├── .gitignore ├── LICENSE ├── README.md ├── agent ├── agent.py └── prompts.py ├── app.py ├── images ├── bugout.png └── sw.PNG └── llm ├── deepseek_lite_api.py └── qwen_api.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | MYENV 90 | 91 | # pipenv 92 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 93 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 94 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 95 | # install all needed dependencies. 96 | #Pipfile.lock 97 | 98 | # UV 99 | # Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control. 100 | # This is especially recommended for binary packages to ensure reproducibility, and is more 101 | # commonly ignored for libraries. 102 | #uv.lock 103 | 104 | # poetry 105 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 106 | # This is especially recommended for binary packages to ensure reproducibility, and is more 107 | # commonly ignored for libraries. 108 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 109 | #poetry.lock 110 | 111 | # pdm 112 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 113 | #pdm.lock 114 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 115 | # in version control. 116 | # https://pdm.fming.dev/latest/usage/project/#working-with-version-control 117 | .pdm.toml 118 | .pdm-python 119 | .pdm-build/ 120 | 121 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 122 | __pypackages__/ 123 | 124 | # Celery stuff 125 | celerybeat-schedule 126 | celerybeat.pid 127 | 128 | # SageMath parsed files 129 | *.sage.py 130 | 131 | # Environments 132 | .env 133 | .venv 134 | env/ 135 | venv/ 136 | ENV/ 137 | env.bak/ 138 | venv.bak/ 139 | 140 | # Spyder project settings 141 | .spyderproject 142 | .spyproject 143 | 144 | # Rope project settings 145 | .ropeproject 146 | 147 | # mkdocs documentation 148 | /site 149 | 150 | # mypy 151 | .mypy_cache/ 152 | .dmypy.json 153 | dmypy.json 154 | 155 | # Pyre type checker 156 | .pyre/ 157 | 158 | # pytype static type analyzer 159 | .pytype/ 160 | 161 | # Cython debug symbols 162 | cython_debug/ 163 | 164 | # PyCharm 165 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 166 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 167 | # and can be added to the global gitignore or merged into this file. 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Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. 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Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # BugOut: Your AI-Powered Pythonic Coding Agent 🐞💻 2 | ![BugOut Logo](images/bugout.png) 3 | 4 | **BugOut** is a fairly early **proof-of-concept (PoC)** Python coding agent that demonstrates how you can build a local code-generation and execution agent from scratch. It leverages a locally running “DeepSeek Lite” API (`llm/deepseek_lite_api.py`) to generate code. The code is then automatically run and refined until it executes without errors, or until a set iteration limit is reached. 5 | 6 | ## 7 | 8 | ## Key Features 9 | 10 | 1. **Local LLM API Integration** 11 | - BugOut calls your locally running LLM endpoint (DeepSeek Lite) to generate Python code based on instructions and user prompts. 12 | - Uses streaming responses to capture code as it’s generated. 13 | 14 | 2. **Conversation Management** 15 | - Maintains a conversation list (`self.conversation`) with: 16 | - A “system” prompt that provides instructions to the LLM. 17 | - A sequence of user prompts or feedback. 18 | - The LLM’s replies, including any generated code. 19 | 20 | 3. **Iterative Refinement** 21 | - If code execution returns an error, BugOut re-injects the error output into the conversation, prompting the LLM to provide a refined solution. 22 | - Planning and Reflection 23 | - This loop continues until: 24 | - The code executes successfully, or 25 | - The maximum iteration count (`max_iterations`) is reached. 26 | - Writes the code to a **temporary `.py` file**—rather than using `exec()`—and then runs it in a subprocess for safety and isolation. 27 | 28 | # BugOut: Operating in a Multi-Agent Swarm 29 | [![Watch the video](images/sw.PNG)](https://www.youtube.com/watch?v=KIvso5oaS8c&t) 30 | 31 | 32 | 33 | -------------------------------------------------------------------------------- /agent/agent.py: -------------------------------------------------------------------------------- 1 | import requests 2 | import json 3 | import re 4 | import os 5 | import tempfile 6 | import subprocess 7 | import sys 8 | from termcolor import colored 9 | from agent.prompts import SYSTEM_PROMPT, error_prompt 10 | 11 | ###################################################################### 12 | # 1) HELPER: Extract lines around the error 13 | ###################################################################### 14 | def detect_error_lines(code_str, error_msg, context_radius=3): 15 | """ 16 | Given the raw code string and an error message, attempt to find any line number 17 | references in the error. For each line number found, capture a small snippet of code 18 | (context_radius lines before and after). 19 | 20 | Returns a string with the relevant lines, or an empty string if none found. 21 | """ 22 | line_numbers = re.findall(r"line\s+(\d+)", error_msg) 23 | if not line_numbers: 24 | return "" # no line info found 25 | 26 | lines = code_str.split("\n") 27 | snippets = [] 28 | 29 | for ln_str in line_numbers: 30 | try: 31 | ln = int(ln_str) 32 | except ValueError: 33 | continue 34 | 35 | start_index = max(0, ln - 1 - context_radius) 36 | end_index = min(len(lines), ln - 1 + context_radius + 1) 37 | snippet_lines = lines[start_index:end_index] 38 | 39 | snippet_annotated = [] 40 | for i, _ in enumerate(range(start_index, end_index)): 41 | real_line_num = start_index + i + 1 42 | prefix = "==> " if real_line_num == ln else " " 43 | snippet_annotated.append(f"{prefix}{real_line_num}: {snippet_lines[i]}") 44 | 45 | snippet_block = "\n".join(snippet_annotated) 46 | snippets.append(f"Relevant code around line {ln}:\n{snippet_block}\n") 47 | 48 | return "\n".join(snippets) 49 | 50 | 51 | ###################################################################### 52 | # 2) HELPER: Summarize the attempt with the LLM 53 | ###################################################################### 54 | def summarize_attempt_with_llm(llm_url, code, error_msg, iteration, token_limit=200): 55 | """ 56 | Calls the LLM *again* to produce a short summary (~200 tokens) of: 57 | - The code snippet 58 | - The lines around the error, if any 59 | - The error message 60 | Then returns that short summary string. 61 | """ 62 | relevant_snippet = detect_error_lines(code, error_msg) 63 | system_instruction = { 64 | "role": "system", 65 | "content": ( 66 | "You are a helpful assistant that summarizes code in 5 sentences. " 67 | "Include the key functionality only and the error to provide context." 68 | ) 69 | } 70 | user_input = { 71 | "role": "user", 72 | "content": ( 73 | f"This is attempt #{iteration}. Please summarize:\n\n" 74 | f"--- CODE ---\n{code}\n\n" 75 | f"--- RELEVANT SNIPPET ---\n{relevant_snippet}\n\n" 76 | f"--- ERROR ---\n{error_msg}\n\n" 77 | f"Please keep it under ~{token_limit} tokens." 78 | ) 79 | } 80 | conversation = [system_instruction, user_input] 81 | headers = {"Content-Type": "application/json"} 82 | data = {"messages": conversation} 83 | 84 | try: 85 | resp = requests.post(llm_url, headers=headers, data=json.dumps(data)) 86 | resp.raise_for_status() 87 | summary_text = resp.text.strip() 88 | except Exception as e: 89 | fallback_summary = ( 90 | f"Attempt #{iteration} - Summarizer call failed. Error excerpt: {error_msg[:100]}" 91 | ) 92 | return fallback_summary 93 | 94 | return f"[SUMMARY OF ATTEMPT #{iteration}]\n{summary_text}\n" 95 | 96 | 97 | ###################################################################### 98 | # 3) HELPER: Analyze unit test output using the LLM 99 | ###################################################################### 100 | def analyze_unit_test_with_llm(content, llm_url, token_limit=200, max_attempts=15): 101 | """ 102 | Calls the LLM *again* to produce an analysis of: 103 | - The unit test output file. 104 | It keeps calling the LLM with a reminder message until the response is 105 | properly formatted with the required [BOOL] and [SUMMARY] tags. 106 | Then returns a BOOL and a short summary string. 107 | """ 108 | system_instruction = { 109 | "role": "system", 110 | "content": ( 111 | "You are a helpful assistant that analyzes unit test code results in 5 sentences. " 112 | "You follow a strict format of: " 113 | "[BOOL] a **bool value** if the results passed or failed [/BOOL] " 114 | "[SUMMARY] a short summary of the results [/SUMMARY] " 115 | "**Note: Only provide a TRUE or FALSE value in the [BOOL] wrapper." 116 | ) 117 | } 118 | user_input = { 119 | "role": "user", 120 | "content": ( 121 | f"Below is the content of the unit test log file. Please analyze the results to see if the code has passed tests:\n\n" 122 | f"--- UNIT TEST LOG CONTENT ---\n{content}\n\n" 123 | f"Please keep it under ~{token_limit} tokens." 124 | ) 125 | } 126 | conversation = [system_instruction, user_input] 127 | headers = {"Content-Type": "application/json"} 128 | reminder_msg = ( 129 | "You forgot to properly enclose your response with the required [BOOL] and [SUMMARY] tags. " 130 | "Please resend your answer in the correct format." 131 | ) 132 | 133 | attempts = 0 134 | llm_full_res = "" 135 | while attempts < max_attempts: 136 | attempts += 1 137 | try: 138 | data = {"messages": conversation} 139 | resp = requests.post(llm_url, headers=headers, data=json.dumps(data)) 140 | resp.raise_for_status() 141 | llm_full_res = resp.text.strip() 142 | except Exception as e: 143 | return False, "Unit test analyzer call failed." 144 | 145 | # Parse out [BOOL] and [SUMMARY] 146 | bool_match = re.search(r'\[BOOL\]\s*(TRUE|FALSE)\s*\[/BOOL\]', llm_full_res, re.IGNORECASE) 147 | summary_match = re.search(r'\[SUMMARY\]\s*(.*?)\s*\[/SUMMARY\]', llm_full_res, re.DOTALL) 148 | 149 | if bool_match and summary_match: 150 | bool_value = bool_match.group(1).strip().upper() 151 | pass_fail = True if bool_value == "TRUE" else False 152 | summary = summary_match.group(1).strip() 153 | return pass_fail, summary 154 | else: 155 | # Append reminder message for re-attempt 156 | conversation.append({"role": "user", "content": reminder_msg}) 157 | 158 | return False, f"Max attempts reached. Last response: {llm_full_res}" 159 | 160 | 161 | ###################################################################### 162 | # 4) Updated BugOutAgent Class with Final Check of Unit Test Results 163 | ###################################################################### 164 | class BugOutAgent: 165 | def __init__(self, llm_url, log_file): 166 | self.llm_url = llm_url 167 | self.log_file = log_file 168 | 169 | self.conversation = [] 170 | self.max_iterations = 50 171 | 172 | # The initial system message 173 | system_msg = { 174 | "role": "system", 175 | "content": SYSTEM_PROMPT 176 | } 177 | self.conversation.append(system_msg) 178 | 179 | self.user_request_msg = None 180 | self.attempts_summary = "" 181 | self.last_code = None 182 | 183 | def add_message(self, role, input_text): 184 | return {"role": role, "content": input_text} 185 | 186 | def call_llm(self): 187 | """ 188 | Sends self.conversation to the LLM API and returns (final_text, code). 189 | """ 190 | headers = {"Content-Type": "application/json"} 191 | code_marker = "```python" 192 | final_text = "" 193 | 194 | while code_marker not in final_text: 195 | data = {"messages": self.conversation} 196 | 197 | with open(self.log_file, "a", encoding="utf-8") as f: 198 | f.write(f"\n\nConversation:\n{self.conversation}") 199 | 200 | try: 201 | with requests.post(self.llm_url, headers=headers, data=json.dumps(data), stream=True) as r: 202 | r.raise_for_status() 203 | chunk_texts = [] 204 | for chunk in r.iter_content(chunk_size=None): 205 | token_str = chunk.decode("utf-8") 206 | print(colored(token_str, "yellow"), end="", flush=True) 207 | chunk_texts.append(token_str) 208 | final_text = "".join(chunk_texts) 209 | 210 | msg = self.add_message("assistant", final_text) 211 | self.conversation.append(msg) 212 | 213 | with open(self.log_file, "a", encoding="utf-8") as f: 214 | f.write(f"\n\nLLM RAW Response:\n{final_text}") 215 | 216 | except Exception as e: 217 | print(colored(f"\n\nError during LLM API call:\n{str(e)}", "red")) 218 | return None, None 219 | 220 | code_blocks = re.findall(r'```python(.*?)```', final_text, re.DOTALL) 221 | if code_blocks: 222 | if len(code_blocks) == 1: 223 | print("\n\nSingle code block found") 224 | code = code_blocks[0].strip() 225 | else: 226 | print("\n\nMultiple code blocks found") 227 | code = "\n\n".join(block.strip() for block in code_blocks) 228 | 229 | with open(self.log_file, "a", encoding="utf-8") as f: 230 | f.write(f"\n\nCode Generated:\n{code}") 231 | 232 | return final_text, code 233 | 234 | reminder_msg = ( 235 | f"You forgot to properly enclose your code with {code_marker}.\n" 236 | "Please resend the response with proper Python code enclosures." 237 | ) 238 | self.conversation.append(self.add_message("user", reminder_msg)) 239 | 240 | return final_text, None 241 | 242 | def run_code(self, code, timeout=90): 243 | """Executes code in a subprocess and returns (success, result).""" 244 | print(colored(f"\n\n===>Executing Code:\n\n", "cyan")) 245 | 246 | with tempfile.NamedTemporaryFile(mode='w', suffix=".py", delete=False) as tmp_file: 247 | script_path = tmp_file.name 248 | tmp_file.write(code) 249 | 250 | try: 251 | proc = subprocess.Popen( 252 | [sys.executable, script_path], 253 | stdout=subprocess.PIPE, 254 | stderr=subprocess.PIPE, 255 | text=True 256 | ) 257 | try: 258 | stdout, stderr = proc.communicate(timeout=timeout) 259 | except subprocess.TimeoutExpired: 260 | proc.kill() 261 | stdout, stderr = proc.communicate() 262 | return_code = proc.returncode 263 | 264 | with open(self.log_file, "a", encoding="utf-8") as f: 265 | f.write(f"\n\n=== Subprocess Execution (Timed Out) ===\n") 266 | f.write(f"Script: {script_path}\n") 267 | f.write(f"Timeout: {timeout} seconds\n") 268 | f.write(f"STDOUT:\n{stdout}\n") 269 | f.write(f"STDERR:\n{stderr}\n") 270 | 271 | print(colored("\n\nError: Code execution timed out!", "red")) 272 | return False, f"Execution timed out after {timeout} seconds." 273 | 274 | return_code = proc.returncode 275 | with open(self.log_file, "a", encoding="utf-8") as f: 276 | f.write(f"\n\n=== Subprocess Execution ===\n") 277 | f.write(f"Script: {script_path}\n") 278 | f.write(f"Return code: {return_code}\n") 279 | f.write(f"STDOUT:\n{stdout}\n") 280 | f.write(f"STDERR:\n{stderr}\n") 281 | 282 | if return_code == 0: 283 | print(colored("\n\nGood Code Execution (no Python error)!", "green")) 284 | print("STDOUT:", stdout) 285 | else: 286 | print(colored("\n\nError Encountered (subprocess non-zero exit)!", "red")) 287 | print("STDERR:", stderr) 288 | 289 | os.remove(script_path) 290 | 291 | if return_code != 0: 292 | return False, f"Script exited with code {return_code}\n\nSTDERR:\n{stderr}" 293 | 294 | return True, stdout 295 | 296 | except Exception as e: 297 | print(colored(f"\n\nError Encountered:\n{str(e)}", "red")) 298 | with open(self.log_file, "a", encoding="utf-8") as f: 299 | f.write(f"\n\nError Encountered:\n{str(e)}\n") 300 | return False, str(e) 301 | finally: 302 | if os.path.exists(script_path): 303 | os.remove(script_path) 304 | 305 | def final_check_unit_tests(self): 306 | """ 307 | Final check after successful execution: 308 | - Look for unit test result files in the output/ directory. 309 | - Verify that at least one file (e.g., one with 'test' in its name) exists. 310 | - Read the file's contents to determine if tests passed. 311 | Returns (True, message) if the unit test results are valid, 312 | or (False, error_message) if not. 313 | """ 314 | output_dir = "output" 315 | if not os.path.isdir(output_dir): 316 | return False, "Output directory 'output/' not found. Unit tests did not run." 317 | 318 | files = os.listdir(output_dir) 319 | if not files: 320 | return False, "Output directory 'output/' is empty. No unit test results found." 321 | 322 | for f in files: 323 | if "test" in f.lower() and f.endswith(".txt"): 324 | test_file = os.path.join(output_dir, f) 325 | try: 326 | with open(test_file, "r", encoding="utf-8") as tf: 327 | content = tf.read() 328 | pass_fail, summary = analyze_unit_test_with_llm(content, self.llm_url, token_limit=200) 329 | if pass_fail: 330 | return True, "Unit tests passed." 331 | else: 332 | return False, summary 333 | except Exception as e: 334 | return False, f"Error reading unit test file {test_file}: {str(e)}" 335 | 336 | return False, "No unit test result file found in output/ directory." 337 | 338 | def generate_and_refine(self, user_request): 339 | """ 340 | Main refinement loop with: 341 | - Additional LLM-based summarization (200 tokens) of code and error. 342 | - Excerpting lines near the error. 343 | - A final check step that loads unit test results from output/ and verifies their validity. 344 | """ 345 | self.user_request_msg = {"role": "user", "content": user_request} 346 | self.conversation.append(self.user_request_msg) 347 | 348 | for iteration in range(1, self.max_iterations + 1): 349 | # 1) Ask the LLM for code 350 | _, code = self.call_llm() 351 | if not code: 352 | continue 353 | 354 | if self.last_code is not None and code.strip() == self.last_code.strip(): 355 | self.conversation.append( 356 | self.add_message("user", "This code is identical to the previous attempt. Please try a new approach.") 357 | ) 358 | continue 359 | self.last_code = code 360 | 361 | # 2) Run the code in a subprocess 362 | success, result = self.run_code(code) 363 | if success: 364 | print("\n\n=== Saving Generated Code Before Test Result Analysis ===\n\n") 365 | generated_code_iteration_path = self.code_out = f"output/generated_code_iteration-{iteration}.py" 366 | # Write the iteration code to your specified output file 367 | with open(generated_code_iteration_path, "w", encoding="utf-8") as f: 368 | f.write(code) 369 | 370 | # === Final Check: Verify unit test results === 371 | final_ok, final_message = self.final_check_unit_tests() 372 | if final_ok: 373 | print(colored("\n\nFinal Check Passed: Unit tests are valid.", "green")) 374 | return code, result 375 | else: 376 | print(colored(f"\n\nFinal Check Failed: {final_message}", "red")) 377 | # Summarize final check failure and update summary 378 | iteration_summary = summarize_attempt_with_llm( 379 | llm_url=self.llm_url, 380 | code=code, 381 | error_msg=final_message, 382 | iteration=iteration, 383 | token_limit=200 384 | ) 385 | # Remove any stale code marker from the cumulative summary 386 | marker = "Last Code Generated with Errors:" 387 | if marker in self.attempts_summary: 388 | idx = self.attempts_summary.rfind(marker) 389 | self.attempts_summary = self.attempts_summary[:idx] 390 | self.attempts_summary += iteration_summary + "\nLast Code Generated with Errors: " + code + "\n" 391 | debug_msg = error_prompt(final_message) 392 | system_msg = self.conversation[0] # system prompt 393 | user_req = self.conversation[1] # original user request 394 | summary_msg = self.add_message( 395 | "assistant", 396 | f"Here is a summary of all attempts so far:\n{self.attempts_summary}" 397 | ) 398 | debug_msg_struct = self.add_message("user", debug_msg) 399 | self.conversation = [ 400 | system_msg, 401 | user_req, 402 | summary_msg, 403 | debug_msg_struct 404 | ] 405 | print(colored(f"===>Error feedback (final check) sent to LLM. Iteration {iteration}", "red")) 406 | continue 407 | else: 408 | iteration_summary = summarize_attempt_with_llm( 409 | llm_url=self.llm_url, 410 | code=code, 411 | error_msg=result, 412 | iteration=iteration, 413 | token_limit=200 414 | ) 415 | # Remove any stale code marker from the cumulative summary 416 | marker = "Last Code Generated with Errors:" 417 | if marker in self.attempts_summary: 418 | idx = self.attempts_summary.rfind(marker) 419 | self.attempts_summary = self.attempts_summary[:idx] 420 | self.attempts_summary += iteration_summary + "\nLast Code Generated with Errors: " + code + "\n" 421 | debug_msg = error_prompt(result) 422 | system_msg = self.conversation[0] 423 | user_req = self.conversation[1] 424 | summary_msg = self.add_message( 425 | "assistant", 426 | f"Here is a summary of all attempts so far:\n{self.attempts_summary}" 427 | ) 428 | debug_msg_struct = self.add_message("user", debug_msg) 429 | self.conversation = [ 430 | system_msg, 431 | user_req, 432 | summary_msg, 433 | debug_msg_struct 434 | ] 435 | print(colored(f"===>Error feedback sent to LLM. Iteration {iteration}", "red")) 436 | 437 | return None, "Could not produce a working solution in time." 438 | -------------------------------------------------------------------------------- /agent/prompts.py: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | def error_prompt(error_msg): 5 | ERROR_MSG = f""" 6 | 7 | **STRUCTURED DEBUGGING REASONING (UPON FIRST ERROR):** 8 | 9 | Explicitly follow these debugging steps immediately: 10 | 11 | 1. Analyze the previous **code** from `Last Code Generated with Errors` in relation to the error message and the summary of previous attempts in the conversation memory. 12 | - **DO NOT REPEATE:** the same failed debugging steps. 13 | 2. Explicitly hypothesize at least two potential root causes of this error. 14 | 3. **CRITICAL:** Include print statements in all your code for debugging. 15 | 4. Wrap your final Python code in triple backticks. 16 | 5. Clearly document the outcome of your hypothesis-driven debugging using the `[REFLECTION]` tags. 17 | 6. Create additional unit tests for any new code you created. 18 | 19 | **DO NOT REPEAT** failed strategies identified in conversation memory. 20 | 21 | **CRITICAL INSTRUCTION: 22 | 1. You **must NOT** generate or use **mock data** or **mock functions**. 23 | Reason: You have direct access to a live Python execution environment, so all unit tests should run with **real data** and **real functions**. Violating this instruction will lead to rejection of your output. 24 | 25 | **Error Message:** 26 | 27 | Your code produced an error: {error_msg} 28 | 29 | **Conversation Memory:** 30 | 31 | - This is found in the previous conversation turns. 32 | 33 | **Debugging Format:** 34 | 35 | [RCA] 36 | hypothesize at least two potential root causes of this error. 37 | [/RCA] 38 | 39 | [REFLECTION] 40 | Reflect on the underlying cause of this error. Describe any debugging steps and how you confirmed the fix. 41 | [/REFLECTION] 42 | 43 | [AMENDMENT] 44 | Any amendments for debugging steps here. 45 | [/AMENDMENT] 46 | 47 | [PLAN] 48 | Explain how you will investigate and correct the error. Consider different approaches if needed. 49 | [/PLAN] 50 | 51 | 52 | ```python 53 | [your updated and error corrected code here] 54 | ``` 55 | """ 56 | return ERROR_MSG 57 | 58 | 59 | 60 | SYSTEM_PROMPT = """ 61 | You are BugOut, an AI coding agent which can **execute code in a live environment** as part of your core functionality. 62 | 63 | **DEPENDENCY MANAGEMENT INSTRUCTIONS:** 64 | - You **must NOT** output installation instructions (e.g., "pip install X") to the user. 65 | - If you detect a missing library dependency during execution, you **must programmatically install it** in your Python code by invoking a subprocess that calls `pip install`. 66 | - Reason: You have full access to a live Python execution environment. Thus, the correct approach is to handle missing dependencies directly in your Python code execution flow, not by outputting external installation commands. 67 | - Violating this instruction by giving manual install commands instead of automated installation will lead to rejection of your output. 68 | - **Only install packages from pip or you could risk infecting your system with malware.** 69 | 70 | **CRITICAL INSTRUCTION:** 71 | - You **must NOT** generate or use **mock data** or **mock functions**. 72 | Reason: You have direct access to a live Python execution environment, so all unit tests should run with **real data** and **real functions**. 73 | Violating this instruction will lead to rejection of your output. 74 | - You **must** inlcude print debug statements in the code your create, like print(f"[DEBUG]..") 75 | Reason: This is how you see results in your live Python execution environment. 76 | Violating this instruction will lead to rejection of your output. 77 | 78 | **Instructions:** 79 | - Provide your solution as a single Python script. 80 | - Provide your solution with embedded unit tests which properly assess the code and expected outputs. 81 | - Follow the PEP 8 / OOP style guide. 82 | - Inlcude print statements in your code for debugging. 83 | - You will reason through the user’s request step-by-step. 84 | - You may keep your reasoning hidden, or you may show a partial explanation of your thought process if needed. 85 | - You will reflect on any areas on planning or code generation which went well or poorly. 86 | - You must create unit tests for the code you generate. 87 | - Unit tests must output test results to **output/test.txt** 88 | - You must load those unit test results from **output/test.txt** and verify for yourself the code is good. 89 | - **READ THOROUGHLY THE SUMMARY OF PREVIOUS ATTEMPTS:** If your current debugging approach resembles any previously attempted solution that failed, you must adopt an entirely new and fundamentally different strategy. 90 | - Ultimately, your job is to generate correct Python code that solves the user’s task. 91 | 92 | **Expected Planning, Reflecting, Amendment and Code Generating Format**: 93 | - When planning about code related tasks, wrap your plans in tags like: 94 | [PLAN] 95 | Your plans here 96 | [/PLAN] 97 | 98 | - When reflecting about your plan, wrap your reflection in tags like: 99 | [REFLECTION] 100 | Your reflection here 101 | [/REFLECTION] 102 | 103 | - After reflecting about plan, make amendments if needed based on your reflections and wrap your amendment in tags like: 104 | [AMENDMENT] 105 | Your amendment here 106 | [/AMENDMENT] 107 | 108 | - When providing your final solution, wrap the Python code in triple backticks, like: 109 | ```python 110 | [your code here] 111 | ``` 112 | - Do not include additional commentary inside those triple backticks (```python). 113 | - You must following all formatting including using appropriate backticks and tags. 114 | 115 | **GUIDELINES FOR UNIT TESTS WITH REAL DATA:** 116 | To ensure meaningful and valid unit tests: 117 | - **You must include unit tests** for each core function in the script to ensure their functionality and usability. 118 | - The unit tests should be written in Python and use the 'unittest' module. 119 | - **Use reflection to assess the coverage and quality of your unit tests for the codebase.** 120 | - **Never** rely on hypothetical or arbitrary scenarios or values not dynamically verified to exist. 121 | - Clearly define each unit test by: 122 | - Dynamically assessing data from the live environment. 123 | - Explicitly specifying the expected outcome based on real conditions. 124 | - Using assertions to rigorously verify functionality. 125 | - Including debug print statements explicitly showing values tested. 126 | - Unit tests must output results to output/ 127 | 128 | **Example:** 129 | [PLAN] 130 | The user has asked me to generate code that... 131 | I need to: 132 | 1. Do something... 133 | 2. Do something else... 134 | [/PLAN] 135 | 136 | [REFLECTION] 137 | My overall plan is good but I need to add better unit tests for #2 by... 138 | [/REFLECTION] 139 | 140 | [AMENDMENT] 141 | I have changed unit tests for #2 to include… 142 | [/AMENDMENT] 143 | 144 | ```python 145 | def better_unit_test(param, param2)... 146 | ``` 147 | 148 | **Remember to:** 149 | 1. Analyze the user’s input. 150 | 2. Summarize your plan or approach. 151 | 3. Generate the code solution in Python with comprehensive **unit tests**. 152 | 4. If there are errors, reflect on the mistakes using the `Debugging Format:`. 153 | 5. Refine the code and repeat. 154 | 6. Inlcude print statements in your code for debugging. 155 | 7. Create unit tests for the code you created. 156 | 8. Unit tests must output test results to **output/test.txt** 157 | 9. **DO NOT** generate or use `mock` data for your unit tests - you are a coding agent with access to a live code execution environment. 158 | 159 | Be sure to return the final code solution in the correct format. 160 | 161 | """ 162 | 163 | -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | import os 2 | from agent.agent import BugOutAgent 3 | 4 | os.system("cls || clear") 5 | 6 | def delete_file(file_path): 7 | if os.path.exists(file_path): 8 | os.remove(file_path) # Remove the file 9 | print(f"File '{file_path}' has been removed.") 10 | else: 11 | print(f"File '{file_path}' does not exist.") 12 | 13 | 14 | if __name__ == "__main__": 15 | log_file = "logs/agent_log.txt" 16 | code_out = "output/generated_code.py" 17 | delete_file(log_file) 18 | delete_file("output/test.txt") 19 | 20 | agent = BugOutAgent("http://127.0.0.1:5000/generate", log_file) 21 | 22 | user_query = """ 23 | Write a Python script designed for Windows environments that comprehensively identifies DLL hijacking vulnerabilities. Your script must perform the following tasks: 24 | 25 | 1. **Module Enumeration:** 26 | - Enumerate loaded modules (DLLs) from running processes and identify their exact file paths. 27 | - Allow users to specify specific processes (by name or PID) to analyze as an option but test the program system-wide. 28 | 29 | 2. **Directory Checks:** 30 | - Identify DLLs loaded from non-standard directories (directories other than standard Windows directories like `C:\Windows\System32`, `C:\Program Files`, etc.). 31 | 32 | 3. **Missing or Non-existent DLLs:** 33 | - Detect any modules that reference non-existent DLL files. 34 | - Clearly list modules and processes referencing these DLLs. 35 | 36 | 4. **Privilege-Aware Security Descriptor Checks:** 37 | - Inspect the file permissions (DACL) of each loaded DLL. 38 | - Explicitly identify DLL files that grant write, modify, or delete permissions to non-privileged groups or users (e.g., "Everyone", "Users", "Authenticated Users"). 39 | - Clearly differentiate between permissions granted to privileged accounts/groups (SYSTEM, Administrators, TrustedInstaller) and those granted to non-privileged groups. 40 | 41 | 5. **Digital Signature Validation:** 42 | - Accurately verify the digital signatures of loaded DLL files using proper Windows API calls (e.g., `WinVerifyTrust`). 43 | - Flag DLLs that are unsigned or have invalid signatures. 44 | 45 | 6. **Environment Variable Analysis:** 46 | - Analyze environment variables (e.g., PATH, AppInit_DLLs) to identify paths susceptible to manipulation that may lead to DLL hijacking. 47 | 48 | 7. **False Positive Mitigation:** 49 | - Include logic or configuration (such as allowlists or filtering known safe DLLs) to reduce false positives. 50 | 51 | 8. **Reporting:** 52 | - Generate a clear, structured report (e.g., printed to console, CSV, or JSON format) detailing potential vulnerabilities, specifying: 53 | - DLL path 54 | - Associated process 55 | - Reason flagged (non-standard directory, insecure permissions, missing file, invalid signature, etc.) 56 | 57 | Ensure your code is well-commented, clearly structured, and robust enough to handle exceptions gracefully. Include comments indicating what each key function or block of code is intended to achieve. 58 | 59 | **Always call the main() function in addition to unittest.** 60 | """ 61 | 62 | 63 | final_code, result = agent.generate_and_refine(user_query) 64 | 65 | if final_code: 66 | print("\n\n=== Final Generated Code ===") 67 | print(final_code+"\n") 68 | print("=== Final Generated Code ===\n\n") 69 | 70 | # Write the final code to your specified output file 71 | with open(code_out, "w", encoding="utf-8") as f: 72 | f.write(final_code) 73 | else: 74 | print("=== No valid solution found ===\n\n") 75 | print(result+"\n\n") 76 | -------------------------------------------------------------------------------- /images/bugout.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AI-Voodoo/BugOut/1738d21e4564ff8af69a8e381a4fd061c0999aba/images/bugout.png -------------------------------------------------------------------------------- /images/sw.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AI-Voodoo/BugOut/1738d21e4564ff8af69a8e381a4fd061c0999aba/images/sw.PNG -------------------------------------------------------------------------------- /llm/deepseek_lite_api.py: -------------------------------------------------------------------------------- 1 | # deepseek_lite_api.py 2 | from flask import Flask, request, Response, stream_with_context, jsonify 3 | from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer 4 | import torch 5 | import threading 6 | 7 | # Initialize tokenizer + model as before 8 | tokenizer = AutoTokenizer.from_pretrained( 9 | "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct", 10 | trust_remote_code=True 11 | ) 12 | model = AutoModelForCausalLM.from_pretrained( 13 | "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct", 14 | trust_remote_code=True, 15 | torch_dtype=torch.bfloat16 16 | ).cuda() 17 | 18 | app = Flask(__name__) 19 | 20 | @app.route('/generate', methods=['POST']) 21 | def generate(): 22 | """ 23 | Returns a chunked stream of tokens from the model. 24 | Each chunk is a bit of text that the model generates. 25 | The agent/client can read these chunks in real time. 26 | """ 27 | try: 28 | data = request.get_json() 29 | if "messages" not in data or not isinstance(data["messages"], list): 30 | return jsonify({"error": "Invalid input format. 'messages' must be a list."}), 400 31 | 32 | messages = data["messages"] 33 | 34 | # Prepare the model inputs 35 | inputs = tokenizer.apply_chat_template( 36 | messages, 37 | add_generation_prompt=True, 38 | return_tensors="pt" 39 | ).to(model.device) 40 | 41 | # Create the streamer 42 | streamer = TextIteratorStreamer( 43 | tokenizer=tokenizer, 44 | skip_prompt=True, 45 | skip_special_tokens=True 46 | ) 47 | 48 | # Our generation kwargs 49 | generation_kwargs = dict( 50 | inputs=inputs, 51 | max_new_tokens=8192, 52 | do_sample=True, 53 | top_k=50, 54 | top_p=0.95, 55 | num_return_sequences=1, 56 | eos_token_id=tokenizer.eos_token_id, 57 | streamer=streamer 58 | ) 59 | 60 | # We'll generate in a separate thread 61 | generation_thread = threading.Thread(target=model.generate, kwargs=generation_kwargs) 62 | generation_thread.start() 63 | 64 | def token_stream(): 65 | # As tokens appear in the streamer, yield them to the client 66 | for new_token in streamer: 67 | # You can encode each token as needed; here we just yield raw text 68 | yield new_token 69 | # Make sure generation is done 70 | generation_thread.join() 71 | 72 | # Return a streaming response so the client sees tokens in real time 73 | return Response(stream_with_context(token_stream()), mimetype="text/plain") 74 | 75 | except Exception as e: 76 | return jsonify({"error": str(e)}), 500 77 | 78 | if __name__ == '__main__': 79 | app.run(host='0.0.0.0', port=5000) 80 | -------------------------------------------------------------------------------- /llm/qwen_api.py: -------------------------------------------------------------------------------- 1 | # qwen_api.py 2 | from flask import Flask, request, Response, stream_with_context, jsonify 3 | from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer 4 | import torch 5 | import threading 6 | 7 | # Define the Qwen model name 8 | model_name = "Qwen/Qwen2.5-Coder-32B-Instruct" 9 | 10 | # Load tokenizer and model using device_map="auto" and torch_dtype="auto" 11 | tokenizer = AutoTokenizer.from_pretrained(model_name) 12 | model = AutoModelForCausalLM.from_pretrained( 13 | model_name, 14 | torch_dtype="auto", 15 | device_map="auto" 16 | ) 17 | 18 | app = Flask(__name__) 19 | 20 | @app.route('/generate', methods=['POST']) 21 | def generate(): 22 | """ 23 | Returns a chunked stream of tokens from the Qwen model. 24 | Each chunk is a bit of text that the model generates in real time. 25 | """ 26 | try: 27 | data = request.get_json() 28 | if "messages" not in data or not isinstance(data["messages"], list): 29 | return jsonify({"error": "Invalid input format. 'messages' must be a list."}), 400 30 | 31 | messages = data["messages"] 32 | 33 | # Create the prompt text using Qwen's chat template 34 | prompt_text = tokenizer.apply_chat_template( 35 | messages, 36 | tokenize=False, 37 | add_generation_prompt=True 38 | ) 39 | 40 | # Tokenize the prompt text and move tensors to the model device 41 | model_inputs = tokenizer([prompt_text], return_tensors="pt").to(model.device) 42 | 43 | # Create the streamer for real-time token generation 44 | streamer = TextIteratorStreamer( 45 | tokenizer=tokenizer, 46 | skip_prompt=True, 47 | skip_special_tokens=True 48 | ) 49 | 50 | # Set up generation parameters (adjusted for Qwen) 51 | generation_kwargs = dict( 52 | **model_inputs, 53 | max_new_tokens=8192, 54 | #do_sample=True, 55 | #top_k=50, 56 | #top_p=0.95, 57 | num_return_sequences=1, 58 | eos_token_id=tokenizer.eos_token_id, 59 | streamer=streamer 60 | ) 61 | 62 | # Generate tokens in a separate thread for streaming response 63 | generation_thread = threading.Thread(target=model.generate, kwargs=generation_kwargs) 64 | generation_thread.start() 65 | 66 | def token_stream(): 67 | # Yield tokens as they are generated 68 | for new_token in streamer: 69 | yield new_token 70 | generation_thread.join() 71 | 72 | return Response(stream_with_context(token_stream()), mimetype="text/plain") 73 | 74 | except Exception as e: 75 | return jsonify({"error": str(e)}), 500 76 | 77 | if __name__ == '__main__': 78 | app.run(host='0.0.0.0', port=5000) 79 | --------------------------------------------------------------------------------