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2 Commits
4de03866f4
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dc08267c15
| Author | SHA1 | Date |
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dc08267c15 | |
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f10909bec3 |
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@ -45,6 +45,157 @@ def get_llm_client(conversation: Conversation = None):
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return client, max_tokens
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class StreamContext:
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"""Context for streaming response state management."""
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def __init__(
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self,
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step_index: int = 0,
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current_step_id: str = None,
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current_step_idx: int = None,
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current_stream_type: str = None,
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full_content: str = "",
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full_thinking: str = ""
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):
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self.step_index = step_index
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self.current_step_id = current_step_id
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self.current_step_idx = current_step_idx
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self.current_stream_type = current_stream_type
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self.full_content = full_content
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self.full_thinking = full_thinking
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self.all_steps = []
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self.all_tool_calls = []
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self.all_tool_results = []
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self.tool_calls_list = []
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def reset_iteration(self):
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"""Reset streaming step tracker for new iteration."""
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self.current_step_id = None
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self.current_step_idx = None
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self.current_stream_type = None
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self.full_content = ""
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self.full_thinking = ""
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self.tool_calls_list = []
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def start_stream_step(self, step_type: str) -> str:
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"""Start a new streaming step. Returns the step_id."""
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self.current_step_idx = self.step_index
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self.current_step_id = f"step-{self.step_index}"
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self.current_stream_type = step_type
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self.step_index += 1
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return self.current_step_id
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def yield_stream_step(self, step_type: str, content: str) -> Dict[str, Any]:
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"""Yield a streaming step event."""
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return _sse_event("process_step", {
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"step": {
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"id": self.current_step_id,
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"index": self.current_step_idx,
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"type": step_type,
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"content": content
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}
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})
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def save_streaming_step(self):
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"""Save the current streaming step to all_steps."""
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if self.current_step_id is None:
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return
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if self.current_stream_type == "thinking":
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self.all_steps.append({
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"id": self.current_step_id,
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"index": self.current_step_idx,
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"type": "thinking",
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"content": self.full_thinking
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})
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elif self.current_stream_type == "text":
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self.all_steps.append({
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"id": self.current_step_id,
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"index": self.current_step_idx,
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"type": "text",
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"content": self.full_content
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})
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def handle_thinking_stream(self, delta: Dict) -> Optional[Dict]:
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"""Handle reasoning/thinking delta. Returns yield_obj if step was yielded."""
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reasoning = delta.get("reasoning_content", "")
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if not reasoning:
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return None
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prev_len = len(self.full_thinking)
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self.full_thinking += reasoning
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if prev_len == 0: # New thinking stream started
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self.start_stream_step("thinking")
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return self.yield_stream_step("thinking", self.full_thinking)
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def handle_text_stream(self, delta: Dict) -> Optional[Dict]:
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"""Handle content delta. Returns yield_obj if step was yielded."""
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content = delta.get("content", "")
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if not content:
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return None
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prev_len = len(self.full_content)
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self.full_content += content
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if prev_len == 0: # New text stream started
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self.start_stream_step("text")
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return self.yield_stream_step("text", self.full_content)
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def handle_tool_call(self) -> tuple:
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"""Handle tool calls. Returns (tool_call_step_ids, tool_call_steps, yield_objs)."""
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tool_call_step_ids = []
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tool_call_steps = []
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yield_objs = []
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for tc in self.tool_calls_list:
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call_step_idx = self.step_index
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call_step_id = f"step-{self.step_index}"
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tool_call_step_ids.append(call_step_id)
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self.step_index += 1
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call_step = {
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"id": call_step_id,
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"index": call_step_idx,
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"type": "tool_call",
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"id_ref": tc.get("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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tool_call_steps.append(call_step)
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yield_objs.append(_sse_event("process_step", {"step": call_step}))
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return tool_call_step_ids, tool_call_steps, yield_objs
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def handle_tool_result(self, tool_result: Dict, tool_call_step_id: str) -> tuple:
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"""Handle single tool result. Returns (result_step, yield_obj)."""
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result_step_idx = self.step_index
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result_step_id = f"step-{self.step_index}"
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self.step_index += 1
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content = tool_result.get("content", "")
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success = True
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try:
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content_obj = json.loads(content)
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if isinstance(content_obj, dict):
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success = content_obj.get("success", True)
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except:
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pass
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result_step = {
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"id": result_step_id,
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"index": result_step_idx,
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"type": "tool_result",
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"id_ref": tool_call_step_id,
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"name": tool_result.get("name", ""),
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"content": content,
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"success": success
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}
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return result_step, _sse_event("process_step", {"step": result_step})
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class ChatService:
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"""Chat service with tool support"""
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@ -129,12 +280,6 @@ class ChatService:
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# 直接使用 provider 的 max_tokens
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max_tokens = provider_max_tokens
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# State tracking
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all_steps = []
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all_tool_calls = []
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all_tool_results = []
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step_index = 0
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# Token usage tracking
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total_usage = {
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"prompt_tokens": 0,
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@ -142,23 +287,12 @@ class ChatService:
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"total_tokens": 0
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}
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# Global step IDs for thinking and text (persist across iterations)
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thinking_step_id = None
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thinking_step_idx = None
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text_step_id = None
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text_step_idx = None
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# Streaming context for state management
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ctx = StreamContext()
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for iteration in range(MAX_ITERATIONS):
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# Stream from LLM
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full_content = ""
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full_thinking = ""
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tool_calls_list = []
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# Step tracking - use unified step-{index} format
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thinking_step_id = None
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thinking_step_idx = None
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text_step_id = None
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text_step_idx = None
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# Reset streaming context for this iteration
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ctx.reset_iteration()
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async for sse_line in llm.stream_call(
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model=model,
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@ -218,19 +352,16 @@ class ChatService:
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if chunk.get("content") or chunk.get("message"):
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content = chunk.get("content") or chunk.get("message", {}).get("content", "")
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if content:
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# BUG FIX: Update full_content so it gets saved to database
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prev_content_len = len(full_content)
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full_content += content
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if prev_content_len == 0: # New text stream started
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text_step_idx = step_index
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text_step_id = f"step-{step_index}"
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step_index += 1
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prev_len = len(ctx.full_content)
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ctx.full_content += content
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if prev_len == 0: # New text stream started
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ctx.start_stream_step("text")
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yield _sse_event("process_step", {
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"step": {
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"id": text_step_id if prev_content_len == 0 else f"step-{step_index - 1}",
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"index": text_step_idx if prev_content_len == 0 else step_index - 1,
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"id": ctx.current_step_id if prev_len == 0 else f"step-{ctx.step_index - 1}",
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"index": ctx.current_step_idx if prev_len == 0 else ctx.step_index - 1,
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"type": "text",
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"content": full_content # Always send accumulated content
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"content": ctx.full_content
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}
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})
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continue
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@ -238,96 +369,43 @@ class ChatService:
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delta = choices[0].get("delta", {})
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# Handle reasoning (thinking)
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reasoning = delta.get("reasoning_content", "")
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if reasoning:
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prev_thinking_len = len(full_thinking)
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full_thinking += reasoning
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if prev_thinking_len == 0: # New thinking stream started
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thinking_step_idx = step_index
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thinking_step_id = f"step-{step_index}"
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step_index += 1
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yield _sse_event("process_step", {
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"step": {
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"id": thinking_step_id,
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"index": thinking_step_idx,
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"type": "thinking",
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"content": full_thinking
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}
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})
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yield_obj = ctx.handle_thinking_stream(delta)
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if yield_obj:
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yield yield_obj
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# Handle content
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content = delta.get("content", "")
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if content:
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prev_content_len = len(full_content)
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full_content += content
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if prev_content_len == 0: # New text stream started
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text_step_idx = step_index
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text_step_id = f"step-{step_index}"
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step_index += 1
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yield _sse_event("process_step", {
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"step": {
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"id": text_step_id,
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"index": text_step_idx,
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"type": "text",
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"content": full_content
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}
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})
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yield_obj = ctx.handle_text_stream(delta)
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if yield_obj:
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yield yield_obj
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# Accumulate tool calls
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tool_calls_delta = delta.get("tool_calls", [])
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for tc in tool_calls_delta:
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idx = tc.get("index", 0)
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if idx >= len(tool_calls_list):
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tool_calls_list.append({
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if idx >= len(ctx.tool_calls_list):
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ctx.tool_calls_list.append({
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"id": tc.get("id", ""),
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"type": "function",
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"function": {"name": "", "arguments": ""}
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})
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func = tc.get("function", {})
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if func.get("name"):
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tool_calls_list[idx]["function"]["name"] += func["name"]
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ctx.tool_calls_list[idx]["function"]["name"] += func["name"]
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if func.get("arguments"):
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tool_calls_list[idx]["function"]["arguments"] += func["arguments"]
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ctx.tool_calls_list[idx]["function"]["arguments"] += func["arguments"]
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# Save thinking step
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if thinking_step_id is not None:
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all_steps.append({
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"id": thinking_step_id,
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"index": thinking_step_idx,
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"type": "thinking",
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"content": full_thinking
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})
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# Save text step
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if text_step_id is not None:
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all_steps.append({
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"id": text_step_id,
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"index": text_step_idx,
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"type": "text",
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"content": full_content
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})
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# Save streaming step (thinking or text)
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ctx.save_streaming_step()
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# Handle tool calls
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if tool_calls_list:
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all_tool_calls.extend(tool_calls_list)
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if ctx.tool_calls_list:
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ctx.all_tool_calls.extend(ctx.tool_calls_list)
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# Yield tool_call steps - use unified step-{index} format
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tool_call_step_ids = [] # Track step IDs for tool calls
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for tc in tool_calls_list:
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call_step_idx = step_index
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call_step_id = f"step-{step_index}"
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tool_call_step_ids.append(call_step_id)
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step_index += 1
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call_step = {
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"id": call_step_id,
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"index": call_step_idx,
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"type": "tool_call",
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"id_ref": tc.get("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 _sse_event("process_step", {"step": call_step})
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# Handle tool_call steps
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tool_call_step_ids, tool_call_steps, yield_objs = ctx.handle_tool_call()
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ctx.all_steps.extend(tool_call_steps)
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for yield_obj in yield_objs:
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yield yield_obj
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# Execute tools
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tool_context = {
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@ -337,39 +415,17 @@ class ChatService:
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"user_permission_level": user_permission_level
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}
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tool_results = self.tool_executor.process_tool_calls_parallel(
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tool_calls_list, tool_context
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ctx.tool_calls_list, tool_context
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)
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# Yield tool_result steps - use unified step-{index} format
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# Handle tool_result steps
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for i, tr in enumerate(tool_results):
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tool_call_step_id = tool_call_step_ids[i] if i < len(tool_call_step_ids) else f"step-{i}"
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result_step_idx = step_index
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result_step_id = f"step-{step_index}"
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step_index += 1
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result_step, yield_obj = ctx.handle_tool_result(tr, tool_call_step_id)
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ctx.all_steps.append(result_step)
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yield yield_obj
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# 解析 content 中的 success 状态
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content = tr.get("content", "")
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success = True
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try:
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content_obj = json.loads(content)
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if isinstance(content_obj, dict):
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success = content_obj.get("success", True)
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except:
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pass
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result_step = {
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"id": result_step_id,
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"index": result_step_idx,
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"type": "tool_result",
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"id_ref": tool_call_step_id, # Reference to the tool_call step
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"name": tr.get("name", ""),
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"content": content,
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"success": success
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}
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all_steps.append(result_step)
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yield _sse_event("process_step", {"step": result_step})
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all_tool_results.append({
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ctx.all_tool_results.append({
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"role": "tool",
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"tool_call_id": tr.get("tool_call_id", ""),
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"content": tr.get("content", "")
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@ -378,27 +434,27 @@ class ChatService:
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# Add assistant message with tool calls for next iteration
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messages.append({
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"role": "assistant",
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"content": full_content or "",
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"tool_calls": tool_calls_list
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"content": ctx.full_content or "",
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"tool_calls": ctx.tool_calls_list
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})
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messages.extend(all_tool_results[-len(tool_results):])
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all_tool_results = []
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messages.extend(ctx.all_tool_results[-len(tool_results):])
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ctx.all_tool_results = []
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continue
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# No tool calls - final iteration, save message
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msg_id = str(uuid.uuid4())
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# 使用 API 返回的真实 completion_tokens,如果 API 没返回则降级使用估算值
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actual_token_count = total_usage.get("completion_tokens", 0) or len(full_content) // 4
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actual_token_count = total_usage.get("completion_tokens", 0) or len(ctx.full_content) // 4
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logger.info(f"[TOKEN] total_usage: {total_usage}, actual_token_count: {actual_token_count}")
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self._save_message(
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conversation.id,
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msg_id,
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full_content,
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all_tool_calls,
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all_tool_results,
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all_steps,
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ctx.full_content,
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ctx.all_tool_calls,
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ctx.all_tool_results,
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ctx.all_steps,
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actual_token_count,
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total_usage
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)
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@ -411,15 +467,15 @@ class ChatService:
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return
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# Max iterations exceeded - save message before error
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if full_content or all_tool_calls:
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if ctx.full_content or ctx.all_tool_calls:
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msg_id = str(uuid.uuid4())
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self._save_message(
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conversation.id,
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msg_id,
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full_content,
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all_tool_calls,
|
||||
all_tool_results,
|
||||
all_steps,
|
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ctx.full_content,
|
||||
ctx.all_tool_calls,
|
||||
ctx.all_tool_results,
|
||||
ctx.all_steps,
|
||||
actual_token_count,
|
||||
total_usage
|
||||
)
|
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|
|
|
|||
|
|
@ -0,0 +1,288 @@
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"""Task module for autonomous task execution"""
|
||||
from dataclasses import dataclass, field
|
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from datetime import datetime
|
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from enum import Enum
|
||||
import logging
|
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from typing import List, Optional, Dict, Any
|
||||
from luxx.utils.helpers import generate_id
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class TaskStatus(Enum):
|
||||
"""Task status enum"""
|
||||
PENDING = "pending"
|
||||
READY = "ready"
|
||||
RUNNING = "running"
|
||||
BLOCK = "block"
|
||||
TERMINATED = "terminated"
|
||||
|
||||
|
||||
class StepStatus(Enum):
|
||||
"""Step status enum"""
|
||||
PENDING = "pending"
|
||||
RUNNING = "running"
|
||||
COMPLETED = "completed"
|
||||
FAILED = "failed"
|
||||
SKIPPED = "skipped"
|
||||
|
||||
|
||||
@dataclass
|
||||
class Step:
|
||||
"""Task step"""
|
||||
id: str
|
||||
name: str
|
||||
description: str = ""
|
||||
depends_on: List[str] = field(default_factory=list)
|
||||
status: StepStatus = StepStatus.PENDING
|
||||
result: Optional[Dict[str, Any]] = None
|
||||
created_at: datetime = field(default_factory=datetime.now)
|
||||
updated_at: datetime = field(default_factory=datetime.now)
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary"""
|
||||
return {
|
||||
"id": self.id,
|
||||
"name": self.name,
|
||||
"description": self.description,
|
||||
"depends_on": self.depends_on,
|
||||
"status": self.status.value,
|
||||
"result": self.result,
|
||||
"created_at": self.created_at.isoformat() if self.created_at else None,
|
||||
"updated_at": self.updated_at.isoformat() if self.updated_at else None
|
||||
}
|
||||
|
||||
|
||||
@dataclass
|
||||
class Task:
|
||||
"""Task entity"""
|
||||
id: str
|
||||
name: str
|
||||
description: str = ""
|
||||
goal: str = ""
|
||||
status: TaskStatus = TaskStatus.PENDING
|
||||
steps: List[Step] = field(default_factory=list)
|
||||
subtasks: List["Task"] = field(default_factory=list)
|
||||
result: Optional[Dict[str, Any]] = None
|
||||
created_at: datetime = field(default_factory=datetime.now)
|
||||
updated_at: datetime = field(default_factory=datetime.now)
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary"""
|
||||
return {
|
||||
"id": self.id,
|
||||
"name": self.name,
|
||||
"description": self.description,
|
||||
"goal": self.goal,
|
||||
"status": self.status.value,
|
||||
"steps": [s.to_dict() for s in self.steps],
|
||||
"subtasks": [t.to_dict() for t in self.subtasks],
|
||||
"result": self.result,
|
||||
"created_at": self.created_at.isoformat() if self.created_at else None,
|
||||
"updated_at": self.updated_at.isoformat() if self.updated_at else None
|
||||
}
|
||||
|
||||
|
||||
class TaskGraph:
|
||||
"""Task graph for managing step dependencies"""
|
||||
|
||||
def __init__(self, task: Task):
|
||||
self.task = task
|
||||
self._adjacency: Dict[str, List[str]] = {}
|
||||
self._reverse_adjacency: Dict[str, List[str]] = {}
|
||||
self._in_degree: Dict[str, int] = {}
|
||||
self._build_graph()
|
||||
|
||||
def _build_graph(self) -> None:
|
||||
"""Build graph from task steps"""
|
||||
for step in self.task.steps:
|
||||
self._adjacency[step.id] = []
|
||||
self._reverse_adjacency[step.id] = []
|
||||
self._in_degree[step.id] = 0
|
||||
|
||||
for step in self.task.steps:
|
||||
for dep_id in step.depends_on:
|
||||
if dep_id in self._adjacency:
|
||||
self._adjacency[dep_id].append(step.id)
|
||||
self._reverse_adjacency[step.id].append(dep_id)
|
||||
self._in_degree[step.id] += 1
|
||||
|
||||
def topological_sort(self) -> List[Step]:
|
||||
"""Get steps in topological order"""
|
||||
in_degree = self._in_degree.copy()
|
||||
queue = [step_id for step_id, degree in in_degree.items() if degree == 0]
|
||||
result = []
|
||||
step_map = {step.id: step for step in self.task.steps}
|
||||
|
||||
while queue:
|
||||
queue.sort()
|
||||
current = queue.pop(0)
|
||||
result.append(step_map[current])
|
||||
|
||||
for dependent_id in self._adjacency[current]:
|
||||
in_degree[dependent_id] -= 1
|
||||
if in_degree[dependent_id] == 0:
|
||||
queue.append(dependent_id)
|
||||
|
||||
return result
|
||||
|
||||
def get_ready_steps(self, completed_step_ids: List[str]) -> List[Step]:
|
||||
"""Get steps that are ready to execute"""
|
||||
step_map = {step.id: step for step in self.task.steps}
|
||||
ready = []
|
||||
|
||||
for step in self.task.steps:
|
||||
if step.id in completed_step_ids:
|
||||
continue
|
||||
if step.status != StepStatus.PENDING:
|
||||
continue
|
||||
deps_completed = all(dep_id in completed_step_ids for dep_id in step.depends_on)
|
||||
if deps_completed:
|
||||
ready.append(step)
|
||||
|
||||
return ready
|
||||
|
||||
def detect_cycles(self) -> List[List[str]]:
|
||||
"""Detect cycles in the graph"""
|
||||
WHITE, GRAY, BLACK = 0, 1, 2
|
||||
color = {step.id: WHITE for step in self.task.steps}
|
||||
cycles = []
|
||||
|
||||
def dfs(node: str, path: List[str]) -> bool:
|
||||
color[node] = GRAY
|
||||
path.append(node)
|
||||
|
||||
for neighbor in self._adjacency.get(node, []):
|
||||
if color[neighbor] == GRAY:
|
||||
cycle_start = path.index(neighbor)
|
||||
cycles.append(path[cycle_start:] + [neighbor])
|
||||
return True
|
||||
elif color[neighbor] == WHITE:
|
||||
if dfs(neighbor, path):
|
||||
return True
|
||||
|
||||
path.pop()
|
||||
color[node] = BLACK
|
||||
return False
|
||||
|
||||
for step in self.task.steps:
|
||||
if color[step.id] == WHITE:
|
||||
dfs(step.id, [])
|
||||
|
||||
return cycles
|
||||
|
||||
def validate(self) -> tuple[bool, Optional[str]]:
|
||||
"""Validate the graph structure"""
|
||||
cycles = self.detect_cycles()
|
||||
if cycles:
|
||||
return False, f"Circular dependency detected: {cycles[0]}"
|
||||
|
||||
step_ids = {step.id for step in self.task.steps}
|
||||
for step in self.task.steps:
|
||||
for dep_id in step.depends_on:
|
||||
if dep_id not in step_ids:
|
||||
return False, f"Step '{step.name}' depends on non-existent step '{dep_id}'"
|
||||
|
||||
return True, None
|
||||
|
||||
|
||||
class TaskService:
|
||||
"""Task service for managing tasks"""
|
||||
|
||||
def __init__(self):
|
||||
self._tasks: Dict[str, Task] = {}
|
||||
|
||||
def create_task(
|
||||
self,
|
||||
name: str,
|
||||
goal: str,
|
||||
description: str = "",
|
||||
steps: List[Dict[str, Any]] = None
|
||||
) -> Task:
|
||||
"""Create a new task"""
|
||||
task_id = generate_id("task")
|
||||
task = Task(
|
||||
id=task_id,
|
||||
name=name,
|
||||
description=description,
|
||||
goal=goal
|
||||
)
|
||||
|
||||
if steps:
|
||||
for step_data in steps:
|
||||
step = Step(
|
||||
id=generate_id("step"),
|
||||
name=step_data.get("name", ""),
|
||||
description=step_data.get("description", "")
|
||||
)
|
||||
task.steps.append(step)
|
||||
|
||||
self._tasks[task_id] = task
|
||||
logger.info(f"Created task: {task_id}")
|
||||
return task
|
||||
|
||||
def get_task(self, task_id: str) -> Optional[Task]:
|
||||
"""Get task by ID"""
|
||||
return self._tasks.get(task_id)
|
||||
|
||||
def list_tasks(self) -> List[Task]:
|
||||
"""List all tasks"""
|
||||
return list(self._tasks.values())
|
||||
|
||||
def update_task_status(
|
||||
self,
|
||||
task_id: str,
|
||||
status: TaskStatus,
|
||||
result: Any = None
|
||||
) -> Optional[Task]:
|
||||
"""Update task status"""
|
||||
task = self._tasks.get(task_id)
|
||||
if not task:
|
||||
return None
|
||||
|
||||
task.status = status
|
||||
task.result = result
|
||||
task.updated_at = datetime.now()
|
||||
return task
|
||||
|
||||
def add_steps(
|
||||
self,
|
||||
task_id: str,
|
||||
steps: List[Dict[str, Any]]
|
||||
) -> Optional[List[Step]]:
|
||||
"""Add steps to task"""
|
||||
task = self._tasks.get(task_id)
|
||||
if not task:
|
||||
return None
|
||||
|
||||
result = []
|
||||
for step_data in steps:
|
||||
step = Step(
|
||||
id=generate_id("step"),
|
||||
name=step_data.get("name", ""),
|
||||
description=step_data.get("description", ""),
|
||||
depends_on=step_data.get("depends_on", [])
|
||||
)
|
||||
task.steps.append(step)
|
||||
result.append(step)
|
||||
|
||||
task.updated_at = datetime.now()
|
||||
return result
|
||||
|
||||
def delete_task(self, task_id: str) -> bool:
|
||||
"""Delete task"""
|
||||
if task_id not in self._tasks:
|
||||
return False
|
||||
|
||||
del self._tasks[task_id]
|
||||
return True
|
||||
|
||||
def build_graph(self, task_id: str) -> Optional[TaskGraph]:
|
||||
"""Build task graph for a task"""
|
||||
task = self._tasks.get(task_id)
|
||||
if not task:
|
||||
return None
|
||||
return TaskGraph(task)
|
||||
|
||||
|
||||
task_service = TaskService()
|
||||
Loading…
Reference in New Issue