add examples on how to use qwen-agent

.gitignore

@@ -31,4 +31,4 @@ qwen_agent.egg-info/*
 build/*
 dist/*
 
-demo/*
+examples/*.ipynb

examples/chess.py

@@ -0,0 +1,56 @@
+from qwen_agent.prompts import RolePlay
+
+# config
+player = '你扮演一个玩五子棋的高手，你下{color}。棋盘中用0代表无棋子、用1黑棋、用-1白棋。用坐标<i,j>表示位置，i代表行，j代表列，棋盘左上角位置为<0,0>，请决定你要下在哪里，你可以随意下到一个位置，不要说你是AI助手不会下！返回格式为坐标：\n<i,j>\n除了这个坐标，不要返回其他任何内容'
+role_black = player.format(color='黑棋')
+role_write = player.format(color='白棋')
+board = '你扮演一个五子棋棋盘，你可以调用代码工具，根据原始棋盘和玩家下棋的位置坐标，把新的棋盘用矩阵展示出来。棋盘中用0代表无棋子、用1表示黑棋、用-1表示白棋。用坐标<i,j>表示位置，i代表行，j代表列，棋盘左上角位置为<0,0>。'
+llm_config = {'model': 'qwen-max', 'api_key': '', 'model_server': 'dashscope'}
+function_list = ['code_interpreter']
+
+# init three agent
+player_black = RolePlay(llm=llm_config, system_instruction=role_black)
+player_white = RolePlay(llm=llm_config, system_instruction=role_write)
+board = RolePlay(function_list=function_list,
+                 llm=llm_config,
+                 system_instruction=board)
+
+
+# define a result_processing function
+def result_processing(response):
+    text = ''
+    for chunk in response:
+        text += chunk
+    print(text)
+
+    if '\nObservation:' in text:
+        # we need the chessboard in this case
+        text = text.split('\nObservation:')[-1].split('\nAnswer:')[0]
+    return text
+
+
+# run agent: init chessboard
+board_display = ''
+position = ''
+response = board.run('初始化一个10*10的棋盘')
+
+while True:
+    # result processing: Extract the chessboard from the answer
+    board_display = result_processing(response)
+
+    # run agent: play black chess
+    response = player_black.run(f'当前棋盘是：\n{board_display}\n，请下黑棋', )
+    position = result_processing(response)
+
+    # run agent: update chessboard
+    response = board.run(
+        f'请更新棋盘并打印，原始棋盘是：\n{board_display}\n黑棋玩家刚下在{position}位置')
+    board_display = result_processing(response)
+
+    # run agent: play white chess
+    response = player_white.run(f'当前棋盘是：\n{board_display}\n，请下白棋:', )
+    position = result_processing(response)
+
+    # run agent: update chessboard
+    response = board.run(
+        f'请更新棋盘并打印，原始棋盘是：\n{board_display}\n白棋玩家刚下在{position}位置')

examples/weather_bot.py

@@ -0,0 +1,20 @@
+from qwen_agent.prompts import RolePlay
+
+# config
+role = '你扮演一个天气预报助手，你需要查询相应地区的天气，同时调用给你的画图工具绘制一张城市的图。'
+llm_config = {'model': 'qwen-max', 'api_key': '', 'model_server': 'dashscope'}
+function_list = ['image_gen', 'amap_weather']
+
+# init agent
+bot = RolePlay(function_list=function_list,
+               llm=llm_config,
+               system_instruction=role)
+
+# run agent
+response = bot.run('朝阳区天气')
+
+# result processing
+text = ''
+for chunk in response:
+    text += chunk
+print(text)

qwen_agent/agent.py

@@ -10,16 +10,19 @@
 class Agent(ABC):
 
     def __init__(self,
-                 function_list: Optional[List[str]] = None,
+                 function_list: Optional[List[Union[str, Dict]]] = None,
                  llm: Optional[Union[Dict, BaseChatModel]] = None,
+                 system_instruction: Optional[str] = None,
                  storage_path: Optional[str] = None,
                  name: Optional[str] = None,
                  description: Optional[str] = None,
                  **kwargs):
         """
         init tools/llm for one agent
 
-        :param function_list: Optional[List[str]] : a list of tool names
+        :param function_list: Optional[List[Union[str, Dict]]] :
+            (1)When str: tool names
+            (2)When Dict: tool cfg
         :param llm: Optional[Union[Dict, BaseChatModel]]:
             (1) When Dict: set the config of llm as {'model': '', 'api_key': '', 'model_server': ''}
             (2) When BaseChatModel: llm is sent by another agent
@@ -45,6 +48,7 @@ def __init__(self,
         self.mem = None
         self.name = name
         self.description = description
+        self.system_instruction = system_instruction or 'You are a helpful assistant.'
 
     def run(self, *args, **kwargs) -> Union[str, Iterator[str]]:
         if 'lang' not in kwargs:
@@ -78,16 +82,21 @@ def _call_tool(self, tool_name: str, tool_args: str, **kwargs):
         """
         return self.function_map[tool_name].call(tool_args, **kwargs)
 
-    def _register_tool(self, tool_name: str):
+    def _register_tool(self, tool: Union[str, Dict]):
         """
         Instantiate the global tool for the agent
 
         """
+        tool_name = tool
+        tool_cfg = None
+        if isinstance(tool, Dict):
+            tool_name = tool['name']
+            tool_cfg = tool
         if tool_name not in TOOL_REGISTRY:
             raise NotImplementedError
-        if tool_name not in self.function_list:
-            self.function_list.append(tool_name)
-            self.function_map[tool_name] = TOOL_REGISTRY[tool_name]()
+        if tool not in self.function_list:
+            self.function_list.append(tool)
+            self.function_map[tool_name] = TOOL_REGISTRY[tool_name](tool_cfg)
 
     def _detect_tool(self, message: Union[str, dict]):
         # use built-in default judgment functions

qwen_agent/agents/article_agent.py

@@ -9,7 +9,7 @@
 class ArticleAgent(Agent):
 
     def __init__(self,
-                 function_list: Optional[List[str]] = None,
+                 function_list: Optional[List[Union[str, Dict]]] = None,
                  llm: Optional[Union[Dict, BaseChatModel]] = None,
                  storage_path: Optional[str] = None,
                  name: Optional[str] = None,

qwen_agent/agents/docqa_agent.py

@@ -9,7 +9,7 @@
 class DocQAAgent(Agent):
 
     def __init__(self,
-                 function_list: Optional[List[str]] = None,
+                 function_list: Optional[List[Union[str, Dict]]] = None,
                  llm: Optional[Union[Dict, BaseChatModel]] = None,
                  storage_path: Optional[str] = None,
                  name: Optional[str] = None,

qwen_agent/llm/qwen_dashscope.py

@@ -126,7 +126,7 @@ def build_raw_prompt(self, messages):
         im_start = '<|im_start|>'
         im_end = '<|im_end|>'
         if messages[0]['role'] == 'system':
-            sys = messages[0]['role']
+            sys = messages[0]['content']
             prompt = f'{im_start}system\n{sys}{im_end}'
         else:
             prompt = f'{im_start}system\nYou are a helpful assistant.{im_end}'

qwen_agent/memory/memory.py

@@ -18,7 +18,7 @@ class Memory(Agent):
     """
 
     def __init__(self,
-                 function_list: Optional[List[str]] = None,
+                 function_list: Optional[List[Union[str, Dict]]] = None,
                  llm: Optional[Union[Dict, BaseChatModel]] = None,
                  storage_path: Optional[str] = None,
                  name: Optional[str] = None,

qwen_agent/prompts/role_play.py

@@ -1,7 +1,5 @@
 from typing import Dict, List, Optional
 
-import jsonlines
-
 from qwen_agent import Agent
 
 TOOL_TEMPLATE_ZH = """# 工具
@@ -15,7 +13,7 @@
 Action: 工具名称，必须是[{tool_names}]之一
 Action Input: 工具输入
 Observation: 工具结果
-Final Answer: 根据工具结果进行回复，如果存在url，请使用如何格式展示出来：![图片](url)
+Answer: 根据工具结果进行回复，如果存在url，请使用如下格式展示出来：![图片](url)
 
 """
 
@@ -54,7 +52,7 @@
 Action: The tool to use, should be one of [{tool_names}]
 Action Input: The input of the tool, need to be formatted as a JSON
 Observation: The result returned by the tool
-Final Answer: Summarize the results based on the Observation
+Answer: Summarize the results based on the Observation
 
 """
 
@@ -89,22 +87,20 @@
     'en': '(You have access to tools: [{tool_names}])',
 }
 
-ACTION_TOKEN = '\nAction:'
-ARGS_TOKEN = '\nAction Input:'
-OBSERVATION_TOKEN = '\nObservation:'
-ANSWER_TOKEN = '\nFinal Answer:'
+ACTION_TOKEN = 'Action:'
+ARGS_TOKEN = 'Action Input:'
+OBSERVATION_TOKEN = 'Observation:'
+ANSWER_TOKEN = 'Answer:'
 
 
 class RolePlay(Agent):
 
     def _run(self,
              user_request,
              response_to_continue: str = None,
-             role_prompt: str = None,
              history: Optional[List[Dict]] = None,
              ref_doc: str = None,
              lang: str = 'zh'):
-        self.role_prompt = role_prompt
 
         self.tool_descs = '\n\n'.join(tool.function_plain_text
                                       for tool in self.function_map.values())
@@ -122,7 +118,7 @@ def _run(self,
             self.query_prefix = SPECIAL_PREFIX_TEMPLATE[lang].format(
                 tool_names=self.tool_names)
         self.system_prompt += PROMPT_TEMPLATE[lang].format(
-            role_prompt=self.role_prompt)
+            role_prompt=self.system_instruction)
 
         # Concat the system as one round of dialogue
         messages = ([{
@@ -152,8 +148,8 @@ def _run(self,
         })
         messages.append({'role': 'assistant', 'content': ''})
 
-        with jsonlines.open('log.jsonl', mode='a') as writer:
-            writer.write(messages)
+        # with jsonlines.open('log.jsonl', mode='a') as writer:
+        #     writer.write(messages)
 
         planning_prompt = self.llm.build_raw_prompt(messages)
         if response_to_continue:
@@ -171,7 +167,7 @@ def _run(self,
             yield output
             if use_tool:
                 observation = self._call_tool(action, action_input)
-                observation = f'\nObservation: {observation}\nFinal Answer:'
+                observation = f'\nObservation: {observation}\nAnswer:'
                 yield observation
                 planning_prompt += output + observation
             else:

qwen_agent/tools/amap_weather.py

@@ -1,3 +1,9 @@
+import os
+from typing import Dict, Optional
+
+import pandas as pd
+import requests
+
 from qwen_agent.tools.base import BaseTool, register_tool
 
 
@@ -8,12 +14,45 @@ class AmapWeather(BaseTool):
     parameters = [{
         'name': 'location',
         'type': 'string',
-        'description': '待查询天气的城市'
+        'description': 'get temperature for a specific location',
+        'required': True
     }]
 
+    def __init__(self, cfg: Optional[Dict] = None):
+        super().__init__(cfg)
+
+        # remote call
+        self.url = 'https://restapi.amap.com/v3/weather/weatherInfo?city={city}&key={key}'
+        self.city_df = pd.read_excel(
+            'https://modelscope.oss-cn-beijing.aliyuncs.com/resource/agent/AMap_adcode_citycode.xlsx'
+        )
+
+        self.token = self.cfg.get('token', os.environ.get('AMAP_TOKEN', ''))
+        assert self.token != '', 'weather api token must be acquired through ' \
+            'https://lbs.amap.com/api/webservice/guide/create-project/get-key and set by AMAP_TOKEN'
+
+    def get_city_adcode(self, city_name):
+        filtered_df = self.city_df[self.city_df['中文名'] == city_name]
+        if len(filtered_df['adcode'].values) == 0:
+            raise ValueError(
+                f'location {city_name} not found, availables are {self.city_df["中文名"]}'
+            )
+        else:
+            return filtered_df['adcode'].values[0]
+
     def call(self, params: str, **kwargs) -> str:
         params = self._verify_args(params)
         if isinstance(params, str):
             return 'Parameter Error'
 
-        raise NotImplementedError
+        location = params['location']
+        response = requests.get(
+            self.url.format(city=self.get_city_adcode(location),
+                            key=self.token))
+        data = response.json()
+        if data['status'] == '0':
+            raise RuntimeError(data)
+        else:
+            weather = data['lives'][0]['weather']
+            temperature = data['lives'][0]['temperature']
+            return f'{location}的天气是{weather}温度是{temperature}度。'

qwen_agent/tools/base.py

@@ -1,6 +1,6 @@
 import json
 from abc import ABC, abstractmethod
-from typing import Dict, List, Union
+from typing import Dict, List, Optional, Union
 
 import json5
 
@@ -23,12 +23,11 @@ class BaseTool(ABC):
     description: str
     parameters: List[Dict]
 
-    def __init__(self, schema: str = 'oai'):
-        """
+    def __init__(self, cfg: Optional[Dict] = None):
+        self.cfg = cfg or {}
 
-        :param schema: Format of tools, default to oai format, in case there is a need for other formats
-        """
-        self.schema = schema
+        # schema: Format of tools, default to oai format, in case there is a need for other formats
+        self.schema = self.cfg.get('schema', 'oai')
         self.function = self._build_function()
         self.function_plain_text = self._parser_function()
 

qwen_agent/tools/doc_parser.py

@@ -131,15 +131,22 @@ def process_file(url: str, content: str, source: str, db: Storage = None):
 
     meta_info = db.get('meta_info')
     if meta_info == 'Not Exist':
-        meta_info = []
+        meta_info = {}
     else:
         meta_info = json5.loads(meta_info)
-    meta_info.append({
+    if isinstance(meta_info, list):
+        logger.info('update meta_info to new format')
+        new_meta_info = {}
+        for x in meta_info:
+            new_meta_info[x['url']] = x
+        meta_info = new_meta_info
+
+    meta_info[url] = {
         'url': url,
         'time': now_time,
         'title': title,
         'checked': True,
-    })
+    }
     db.put('meta_info', json.dumps(meta_info, ensure_ascii=False))
 
     return new_record_str
@@ -171,6 +178,7 @@ def read_data_by_condition(db: Storage = None, **kwargs):
         records = []
     else:
         records = json5.loads(meta_info)
+        records = records.values()
 
     if 'time_limit' in kwargs:
         filter_records = []
@@ -214,7 +222,6 @@ class DocParser(BaseTool):
     def call(self,
              params: str,
              db: Storage = None,
-             re_parse: bool = False,
              raw: bool = False,
              **kwargs) -> str:
         params = self._verify_args(params)
@@ -227,7 +234,8 @@ def call(self,
         record = None
         if 'url' in params:
             record = db.get(params['url'])
-            if re_parse or record == 'Not Exist':
+            # need to parse and save doc
+            if 'content' in kwargs:
                 record = process_file(url=params['url'],
                                       content=kwargs['content'],
                                       source=kwargs['type'],