages.extend(tool_results)
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all_tool_results.extend(tool_results)
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continue
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# No tool calls - finish
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# Send thinking as a step if exists
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# --- No tool calls: final iteration — emit remaining steps and save ---
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if full_thinking:
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yield f"event: process_step\ndata: {json.dumps({'index': step_index, 'type': 'thinking', 'content': full_thinking}, ensure_ascii=False)}\n\n"
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step_data = {
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'id': f'step-{step_index}',
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'index': step_index,
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'type': 'thinking',
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'content': full_thinking,
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}
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all_steps.append(step_data)
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yield f"event: process_step\ndata: {json.dumps(step_data, ensure_ascii=False)}\n\n"
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step_index += 1
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# Send text as a step if exists
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if full_content:
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yield f"event: process_step\ndata: {json.dumps({'index': step_index, 'type': 'text', 'content': full_content}, ensure_ascii=False)}\n\n"
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step_data = {
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'id': f'step-{step_index}',
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'index': step_index,
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'type': 'text',
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'content': full_content,
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}
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all_steps.append(step_data)
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yield f"event: process_step\ndata: {json.dumps(step_data, ensure_ascii=False)}\n\n"
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step_index += 1
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suggested_title = None
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with app.app_context():
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# Build content JSON
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# Build content JSON with ordered steps array for DB storage.
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# 'steps' is the single source of truth for rendering order.
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content_json = {
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"text": full_content,
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}
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if full_thinking:
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content_json["thinking"] = full_thinking
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if all_tool_calls:
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content_json["tool_calls"] = self._build_tool_calls_json(all_tool_calls, all_tool_results)
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# Store ordered steps — the single source of truth for rendering order
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content_json["steps"] = all_steps
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msg = Message(
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id=msg_id,
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@ -208,15 +256,13 @@ class ChatService:
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if user:
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record_token_usage(user.id, conv_model, prompt_tokens, token_count)
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# Check if we need to set title (first message in conversation)
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# Auto-generate title from first user message if needed
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conv = db.session.get(Conversation, conv_id)
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if conv and (not conv.title or conv.title == "新对话"):
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# Get user message content
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user_msg = Message.query.filter_by(
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conversation_id=conv_id, role="user"
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).order_by(Message.created_at.asc()).first()
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if user_msg and user_msg.content:
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# Parse content JSON to get text
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try:
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content_data = json.loads(user_msg.content)
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title_text = content_data.get("text", "")[:30]
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@ -226,7 +272,6 @@ class ChatService:
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suggested_title = title_text
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else:
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suggested_title = "新对话"
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# Refresh conv to avoid stale state
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db.session.refresh(conv)
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conv.title = suggested_title
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db.session.commit()
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@ -63,7 +63,12 @@ def to_dict(inst, **extra):
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def message_to_dict(msg: Message) -> dict:
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"""Convert message to dict, parsing JSON content"""
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"""Convert message to dict, parsing JSON content.
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For assistant messages, extracts the 'steps' array which preserves the
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ordered sequence of thinking/text/tool_call/tool_result steps, so the
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frontend can render them in the correct interleaved order.
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"""
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result = to_dict(msg)
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# Parse content JSON
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@ -71,16 +76,15 @@ def message_to_dict(msg: Message) -> dict:
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try:
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content_data = json.loads(msg.content)
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if isinstance(content_data, dict):
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# Extract all fields from JSON
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result["text"] = content_data.get("text", "")
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if content_data.get("attachments"):
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result["attachments"] = content_data["attachments"]
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if content_data.get("thinking"):
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result["thinking"] = content_data["thinking"]
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if content_data.get("tool_calls"):
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result["tool_calls"] = content_data["tool_calls"]
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# Extract ordered steps array for correct rendering order
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if content_data.get("steps"):
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result["process_steps"] = content_data["steps"]
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else:
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# Fallback: plain text
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result["text"] = msg.content
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except (json.JSONDecodeError, TypeError):
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result["text"] = msg.content
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@ -175,7 +175,6 @@ classDiagram
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```json
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{
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"text": "AI 回复的文本内容",
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"thinking": "思考过程（可选）",
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"tool_calls": [
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{
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"id": "call_xxx",
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@ -189,10 +188,55 @@ classDiagram
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"skipped": false,
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"execution_time": 0.5
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}
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],
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"steps": [
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{
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"id": "step-0",
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"index": 0,
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"type": "thinking",
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"content": "第一轮思考过程..."
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},
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{
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"id": "step-1",
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"index": 1,
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"type": "text",
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"content": "工具调用前的文本..."
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},
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{
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"id": "step-2",
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"index": 2,
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"type": "tool_call",
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"id_ref": "call_abc123",
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"name": "web_search",
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"arguments": "{\"query\": \"...\"}"
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},
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{
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"id": "step-3",
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"index": 3,
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"type": "tool_result",
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"id_ref": "call_abc123",
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"name": "web_search",
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"content": "{\"success\": true, ...}",
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"skipped": false
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},
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{
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"id": "step-4",
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"index": 4,
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"type": "thinking",
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"content": "第二轮思考过程..."
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},
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{
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"id": "step-5",
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"index": 5,
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"type": "text",
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"content": "最终回复文本..."
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}
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]
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}
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```
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`steps` 字段是**渲染顺序的唯一数据源**，按 `index` 顺序排列。thinking、text、tool_call、tool_result 可以在多轮迭代中穿插出现。`id_ref` 用于 tool_call 和 tool_result 步骤之间的匹配（对应 LLM 返回的工具调用 ID）。`tool_calls` 字段保留用于向后兼容旧版前端。
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### 服务层
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```mermaid
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@ -426,33 +470,53 @@ def process_tool_calls(self, tool_calls, context=None):
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| `message` | 回复内容的增量片段 |
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| `tool_calls` | 工具调用信息 |
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| `tool_result` | 工具执行结果 |
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| `process_step` | 处理步骤（按顺序：thinking/text/tool_call/tool_result），支持穿插显示 |
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| `process_step` | 有序处理步骤（thinking/text/tool_call/tool_result），支持穿插显示。携带 `id`、`index` 确保渲染顺序 |
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| `error` | 错误信息 |
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| `done` | 回复结束，携带 message_id 和 token_count |
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### process_step 事件格式
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每个 `process_step` 事件携带一个带 `id`、`index` 和 `type` 的步骤对象。步骤按 `index` 顺序排列，确保前端可以正确渲染穿插的思考、文本和工具调用。
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```json
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// 思考过程
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{"index": 0, "type": "thinking", "content": "完整思考内容..."}
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{"id": "step-0", "index": 0, "type": "thinking", "content": "完整思考内容..."}
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// 回复文本（可穿插在任意步骤之间）
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{"index": 1, "type": "text", "content": "回复文本内容..."}
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{"id": "step-1", "index": 1, "type": "text", "content": "回复文本内容..."}
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// 工具调用
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{"index": 2, "type": "tool_call", "id": "call_abc123", "name": "web_search", "arguments": "{\"query\": \"...\"}"}
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// 工具调用（id_ref 存储工具调用 ID，用于与 tool_result 匹配）
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{"id": "step-2", "index": 2, "type": "tool_call", "id_ref": "call_abc123", "name": "web_search", "arguments": "{\"query\": \"...\"}"}
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// 工具返回
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{"index": 3, "type": "tool_result", "id": "call_abc123", "name": "web_search", "content": "{\"success\": true, ...}", "skipped": false}
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// 工具返回（id_ref 与 tool_call 的 id_ref 匹配）
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{"id": "step-3", "index": 3, "type": "tool_result", "id_ref": "call_abc123", "name": "web_search", "content": "{\"success\": true, ...}", "skipped": false}
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```
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字段说明：
|
||||
- `index`: 步骤序号，确保按正确顺序显示
|
||||
- `type`: 步骤类型（thinking/tool_call/tool_result）
|
||||
- `id`: 工具调用唯一标识，用于匹配工具调用和返回结果
|
||||
- `name`: 工具名称
|
||||
- `content`: 内容或结果
|
||||
- `skipped`: 工具是否被跳过（失败后跳过）
|
||||
|
||||
| 字段 | 说明 |
|
||||
|------|------|
|
||||
| `id` | 步骤唯一标识（格式 `step-{index}`），用于前端 key |
|
||||
| `index` | 步骤序号，确保按正确顺序显示 |
|
||||
| `type` | 步骤类型：`thinking` / `text` / `tool_call` / `tool_result` |
|
||||
| `id_ref` | 工具调用引用 ID（仅 tool_call/tool_result），用于匹配调用与结果 |
|
||||
| `name` | 工具名称（仅 tool_call/tool_result） |
|
||||
| `arguments` | 工具调用参数 JSON 字符串（仅 tool_call） |
|
||||
| `content` | 内容（thinking 的思考内容、text 的文本、tool_result 的返回结果） |
|
||||
| `skipped` | 工具是否被跳过（仅 tool_result） |
|
||||
|
||||
### 多轮迭代中的步骤顺序
|
||||
|
||||
一次完整的 LLM 交互可能经历多轮工具调用循环，每轮产生的步骤按以下顺序追加：
|
||||
|
||||
```
|
||||
迭代 1: thinking → text → tool_call → tool_result
|
||||
迭代 2: thinking → text → tool_call → tool_result
|
||||
...
|
||||
最终轮: thinking → text（无工具调用，结束）
|
||||
```
|
||||
|
||||
所有步骤通过全局递增的 `index` 保证顺序。后端在完成所有迭代后，将这些步骤存入 `content_json["steps"]` 数组写入数据库。前端页面刷新时从 API 加载消息，`message_to_dict` 提取 `steps` 字段映射为 `process_steps` 返回，ProcessBlock 组件按 `index` 顺序渲染。
|
||||
|
||||
---
|
||||
|
||||
|
|
@ -509,10 +573,12 @@ def process_tool_calls(self, tool_calls, context=None):
|
|||
| `id` | String(64) | UUID 主键 |
|
||||
| `conversation_id` | String(64) | 外键关联 Conversation |
|
||||
| `role` | String(16) | user/assistant/system/tool |
|
||||
| `content` | LongText | JSON 格式内容（见上方结构说明） |
|
||||
| `content` | LongText | JSON 格式内容（见上方结构说明），assistant 消息包含 `steps` 有序步骤数组 |
|
||||
| `token_count` | Integer | Token 数量 |
|
||||
| `created_at` | DateTime | 创建时间 |
|
||||
|
||||
`message_to_dict()` 辅助函数负责解析 `content` JSON，并提取 `steps` 字段映射为 `process_steps` 返回给前端，确保页面刷新后仍能按正确顺序渲染穿插的思考、文本和工具调用。
|
||||
|
||||
### TokenUsage（Token 使用统计）
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|
|
|
|||
|
|
@ -2,6 +2,7 @@
|
|||
<div class="app">
|
||||
<Sidebar
|
||||
:conversations="conversations"
|
||||
:projects="projects"
|
||||
:current-id="currentConvId"
|
||||
:loading="loadingConvs"
|
||||
:has-more="hasMoreConvs"
|
||||
|
|
@ -11,6 +12,7 @@
|
|||
@create-project="showCreateModal = true"
|
||||
@browse-project="browseProject"
|
||||
@create-in-project="createConversationInProject"
|
||||
@delete-project="deleteProject"
|
||||
@toggle-settings="togglePanel('settings')"
|
||||
@toggle-stats="togglePanel('stats')"
|
||||
/>
|
||||
|
|
@ -42,7 +44,6 @@
|
|||
:messages="messages"
|
||||
:streaming="streaming"
|
||||
:streaming-content="streamContent"
|
||||
:streaming-thinking="streamThinking"
|
||||
:streaming-tool-calls="streamToolCalls"
|
||||
:streaming-process-steps="streamProcessSteps"
|
||||
:has-more-messages="hasMoreMessages"
|
||||
|
|
@ -128,6 +129,9 @@ const loadingConvs = ref(false)
|
|||
const hasMoreConvs = ref(false)
|
||||
const nextConvCursor = ref(null)
|
||||
|
||||
// -- Projects state --
|
||||
const projects = ref([])
|
||||
|
||||
// -- Messages state --
|
||||
const messages = shallowRef([])
|
||||
const hasMoreMessages = ref(false)
|
||||
|
|
@ -135,11 +139,14 @@ const loadingMessages = ref(false)
|
|||
const nextMsgCursor = ref(null)
|
||||
|
||||
// -- Streaming state --
|
||||
// These refs hold the real-time streaming data for the current conversation.
|
||||
// When switching conversations, the current state is saved to streamStates Map
|
||||
// and restored when switching back. On stream completion (onDone), the finalized
|
||||
// processSteps are stored in the message object and later persisted to DB.
|
||||
const streaming = ref(false)
|
||||
const streamContent = ref('')
|
||||
const streamThinking = ref('')
|
||||
const streamToolCalls = shallowRef([])
|
||||
const streamProcessSteps = shallowRef([])
|
||||
const streamContent = ref('') // Accumulated text content during current iteration
|
||||
const streamToolCalls = shallowRef([]) // All tool calls across iterations (legacy compat)
|
||||
const streamProcessSteps = shallowRef([]) // Ordered steps: thinking/text/tool_call/tool_result
|
||||
|
||||
// 保存每个对话的流式状态
|
||||
const streamStates = new Map()
|
||||
|
|
@ -147,7 +154,6 @@ const streamStates = new Map()
|
|||
function setStreamState(isActive) {
|
||||
streaming.value = isActive
|
||||
streamContent.value = ''
|
||||
streamThinking.value = ''
|
||||
streamToolCalls.value = []
|
||||
streamProcessSteps.value = []
|
||||
}
|
||||
|
|
@ -253,7 +259,6 @@ async function selectConversation(id) {
|
|||
streamStates.set(currentConvId.value, {
|
||||
streaming: true,
|
||||
streamContent: streamContent.value,
|
||||
streamThinking: streamThinking.value,
|
||||
streamToolCalls: [...streamToolCalls.value],
|
||||
streamProcessSteps: [...streamProcessSteps.value],
|
||||
messages: [...messages.value],
|
||||
|
|
@ -269,7 +274,6 @@ async function selectConversation(id) {
|
|||
if (savedState && savedState.streaming) {
|
||||
streaming.value = true
|
||||
streamContent.value = savedState.streamContent
|
||||
streamThinking.value = savedState.streamThinking
|
||||
streamToolCalls.value = savedState.streamToolCalls
|
||||
streamProcessSteps.value = savedState.streamProcessSteps
|
||||
messages.value = savedState.messages || []
|
||||
|
|
@ -310,13 +314,6 @@ function loadMoreMessages() {
|
|||
// -- Helpers: create stream callbacks for a conversation --
|
||||
function createStreamCallbacks(convId, { updateConvList = true } = {}) {
|
||||
return {
|
||||
onThinkingStart() {
|
||||
updateStreamField(convId, 'streamThinking', streamThinking, '')
|
||||
updateStreamField(convId, 'streamContent', streamContent, '')
|
||||
},
|
||||
onThinking(text) {
|
||||
updateStreamField(convId, 'streamThinking', streamThinking, prev => (prev || '') + text)
|
||||
},
|
||||
onMessage(text) {
|
||||
updateStreamField(convId, 'streamContent', streamContent, prev => (prev || '') + text)
|
||||
},
|
||||
|
|
@ -335,6 +332,10 @@ function createStreamCallbacks(convId, { updateConvList = true } = {}) {
|
|||
})
|
||||
},
|
||||
onProcessStep(step) {
|
||||
// Insert step at its index position to preserve ordering.
|
||||
// Uses sparse array strategy: fills gaps with null.
|
||||
// Each step carries { id, index, type, content, ... } —
|
||||
// these are the same steps that get stored to DB as the 'steps' array.
|
||||
updateStreamField(convId, 'streamProcessSteps', streamProcessSteps, prev => {
|
||||
const steps = prev ? [...prev] : []
|
||||
while (steps.length <= step.index) steps.push(null)
|
||||
|
|
@ -347,12 +348,15 @@ function createStreamCallbacks(convId, { updateConvList = true } = {}) {
|
|||
|
||||
if (currentConvId.value === convId) {
|
||||
streaming.value = false
|
||||
|
||||
// Build the final message object.
|
||||
// process_steps is the primary ordered data for rendering (thinking/text/tool_call/tool_result).
|
||||
// When page reloads, these steps are loaded from DB via the 'steps' field in content JSON.
|
||||
messages.value = [...messages.value, {
|
||||
id: data.message_id,
|
||||
conversation_id: convId,
|
||||
role: 'assistant',
|
||||
text: streamContent.value,
|
||||
thinking: streamThinking.value || null,
|
||||
tool_calls: streamToolCalls.value.length > 0 ? streamToolCalls.value : null,
|
||||
process_steps: streamProcessSteps.value.filter(Boolean),
|
||||
token_count: data.token_count,
|
||||
|
|
@ -507,13 +511,13 @@ async function createProject() {
|
|||
creatingProject.value = true
|
||||
try {
|
||||
await projectApi.create({
|
||||
user_id: 1,
|
||||
name: newProjectName.value.trim(),
|
||||
description: newProjectDesc.value.trim(),
|
||||
})
|
||||
showCreateModal.value = false
|
||||
newProjectName.value = ''
|
||||
newProjectDesc.value = ''
|
||||
await loadProjects()
|
||||
} catch (e) {
|
||||
console.error('Failed to create project:', e)
|
||||
} finally {
|
||||
|
|
@ -521,8 +525,47 @@ async function createProject() {
|
|||
}
|
||||
}
|
||||
|
||||
// -- Load projects --
|
||||
async function loadProjects() {
|
||||
try {
|
||||
const res = await projectApi.list()
|
||||
projects.value = res.data.projects || []
|
||||
} catch (e) {
|
||||
console.error('Failed to load projects:', e)
|
||||
}
|
||||
}
|
||||
|
||||
// -- Delete project --
|
||||
async function deleteProject(project) {
|
||||
if (!confirm(`确定删除项目「${project.name}」及其所有对话？`)) return
|
||||
try {
|
||||
await projectApi.delete(project.id)
|
||||
// Remove conversations belonging to this project
|
||||
conversations.value = conversations.value.filter(c => c.project_id !== project.id)
|
||||
// If current conversation was in this project, switch away
|
||||
if (currentConvId.value && conversations.value.length > 0) {
|
||||
const currentConv = conversations.value.find(c => c.id === currentConvId.value)
|
||||
if (!currentConv || currentConv.project_id === project.id) {
|
||||
await selectConversation(conversations.value[0].id)
|
||||
}
|
||||
} else if (conversations.value.length === 0) {
|
||||
currentConvId.value = null
|
||||
messages.value = []
|
||||
currentProject.value = null
|
||||
}
|
||||
if (currentProject.value?.id === project.id) {
|
||||
currentProject.value = null
|
||||
showFileExplorer.value = false
|
||||
}
|
||||
await loadProjects()
|
||||
} catch (e) {
|
||||
console.error('Failed to delete project:', e)
|
||||
}
|
||||
}
|
||||
|
||||
// -- Init --
|
||||
onMounted(() => {
|
||||
loadProjects()
|
||||
loadConversations()
|
||||
})
|
||||
</script>
|
||||
|
|
|
|||
|
|
@ -194,8 +194,8 @@ export const messageApi = {
|
|||
}
|
||||
|
||||
export const projectApi = {
|
||||
list(userId) {
|
||||
return request(`/projects${buildQueryParams({ user_id: userId })}`)
|
||||
list() {
|
||||
return request('/projects')
|
||||
},
|
||||
|
||||
create(data) {
|
||||
|
|
@ -211,7 +211,6 @@ export const projectApi = {
|
|||
|
||||
uploadFolder(data) {
|
||||
const formData = new FormData()
|
||||
formData.append('user_id', String(data.user_id))
|
||||
formData.append('name', data.name || '')
|
||||
formData.append('description', data.description || '')
|
||||
for (const file of data.files) {
|
||||
|
|
|
|||
|
|
@ -27,12 +27,11 @@
|
|||
v-for="msg in messages"
|
||||
:key="msg.id"
|
||||
:data-msg-id="msg.id"
|
||||
v-memo="[msg.text, msg.thinking, msg.tool_calls, msg.process_steps, msg.attachments]"
|
||||
v-memo="[msg.text, msg.tool_calls, msg.process_steps, msg.attachments]"
|
||||
>
|
||||
<MessageBubble
|
||||
:role="msg.role"
|
||||
:text="msg.text"
|
||||
:thinking-content="msg.thinking"
|
||||
:tool-calls="msg.tool_calls"
|
||||
:process-steps="msg.process_steps"
|
||||
:token-count="msg.token_count"
|
||||
|
|
@ -48,7 +47,6 @@
|
|||
<div class="avatar">claw</div>
|
||||
<div class="message-body">
|
||||
<ProcessBlock
|
||||
:thinking-content="streamingThinking"
|
||||
:tool-calls="streamingToolCalls"
|
||||
:process-steps="streamingProcessSteps"
|
||||
:streaming-content="streamingContent"
|
||||
|
|
@ -90,7 +88,6 @@ const props = defineProps({
|
|||
messages: { type: Array, required: true },
|
||||
streaming: { type: Boolean, default: false },
|
||||
streamingContent: { type: String, default: '' },
|
||||
streamingThinking: { type: String, default: '' },
|
||||
streamingToolCalls: { type: Array, default: () => [] },
|
||||
streamingProcessSteps: { type: Array, default: () => [] },
|
||||
hasMoreMessages: { type: Boolean, default: false },
|
||||
|
|
|
|||
|
|
@ -3,7 +3,7 @@
|
|||
<div v-if="role === 'user'" class="avatar">user</div>
|
||||
<div v-else class="avatar">claw</div>
|
||||
<div class="message-container">
|
||||
<!-- 附件列表 -->
|
||||
<!-- File attachments list -->
|
||||
<div v-if="attachments && attachments.length > 0" class="attachments-list">
|
||||
<div v-for="(file, index) in attachments" :key="index" class="attachment-item">
|
||||
<span class="attachment-icon">{{ file.extension }}</span>
|
||||
|
|
@ -11,18 +11,18 @@
|
|||
</div>
|
||||
</div>
|
||||
<div ref="messageRef" class="message-body">
|
||||
<!-- 新格式: processSteps 包含所有步骤（含 text），统一通过 ProcessBlock 渲染 -->
|
||||
<!-- Primary rendering path: processSteps contains all ordered steps -->
|
||||
<!-- (thinking, text, tool_call, tool_result) from both streaming and DB load -->
|
||||
<ProcessBlock
|
||||
v-if="processSteps && processSteps.length > 0"
|
||||
:process-steps="processSteps"
|
||||
:thinking-content="thinkingContent"
|
||||
:tool-calls="toolCalls"
|
||||
/>
|
||||
<!-- 旧格式: 无 processSteps，分开渲染 ProcessBlock + 文本 -->
|
||||
<!-- Fallback path: old messages without processSteps in DB, -->
|
||||
<!-- render toolCalls via ProcessBlock and text separately -->
|
||||
<template v-else>
|
||||
<ProcessBlock
|
||||
v-if="thinkingContent || (toolCalls && toolCalls.length > 0)"
|
||||
:thinking-content="thinkingContent"
|
||||
v-if="toolCalls && toolCalls.length > 0"
|
||||
:tool-calls="toolCalls"
|
||||
/>
|
||||
<div class="md-content message-content" v-html="renderedContent"></div>
|
||||
|
|
@ -62,15 +62,18 @@ import { useCodeEnhancement } from '../composables/useCodeEnhancement'
|
|||
import ProcessBlock from './ProcessBlock.vue'
|
||||
|
||||
const props = defineProps({
|
||||
role: { type: String, required: true },
|
||||
text: { type: String, default: '' },
|
||||
thinkingContent: { type: String, default: '' },
|
||||
toolCalls: { type: Array, default: () => [] },
|
||||
role: { type: String, required: true }, // 'user' or 'assistant'
|
||||
text: { type: String, default: '' }, // Plain text content (legacy / user messages)
|
||||
toolCalls: { type: Array, default: () => [] }, // Tool calls array (legacy fallback)
|
||||
// Ordered steps array — primary rendering data source.
|
||||
// During streaming: accumulated from process_step SSE events.
|
||||
// On page load: loaded from DB via message_to_dict extracting 'steps' field.
|
||||
// Each step: { id, index, type: 'thinking'|'text'|'tool_call'|'tool_result', content, ... }
|
||||
processSteps: { type: Array, default: () => [] },
|
||||
tokenCount: { type: Number, default: 0 },
|
||||
createdAt: { type: String, default: '' },
|
||||
deletable: { type: Boolean, default: false },
|
||||
attachments: { type: Array, default: () => [] },
|
||||
attachments: { type: Array, default: () => [] }, // User file attachments
|
||||
})
|
||||
|
||||
defineEmits(['delete', 'regenerate'])
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
<template>
|
||||
<div ref="processRef" class="process-block" :class="{ 'is-streaming': streaming }">
|
||||
<!-- 流式加载：还没有任何步骤时 -->
|
||||
<!-- Placeholder while waiting for the first process step to arrive -->
|
||||
<div v-if="streaming && processItems.length === 0" class="streaming-placeholder">
|
||||
<div class="streaming-icon">
|
||||
<svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
|
||||
|
|
@ -10,10 +10,10 @@
|
|||
<span class="streaming-text">正在思考中<span class="dots">...</span></span>
|
||||
</div>
|
||||
|
||||
<!-- 按序渲染步骤 -->
|
||||
<!-- Render all steps in order: thinking, text, tool_call, tool_result interleaved -->
|
||||
<template v-else>
|
||||
<template v-for="item in processItems" :key="item.key">
|
||||
<!-- 思考过程 -->
|
||||
<!-- Thinking block -->
|
||||
<div v-if="item.type === 'thinking'" class="step-item thinking">
|
||||
<div class="step-header" @click="toggleItem(item.key)">
|
||||
<svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
|
||||
|
|
@ -30,7 +30,7 @@
|
|||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 工具调用 -->
|
||||
<!-- Tool call block -->
|
||||
<div v-else-if="item.type === 'tool_call'" class="step-item tool_call" :class="{ loading: item.loading }">
|
||||
<div class="step-header" @click="toggleItem(item.key)">
|
||||
<svg width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
|
||||
|
|
@ -56,11 +56,11 @@
|
|||
</div>
|
||||
</div>
|
||||
|
||||
<!-- 文本内容 - 直接渲染 markdown -->
|
||||
<!-- Text content — render as markdown -->
|
||||
<div v-else-if="item.type === 'text'" class="step-item text-content md-content" v-html="item.rendered"></div>
|
||||
</template>
|
||||
|
||||
<!-- 流式进行中指示器 -->
|
||||
<!-- Active streaming indicator (cursor) -->
|
||||
<div v-if="streaming" class="streaming-indicator">
|
||||
<svg class="spinner" width="14" height="14" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
|
||||
<path d="M21 12a9 9 0 1 1-6.219-8.56"/>
|
||||
|
|
@ -78,7 +78,6 @@ import { formatJson, truncate } from '../utils/format'
|
|||
import { useCodeEnhancement } from '../composables/useCodeEnhancement'
|
||||
|
||||
const props = defineProps({
|
||||
thinkingContent: { type: String, default: '' },
|
||||
toolCalls: { type: Array, default: () => [] },
|
||||
processSteps: { type: Array, default: () => [] },
|
||||
streamingContent: { type: String, default: '' },
|
||||
|
|
@ -87,7 +86,7 @@ const props = defineProps({
|
|||
|
||||
const expandedKeys = ref({})
|
||||
|
||||
// 流式时自动展开
|
||||
// Auto-collapse all items when a new stream starts
|
||||
watch(() => props.streaming, (v) => {
|
||||
if (v) expandedKeys.value = {}
|
||||
})
|
||||
|
|
@ -110,30 +109,45 @@ function getResultSummary(result) {
|
|||
}
|
||||
}
|
||||
|
||||
// Build ordered process items from all available data (thinking, tool calls, text).
|
||||
// During streaming, processSteps accumulate completed iterations while streamingContent
|
||||
// represents the text being generated in the current (latest) iteration.
|
||||
// When loaded from DB, steps use 'id_ref' for tool_call/tool_result matching;
|
||||
// during streaming they use 'id'. Both fields are normalized here.
|
||||
const processItems = computed(() => {
|
||||
const items = []
|
||||
|
||||
// 优先使用 processSteps（按顺序）
|
||||
// Build items from processSteps — finalized steps sent by backend or loaded from DB.
|
||||
// Steps are ordered: each iteration produces thinking → text → tool_call → tool_result.
|
||||
if (props.processSteps && props.processSteps.length > 0) {
|
||||
for (const step of props.processSteps) {
|
||||
if (!step) continue
|
||||
|
||||
if (step.type === 'thinking') {
|
||||
items.push({ type: 'thinking', content: step.content, summary: truncate(step.content), key: `thinking-${step.index}` })
|
||||
items.push({
|
||||
type: 'thinking',
|
||||
content: step.content,
|
||||
summary: truncate(step.content),
|
||||
key: step.id || `thinking-${step.index}`,
|
||||
})
|
||||
} else if (step.type === 'tool_call') {
|
||||
// Normalize: DB-loaded steps use 'id_ref', streaming steps use 'id'
|
||||
const toolId = step.id_ref || step.id
|
||||
items.push({
|
||||
type: 'tool_call',
|
||||
toolName: step.name || '未知工具',
|
||||
arguments: formatJson(step.arguments),
|
||||
summary: truncate(step.arguments),
|
||||
id: step.id,
|
||||
key: `tool_call-${step.id || step.index}`,
|
||||
id: toolId,
|
||||
key: step.id || `tool_call-${toolId || step.index}`,
|
||||
loading: false,
|
||||
result: null,
|
||||
})
|
||||
} else if (step.type === 'tool_result') {
|
||||
// Merge result back into its corresponding tool_call item by matching tool ID
|
||||
const toolId = step.id_ref || step.id
|
||||
const summary = getResultSummary(step.content)
|
||||
const match = items.findLast(it => it.type === 'tool_call' && it.id === step.id)
|
||||
const match = items.findLast(it => it.type === 'tool_call' && it.id === toolId)
|
||||
if (match) {
|
||||
match.result = formatJson(step.content)
|
||||
match.resultSummary = summary.text
|
||||
|
|
@ -145,12 +159,12 @@ const processItems = computed(() => {
|
|||
type: 'text',
|
||||
content: step.content,
|
||||
rendered: renderMarkdown(step.content),
|
||||
key: `text-${step.index}`,
|
||||
key: step.id || `text-${step.index}`,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// 流式中最后一个 tool_call（尚无结果时）标记为 loading
|
||||
// Mark the last tool_call as loading if it has no result yet (still executing)
|
||||
if (props.streaming && items.length > 0) {
|
||||
const last = items[items.length - 1]
|
||||
if (last.type === 'tool_call' && !last.result) {
|
||||
|
|
@ -158,26 +172,18 @@ const processItems = computed(() => {
|
|||
}
|
||||
}
|
||||
|
||||
// 流式中追加正在增长的文本（仅当还没有 text 类型的步骤时）
|
||||
// Append the currently streaming text as a live text item.
|
||||
// This text belongs to the latest LLM iteration that hasn't finished yet.
|
||||
if (props.streaming && props.streamingContent) {
|
||||
const hasTextStep = items.some(it => it.type === 'text')
|
||||
if (!hasTextStep) {
|
||||
items.push({
|
||||
type: 'text',
|
||||
content: props.streamingContent,
|
||||
rendered: renderMarkdown(props.streamingContent) || '<span class="placeholder">...</span>',
|
||||
key: 'text-streaming',
|
||||
})
|
||||
}
|
||||
items.push({
|
||||
type: 'text',
|
||||
content: props.streamingContent,
|
||||
rendered: renderMarkdown(props.streamingContent) || '<span class="placeholder">...</span>',
|
||||
key: 'text-streaming',
|
||||
})
|
||||
}
|
||||
} else {
|
||||
// 回退逻辑：旧版 thinking + toolCalls
|
||||
if (props.thinkingContent) {
|
||||
items.push({ type: 'thinking', content: props.thinkingContent, summary: truncate(props.thinkingContent), key: 'thinking-0' })
|
||||
} else if (props.streaming && items.length === 0) {
|
||||
items.push({ type: 'thinking', content: '', key: 'thinking-loading' })
|
||||
}
|
||||
|
||||
// Fallback: legacy mode for old messages without processSteps stored in DB
|
||||
if (props.toolCalls && props.toolCalls.length > 0) {
|
||||
props.toolCalls.forEach((call, i) => {
|
||||
const toolName = call.function?.name || '未知工具'
|
||||
|
|
@ -197,7 +203,7 @@ const processItems = computed(() => {
|
|||
})
|
||||
}
|
||||
|
||||
// 旧模式下追加流式文本
|
||||
// Append streaming text in legacy mode
|
||||
if (props.streaming && props.streamingContent) {
|
||||
items.push({
|
||||
type: 'text',
|
||||
|
|
@ -211,10 +217,10 @@ const processItems = computed(() => {
|
|||
return items
|
||||
})
|
||||
|
||||
// 增强 processBlock 内代码块
|
||||
// Enhance code blocks inside process items (syntax highlighting, copy buttons)
|
||||
const { debouncedEnhance } = useCodeEnhancement(processRef, processItems, { deep: true })
|
||||
|
||||
// 流式时使用节流的代码块增强，减少 DOM 操作
|
||||
// Throttle code enhancement during streaming to reduce DOM operations
|
||||
watch(() => props.streamingContent?.length, () => {
|
||||
if (props.streaming) debouncedEnhance()
|
||||
})
|
||||
|
|
@ -225,7 +231,7 @@ watch(() => props.streamingContent?.length, () => {
|
|||
width: 100%;
|
||||
}
|
||||
|
||||
/* 流式占位 */
|
||||
/* Streaming placeholder while waiting for first step */
|
||||
.streaming-placeholder {
|
||||
padding: 16px 20px;
|
||||
display: flex;
|
||||
|
|
@ -263,7 +269,7 @@ watch(() => props.streamingContent?.length, () => {
|
|||
50% { opacity: 1; }
|
||||
}
|
||||
|
||||
/* 步骤通用 */
|
||||
/* Step items (shared) */
|
||||
.step-item {
|
||||
margin-bottom: 8px;
|
||||
}
|
||||
|
|
@ -272,7 +278,7 @@ watch(() => props.streamingContent?.length, () => {
|
|||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
/* 思考过程 */
|
||||
/* Thinking and tool call step headers */
|
||||
.thinking .step-header,
|
||||
.tool_call .step-header {
|
||||
display: flex;
|
||||
|
|
@ -361,7 +367,7 @@ watch(() => props.streamingContent?.length, () => {
|
|||
background: var(--bg-hover);
|
||||
}
|
||||
|
||||
/* 步骤展开内容 */
|
||||
/* Expandable step content panel */
|
||||
.step-content {
|
||||
padding: 12px;
|
||||
margin-top: 4px;
|
||||
|
|
@ -404,7 +410,7 @@ watch(() => props.streamingContent?.length, () => {
|
|||
word-break: break-word;
|
||||
}
|
||||
|
||||
/* 文本内容直接渲染 */
|
||||
/* Text content — rendered as markdown */
|
||||
.text-content {
|
||||
padding: 0;
|
||||
font-size: 15px;
|
||||
|
|
@ -418,7 +424,7 @@ watch(() => props.streamingContent?.length, () => {
|
|||
color: var(--text-tertiary);
|
||||
}
|
||||
|
||||
/* 流式指示器 */
|
||||
/* Streaming cursor indicator */
|
||||
.streaming-indicator {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
|
|
|
|||
|
|
@ -35,6 +35,16 @@
|
|||
<path d="M22 19a2 2 0 0 1-2 2H4a2 2 0 0 1-2-2V5a2 2 0 0 1 2-2h5l2 3h9a2 2 0 0 1 2 2z"/>
|
||||
</svg>
|
||||
</button>
|
||||
<button
|
||||
class="btn-group-action btn-delete-project"
|
||||
title="删除项目"
|
||||
@click.stop="$emit('deleteProject', { id: group.id, name: group.name })"
|
||||
>
|
||||
<svg width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
|
||||
<polyline points="3 6 5 6 21 6"></polyline>
|
||||
<path d="M19 6v14a2 2 0 0 1-2 2H7a2 2 0 0 1-2-2V6m3 0V4a2 2 0 0 1 2-2h4a2 2 0 0 1 2 2v2"/>
|
||||
</svg>
|
||||
</button>
|
||||
</div>
|
||||
<div v-show="expandedGroups[group.id]">
|
||||
<div
|
||||
|
|
@ -60,8 +70,8 @@
|
|||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Standalone conversations -->
|
||||
<div v-if="groupedData.standalone.length > 0" class="project-group">
|
||||
<!-- Standalone conversations (always visible) -->
|
||||
<div class="project-group">
|
||||
<div class="project-header" @click="toggleGroup('__standalone__')">
|
||||
<svg class="chevron" :class="{ collapsed: !expandedGroups['__standalone__'] }" width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
|
||||
<polyline points="6 9 12 15 18 9"/>
|
||||
|
|
@ -131,12 +141,13 @@ import { formatTime } from '../utils/format'
|
|||
|
||||
const props = defineProps({
|
||||
conversations: { type: Array, required: true },
|
||||
projects: { type: Array, default: () => [] },
|
||||
currentId: { type: String, default: null },
|
||||
loading: { type: Boolean, default: false },
|
||||
hasMore: { type: Boolean, default: false },
|
||||
})
|
||||
|
||||
const emit = defineEmits(['select', 'delete', 'loadMore', 'createProject', 'browseProject', 'createInProject', 'toggleSettings', 'toggleStats'])
|
||||
const emit = defineEmits(['select', 'delete', 'loadMore', 'createProject', 'browseProject', 'createInProject', 'toggleSettings', 'toggleStats', 'deleteProject'])
|
||||
|
||||
const expandedGroups = reactive({})
|
||||
|
||||
|
|
@ -144,6 +155,16 @@ const groupedData = computed(() => {
|
|||
const groups = {}
|
||||
const standalone = []
|
||||
|
||||
// First, initialize groups from projects list (includes projects with 0 conversations)
|
||||
for (const p of props.projects) {
|
||||
groups[p.id] = {
|
||||
id: p.id,
|
||||
name: p.name,
|
||||
conversations: [],
|
||||
}
|
||||
}
|
||||
|
||||
// Then merge conversations into groups
|
||||
for (const conv of props.conversations) {
|
||||
if (conv.project_id) {
|
||||
if (!groups[conv.project_id]) {
|
||||
|
|
@ -162,7 +183,7 @@ const groupedData = computed(() => {
|
|||
for (const id of Object.keys(groups)) {
|
||||
if (!(id in expandedGroups)) expandedGroups[id] = true
|
||||
}
|
||||
if (standalone.length > 0 && !('__standalone__' in expandedGroups)) {
|
||||
if (!('__standalone__' in expandedGroups)) {
|
||||
expandedGroups['__standalone__'] = true
|
||||
}
|
||||
|
||||
|
|
@ -320,6 +341,11 @@ function onScroll(e) {
|
|||
opacity: 1;
|
||||
}
|
||||
|
||||
.btn-delete-project:hover {
|
||||
color: var(--danger-color);
|
||||
background: var(--danger-bg);
|
||||
}
|
||||
|
||||
.conversation-item {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
|
|
|
|||
Loading…
Reference in New Issue