From 499f0119bb9f5dee0c330fb08e5d4ea0768a74c0 Mon Sep 17 00:00:00 2001 From: Liang Jiaqing Date: Mon, 13 Apr 2026 20:20:31 +0800 Subject: [PATCH] refactor llm session params and thinking parsing --- agentmain.py | 6 +---- llmcore.py | 76 +++++++++++++++++++--------------------------------- 2 files changed, 29 insertions(+), 53 deletions(-) diff --git a/agentmain.py b/agentmain.py index f682c51..2f6191e 100644 --- a/agentmain.py +++ b/agentmain.py @@ -5,7 +5,7 @@ if sys.stderr is None: sys.stderr = open(os.devnull, "w") elif hasattr(sys.stderr, 'reconfigure'): sys.stderr.reconfigure(errors='replace') sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) -from llmcore import SiderLLMSession, LLMSession, ToolClient, ClaudeSession, MixinSession, NativeToolClient, NativeClaudeSession, build_multimodal_content, NativeOAISession +from llmcore import SiderLLMSession, LLMSession, ToolClient, ClaudeSession, MixinSession, NativeToolClient, NativeClaudeSession, NativeOAISession from agent_loop import agent_runner_loop from ga import GenericAgentHandler, smart_format, get_global_memory, format_error, consume_file @@ -115,10 +115,6 @@ class GeneraticAgent: if source == 'feishu' and len(self.history) > 1: # 如果有历史记录且来自飞书，注入到首轮 user_input 中（支持/restore恢复上下文） user_input = handler._get_anchor_prompt() + f"\n\n### 用户当前消息\n{raw_query}" initial_user_content = None - if images and isinstance(self.llmclient.backend, LLMSession): - initial_user_content = build_multimodal_content(user_input, images) - elif images: - print(f"[INFO] backend {type(self.llmclient.backend).__name__} does not support direct multimodal input, fallback to text attachment hints.") # although new handler, the **full** history is in llmclient, so it is full history! gen = agent_runner_loop(self.llmclient, sys_prompt, user_input, handler, TOOLS_SCHEMA, max_turns=40, verbose=self.verbose, diff --git a/llmcore.py b/llmcore.py index 4236a2f..e89f821 100644 --- a/llmcore.py +++ b/llmcore.py @@ -90,25 +90,6 @@ def auto_make_url(base, path): if b.endswith(p): return b return f"{b}/{p}" if re.search(r'/v\d+(/|$)', b) else f"{b}/v1/{p}" -def build_multimodal_content(prompt_text, image_paths): - parts = [] - text = prompt_text if isinstance(prompt_text, str) else str(prompt_text or "") - if text.strip(): - parts.append({"type": "text", "text": text}) - else: - parts.append({"type": "text", "text": "请查看图片并理解用户意图。"}) - for path in image_paths or []: - if not path or not os.path.isfile(path): continue - try: - mime = mimetypes.guess_type(path)[0] or "image/png" - if not mime.startswith("image/"): mime = "image/png" - with open(path, "rb") as f: - data_url = f"data:{mime};base64,{base64.b64encode(f.read()).decode('ascii')}" - parts.append({"type": "image_url", "image_url": {"url": data_url}}) - except Exception as e: - print(f"[WARN] encode image failed {path}: {e}") - return parts - class SiderLLMSession: def __init__(self, cfg): from sider_ai_api import Session # 不使用sider的话没必要安装这个包 @@ -145,6 +126,7 @@ def _parse_claude_sse(resp_lines): elif evt_type == "content_block_start": block = evt.get("content_block", {}) if block.get("type") == "text": current_block = {"type": "text", "text": ""} + elif block.get("type") == "thinking": current_block = {"type": "thinking", "thinking": ""} elif block.get("type") == "tool_use": current_block = {"type": "tool_use", "id": block.get("id", ""), "name": block.get("name", ""), "input": {}} tool_json_buf = "" @@ -154,6 +136,8 @@ def _parse_claude_sse(resp_lines): text = delta.get("text", "") if current_block and current_block.get("type") == "text": current_block["text"] += text if text: yield text + elif delta.get("type") == "thinking_delta": + if current_block and current_block.get("type") == "thinking": current_block["thinking"] += delta.get("thinking", "") elif delta.get("type") == "input_json_delta": tool_json_buf += delta.get("partial_json", "") elif evt_type == "content_block_stop": if current_block: @@ -458,7 +442,8 @@ class BaseSession: if effort and not self.reasoning_effort: print(f"[WARN] Invalid reasoning_effort {effort!r}, ignored.") mode = str(cfg.get('api_mode', 'chat_completions')).strip().lower().replace('-', '_') self.api_mode = 'responses' if mode in ('responses', 'response') else 'chat_completions' - self.temperature = cfg.get('temperature') + self.temperature = cfg.get('temperature', 1.0) + self.max_tokens = cfg.get('max_tokens', 8192) def ask(self, prompt, stream=False): def _ask_gen(): content = '' @@ -480,13 +465,11 @@ class BaseSession: return _ask_gen() if stream else ''.join(list(_ask_gen())) class ClaudeSession(BaseSession): - def raw_ask(self, messages, temperature=0.5, max_tokens=6144): + def raw_ask(self, messages): model = self.default_model - ml = model.lower() - if 'kimi' in ml or 'moonshot' in ml: temperature = 1.0 # kimi/moonshot only accepts temp 1.0 - elif 'minimax' in ml: temperature = max(0.01, min(temperature, 1.0)) # MiniMax requires temp in (0, 1] headers = {"x-api-key": self.api_key, "Content-Type": "application/json", "anthropic-version": "2023-06-01", "anthropic-beta": "prompt-caching-2024-07-31"} - payload = {"model": model, "messages": messages, "temperature": temperature, "max_tokens": max_tokens, "stream": True} + payload = {"model": model, "messages": messages, "temperature": self.temperature, "max_tokens": self.max_tokens, "stream": True} + if self.reasoning_effort: payload["reasoning_effort"] = self.reasoning_effort if self.system: payload["system"] = [{"type": "text", "text": self.system, "cache_control": {"type": "persistent"}}] try: with requests.post(auto_make_url(self.api_base, "messages"), headers=headers, json=payload, stream=True, timeout=(self.connect_timeout, self.read_timeout)) as r: @@ -503,11 +486,11 @@ class ClaudeSession(BaseSession): return msgs class LLMSession(BaseSession): - def raw_ask(self, messages, temperature=0.5): + def raw_ask(self, messages): return (yield from _openai_stream(self.api_base, self.api_key, messages, self.default_model, self.api_mode, - temperature=temperature, reasoning_effort=self.reasoning_effort, - max_retries=self.max_retries, connect_timeout=self.connect_timeout, - read_timeout=self.read_timeout, proxies=self.proxies)) + temperature=self.temperature, reasoning_effort=self.reasoning_effort, + max_tokens=self.max_tokens, max_retries=self.max_retries, + connect_timeout=self.connect_timeout, read_timeout=self.read_timeout, proxies=self.proxies)) def make_messages(self, raw_list): return _msgs_claude2oai(raw_list) def _fix_messages(messages): @@ -536,10 +519,9 @@ class NativeClaudeSession(BaseSession): self._account_uuid = str(uuid.uuid4()) self._device_id = uuid.uuid4().hex + uuid.uuid4().hex[:32] self.tools = None - def raw_ask(self, messages, temperature=0.5, max_tokens=6144): + def raw_ask(self, messages): messages = _fix_messages(messages) model = self.default_model - if self.temperature is not None: temperature = self.temperature beta_parts = ["claude-code-20250219", "interleaved-thinking-2025-05-14", "redact-thinking-2026-02-12", "prompt-caching-scope-2026-01-05"] if "[1m]" in model.lower(): beta_parts.insert(1, "context-1m-2025-08-07"); model = model.replace("[1m]", "").replace("[1M]", "") @@ -548,7 +530,8 @@ class NativeClaudeSession(BaseSession): "user-agent": "claude-cli/2.1.90 (external, cli)", "x-app": "cli"} if self.api_key.startswith("sk-ant-"): headers["x-api-key"] = self.api_key else: headers["authorization"] = f"Bearer {self.api_key}" - payload = {"model": model, "messages": messages, "temperature": temperature, "max_tokens": max_tokens, "stream": True} + payload = {"model": model, "messages": messages, "temperature": self.temperature, "max_tokens": self.max_tokens, "stream": True} + if self.reasoning_effort: payload["reasoning_effort"] = self.reasoning_effort payload["metadata"] = {"user_id": json.dumps({"device_id": self._device_id, "account_uuid": self._account_uuid, "session_id": self._session_id}, separators=(',', ':'))} if self.tools: claude_tools = openai_tools_to_claude(self.tools) @@ -588,21 +571,24 @@ class NativeClaudeSession(BaseSession): content = "\n".join(text_parts).strip() tool_calls = [MockToolCall(b["name"], b.get("input", {}), id=b.get("id", "")) for b in content_blocks if b.get("type") == "tool_use"] if not tool_calls: tool_calls, content = _parse_text_tool_calls(content) - think_pattern = r"(.*?)"; thinking = '' - think_match = re.search(think_pattern, content, re.DOTALL) - if think_match: - thinking = think_match.group(1).strip() - content = re.sub(think_pattern, "", content, flags=re.DOTALL) + thinking_parts = [b["thinking"] for b in content_blocks if b.get("type") == "thinking"] + thinking = "\n".join(thinking_parts).strip() + if not thinking: + think_pattern = r"(.*?)" + think_match = re.search(think_pattern, content, re.DOTALL) + if think_match: + thinking = think_match.group(1).strip() + content = re.sub(think_pattern, "", content, flags=re.DOTALL) return MockResponse(thinking, content, tool_calls, str(content_blocks)) class NativeOAISession(NativeClaudeSession): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) - def raw_ask(self, messages, temperature=0.5, max_tokens=6144, **kw): + def raw_ask(self, messages): """OpenAI streaming. yields text chunks, generator return = list[content_block]""" msgs = ([{"role": "system", "content": self.system}] if self.system else []) + _msgs_claude2oai(messages) return (yield from _openai_stream(self.api_base, self.api_key, msgs, self.default_model, self.api_mode, - temperature=temperature, max_tokens=max_tokens, + temperature=self.temperature, max_tokens=self.max_tokens, tools=self.tools, reasoning_effort=self.reasoning_effort, max_retries=self.max_retries, connect_timeout=self.connect_timeout, read_timeout=self.read_timeout, proxies=self.proxies)) @@ -819,8 +805,9 @@ class MixinSession: self.default_model = getattr(self._sessions[0], 'default_model', None) self._cur_idx, self._switched_at = 0, 0.0 def __getattr__(self, name): return getattr(self._sessions[0], name) + _BROADCAST_ATTRS = frozenset({'system', 'tools', 'temperature', 'max_tokens', 'reasoning_effort'}) def __setattr__(self, name, value): - if name in ('system', 'tools'): + if name in self._BROADCAST_ATTRS: for s in self._sessions: v = openai_tools_to_claude(value) if name == 'tools' and type(s) is NativeClaudeSession else value setattr(s, name, v) @@ -901,13 +888,6 @@ class NativeToolClient: while True: chunk = next(gen); yield chunk except StopIteration as e: resp = e.value - if resp: - _write_llm_log('Response', resp.raw) - text = resp.content - think_match = re.search(r'(.*?)', text, re.DOTALL) - if think_match: - resp.thinking = think_match.group(1).strip() - text = re.sub(r'.*?', '', text, flags=re.DOTALL) - resp.content = text.strip() + if resp: _write_llm_log('Response', resp.raw) if resp and hasattr(resp, 'tool_calls') and resp.tool_calls: self._pending_tool_ids = [tc.id for tc in resp.tool_calls] return resp \ No newline at end of file