Merge branch 'geekan/main' into feature/toollib/git

config/config2.example.yaml

@@ -4,6 +4,7 @@ llm:
   api_key: "YOUR_API_KEY"
   model: "gpt-4-turbo-preview"  # or gpt-3.5-turbo-1106 / gpt-4-1106-preview
   proxy: "YOUR_PROXY"  # for LLM API requests
+  # timeout: 600 # Optional. If set to 0, default value is 300.
   pricing_plan: "" # Optional. If invalid, it will be automatically filled in with the value of the `model`.
   # Azure-exclusive pricing plan mappings：
   # - gpt-3.5-turbo 4k: "gpt-3.5-turbo-1106"

metagpt/actions/action_node.py

@@ -17,6 +17,7 @@ from pydantic import BaseModel, Field, create_model, model_validator
 from tenacity import retry, stop_after_attempt, wait_random_exponential
 
 from metagpt.actions.action_outcls_registry import register_action_outcls
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.llm import BaseLLM
 from metagpt.logs import logger
 from metagpt.provider.postprocess.llm_output_postprocess import llm_output_postprocess
@@ -416,7 +417,7 @@ class ActionNode:
         images: Optional[Union[str, list[str]]] = None,
         system_msgs: Optional[list[str]] = None,
         schema="markdown",  # compatible to original format
-        timeout=3,
+        timeout=USE_CONFIG_TIMEOUT,
     ) -> (str, BaseModel):
         """Use ActionOutput to wrap the output of aask"""
         content = await self.llm.aask(prompt, system_msgs, images=images, timeout=timeout)
@@ -448,7 +449,9 @@ class ActionNode:
     def set_context(self, context):
         self.set_recursive("context", context)
 
-    async def simple_fill(self, schema, mode, images: Optional[Union[str, list[str]]] = None, timeout=3, exclude=None):
+    async def simple_fill(
+        self, schema, mode, images: Optional[Union[str, list[str]]] = None, timeout=USE_CONFIG_TIMEOUT, exclude=None
+    ):
         prompt = self.compile(context=self.context, schema=schema, mode=mode, exclude=exclude)
 
         if schema != "raw":
@@ -473,7 +476,7 @@ class ActionNode:
         mode="auto",
         strgy="simple",
         images: Optional[Union[str, list[str]]] = None,
-        timeout=3,
+        timeout=USE_CONFIG_TIMEOUT,
         exclude=[],
     ):
         """Fill the node(s) with mode.

metagpt/configs/llm_config.py

@@ -10,6 +10,7 @@ from typing import Optional
 
 from pydantic import field_validator
 
+from metagpt.const import LLM_API_TIMEOUT
 from metagpt.utils.yaml_model import YamlModel
 
 
@@ -74,7 +75,7 @@ class LLMConfig(YamlModel):
     stream: bool = False
     logprobs: Optional[bool] = None  # https://cookbook.openai.com/examples/using_logprobs
     top_logprobs: Optional[int] = None
-    timeout: int = 60
+    timeout: int = 600
 
     # For Network
     proxy: Optional[str] = None
@@ -88,3 +89,8 @@ class LLMConfig(YamlModel):
         if v in ["", None, "YOUR_API_KEY"]:
             raise ValueError("Please set your API key in config2.yaml")
         return v
+
+    @field_validator("timeout")
+    @classmethod
+    def check_timeout(cls, v):
+        return v or LLM_API_TIMEOUT

metagpt/const.py

@@ -123,7 +123,6 @@ BASE64_FORMAT = "base64"
 
 # REDIS
 REDIS_KEY = "REDIS_KEY"
-LLM_API_TIMEOUT = 300
 
 # Message id
 IGNORED_MESSAGE_ID = "0"
@@ -132,3 +131,7 @@ IGNORED_MESSAGE_ID = "0"
 GENERALIZATION = "Generalize"
 COMPOSITION = "Composite"
 AGGREGATION = "Aggregate"
+
+# Timeout
+USE_CONFIG_TIMEOUT = 0  # Using llm.timeout configuration.
+LLM_API_TIMEOUT = 300

metagpt/provider/anthropic_api.py

@@ -5,6 +5,7 @@ from anthropic import AsyncAnthropic
 from anthropic.types import Message, Usage
 
 from metagpt.configs.llm_config import LLMConfig, LLMType
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import log_llm_stream
 from metagpt.provider.base_llm import BaseLLM
 from metagpt.provider.llm_provider_registry import register_provider
@@ -41,15 +42,15 @@ class AnthropicLLM(BaseLLM):
     def get_choice_text(self, resp: Message) -> str:
         return resp.content[0].text
 
-    async def _achat_completion(self, messages: list[dict], timeout: int = 3) -> Message:
+    async def _achat_completion(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> Message:
         resp: Message = await self.aclient.messages.create(**self._const_kwargs(messages))
         self._update_costs(resp.usage, self.model)
         return resp
 
-    async def acompletion(self, messages: list[dict], timeout: int = 3) -> Message:
-        return await self._achat_completion(messages, timeout=timeout)
+    async def acompletion(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> Message:
+        return await self._achat_completion(messages, timeout=self.get_timeout(timeout))
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         stream = await self.aclient.messages.create(**self._const_kwargs(messages, stream=True))
         collected_content = []
         usage = Usage(input_tokens=0, output_tokens=0)

metagpt/provider/base_llm.py

@@ -23,6 +23,7 @@ from tenacity import (
 )
 
 from metagpt.configs.llm_config import LLMConfig
+from metagpt.const import LLM_API_TIMEOUT, USE_CONFIG_TIMEOUT
 from metagpt.logs import logger
 from metagpt.schema import Message
 from metagpt.utils.common import log_and_reraise
@@ -130,7 +131,7 @@ class BaseLLM(ABC):
         system_msgs: Optional[list[str]] = None,
         format_msgs: Optional[list[dict[str, str]]] = None,
         images: Optional[Union[str, list[str]]] = None,
-        timeout=3,
+        timeout=USE_CONFIG_TIMEOUT,
         stream=True,
     ) -> str:
         if system_msgs:
@@ -146,31 +147,31 @@ class BaseLLM(ABC):
         else:
             message.extend(msg)
         logger.debug(message)
-        rsp = await self.acompletion_text(message, stream=stream, timeout=timeout)
+        rsp = await self.acompletion_text(message, stream=stream, timeout=self.get_timeout(timeout))
         return rsp
 
     def _extract_assistant_rsp(self, context):
         return "\n".join([i["content"] for i in context if i["role"] == "assistant"])
 
-    async def aask_batch(self, msgs: list, timeout=3) -> str:
+    async def aask_batch(self, msgs: list, timeout=USE_CONFIG_TIMEOUT) -> str:
         """Sequential questioning"""
         context = []
         for msg in msgs:
             umsg = self._user_msg(msg)
             context.append(umsg)
-            rsp_text = await self.acompletion_text(context, timeout=timeout)
+            rsp_text = await self.acompletion_text(context, timeout=self.get_timeout(timeout))
             context.append(self._assistant_msg(rsp_text))
         return self._extract_assistant_rsp(context)
 
-    async def aask_code(self, messages: Union[str, Message, list[dict]], timeout=3, **kwargs) -> dict:
+    async def aask_code(self, messages: Union[str, Message, list[dict]], timeout=USE_CONFIG_TIMEOUT, **kwargs) -> dict:
         raise NotImplementedError
 
     @abstractmethod
-    async def _achat_completion(self, messages: list[dict], timeout=3):
+    async def _achat_completion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT):
         """_achat_completion implemented by inherited class"""
 
     @abstractmethod
-    async def acompletion(self, messages: list[dict], timeout=3):
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT):
         """Asynchronous version of completion
         All GPTAPIs are required to provide the standard OpenAI completion interface
         [
@@ -181,7 +182,7 @@ class BaseLLM(ABC):
         """
 
     @abstractmethod
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         """_achat_completion_stream implemented by inherited class"""
 
     @retry(
@@ -191,11 +192,13 @@ class BaseLLM(ABC):
         retry=retry_if_exception_type(ConnectionError),
         retry_error_callback=log_and_reraise,
     )
-    async def acompletion_text(self, messages: list[dict], stream: bool = False, timeout: int = 3) -> str:
+    async def acompletion_text(
+        self, messages: list[dict], stream: bool = False, timeout: int = USE_CONFIG_TIMEOUT
+    ) -> str:
         """Asynchronous version of completion. Return str. Support stream-print"""
         if stream:
-            return await self._achat_completion_stream(messages, timeout=timeout)
-        resp = await self._achat_completion(messages, timeout=timeout)
+            return await self._achat_completion_stream(messages, timeout=self.get_timeout(timeout))
+        resp = await self._achat_completion(messages, timeout=self.get_timeout(timeout))
         return self.get_choice_text(resp)
 
     def get_choice_text(self, rsp: dict) -> str:
@@ -258,3 +261,6 @@ class BaseLLM(ABC):
         """Set model and return self. For example, `with_model("gpt-3.5-turbo")`."""
         self.config.model = model
         return self
+
+    def get_timeout(self, timeout: int) -> int:
+        return timeout or self.config.timeout or LLM_API_TIMEOUT

metagpt/provider/dashscope_api.py

@@ -25,6 +25,7 @@ from dashscope.common.error import (
     UnsupportedApiProtocol,
 )
 
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import log_llm_stream
 from metagpt.provider.base_llm import BaseLLM, LLMConfig
 from metagpt.provider.llm_provider_registry import LLMType, register_provider
@@ -202,16 +203,16 @@ class DashScopeLLM(BaseLLM):
         self._update_costs(dict(resp.usage))
         return resp.output
 
-    async def _achat_completion(self, messages: list[dict], timeout: int = 3) -> GenerationOutput:
+    async def _achat_completion(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> GenerationOutput:
         resp: GenerationResponse = await self.aclient.acall(**self._const_kwargs(messages, stream=False))
         self._check_response(resp)
         self._update_costs(dict(resp.usage))
         return resp.output
 
-    async def acompletion(self, messages: list[dict], timeout=3) -> GenerationOutput:
-        return await self._achat_completion(messages, timeout=timeout)
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> GenerationOutput:
+        return await self._achat_completion(messages, timeout=self.get_timeout(timeout))
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         resp = await self.aclient.acall(**self._const_kwargs(messages, stream=True))
         collected_content = []
         usage = {}

metagpt/provider/general_api_base.py

@@ -573,7 +573,7 @@ class APIRequestor:
                 total=request_timeout[1],
             )
         else:
-            timeout = aiohttp.ClientTimeout(total=request_timeout if request_timeout else TIMEOUT_SECS)
+            timeout = aiohttp.ClientTimeout(total=request_timeout or TIMEOUT_SECS)
 
         if files:
             # TODO: Use `aiohttp.MultipartWriter` to create the multipart form data here.

metagpt/provider/google_gemini_api.py

@@ -16,6 +16,7 @@ from google.generativeai.types.generation_types import (
 )
 
 from metagpt.configs.llm_config import LLMConfig, LLMType
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import log_llm_stream, logger
 from metagpt.provider.base_llm import BaseLLM
 from metagpt.provider.llm_provider_registry import register_provider
@@ -123,16 +124,18 @@ class GeminiLLM(BaseLLM):
         self._update_costs(usage)
         return resp
 
-    async def _achat_completion(self, messages: list[dict], timeout: int = 3) -> "AsyncGenerateContentResponse":
+    async def _achat_completion(
+        self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT
+    ) -> "AsyncGenerateContentResponse":
         resp: AsyncGenerateContentResponse = await self.llm.generate_content_async(**self._const_kwargs(messages))
         usage = await self.aget_usage(messages, resp.text)
         self._update_costs(usage)
         return resp
 
-    async def acompletion(self, messages: list[dict], timeout=3) -> dict:
-        return await self._achat_completion(messages, timeout=timeout)
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> dict:
+        return await self._achat_completion(messages, timeout=self.get_timeout(timeout))
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         resp: AsyncGenerateContentResponse = await self.llm.generate_content_async(
             **self._const_kwargs(messages, stream=True)
         )

metagpt/provider/human_provider.py

@@ -6,6 +6,7 @@ Author: garylin2099
 from typing import Optional
 
 from metagpt.configs.llm_config import LLMConfig
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import logger
 from metagpt.provider.base_llm import BaseLLM
 
@@ -18,7 +19,7 @@ class HumanProvider(BaseLLM):
     def __init__(self, config: LLMConfig):
         pass
 
-    def ask(self, msg: str, timeout=3) -> str:
+    def ask(self, msg: str, timeout=USE_CONFIG_TIMEOUT) -> str:
         logger.info("It's your turn, please type in your response. You may also refer to the context below")
         rsp = input(msg)
         if rsp in ["exit", "quit"]:
@@ -31,20 +32,20 @@ class HumanProvider(BaseLLM):
         system_msgs: Optional[list[str]] = None,
         format_msgs: Optional[list[dict[str, str]]] = None,
         generator: bool = False,
-        timeout=3,
+        timeout=USE_CONFIG_TIMEOUT,
     ) -> str:
-        return self.ask(msg, timeout=timeout)
+        return self.ask(msg, timeout=self.get_timeout(timeout))
 
-    async def _achat_completion(self, messages: list[dict], timeout=3):
+    async def _achat_completion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT):
         pass
 
-    async def acompletion(self, messages: list[dict], timeout=3):
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT):
         """dummy implementation of abstract method in base"""
         return []
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         pass
 
-    async def acompletion_text(self, messages: list[dict], stream=False, timeout=3) -> str:
+    async def acompletion_text(self, messages: list[dict], stream=False, timeout=USE_CONFIG_TIMEOUT) -> str:
         """dummy implementation of abstract method in base"""
         return ""

metagpt/provider/ollama_api.py

@@ -5,7 +5,7 @@
 import json
 
 from metagpt.configs.llm_config import LLMConfig, LLMType
-from metagpt.const import LLM_API_TIMEOUT
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import log_llm_stream
 from metagpt.provider.base_llm import BaseLLM
 from metagpt.provider.general_api_requestor import GeneralAPIRequestor
@@ -50,28 +50,28 @@ class OllamaLLM(BaseLLM):
         chunk = chunk.decode(encoding)
         return json.loads(chunk)
 
-    async def _achat_completion(self, messages: list[dict], timeout: int = 3) -> dict:
+    async def _achat_completion(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> dict:
         resp, _, _ = await self.client.arequest(
             method=self.http_method,
             url=self.suffix_url,
             params=self._const_kwargs(messages),
-            request_timeout=LLM_API_TIMEOUT,
+            request_timeout=self.get_timeout(timeout),
         )
         resp = self._decode_and_load(resp)
         usage = self.get_usage(resp)
         self._update_costs(usage)
         return resp
 
-    async def acompletion(self, messages: list[dict], timeout=3) -> dict:
-        return await self._achat_completion(messages, timeout=timeout)
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> dict:
+        return await self._achat_completion(messages, timeout=self.get_timeout(timeout))
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         stream_resp, _, _ = await self.client.arequest(
             method=self.http_method,
             url=self.suffix_url,
             stream=True,
             params=self._const_kwargs(messages, stream=True),
-            request_timeout=LLM_API_TIMEOUT,
+            request_timeout=self.get_timeout(timeout),
         )
 
         collected_content = []

metagpt/provider/openai_api.py

@@ -25,6 +25,7 @@ from tenacity import (
 )
 
 from metagpt.configs.llm_config import LLMConfig, LLMType
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import log_llm_stream, logger
 from metagpt.provider.base_llm import BaseLLM
 from metagpt.provider.constant import GENERAL_FUNCTION_SCHEMA
@@ -74,9 +75,9 @@ class OpenAILLM(BaseLLM):
 
         return params
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout=3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> str:
         response: AsyncStream[ChatCompletionChunk] = await self.aclient.chat.completions.create(
-            **self._cons_kwargs(messages, timeout=timeout), stream=True
+            **self._cons_kwargs(messages, timeout=self.get_timeout(timeout)), stream=True
         )
         usage = None
         collected_messages = []
@@ -104,7 +105,7 @@ class OpenAILLM(BaseLLM):
         self._update_costs(usage)
         return full_reply_content
 
-    def _cons_kwargs(self, messages: list[dict], timeout=3, **extra_kwargs) -> dict:
+    def _cons_kwargs(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT, **extra_kwargs) -> dict:
         kwargs = {
             "messages": messages,
             "max_tokens": self._get_max_tokens(messages),
@@ -112,20 +113,20 @@ class OpenAILLM(BaseLLM):
             # "stop": None,  # default it's None and gpt4-v can't have this one
             "temperature": self.config.temperature,
             "model": self.model,
-            "timeout": max(self.config.timeout, timeout),
+            "timeout": self.get_timeout(timeout),
         }
         if extra_kwargs:
             kwargs.update(extra_kwargs)
         return kwargs
 
-    async def _achat_completion(self, messages: list[dict], timeout=3) -> ChatCompletion:
-        kwargs = self._cons_kwargs(messages, timeout=timeout)
+    async def _achat_completion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> ChatCompletion:
+        kwargs = self._cons_kwargs(messages, timeout=self.get_timeout(timeout))
         rsp: ChatCompletion = await self.aclient.chat.completions.create(**kwargs)
         self._update_costs(rsp.usage)
         return rsp
 
-    async def acompletion(self, messages: list[dict], timeout=3) -> ChatCompletion:
-        return await self._achat_completion(messages, timeout=timeout)
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> ChatCompletion:
+        return await self._achat_completion(messages, timeout=self.get_timeout(timeout))
 
     @retry(
         wait=wait_random_exponential(min=1, max=60),
@@ -134,24 +135,24 @@ class OpenAILLM(BaseLLM):
         retry=retry_if_exception_type(APIConnectionError),
         retry_error_callback=log_and_reraise,
     )
-    async def acompletion_text(self, messages: list[dict], stream=False, timeout=3) -> str:
+    async def acompletion_text(self, messages: list[dict], stream=False, timeout=USE_CONFIG_TIMEOUT) -> str:
         """when streaming, print each token in place."""
         if stream:
             return await self._achat_completion_stream(messages, timeout=timeout)
 
-        rsp = await self._achat_completion(messages, timeout=timeout)
+        rsp = await self._achat_completion(messages, timeout=self.get_timeout(timeout))
         return self.get_choice_text(rsp)
 
     async def _achat_completion_function(
-        self, messages: list[dict], timeout: int = 3, **chat_configs
+        self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT, **chat_configs
     ) -> ChatCompletion:
         messages = self.format_msg(messages)
-        kwargs = self._cons_kwargs(messages=messages, timeout=timeout, **chat_configs)
+        kwargs = self._cons_kwargs(messages=messages, timeout=self.get_timeout(timeout), **chat_configs)
         rsp: ChatCompletion = await self.aclient.chat.completions.create(**kwargs)
         self._update_costs(rsp.usage)
         return rsp
 
-    async def aask_code(self, messages: list[dict], timeout: int = 3, **kwargs) -> dict:
+    async def aask_code(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT, **kwargs) -> dict:
         """Use function of tools to ask a code.
         Note: Keep kwargs consistent with https://platform.openai.com/docs/api-reference/chat/create
 

metagpt/provider/qianfan_api.py

@@ -9,6 +9,7 @@ from qianfan import ChatCompletion
 from qianfan.resources.typing import JsonBody
 
 from metagpt.configs.llm_config import LLMConfig, LLMType
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import log_llm_stream
 from metagpt.provider.base_llm import BaseLLM
 from metagpt.provider.llm_provider_registry import register_provider
@@ -107,15 +108,15 @@ class QianFanLLM(BaseLLM):
         self._update_costs(resp.body.get("usage", {}))
         return resp.body
 
-    async def _achat_completion(self, messages: list[dict], timeout: int = 3) -> JsonBody:
+    async def _achat_completion(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> JsonBody:
         resp = await self.aclient.ado(**self._const_kwargs(messages=messages, stream=False))
         self._update_costs(resp.body.get("usage", {}))
         return resp.body
 
-    async def acompletion(self, messages: list[dict], timeout: int = 3) -> JsonBody:
-        return await self._achat_completion(messages, timeout=timeout)
+    async def acompletion(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> JsonBody:
+        return await self._achat_completion(messages, timeout=self.get_timeout(timeout))
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         resp = await self.aclient.ado(**self._const_kwargs(messages=messages, stream=True))
         collected_content = []
         usage = {}

metagpt/provider/spark_api.py

@@ -17,6 +17,7 @@ from wsgiref.handlers import format_date_time
 import websocket  # 使用websocket_client
 
 from metagpt.configs.llm_config import LLMConfig, LLMType
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import logger
 from metagpt.provider.base_llm import BaseLLM
 from metagpt.provider.llm_provider_registry import register_provider
@@ -31,19 +32,19 @@ class SparkLLM(BaseLLM):
     def get_choice_text(self, rsp: dict) -> str:
         return rsp["payload"]["choices"]["text"][-1]["content"]
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout: int = 3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout: int = USE_CONFIG_TIMEOUT) -> str:
         pass
 
-    async def acompletion_text(self, messages: list[dict], stream=False, timeout: int = 3) -> str:
+    async def acompletion_text(self, messages: list[dict], stream=False, timeout: int = USE_CONFIG_TIMEOUT) -> str:
         # 不支持
         # logger.warning("当前方法无法支持异步运行。当你使用acompletion时，并不能并行访问。")
         w = GetMessageFromWeb(messages, self.config)
         return w.run()
 
-    async def _achat_completion(self, messages: list[dict], timeout=3):
+    async def _achat_completion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT):
         pass
 
-    async def acompletion(self, messages: list[dict], timeout=3):
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT):
         # 不支持异步
         w = GetMessageFromWeb(messages, self.config)
         return w.run()

metagpt/provider/zhipuai_api.py

@@ -8,6 +8,7 @@ from typing import Optional
 from zhipuai.types.chat.chat_completion import Completion
 
 from metagpt.configs.llm_config import LLMConfig, LLMType
+from metagpt.const import USE_CONFIG_TIMEOUT
 from metagpt.logs import log_llm_stream
 from metagpt.provider.base_llm import BaseLLM
 from metagpt.provider.llm_provider_registry import register_provider
@@ -45,22 +46,22 @@ class ZhiPuAILLM(BaseLLM):
         kwargs = {"model": self.model, "messages": messages, "stream": stream, "temperature": 0.3}
         return kwargs
 
-    def completion(self, messages: list[dict], timeout=3) -> dict:
+    def completion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> dict:
         resp: Completion = self.llm.chat.completions.create(**self._const_kwargs(messages))
         usage = resp.usage.model_dump()
         self._update_costs(usage)
         return resp.model_dump()
 
-    async def _achat_completion(self, messages: list[dict], timeout=3) -> dict:
+    async def _achat_completion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> dict:
         resp = await self.llm.acreate(**self._const_kwargs(messages))
         usage = resp.get("usage", {})
         self._update_costs(usage)
         return resp
 
-    async def acompletion(self, messages: list[dict], timeout=3) -> dict:
-        return await self._achat_completion(messages, timeout=timeout)
+    async def acompletion(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> dict:
+        return await self._achat_completion(messages, timeout=self.get_timeout(timeout))
 
-    async def _achat_completion_stream(self, messages: list[dict], timeout=3) -> str:
+    async def _achat_completion_stream(self, messages: list[dict], timeout=USE_CONFIG_TIMEOUT) -> str:
         response = await self.llm.acreate_stream(**self._const_kwargs(messages, stream=True))
         collected_content = []
         usage = {}

metagpt/utils/common.py

@@ -18,6 +18,7 @@ import csv
 import importlib
 import inspect
 import json
+import mimetypes
 import os
 import platform
 import re
@@ -819,3 +820,21 @@ See FAQ 5.8
 """
     )
     raise retry_state.outcome.exception()
+
+
+def get_markdown_codeblock_type(filename: str) -> str:
+    """Return the markdown code-block type corresponding to the file extension."""
+    mime_type, _ = mimetypes.guess_type(filename)
+    mappings = {
+        "text/x-shellscript": "bash",
+        "text/x-c++src": "cpp",
+        "text/css": "css",
+        "text/html": "html",
+        "text/x-java": "java",
+        "application/javascript": "javascript",
+        "application/json": "json",
+        "text/x-python": "python",
+        "text/x-ruby": "ruby",
+        "application/sql": "sql",
+    }
+    return mappings.get(mime_type, "text")

metagpt/utils/repair_llm_raw_output.py

@@ -340,7 +340,9 @@ def extract_state_value_from_output(content: str) -> str:
         content (str): llm's output from `Role._think`
     """
     content = content.strip()  # deal the output cases like " 0", "0\n" and so on.
-    pattern = r"([0-9])"  # TODO find the number using a more proper method not just extract from content using pattern
+    pattern = (
+        r"(?<!-)[0-9]"  # TODO find the number using a more proper method not just extract from content using pattern
+    )
     matches = re.findall(pattern, content, re.DOTALL)
     matches = list(set(matches))
     state = matches[0] if len(matches) > 0 else "-1"

metagpt/utils/repo_to_markdown.py

@@ -0,0 +1,80 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+This file provides functionality to convert a local repository into a markdown representation.
+"""
+from __future__ import annotations
+
+import mimetypes
+from pathlib import Path
+
+from gitignore_parser import parse_gitignore
+
+from metagpt.logs import logger
+from metagpt.utils.common import aread, awrite, get_markdown_codeblock_type, list_files
+from metagpt.utils.tree import tree
+
+
+async def repo_to_markdown(repo_path: str | Path, output: str | Path = None, gitignore: str | Path = None) -> str:
+    """
+    Convert a local repository into a markdown representation.
+
+    This function takes a path to a local repository and generates a markdown representation of the repository structure,
+    including directory trees and file listings.
+
+    Args:
+        repo_path (str | Path): The path to the local repository.
+        output (str | Path, optional): The path to save the generated markdown file. Defaults to None.
+        gitignore (str | Path, optional): The path to the .gitignore file. Defaults to None.
+
+    Returns:
+        str: The markdown representation of the repository.
+    """
+    repo_path = Path(repo_path)
+    gitignore = Path(gitignore or Path(__file__).parent / "../../.gitignore").resolve()
+
+    markdown = await _write_dir_tree(repo_path=repo_path, gitignore=gitignore)
+
+    gitignore_rules = parse_gitignore(full_path=str(gitignore))
+    markdown += await _write_files(repo_path=repo_path, gitignore_rules=gitignore_rules)
+
+    if output:
+        await awrite(filename=str(output), data=markdown, encoding="utf-8")
+    return markdown
+
+
+async def _write_dir_tree(repo_path: Path, gitignore: Path) -> str:
+    try:
+        content = tree(repo_path, gitignore, run_command=True)
+    except Exception as e:
+        logger.info(f"{e}, using safe mode.")
+        content = tree(repo_path, gitignore, run_command=False)
+
+    doc = f"## Directory Tree\n```text\n{content}\n```\n---\n\n"
+    return doc
+
+
+async def _write_files(repo_path, gitignore_rules) -> str:
+    filenames = list_files(repo_path)
+    markdown = ""
+    for filename in filenames:
+        if gitignore_rules(str(filename)):
+            continue
+        markdown += await _write_file(filename=filename, repo_path=repo_path)
+    return markdown
+
+
+async def _write_file(filename: Path, repo_path: Path) -> str:
+    relative_path = filename.relative_to(repo_path)
+    markdown = f"## {relative_path}\n"
+
+    mime_type, _ = mimetypes.guess_type(filename.name)
+    if "text/" not in mime_type:
+        logger.info(f"Ignore content: {filename}")
+        markdown += "<binary file>\n---\n\n"
+        return markdown
+    content = await aread(filename, encoding="utf-8")
+    content = content.replace("```", "\\`\\`\\`").replace("---", "\\-\\-\\-")
+    code_block_type = get_markdown_codeblock_type(filename.name)
+    markdown += f"```{code_block_type}\n{content}\n```\n---\n\n"
+    return markdown

requirements.txt

@@ -34,7 +34,7 @@ PyYAML==6.0.1
 # sentence_transformers==2.2.2
 setuptools==65.6.3
 tenacity==8.2.3
-tiktoken==0.5.2
+tiktoken==0.6.0
 tqdm==4.66.2
 #unstructured[local-inference]
 # selenium>4

tests/metagpt/utils/test_repo_to_markdown.py

@@ -0,0 +1,25 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+import uuid
+from pathlib import Path
+
+import pytest
+
+from metagpt.utils.repo_to_markdown import repo_to_markdown
+
+
+@pytest.mark.parametrize(
+    ["repo_path", "output"],
+    [(Path(__file__).parent.parent, Path(__file__).parent.parent.parent / f"workspace/unittest/{uuid.uuid4().hex}.md")],
+)
+@pytest.mark.asyncio
+async def test_repo_to_markdown(repo_path: Path, output: Path):
+    markdown = await repo_to_markdown(repo_path=repo_path, output=output)
+    assert output.exists()
+    assert markdown
+
+    output.unlink(missing_ok=True)
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-s"])