update llm

requirements.txt

@@ -6,7 +6,6 @@ PyYAML>=6.0
 # LLM integration
 litellm>=1.0.0
 omegaconf>=2.3.0
-langchain>=0.1.0
 json5>=0.9.0
 
 # Development and testing (optional)

src/utils/llm.py

@@ -1,5 +1,4 @@
 from litellm import completion
-from langchain.prompts import PromptTemplate
 from pathlib import Path
 import asyncio
 import re
@@ -14,14 +13,13 @@ def get_prompt(template: str, infos: dict) -> str:
     """
     根据模板，获取提示词
     """
-    prompt_template = PromptTemplate(template=template)
     # 将 dict/list 等结构化对象转为 JSON 字符串
     # 策略：
     # - avatar_infos: 不包装 intent（模板里已经说明是 dict[Name, info]）
     # - general_action_infos: 强制包装 intent 以凸显语义
     # - 其他容器类型：默认包装 intent
     processed_infos = intentify_prompt_infos(infos)
-    return prompt_template.format(**processed_infos)
+    return template.format(**processed_infos)
 
 
 def call_llm(prompt: str, mode="normal") -> str:
@@ -161,25 +159,55 @@ def parse_llm_response(res: str) -> dict:
     return obj
 
 
-def get_prompt_and_call_llm(template_path: Path, infos: dict, mode="normal") -> str:
+def call_and_parse_llm(prompt: str, mode: str = "normal") -> dict:
+    """
+    将 LLM 调用与解析合并，并在解析失败时按配置重试。
+    成功返回 dict，超过重试次数仍失败则抛错。
+    """
+    max_retries = int(getattr(CONFIG.llm, "max_parse_retries", 0))
+    last_err: Exception | None = None
+    for _ in range(1 + max_retries):
+        res = call_llm(prompt, mode)
+        try:
+            return parse_llm_response(res)
+        except Exception as e:
+            last_err = e
+            continue
+    raise ValueError(f"LLM响应解析失败，已重试 {max_retries} 次") from last_err
+
+
+async def call_and_parse_llm_async(prompt: str, mode: str = "normal") -> dict:
+    """
+    异步版本：将 LLM 调用与解析合并，并在解析失败时按配置重试。
+    成功返回 dict，超过重试次数仍失败则抛错。
+    """
+    max_retries = int(getattr(CONFIG.llm, "max_parse_retries", 0))
+    last_err: Exception | None = None
+    for _ in range(1 + max_retries):
+        res = await call_llm_async(prompt, mode)
+        try:
+            return parse_llm_response(res)
+        except Exception as e:
+            last_err = e
+            continue
+    raise ValueError(f"LLM响应解析失败，已重试 {max_retries} 次") from last_err
+
+
+def get_prompt_and_call_llm(template_path: Path, infos: dict, mode="normal") -> dict:
     """
     根据模板，获取提示词，并调用LLM
     """
     template = read_txt(template_path)
     prompt = get_prompt(template, infos)
-    res = call_llm(prompt, mode)
-    json_res = parse_llm_response(res)
-    return json_res
+    return call_and_parse_llm(prompt, mode)
 
-async def get_prompt_and_call_llm_async(template_path: Path, infos: dict, mode="normal") -> str:
+async def get_prompt_and_call_llm_async(template_path: Path, infos: dict, mode="normal") -> dict:
     """
     异步版本：根据模板，获取提示词，并调用LLM
     """
     template = read_txt(template_path)
     prompt = get_prompt(template, infos)
-    res = await call_llm_async(prompt, mode)
-    json_res = parse_llm_response(res)
-    return json_res
+    return await call_and_parse_llm_async(prompt, mode)
 
 def get_ai_prompt_and_call_llm(infos: dict, mode="normal") -> dict:
     """

static/config.yml

@@ -4,6 +4,7 @@ llm:
   fast_model_name: "your-fast-model-name"
   key: "your-api-key"
   base_url: "your-base-url-of-llm"
+  max_parse_retries: 3
 
 paths:
   templates: static/templates/
@@ -11,7 +12,7 @@ paths:
 
 ai:
   mode: "llm" # "rule" or "llm"
-  max_decide_num: 3
+  max_decide_num: 4
 
 game:
   init_npc_num: 9