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src/Makefile

@@ -11,4 +11,7 @@ lint:
 	black . --check
 
 test:
-	pytest .
+	echo "Running tests for sherpa"
+	pytest tests
+	echo "Running tests for sherpa slackapp"
+	cd apps/slackapp && pytest tests

src/apps/slackapp/pyproject.toml

@@ -33,6 +33,9 @@ build-backend = "poetry.core.masonry.api"
 pythonpath = [
   "."
 ]
+markers = [
+  "external_api:  this test calls 3rd party APIs"
+]
 
 [tool.black]
 line-length = 88

src/apps/slackapp/slackapp/bolt_app.py

@@ -7,12 +7,14 @@
 from typing import Dict, List
 
 from flask import Flask, request
+from langchain.schema import AIMessage, BaseMessage, HumanMessage
 from loguru import logger
 from slack_bolt import App
 from slack_bolt.adapter.flask import SlackRequestHandler
 from slackapp.routes.whitelist import whitelist_blueprint
 
 import sherpa_ai.config as cfg
+from sherpa_ai.config import AgentConfig
 from sherpa_ai.connectors.vectorstores import get_vectordb
 from sherpa_ai.database.user_usage_tracker import UserUsageTracker
 from sherpa_ai.error_handling import AgentErrorHandler
@@ -47,23 +49,48 @@ def hello_command(ack, body):
     ack(f"Hi, <@{user_id}>!")
 
 
-def contains_verbose(query: str) -> bool:
-    """looks for -verbose in the question and returns True or False"""
-    return "-verbose" in query.lower()
+def convert_thread_history_messages(messages: List[dict]) -> List[BaseMessage]:
+    results = []
 
+    for message in messages:
+        logger.info(message)
+        if message["type"] != "message" and message["type"] != "text":
+            continue
 
-def contains_verbosex(query: str) -> bool:
-    """looks for -verbosex in the question and returns True or False"""
-    return "-verbosex" in query.lower()
+        message_cls = AIMessage if message["user"] == self.ai_id else HumanMessage
+        # replace the at in the message with the name of the bot
+        text = message["text"].replace(f"@{self.ai_id}", f"@{self.ai_name}")
+
+        text = text.split("#verbose", 1)[0]  # remove everything after #verbose
+        text = text.replace("-verbose", "")  # remove -verbose if it exists
+        results.append(message_cls(content=text))
+
+    return results
 
 
 def get_response(
     question: str,
-    previous_messages: List[Dict],
-    verbose_logger: BaseVerboseLogger,
+    previous_messages: List[BaseMessage],
     user_id: str,
     team_id: str,
-):
+    verbose_logger: BaseVerboseLogger,
+    bot_info: Dict[str, str],
+) -> str:
+    """
+    Get response from the task agent for the question
+
+    Args:
+        question (str): question to be answered
+        previous_messages (List[BaseMessage]): previous messages in the thread
+        user_id (str): user id of the user who asked the question
+        team_id (str): team id of the workspace
+        verbose_logger (BaseVerboseLogger): verbose logger to be used
+        bot_info (Dict[str, str]): information of the Slack bot
+
+    Returns:
+        str: response from the task agent
+    """
+
     llm = SherpaChatOpenAI(
         openai_api_key=cfg.OPENAI_API_KEY,
         request_timeout=120,
@@ -74,84 +101,73 @@ def get_response(
 
     memory = get_vectordb()
 
-    tools = get_tools(memory)
+    question, agent_config = AgentConfig.from_input(question)
+    verbose_logger = verbose_logger if agent_config.verbose else DummyVerboseLogger()
+
+    tools = get_tools(memory, agent_config)
     ai_name = "Sherpa"
-    ai_id = bot["user_id"]
+    ai_id = bot_info["user_id"]
 
     task_agent = TaskAgent.from_llm_and_tools(
         ai_name="Sherpa",
         ai_role="assistant",
-        ai_id=bot["user_id"],
+        ai_id=bot_info["user_id"],
         memory=memory,
         tools=tools,
         previous_messages=previous_messages,
         llm=llm,
         verbose_logger=verbose_logger,
+        agent_config=agent_config,
     )
     error_handler = AgentErrorHandler()
 
     question = question.replace(f"@{ai_id}", f"@{ai_name}")
-    if contains_verbosex(query=question):
-        logger.info("Verbose mode is on, show all")
-        question = question.replace("-verbose", "")
-        response = error_handler.run_with_error_handling(task_agent.run, task=question)
-        agent_log = task_agent.logger  # logger is updated after running task_agent.run
-        try:  # in case log_formatter fails
-            verbose_message = log_formatter(agent_log)
-        except KeyError:
-            verbose_message = str(agent_log)
-        return response, verbose_message
-
-    elif contains_verbose(query=question):
-        logger.info("Verbose mode is on, commands only")
-        question = question.replace("-verbose", "")
-        response = error_handler.run_with_error_handling(task_agent.run, task=question)
-
-        agent_log = task_agent.logger  # logger is updated after running task_agent.run
-        try:  # in case log_formatter fails
-            verbose_message = show_commands_only(agent_log)
-        except KeyError:
-            verbose_message = str(agent_log)
-        return response, verbose_message
+    response = error_handler.run_with_error_handling(task_agent.run, task=question)
 
-    else:
-        logger.info("Verbose mode is off")
-        response = error_handler.run_with_error_handling(task_agent.run, task=question)
-        return response, None
-
-def file_event_handler(say , files , team_id ,user_id , thread_ts , question):
-    if files[0]['size'] > cfg.FILE_SIZE_LIMIT:
-            say("Sorry, the file you attached is larger than 2mb. Please try again with a smaller file" , thread_ts=thread_ts)
-            return { "status":"error" }
-    file_prompt = QuestionWithFileHandler( question=question , team_id=team_id , user_id=user_id, files=files , token=cfg.SLACK_OAUTH_TOKEN )
+    return response
+
+
+def file_event_handler(say, files, team_id, user_id, thread_ts, question):
+    if files[0]["size"] > cfg.FILE_SIZE_LIMIT:
+        say(
+            "Sorry, the file you attached is larger than 2mb. Please try again with a smaller file",
+            thread_ts=thread_ts,
+        )
+        return {"status": "error"}
+    file_prompt = QuestionWithFileHandler(
+        question=question,
+        team_id=team_id,
+        user_id=user_id,
+        files=files,
+        token=cfg.SLACK_OAUTH_TOKEN,
+    )
     file_prompt_data = file_prompt.reconstruct_prompt_with_file()
-    if file_prompt_data['status']=='success':
-        question =  file_prompt_data['data']
-        return {"status":"success" , "question":question}
+    if file_prompt_data["status"] == "success":
+        question = file_prompt_data["data"]
+        return {"status": "success", "question": question}
     else:
-        say(file_prompt_data['message'] , thread_ts=thread_ts)
-        return { "status":"error" }
+        say(file_prompt_data["message"], thread_ts=thread_ts)
+        return {"status": "error"}
+
 
 @app.event("app_mention")
 def event_test(client, say, event):
     question = event["text"]
     thread_ts = event.get("thread_ts", None) or event["ts"]
     replies = client.conversations_replies(channel=event["channel"], ts=thread_ts)
     previous_messages = replies["messages"][:-1]
-
-
-    # check if the verbose is on
-    verbose_on = contains_verbose(question)
-    verbose_logger = (
-        SlackVerboseLogger(say, thread_ts) if verbose_on else DummyVerboseLogger()
-    )
+    previous_messages = convert_thread_history_messages(previous_messages)
 
     input_message = replies["messages"][-1]
-    user_id = input_message["user"] 
-    
-    # teamid is found on different places depending on the message from slack 
+    user_id = input_message["user"]
+
+    # teamid is found on different places depending on the message from slack
     # if file exist it will be inside one of the files other wise on the parent message
-    team_id = input_message['files'][0]["user_team"] if 'files' in input_message else input_message["team"] 
+    team_id = (
+        input_message["files"][0]["user_team"]
+        if "files" in input_message
+        else input_message["team"]
+    )
     combined_id = user_id + "_" + team_id
 
     if cfg.FLASK_DEBUG:
@@ -173,26 +189,42 @@ def event_test(client, say, event):
 
     if can_excute:
         if "files" in event:
-            files = event['files']
-            file_event = file_event_handler( files=files ,say=say ,team_id=team_id , thread_ts=thread_ts , user_id=user_id , question=question)
-            if file_event['status']=="error":
+            files = event["files"]
+            file_event = file_event_handler(
+                files=files,
+                say=say,
+                team_id=team_id,
+                thread_ts=thread_ts,
+                user_id=user_id,
+                question=question,
+            )
+            if file_event["status"] == "error":
                 return
             else:
-                question = file_event['question']
+                question = file_event["question"]
         else:
             # used to reconstruct the question. if the question contains a link recreate
             # them so that they contain scraped and summarized content of the link
             reconstructor = PromptReconstructor(
                 question=question, slack_message=[replies["messages"][-1]]
             )
             question = reconstructor.reconstruct_prompt()
-        results, _ = get_response(
-            question, previous_messages, verbose_logger, user_id, team_id
+
+        results = get_response(
+            question,
+            previous_messages,
+            user_id,
+            team_id,
+            verbose_logger=SlackVerboseLogger(say, thread_ts),
+            bot_info=bot,
         )
 
         say(results, thread_ts=thread_ts)
     else:
-        say(f"""I'm sorry for any inconvenience, but it appears you've gone over your daily token limit. Don't worry, you'll be able to use our service again in approximately {usage_cheker['time_left']}.Thank you for your patience and understanding.""", thread_ts=thread_ts)
+        say(
+            f"""I'm sorry for any inconvenience, but it appears you've gone over your daily token limit. Don't worry, you'll be able to use our service again in approximately {usage_cheker['time_left']}.Thank you for your patience and understanding.""",
+            thread_ts=thread_ts,
+        )
 
 
 @app.event("app_home_opened")

src/apps/slackapp/tests/test_get_response.py

@@ -0,0 +1,57 @@
+from datetime import datetime
+
+import pytest
+from slackapp.bolt_app import get_response
+
+import sherpa_ai.config as cfg
+from sherpa_ai.verbose_loggers import DummyVerboseLogger
+
+
+@pytest.mark.external_api
+def test_get_response_contains_todays_date():
+    question = "What is the date today, using the following format: YYYY-MM-DD?"
+    date = datetime.now().strftime("%Y-%m-%d")
+
+    if cfg.SERPER_API_KEY is None:
+        pytest.skip(
+            "SERPER_API_KEY not found in environment variables, skipping this test"
+        )
+
+    verbose_logger = DummyVerboseLogger()
+
+    response = get_response(
+        question=question,
+        previous_messages=[],
+        user_id="",
+        team_id="",
+        verbose_logger=verbose_logger,
+        bot_info={"user_id": "Sherpa"},
+    )
+    assert date in response, "Today's date not found in response"
+
+
+@pytest.mark.external_api
+def test_response_contains_correct_info():
+    question = "What is AutoGPT and how does it compare with MetaGPT"
+
+    if cfg.SERPER_API_KEY is None:
+        pytest.skip(
+            "SERPER_API_KEY not found in environment variables, skipping this test"
+        )
+
+    verbose_logger = DummyVerboseLogger()
+
+    response = get_response(
+        question=question,
+        previous_messages=[],
+        user_id="",
+        team_id="",
+        verbose_logger=verbose_logger,
+        bot_info={"user_id": "Sherpa"},
+    )
+
+    print(response)
+    assert response is not None
+    assert response != ""
+    assert "AutoGPT" in response
+    assert "MetaGPT" in response

src/pyproject.toml

@@ -43,7 +43,7 @@ pythonpath = [
   "."
 ]
 markers = [
-  "real:  this test calls 3rd party APIs"
+  "external_api:  this test calls 3rd party APIs"
 ]
 
 [tool.black]

src/sherpa_ai/actions/google_search.py

@@ -2,6 +2,7 @@
 from loguru import logger
 
 from sherpa_ai.actions.base import BaseAction
+from sherpa_ai.config.task_config import AgentConfig
 from sherpa_ai.tools import SearchTool
 
 SEARCH_SUMMARY_DESCRIPTION = """Role Description: {role_description}
@@ -23,6 +24,7 @@ def __init__(
         task: str,
         llm: BaseLanguageModel,
         description: str = SEARCH_SUMMARY_DESCRIPTION,
+        config: AgentConfig = AgentConfig(),
         n: int = 5,
     ):
         self.role_description = role_description
@@ -32,7 +34,7 @@ def __init__(
         self.llm = llm
         self.n = n
 
-        self.search_tool = SearchTool()
+        self.search_tool = SearchTool(config=config)
 
     def execute(self, query) -> str:
         result = self.search_tool._run(query)

src/sherpa_ai/actions/planning.py

@@ -116,8 +116,8 @@ def execute(
         self,
         task: str,
         agent_pool_description: str,
-        last_plan: Optional[str],
-        feedback: Optional[str],
+        last_plan: Optional[str] = None,
+        feedback: Optional[str] = None,
     ) -> Plan:
         """
         Execute the action

src/sherpa_ai/config.py → src/sherpa_ai/config/__init__.py

@@ -17,6 +17,8 @@
 from dotenv import find_dotenv, load_dotenv
 from loguru import logger
 
+from sherpa_ai.config.task_config import AgentConfig
+
 env_path = find_dotenv(usecwd=True)
 load_dotenv(env_path)
 
@@ -109,3 +111,7 @@ def check_vectordb_setting():
     logger.info("Config: OpenAI environment variables are set")
 
 check_vectordb_setting()
+
+__all__ = [
+    "AgentConfig",
+]