Spaces:
Sleeping
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Update app.py
Browse files
app.py
CHANGED
@@ -1,6 +1,7 @@
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import os
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import subprocess
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import streamlit as st
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from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
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import black
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from pylint import lint
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@@ -12,7 +13,16 @@ import requests
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from bs4 import BeautifulSoup
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from typing import List, Dict, Optional
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class InvalidActionError(Exception):
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"""Raised when an invalid action is provided."""
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pass
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@@ -25,18 +35,6 @@ class CodeGenerationError(Exception):
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"""Raised when code generation fails."""
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pass
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class CodeRefinementError(Exception):
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"""Raised when code refinement fails."""
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pass
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class CodeTestingError(Exception):
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"""Raised when code testing fails."""
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pass
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class CodeIntegrationError(Exception):
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"""Raised when code integration fails."""
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pass
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class AppTestingError(Exception):
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"""Raised when app testing fails."""
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pass
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@@ -53,14 +51,16 @@ class SearchError(Exception):
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"""Raised when search fails."""
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pass
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class AIAgent:
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def __init__(self):
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self.tools = {
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"SEARCH": self.search,
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"CODEGEN": self.code_generation,
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"REFINE-CODE":
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"TEST-CODE":
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"INTEGRATE-CODE":
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"TEST-APP": self.test_app,
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"GENERATE-REPORT": self.generate_report,
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"WORKSPACE-EXPLORER": self.workspace_explorer,
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@@ -82,10 +82,9 @@ class AIAgent:
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self.prompts: List[str] = [] # Store prompts for future use
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self.code_generator = pipeline('text-generation', model='gpt2') # Initialize code generator
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def search(self, query: str) -> List[str]:
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"""
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Performs a web search using the specified search engine.
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"""
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search_url = self.search_engine_url + query
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try:
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response = requests.get(search_url)
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@@ -96,68 +95,27 @@ class AIAgent:
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except requests.exceptions.RequestException as e:
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raise SearchError(f"Error during search: {e}")
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def code_generation(self, snippet: str) -> str:
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"""
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Generates code based on the provided snippet.
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"""
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try:
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generated_text = self.code_generator(snippet, max_length=500, num_return_sequences=1)[0]['generated_text']
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return generated_text
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except Exception as e:
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raise CodeGenerationError(f"Error during code generation: {e}")
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"""
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Refines the code in the specified file.
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"""
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try:
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with open(file_path, 'r') as f:
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code = f.read()
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refined_code = black.format_str(code, mode=black.FileMode())
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return refined_code
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except black.InvalidInput:
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raise CodeRefinementError("Error: Invalid code input for black formatting.")
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except Exception as e:
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raise CodeRefinementError(f"Error during code refinement: {e}")
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def test_code(self, file_path: str) -> str:
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"""
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Tests the code in the specified file.
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"""
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try:
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with open(file_path, 'r') as f:
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code = f.read()
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output = StringIO()
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lint.run(code, output=output)
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return output.getvalue()
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except Exception as e:
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raise CodeTestingError(f"Error during code testing: {e}")
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def integrate_code(self, file_path: str, code_snippet: str) -> str:
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"""
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Integrates the code snippet into the specified file.
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"""
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try:
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with open(file_path, 'a') as f:
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f.write(code_snippet)
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return "Code integrated successfully."
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except Exception as e:
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raise CodeIntegrationError(f"Error during code integration: {e}")
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def test_app(self) -> str:
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"""
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Tests the functionality of the app.
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"""
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try:
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subprocess.run(['streamlit', 'run', 'app.py'], check=True)
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return "App tested successfully."
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except subprocess.CalledProcessError as e:
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raise AppTestingError(f"Error during app testing: {e}")
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def generate_report(self) -> str:
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"""
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Generates a report based on the task history.
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"""
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report = f"## Task Report: {self.current_task}\n\n"
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for task in self.task_history:
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report += f"**Action:** {task['action']}\n"
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report += f"**Output:** {task['output']}\n\n"
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return report
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def workspace_explorer(self) -> str:
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"""
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Provides a workspace explorer functionality.
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"""
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try:
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current_directory = os.getcwd()
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directories = []
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@@ -183,20 +140,18 @@ class AIAgent:
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except Exception as e:
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raise WorkspaceExplorerError(f"Error during workspace exploration: {e}")
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def add_prompt(self, prompt: str) -> str:
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"""
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Adds a new prompt to the agent's knowledge base.
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"""
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try:
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self.prompts.append(prompt)
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return f"Prompt '{prompt}' added successfully."
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except Exception as e:
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raise PromptManagementError(f"Error adding prompt: {e}")
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def action_prompt(self, action: str) -> str:
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"""
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Provides a prompt for a specific action.
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"""
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try:
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if action == "SEARCH":
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return "What do you want to search for?"
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@@ -241,29 +196,25 @@ class AIAgent:
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except InvalidActionError as e:
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raise e
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def compress_history_prompt(self) -> str:
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"""
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Provides a prompt to compress the task history.
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"""
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return "Do you want to compress the task history?"
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def log_prompt(self) -> str:
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"""
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Provides a prompt to log a specific event.
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"""
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return "What event do you want to log?"
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def log_response(self, event: str) -> str:
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"""
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Logs the specified event.
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"""
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print(f"Event logged: {event}")
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return "Event logged successfully."
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def modify_prompt(self, prompt: str) -> str:
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"""
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Modifies an existing prompt.
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"""
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try:
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# Find the prompt to modify
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# Update the prompt
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except Exception as e:
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raise PromptManagementError(f"Error modifying prompt: {e}")
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def prefix(self, text: str) -> str:
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"""
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Adds a prefix to the provided text.
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"""
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return f"PREFIX: {text}"
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def search_query(self, query: str) -> str:
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"""
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Provides a search query for the specified topic.
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"""
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return f"Search query: {query}"
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def read_prompt(self, file_path: str) -> str:
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"""
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Provides a prompt to read the contents of a file.
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"""
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try:
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with open(file_path, 'r') as f:
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contents = f.read()
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return contents
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except Exception as e:
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raise InvalidInputError(f"Error reading file: {e}")
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def task_prompt(self) -> str:
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"""
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Provides a prompt to start a new task.
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"""
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return "What task do you want to start?"
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def understand_test_results_prompt(self) -> str:
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"""
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Provides a prompt to understand the test results.
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"""
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return "What do you want to know about the test results?"
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def handle_input(self, input_str: str):
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"""
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"""
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if input_str:
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action, *args = input_str.split()
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if action in self.tools:
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if args:
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print(f"Action: {action}\nInput: {' '.join(args)}\nOutput: {self.tools[action](' '.join(args))}")
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else:
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raise InvalidActionError("Invalid action. Please choose a valid action from the list of tools.")
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CodeTestingError, CodeIntegrationError, AppTestingError, WorkspaceExplorerError,
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PromptManagementError, SearchError) as e:
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print(f"Error: {e}")
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def run(self):
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"""
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Runs the agent continuously, waiting for user input.
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"""
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while True:
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input_str = input("Enter a command for the AI Agent: ")
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self.handle_input(input_str)
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if __name__ == '__main__':
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agent = AIAgent()
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st.title("AI Agent")
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import os
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import subprocess
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import streamlit as st # For Streamlit
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import gradio as gr # For Gradio
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from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
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import black
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from pylint import lint
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from bs4 import BeautifulSoup
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from typing import List, Dict, Optional
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from utils.code_utils import (
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refine_code,
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test_code,
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integrate_code,
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CodeRefinementError,
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CodeTestingError,
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CodeIntegrationError,
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)
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# --- Define custom exceptions for better error handling ---
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class InvalidActionError(Exception):
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"""Raised when an invalid action is provided."""
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pass
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"""Raised when code generation fails."""
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pass
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class AppTestingError(Exception):
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"""Raised when app testing fails."""
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pass
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"""Raised when search fails."""
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pass
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# --- Define a class for the AI Agent ---
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class AIAgent:
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def __init__(self):
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# --- Initialize tools and attributes ---
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self.tools = {
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"SEARCH": self.search,
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"CODEGEN": self.code_generation,
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"REFINE-CODE": refine_code, # Use external function
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"TEST-CODE": test_code, # Use external function
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"INTEGRATE-CODE": integrate_code, # Use external function
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"TEST-APP": self.test_app,
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"GENERATE-REPORT": self.generate_report,
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"WORKSPACE-EXPLORER": self.workspace_explorer,
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self.prompts: List[str] = [] # Store prompts for future use
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self.code_generator = pipeline('text-generation', model='gpt2') # Initialize code generator
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# --- Implement search functionality ---
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def search(self, query: str) -> List[str]:
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"""Performs a web search using the specified search engine."""
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search_url = self.search_engine_url + query
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try:
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response = requests.get(search_url)
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except requests.exceptions.RequestException as e:
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raise SearchError(f"Error during search: {e}")
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# --- Implement code generation functionality ---
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def code_generation(self, snippet: str) -> str:
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"""Generates code based on the provided snippet."""
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try:
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generated_text = self.code_generator(snippet, max_length=500, num_return_sequences=1)[0]['generated_text']
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return generated_text
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except Exception as e:
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raise CodeGenerationError(f"Error during code generation: {e}")
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# --- Implement app testing functionality ---
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def test_app(self) -> str:
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"""Tests the functionality of the app."""
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try:
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subprocess.run(['streamlit', 'run', 'app.py'], check=True)
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return "App tested successfully."
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except subprocess.CalledProcessError as e:
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raise AppTestingError(f"Error during app testing: {e}")
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# --- Implement report generation functionality ---
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def generate_report(self) -> str:
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"""Generates a report based on the task history."""
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report = f"## Task Report: {self.current_task}\n\n"
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for task in self.task_history:
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report += f"**Action:** {task['action']}\n"
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report += f"**Output:** {task['output']}\n\n"
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return report
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# --- Implement workspace exploration functionality ---
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def workspace_explorer(self) -> str:
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"""Provides a workspace explorer functionality."""
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try:
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current_directory = os.getcwd()
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directories = []
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except Exception as e:
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raise WorkspaceExplorerError(f"Error during workspace exploration: {e}")
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# --- Implement prompt management functionality ---
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def add_prompt(self, prompt: str) -> str:
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"""Adds a new prompt to the agent's knowledge base."""
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try:
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self.prompts.append(prompt)
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return f"Prompt '{prompt}' added successfully."
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except Exception as e:
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raise PromptManagementError(f"Error adding prompt: {e}")
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# --- Implement prompt generation functionality ---
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def action_prompt(self, action: str) -> str:
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"""Provides a prompt for a specific action."""
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try:
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if action == "SEARCH":
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return "What do you want to search for?"
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except InvalidActionError as e:
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raise e
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# --- Implement prompt generation functionality ---
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def compress_history_prompt(self) -> str:
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"""Provides a prompt to compress the task history."""
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return "Do you want to compress the task history?"
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# --- Implement prompt generation functionality ---
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def log_prompt(self) -> str:
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"""Provides a prompt to log a specific event."""
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return "What event do you want to log?"
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# --- Implement logging functionality ---
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def log_response(self, event: str) -> str:
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"""Logs the specified event."""
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print(f"Event logged: {event}")
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return "Event logged successfully."
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# --- Implement prompt modification functionality ---
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def modify_prompt(self, prompt: str) -> str:
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"""Modifies an existing prompt."""
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try:
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# Find the prompt to modify
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# Update the prompt
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except Exception as e:
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raise PromptManagementError(f"Error modifying prompt: {e}")
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# --- Implement prefix functionality ---
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def prefix(self, text: str) -> str:
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"""Adds a prefix to the provided text."""
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return f"PREFIX: {text}"
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# --- Implement search query generation functionality ---
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def search_query(self, query: str) -> str:
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"""Provides a search query for the specified topic."""
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return f"Search query: {query}"
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# --- Implement file reading functionality ---
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def read_prompt(self, file_path: str) -> str:
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"""Provides a prompt to read the contents of a file."""
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try:
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with open(file_path, 'r') as f:
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contents = f.read()
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return contents
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except FileNotFoundError:
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raise InvalidInputError(f"Error: File not found: {file_path}")
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except Exception as e:
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raise InvalidInputError(f"Error reading file: {e}")
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# --- Implement task prompt generation functionality ---
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def task_prompt(self) -> str:
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"""Provides a prompt to start a new task."""
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return "What task do you want to start?"
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# --- Implement test results understanding prompt generation functionality ---
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def understand_test_results_prompt(self) -> str:
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"""Provides a prompt to understand the test results."""
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return "What do you want to know about the test results?"
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# --- Implement input handling functionality ---
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258 |
def handle_input(self, input_str: str):
|
259 |
+
"""Handles user input and executes the corresponding action."""
|
260 |
+
try:
|
|
|
|
|
261 |
action, *args = input_str.split()
|
262 |
if action in self.tools:
|
263 |
if args:
|
|
|
275 |
print(f"Action: {action}\nInput: {' '.join(args)}\nOutput: {self.tools[action](' '.join(args))}")
|
276 |
else:
|
277 |
raise InvalidActionError("Invalid action. Please choose a valid action from the list of tools.")
|
278 |
+
except (InvalidActionError, InvalidInputError, CodeGenerationError,
|
279 |
+
CodeRefinementError, CodeTestingError, CodeIntegrationError,
|
280 |
+
AppTestingError, WorkspaceExplorerError, PromptManagementError,
|
281 |
+
SearchError) as e:
|
|
|
|
|
282 |
print(f"Error: {e}")
|
283 |
|
284 |
+
# --- Implement the main loop of the agent ---
|
285 |
def run(self):
|
286 |
+
"""Runs the agent continuously, waiting for user input."""
|
|
|
|
|
287 |
while True:
|
288 |
input_str = input("Enter a command for the AI Agent: ")
|
289 |
self.handle_input(input_str)
|
290 |
|
291 |
+
# --- Streamlit Integration ---
|
292 |
if __name__ == '__main__':
|
293 |
agent = AIAgent()
|
294 |
st.title("AI Agent")
|