agent

LikithMeruvu · LikithMeruvu · commit f4b0c8285b75 · 2024-06-08T13:18:52.000+05:30
diff --git a/main.py b/main.py
@@ -1,43 +1,3 @@
-# from langchain.agents import initialize_agent
-# from langchain_experimental.utilities import PythonREPL
-# from langchain_community.tools.ddg_search.tool import DuckDuckGoSearchRun
-# from langchain_core.tools import Tool
-# from langchain_groq import ChatGroq
-
-# # Create the Python REPL tool
-# python_repl = PythonREPL()
-# python_repl_tool = Tool(
-#     name="python_repl",
-#     description="A Python shell. Use this to execute python commands. Input should be a valid python command. If you want to see the output of a value, you should print it out with `print(...)`.",
-#     func=python_repl.run,
-# )
-
-# # Create the DuckDuckGo search tool
-# duckduckgo_search = DuckDuckGoSearchRun()
-# duckduckgo_search_tool = Tool(
-#     name="duckduckgo_search",
-#     description="A wrapper around DuckDuckGo Search. Useful for when you need to answer questions about current events. Input should be a search query.",
-#     func=duckduckgo_search.run,
-# )
-
-# # Create the list of tools
-# tools = [python_repl_tool, duckduckgo_search_tool]
-
-# # Initialize the LLM
-# llm = ChatGroq(temperature=0, groq_api_key="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", model_name="llama3-70b-8192")
-
-# # Initialize the agent
-# agent = initialize_agent(tools, llm, agent_type="zero-shot-react-description")
-
-# # Run the agent
-# while True:
-#     user_input = input("Enter a command or search query (or 'quit' to stop): ")
-#     if user_input.lower() == 'quit':
-#         break
-#     result = agent.run(user_input)
-#     print(result)
-
-
 
 from langchain.agents import initialize_agent
 from langchain_experimental.utilities import PythonREPL
diff --git a/openai-agent.py b/openai-agent.py
@@ -0,0 +1,95 @@
+import logging
+from crewai import Agent, Task, Crew, Process
+from langchain.agents import Tool
+from langchain_experimental.utilities import PythonREPL
+from langchain_community.tools import DuckDuckGoSearchRun
+
+import os
+os.environ["OPENAI_API_KEY"] = "your_key"
+
+# Create the Python REPL tool
+python_repl = PythonREPL()
+python_repl_tool = Tool(
+    name="python_repl",
+    description="This tool can execute python code and shell commands Use with caution",
+    func=python_repl.run,
+)
+
+# Create the DuckDuckGo search tool
+duckduckgo_search_tool = Tool(
+    name="duckduckgo_search",
+    description="A wrapper around DuckDuckGo Search.",
+    func=DuckDuckGoSearchRun().run,
+)
+
+class CustomAgent(Agent):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.max_attempts = 3
+        self.attempts = 0
+
+    def run(self, task):
+        if self.attempts < self.max_attempts:
+            self.attempts += 1
+            return super().run(task)
+        else:
+            return "Task failed after {} attempts.".format(self.max_attempts)
+
+coderAgent = CustomAgent(
+    role='Senior Software engineer and developer',
+    goal='Write production grade bug free code on this user prompt :- {topic}',
+    verbose=True,
+    memory=True,
+    backstory="You are an experienced developer in big tech companies",
+    max_iter=5,
+    max_rpm=2,
+    tools=[duckduckgo_search_tool],
+    allow_delegation=True
+)
+
+DebuggerAgent = CustomAgent(
+    role='Code Debugger and bug solving agent',
+    goal='You debug the code line by line and solve bugs and errors in the code by using Python_repl tool',
+    verbose=True,
+    memory=True,
+    backstory="You are a debugger agent with access to a python interpreter",
+    tools=[duckduckgo_search_tool, python_repl_tool],
+    max_iter=5,
+    max_rpm=2,
+    allow_delegation=True
+)
+
+coding_task = Task(
+    description="Write code in this {topic}.",
+    expected_output='A Bug-free and production-grade code on {topic}',
+    tools=[duckduckgo_search_tool],
+    agent=coderAgent,
+)
+
+debug_task = Task(
+    description="You should run the python code given by the CoderAgent and Check for bugs and errors",
+    expected_output='you should communicate to CoderAgent and give feedback on the code if the code got error while execution',
+    tools=[duckduckgo_search_tool, python_repl_tool],
+    agent=DebuggerAgent,
+    output_file='temp.py'
+)
+
+Final_check = Task(
+    description="You fill finalize the Code which is verified by debugger agent Which is error free no bugs",
+    expected_output="You should communicate to DebuggerAgent and if the code is bug free and executed Without errors then return the code to user",
+    agent=coderAgent,
+    tools=[duckduckgo_search_tool]
+)
+
+crew = Crew(
+    agents=[coderAgent, DebuggerAgent],
+    tasks=[coding_task, debug_task, Final_check],
+    process=Process.sequential,
+    memory=True,
+    cache=True,
+    max_rpm=5,
+    share_crew=True
+)
+
+result = crew.kickoff(inputs={'topic': 'Write me code for A* searching algo using python'})
+print(result)
diff --git a/python-coding-agent.py b/python-coding-agent.py
@@ -0,0 +1,88 @@
+import logging
+from crewai import Agent, Task, Crew, Process
+from langchain.agents import Tool
+from langchain_experimental.utilities import PythonREPL
+from langchain_community.tools import DuckDuckGoSearchRun
+from langchain_groq import ChatGroq
+
+import os
+os.environ["OPENAI_API_KEY"] = "Your_api"
+
+llm = ChatGroq(temperature=0, groq_api_key="Your_api", model_name="llama3-70b-8192")
+
+
+# Create the Python REPL tool
+python_repl = PythonREPL()
+python_repl_tool = Tool(
+    name="python_repl",
+    description="This tool can execute python code and shell commands (pip commands to modules installation) Use with caution",
+    func=python_repl.run,
+)
+
+# Create the DuckDuckGo search tool
+duckduckgo_search_tool = Tool(
+    name="duckduckgo_search",
+    description="A wrapper around DuckDuckGo Search.",
+    func=DuckDuckGoSearchRun().run,
+)
+
+coderAgent = Agent(
+    role='Senior Software engineer and developer',
+    goal='Write production grade bug free code on this user prompt :- {topic}',
+    verbose=True,
+    memory=True,
+    backstory="You are an experienced developer in big tech companies",
+    max_iter=3,
+    llm = llm,
+    max_rpm=10,
+    tools=[duckduckgo_search_tool],
+    allow_delegation=False
+)
+
+DebuggerAgent = Agent(
+    role='Code Debugger and bug solving agent',
+    goal='You debug the code line by line and solve bugs and errors in the code by using Python_repl tool. You also have Access to search tool which can assist you for searching that bug',
+    verbose=True,
+    memory=True,
+    backstory="You are a debugger agent with access to a python interpreter",
+    tools=[duckduckgo_search_tool, python_repl_tool],
+    max_iter=3,
+    llm = llm,
+    max_rpm=10,
+    allow_delegation=True
+)
+
+coding_task = Task(
+    description="Write code in this {topic}.",
+    expected_output='A Bug-free and production-grade code on {topic}',
+    tools=[duckduckgo_search_tool],
+    agent=coderAgent,
+)
+
+debug_task = Task(
+    description="You should run the python code given by the CoderAgent and Check for bugs and errors",
+    expected_output='you should communicate to CoderAgent and give feedback on the code if the code got error while execution',
+    tools=[duckduckgo_search_tool, python_repl_tool],
+    agent=DebuggerAgent,
+    output_file='temp.py'
+)
+
+Final_check = Task(
+    description="You fill finalize the Code which is verified by debugger agent Which is error free no bugs",
+    expected_output="You should communicate to DebuggerAgent and if the code is bug free and executed Without errors then return the code to user",
+    agent=coderAgent,
+    tools=[duckduckgo_search_tool]
+)
+
+crew = Crew(
+    agents=[coderAgent, DebuggerAgent],
+    tasks=[coding_task, debug_task, Final_check],
+    process=Process.sequential,
+    memory=True,
+    cache=True,
+    max_rpm=25,
+    share_crew=True
+)
+
+result = crew.kickoff(inputs={'topic': 'Write me code for djkastra searching algo using python'})
+print(result)
diff --git a/t.py b/t.py
diff --git a/temp.py b/temp.py
@@ -1,70 +1,41 @@
-from langchain.agents import initialize_agent
-from langchain_experimental.utilities import PythonREPL
-from langchain_community.tools.ddg_search.tool import DuckDuckGoSearchRun
-from langchain_core.tools import Tool
-from langchain_groq import ChatGroq
-from langchain_community.agent_toolkits import FileManagementToolkit
-# from tempfile import TemporaryDirectory
-import os
+The code has a bug. The error is a NameError("name 'sys' is not defined"). This error occurs because the 'sys' module is not imported. 
 
-# Create the temporary directory for file operations
-working_directory = os.getcwd()
+The corrected code is:
 
-# Create the file management toolkit
-file_management_toolkit = FileManagementToolkit(root_dir=str(working_directory))
-file_tools = file_management_toolkit.get_tools()
+```
+import sys
+import heapq
 
-# Extract individual file operation tools
-read_tool, write_tool, list_tool, copy_tool, delete_tool, move_tool, search_tool = file_tools
+def dijkstra(graph, start):
+    distances = {node: sys.maxsize for node in graph}
+    distances[start] = 0
+    pq = [(0, start)]
 
-# Wrap the file operation tools with Tool class
-read_file_tool = Tool(
-    name="read_file",
-    description="Read a file from the file system.",
-    func=read_tool.invoke,
-)
+    while pq:
+        current_distance, current_node = heapq.heappop(pq)
 
-write_file_tool = Tool(
-    name="write_file",
-    description="Write a file to the file system.",
-    func=write_tool.invoke,
-)
+        if current_distance > distances[current_node]:
+            continue
 
-list_directory_tool = Tool(
-    name="list_directory",
-    description="List files in a directory.",
-    func=list_tool.invoke,
-)
+        for neighbor, weight in graph[current_node].items():
+            distance = current_distance + weight
 
-# Create the Python REPL tool
-python_repl = PythonREPL()
-python_repl_tool = Tool(
-    name="python_repl",
-    description="A Python shell. Use this to execute python commands. Input should be a valid python command. If you want to see the output of a value, you should print it out with `print(...)`.",
-    func=python_repl.run,
-)
+            if distance < distances[neighbor]:
+                distances[neighbor] = distance
+                heapq.heappush(pq, (distance, neighbor))
 
-# Create the DuckDuckGo search tool
-duckduckgo_search = DuckDuckGoSearchRun()
-duckduckgo_search_tool = Tool(
-    name="duckduckgo_search",
-    description="A wrapper around DuckDuckGo Search. Useful for when you need to answer questions about current events. Input should be a search query.",
-    func=duckduckgo_search.run,
-)
+    return distances
 
-# Create the list of tools
-tools = [python_repl_tool, duckduckgo_search_tool, read_file_tool, write_file_tool, list_directory_tool]
+graph = {
+    'A': {'B': 1, 'C': 4},
+    'B': {'A': 1, 'C': 2, 'D': 5},
+    'C': {'A': 4, 'B': 2, 'D': 1},
+    'D': {'B': 5, 'C': 1}
+}
 
-# Initialize the LLM
-llm = ChatGroq(temperature=0, groq_api_key="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", model_name="llama3-8b-8192")
+start_node = 'A'
+result = dijkstra(graph, start_node)
+print(f"Shortest distances from {start_node}: {result}")
+```
 
-# Initialize the agent
-agent = initialize_agent(tools, llm, agent_type="zero-shot-react-description")
-
-# Run the agent
-while True:
-    user_input = input("Enter a command or search query (or 'quit' to stop): ")
-    if user_input.lower() == 'quit':
-        break
-    result = agent.run(user_input)
-    print(result)
+This code should run without errors and produce the correct output.
diff --git a/x.py b/x.py
