{ "code_blocks": [ { "id": "repo_to_md/core.py::is_excluded", "parent_id": null, "file_path": "repo_to_md/core.py", "type": "function", "name": "is_excluded", "start_line": 35, "end_line": 42, "source_code": "def is_excluded(filepath: str) -> bool:\n path = Path(filepath)\n if path.name in EXCLUDE_FILENAMES or path.suffix.lower() in EXCLUDE_EXTENSIONS:\n return True\n normalized_path = path.as_posix()\n if any(pattern in normalized_path for pattern in EXCLUDE_PATTERNS):\n return True\n return False", "docstring": "", "dependencies": [ "Path", "any" ], "level": 0, "structural_vector": [ 1, 0, 0.14154411764705882, 0.029411764705882353 ], "semantic_embedding": [ 0.006937084719538689, 0.10042242705821991, -0.009279998950660229, 0.005719874519854784, 0.08334039151668549, -0.08946368098258972, 0.018270030617713928, -0.0331353060901165, -0.006408145651221275, -0.043831225484609604, 0.06881918013095856, 0.0710744559764862, 0.042097799479961395, -0.00043842688319273293, -0.05033984035253525, 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b'\\n\\r\\t\\f\\b')\n if len(sample) > 0:\n non_text_ratio = sum(1 for byte in sample if byte not in text_chars) / len(sample)\n if non_text_ratio > 0.30:\n return True\n\n try:\n content.decode('utf-8')\n return False\n except UnicodeDecodeError:\n return True", "docstring": "", "dependencies": [ "bytes", "set", "sum", "Path", "range", "len" ], "level": 0, "structural_vector": [ 1, 0, 0.21875, 0.11764705882352941 ], "semantic_embedding": [ -0.013621706515550613, -0.0004795195418410003, -0.04815283045172691, -0.010556456632912159, 0.07515478134155273, -0.08804025501012802, 0.031899672001600266, 0.030750954523682594, -0.05685024708509445, -0.03443317487835884, 0.030510056763887405, 0.015093292109668255, 0.07107400894165039, 0.05072636902332306, -0.033736493438482285, 0.018141135573387146, -0.08546683192253113, 0.008019623346626759, 0.010775289498269558, 0.0009466152987442911, 0.07434859126806259, 0.06757119297981262, 0.09917057305574417, -0.0037141048815101385, -0.0067008426412940025, 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"repo_to_md/core.py::generate_file_tree", "parent_id": null, "file_path": "repo_to_md/core.py", "type": "function", "name": "generate_file_tree", "start_line": 77, "end_line": 95, "source_code": "def generate_file_tree(paths: List[str]) -> str:\n tree = [\"\ud83d\udcc1 Root\"]\n structure = {}\n for path in sorted(paths):\n parts = path.split('/')\n current_level = structure\n for part in parts:\n current_level = current_level.setdefault(part, {})\n\n def build_tree(level_structure, indent=\"\"):\n for name in sorted(level_structure.keys()):\n is_dir = bool(level_structure[name])\n icon = \"\ud83d\udcc1\" if is_dir else \"\ud83d\udcc4\"\n tree.append(f\"{indent}{icon} {name}\")\n if is_dir:\n build_tree(level_structure[name], indent + \" \")\n\n build_tree(structure)\n return \"\\n\".join(tree) + \"\\n\\n\"", "docstring": "", "dependencies": [ "sorted", "build_tree", "bool" ], "level": 0, "structural_vector": [ 1, 0, 0.3161764705882353, 0.06985294117647059 ], "semantic_embedding": [ 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is_dir:\n build_tree(level_structure[name], indent + \" \")", "docstring": "", "dependencies": [ "sorted", "build_tree", "bool" ], "level": 1, "structural_vector": [ 1, 1, 0.3272058823529412, 0.025735294117647058 ], "semantic_embedding": [ -0.0251068864017725, 0.0644279196858406, 0.008202411234378815, 0.014018724672496319, 0.00884222611784935, -0.09405726939439774, -0.019196949899196625, 0.0018988557858392596, -0.0420822948217392, 0.04878365993499756, 0.03652719780802727, 0.011616618372499943, 0.06529701501131058, -0.007208583410829306, -0.004369298927485943, 0.07224195450544357, -0.14132045209407806, 0.03320233151316643, 0.055868253111839294, -0.12430395185947418, 0.07565829902887344, 0.07451476156711578, 0.08022025227546692, 0.06864983588457108, 0.028832338750362396, -0.031669195741415024, -0.0338251031935215, 0.048628583550453186, -0.006700450088828802, -0.031638823449611664, 0.011534446850419044, 0.011653231456875801, 0.08741989731788635, 0.05995211377739906, 0.03621982783079147, 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str) -> Tuple[Optional[List[Dict]], Optional[str]]:\n try:\n repo_info_url = f\"{GITHUB_API}{owner}/{repo}\"\n repo_response = requests.get(repo_info_url, headers=HEADERS, timeout=10)\n repo_response.raise_for_status()\n default_branch = repo_response.json()['default_branch']\n\n branch_info_url = f\"{GITHUB_API}{owner}/{repo}/branches/{default_branch}\"\n branch_response = requests.get(branch_info_url, headers=HEADERS, timeout=10)\n branch_response.raise_for_status()\n tree_sha = branch_response.json()['commit']['commit']['tree']['sha']\n\n tree_url = f\"{GITHUB_API}{owner}/{repo}/git/trees/{tree_sha}?recursive=1\"\n tree_response = requests.get(tree_url, headers=HEADERS, timeout=30)\n tree_response.raise_for_status()\n\n files = [\n {\"path\": item['path']}\n for item in tree_response.json()['tree']\n if item['type'] == 'blob'\n ]\n return files, default_branch\n\n except requests.RequestException as e:\n error_message = f\"Error fetching from GitHub API: {e}. \"\n if 'rate limit' in str(e).lower() and not GITHUB_TOKEN:\n error_message += \"You may have hit the rate limit. Please set a GITHUB_TOKEN environment variable.\"\n raise ConnectionError(error_message) from e", "docstring": "", "dependencies": [ "str", "ConnectionError" ], "level": 0, "structural_vector": [ 1, 0, 0.40625, 0.10294117647058823 ], "semantic_embedding": [ -0.03288842737674713, 0.03546088561415672, -0.020678341388702393, -0.014262570068240166, 0.012864277698099613, -0.11261261254549026, -0.03552332893013954, 0.06828689575195312, -0.03265795856714249, 0.014116073958575726, 0.01800219528377056, 0.024294313043355942, 0.006940194871276617, 0.009926021099090576, 0.015162180177867413, 0.02099229022860527, -0.09073255956172943, 0.06349126994609833, 0.049108315259218216, -0.07698898762464523, 0.03460536152124405, 0.11082529276609421, 0.047854840755462646, 0.04198482632637024, 0.005353173241019249, -0.13180486857891083, -0.0655784159898758, -0.004287826828658581, -0.07740931212902069, 0.004850021097809076, 0.06882750988006592, -0.02393290027976036, -0.016070852056145668, 0.018298279494047165, 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0.07674093544483185, -0.010513098910450935, -0.049676887691020966, -0.07832282036542892, 0.010431261733174324, -0.01703249104321003, 0.02115880697965622, 0.006588747259229422, 0.08053851127624512, -0.0024268943816423416, -0.0408727303147316, 0.007989023812115192, -0.020552940666675568, 0.019617844372987747, -0.045129284262657166, -0.01342475414276123, -0.0015167936217039824, 0.0331377275288105, 0.027976026758551598, -0.02317367121577263, -0.007476672064512968, -0.037083595991134644, -0.030192088335752487, -0.00580093776807189, -0.06439600884914398, 0.0430155023932457, 0.062271833419799805, -0.007264012936502695, -0.006762107368558645, -0.08391717076301575, 0.10625950992107391, 0.02245907112956047, 0.05596037209033966, 0.015709513798356056 ] }, { "id": "repo_to_md/core.py::get_hf_files", "parent_id": null, "file_path": "repo_to_md/core.py", "type": "function", "name": "get_hf_files", "start_line": 126, "end_line": 132, "source_code": "def get_hf_files(owner: str, repo: str) -> List[Dict]:\n try:\n api = HfApi(token=os.getenv('HF_TOKEN'))\n file_paths = api.list_repo_files(repo_id=f'{owner}/{repo}', repo_type=\"space\")\n return [{\"path\": path} for path in file_paths]\n except Exception as e:\n raise ConnectionError(f\"Error fetching from Hugging Face Hub: {e}\") from e", "docstring": "", "dependencies": [ "HfApi", "ConnectionError" ], "level": 0, "structural_vector": [ 1, 0, 0.4742647058823529, 0.025735294117647058 ], "semantic_embedding": [ -0.018810968846082687, 0.018588028848171234, -0.03804287314414978, -0.001439166720956564, 0.051145635545253754, -0.07517017424106598, 0.017350299283862114, 0.04510853812098503, -0.054899271577596664, 0.004809103440493345, 0.056756217032670975, -0.0009501352906227112, -0.007031230255961418, 0.012550591491162777, 0.01966274529695511, 0.018390994518995285, -0.0980478823184967, 0.007654647342860699, 0.06500386446714401, -0.006424046587198973, -0.0179385244846344, 0.08314160257577896, 0.025356270372867584, 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0.06945544481277466 ] }, { "id": "repo_to_md/core.py::get_repo_contents", "parent_id": null, "file_path": "repo_to_md/core.py", "type": "function", "name": "get_repo_contents", "start_line": 134, "end_line": 154, "source_code": "def get_repo_contents(url: str) -> Tuple[Optional[str], Optional[str], Optional[str], Union[List[Dict], str], bool]:\n try:\n parts = url.rstrip('/').split('/')\n owner, repo = parts[-2], parts[-1]\n is_hf = \"huggingface.co\" in url.lower()\n default_branch = None\n\n if is_hf:\n files = get_hf_files(owner, repo)\n else:\n files, default_branch = get_github_files_recursive(owner, repo)\n\n if not files:\n error_msg = f\"No files found in {'Hugging Face Space' if is_hf else 'GitHub repository'}.\"\n if not is_hf and not GITHUB_TOKEN:\n error_msg += \" If this is a private repo or you've hit a rate limit, please set a GITHUB_TOKEN.\"\n raise ValueError(error_msg)\n \n return owner, repo, default_branch, files, is_hf\n except Exception as e:\n return None, None, None, f\"Error fetching repo contents: {str(e)}\", False", "docstring": "", "dependencies": [ "get_hf_files", "get_github_files_recursive", "str", "ValueError" ], "level": 0, "structural_vector": [ 1, 0, 0.5294117647058824, 0.07720588235294118 ], "semantic_embedding": [ -0.04574240371584892, 0.002149958163499832, -0.015762673690915108, -0.013139449991285801, 0.0697396993637085, -0.10136795043945312, 0.0062111723236739635, -0.004696095362305641, -0.026436690241098404, 0.00389114604331553, 0.06017954275012016, 0.03580391779541969, 0.01848083734512329, -0.0029591978527605534, 0.0019432406406849623, 0.03709331154823303, -0.0691317617893219, 0.05571642518043518, 0.06135821342468262, -0.05753299966454506, 0.014522920362651348, 0.12262275815010071, 0.06016620248556137, 0.04629301279783249, 0.006378532387316227, -0.07218844443559647, -0.09638320654630661, 0.024888891726732254, -0.05930781364440918, -0.0246946569532156, 0.10166987776756287, 0.0137359369546175, -0.005042108241468668, 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"def process_file_content(file_info: Dict, owner: str, repo: str, default_branch: Optional[str] = None, is_hf: bool = False) -> str:\n file_path = file_info['path']\n try:\n if is_hf:\n url = f\"https://huggingface.co/spaces/{owner}/{repo}/raw/main/{file_path}\"\n response = requests.get(url, timeout=10)\n else:\n url = f\"https://raw.githubusercontent.com/{owner}/{repo}/{default_branch}/{file_path}\"\n response = requests.get(url, timeout=10)\n\n response.raise_for_status()\n content_raw = response.content\n \n if is_binary_content(file_path, content_raw):\n return f\"### File: {file_path}\\n[Binary file - {len(content_raw)} bytes]\\n\\n\"\n \n text_content = content_raw.decode('utf-8', errors='replace')\n file_extension = Path(file_path).suffix[1:].lower() or 'text'\n \n if file_extension == 'json':\n try:\n formatted_json = json.dumps(json.loads(text_content), indent=2)\n return f\"### File: {file_path}\\n```json\\n{formatted_json}\\n```\\n\\n\"\n except json.JSONDecodeError:\n return f\"### File: {file_path}\\n```json\\n{text_content}\\n```\\n[Note: Invalid JSON format]\\n\\n\"\n \n return f\"### File: {file_path}\\n```{file_extension}\\n{text_content}\\n```\\n\\n\"\n\n except requests.RequestException as e:\n error_message = f\"Error fetching file content: {e}\"\n if '404' in str(e):\n error_message += \" (This can happen with submodules or broken links)\"\n return f\"### File: {file_path}\\n[{error_message}]\\n\\n\"\n except Exception as e:\n return f\"### File: {file_path}\\n[Error processing file: {str(e)}]\\n\\n\"", "docstring": "", "dependencies": [ "Path", "str", "len", "is_binary_content" ], "level": 0, "structural_vector": [ 1, 0, 0.6360294117647058, 0.12867647058823528 ], "semantic_embedding": [ -0.03695813566446304, 0.03529965132474899, -0.04550885781645775, -0.006425614934414625, 0.04502463713288307, -0.13145801424980164, -0.032016754150390625, 0.0481603778898716, -0.009620551019906998, 0.02245173417031765, 0.002777279820293188, 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indent=2)\n return f\"### File: {filename}\\n```json\\n{formatted_json}\\n```\\n\\n\"\n except json.JSONDecodeError:\n return f\"### File: {filename}\\n```json\\n{text_content}\\n```\\n[Note: Invalid JSON format]\\n\\n\"\n return f\"### File: {filename}\\n```{file_extension}\\n{text_content}\\n```\\n\\n\"\n except Exception as e:\n return f\"### File: {filename}\\n[Error processing file: {str(e)}]\\n\\n\"", "docstring": "", "dependencies": [ "Path", "str", "is_binary_content", "len", "getattr" ], "level": 0, "structural_vector": [ 1, 0, 0.7408088235294118, 0.07352941176470588 ], "semantic_embedding": [ -0.06286773085594177, 0.03990007936954498, -0.04279216006398201, -0.01420694962143898, 0.053851816803216934, -0.1096828505396843, -0.06309209764003754, 0.08624651283025742, -0.03751489892601967, 0.017782166600227356, -0.004381720442324877, 0.030991246923804283, 0.008282042108476162, 0.055208660662174225, -0.0051946756429970264, -0.03167613595724106, -0.13788682222366333, 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0.05271568149328232, -0.012385761365294456, 0.007739881984889507, 0.10135666280984879, 0.057192981243133545, 0.06350812315940857, 0.016355441883206367 ] }, { "id": "repo_to_md/core.py::create_markdown_document", "parent_id": null, "file_path": "repo_to_md/core.py", "type": "function", "name": "create_markdown_document", "start_line": 213, "end_line": 243, "source_code": "def create_markdown_document(url: Optional[str] = None, files: Optional[List[object]] = None) -> str:\n if url:\n owner, repo, default_branch, contents, is_hf = get_repo_contents(url)\n if isinstance(contents, str):\n return f\"Error: {contents}\"\n \n filtered_contents = [item for item in contents if not is_excluded(item['path'])]\n if not filtered_contents:\n return \"Error: No non-excluded files found in the repository.\"\n\n markdown_content = [\n f\"# {'Space' if is_hf else 'Repository'}: {owner}/{repo}\\n\",\n \"## File Structure\\n\",\n generate_file_tree([item['path'] for item in filtered_contents]),\n f\"Below are the contents of all files in the {'space' if is_hf else 'repository'}:\\n\\n\"\n ]\n markdown_content.extend(process_file_content(item, owner, repo, default_branch, is_hf) for item in filtered_contents)\n else:\n filtered_files = [file for file in files if hasattr(file, 'filename') and not is_excluded(file.filename)]\n if not filtered_files:\n return \"Error: No non-excluded files were uploaded.\"\n\n markdown_content = [\n \"# Uploaded Files\\n\",\n \"## File Structure\\n\",\n generate_file_tree([file.filename for file in filtered_files]),\n \"Below are the contents of all uploaded files:\\n\\n\"\n ]\n markdown_content.extend(process_uploaded_file(file) for file in filtered_files)\n \n return \"\".join(markdown_content)", "docstring": "", "dependencies": [ "get_repo_contents", "generate_file_tree", "hasattr", "is_excluded", "process_file_content", "process_uploaded_file", "isinstance" ], "level": 0, "structural_vector": [ 1, 0, 0.8382352941176471, 0.11397058823529412 ], 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line.startswith(\"### File: \"):\n if current_filename:\n content = \"\\n\".join(current_content) if not is_binary else \"\"\n files.append({\"filename\": current_filename, \"content\": \"[Binary File]\" if is_binary else content, \"is_binary\": is_binary, \"filepath\": current_filename})\n buffers[current_filename] = b\"[Binary content not stored]\" if is_binary else content.encode('utf-8')\n current_filename, current_content = line[len(\"### File: \"):].strip(), []\n is_binary, in_code_block = False, False\n elif line.startswith(\"[Binary file - \") and current_filename:\n is_binary = True\n elif line.startswith(\"```\"):\n in_code_block = not in_code_block\n elif in_code_block and not is_binary:\n current_content.append(line)\n\n if current_filename:\n content = \"\\n\".join(current_content) if not is_binary else \"\"\n files.append({\"filename\": current_filename, \"content\": \"[Binary File]\" if is_binary else content, \"is_binary\": is_binary, \"filepath\": current_filename})\n buffers[current_filename] = b\"[Binary content not stored]\" if is_binary else content.encode('utf-8')\n\n if not files:\n return \"Error: No files found in the markdown document.\", {}\n return files, buffers", "docstring": "", "dependencies": [ "len" ], "level": 0, "structural_vector": [ 1, 0, 0.9503676470588235, 0.10294117647058823 ], "semantic_embedding": [ -0.004141382407397032, 0.06344085186719894, -0.007676109205931425, 0.010203923098742962, 0.04699854925274849, -0.057045258581638336, 0.015712624415755272, 0.052241433411836624, -0.0805465430021286, 0.03432656452059746, -0.031302560120821, 0.061187196522951126, 0.04414503276348114, 0.028622420504689217, 0.021393340080976486, 0.036783043295145035, -0.11510656028985977, 0.08685843646526337, 0.009796100668609142, -0.034877851605415344, 0.07113804668188095, 0.10087250918149948, 0.05151599645614624, 0.07221443951129913, 0.0033920907881110907, -0.017882414162158966, -0.018862735480070114, 0.008859194815158844, -0.0860481932759285, 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"function", "name": "find_template_path", "start_line": 18, "end_line": 27, "source_code": "def find_template_path() -> str:\n possible_paths = [\n Path(__file__).parent / \"templates\",\n Path(__file__).parent.parent / \"templates\",\n Path(sys.executable).parent / \"site-packages/repo_to_md/templates\"\n ]\n for path in possible_paths:\n if path.exists():\n return str(path)\n raise FileNotFoundError(\"Template directory not found\")", "docstring": "", "dependencies": [ "Path", "FileNotFoundError", "str" ], "level": 0, "structural_vector": [ 1, 0, 0.12362637362637363, 0.054945054945054944 ], "semantic_embedding": [ -0.044972315430641174, 0.014763318002223969, -0.019159985706210136, -0.04832419380545616, 0.06205426901578903, -0.011874849908053875, -0.026133064180612564, 0.011998182162642479, -0.0020100355613976717, -0.008716060779988766, 0.020660055801272392, 0.025211704894900322, -0.026535818353295326, 0.0544254370033741, 0.019049810245633125, 0.035583529621362686, 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No file structure found.\"\n return f\"
Please provide Markdown input.
'}), 400\n\n files, buffers = markdown_to_files(markdown_text)\n if isinstance(files, str):\n return jsonify({'error': files, 'files': [], 'combined_html': 'Invalid Markdown format.
'}), 400\n\n reverse_buffers.clear()\n reverse_buffers.update({k: v.encode('utf-8') if isinstance(v, str) else v for k, v in buffers.items()})\n combined_html = \"\"\n has_html = False\n\n for file_info in files:\n if not file_info['is_binary'] and file_info['filename'].endswith(\".html\"):\n has_html = True\n html_content = rebuild_html_content(reverse_buffers[file_info['filepath']], reverse_buffers)\n filepath = Path(g.temp_dir) / file_info['filepath']\n filepath.parent.mkdir(parents=True, exist_ok=True)\n filepath.write_bytes(html_content)\n combined_html += f\"\"\n\n if not has_html:\n tree_path = Path(g.temp_dir) / \"file_tree.html\"\n tree_html = f\"{extract_file_tree(markdown_text)}\"\n tree_path.write_text(tree_html, encoding='utf-8')\n combined_html = f\"\"\n\n return jsonify({'files': files, 'combined_html': combined_html, 'error': None})\n\n @app.route('/temp/Please provide Markdown input.
'}), 400\n\n files, buffers = markdown_to_files(markdown_text)\n if isinstance(files, str):\n return jsonify({'error': files, 'files': [], 'combined_html': 'Invalid Markdown format.
'}), 400\n\n reverse_buffers.clear()\n reverse_buffers.update({k: v.encode('utf-8') if isinstance(v, str) else v for k, v in buffers.items()})\n combined_html = \"\"\n has_html = False\n\n for file_info in files:\n if not file_info['is_binary'] and file_info['filename'].endswith(\".html\"):\n has_html = True\n html_content = rebuild_html_content(reverse_buffers[file_info['filepath']], reverse_buffers)\n filepath = Path(g.temp_dir) / file_info['filepath']\n filepath.parent.mkdir(parents=True, exist_ok=True)\n filepath.write_bytes(html_content)\n combined_html += f\"\"\n\n if not has_html:\n tree_path = Path(g.temp_dir) / \"file_tree.html\"\n tree_html = f\"{extract_file_tree(markdown_text)}\"\n tree_path.write_text(tree_html, encoding='utf-8')\n combined_html = f\"\"\n\n return jsonify({'files': files, 'combined_html': combined_html, 'error': None})", "docstring": "", "dependencies": [ "markdown_to_files", "jsonify", "Path", "extract_file_tree", "isinstance", "rebuild_html_content" ], 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"type": "function", "name": "download_extracted", "start_line": 169, "end_line": 177, "source_code": "def download_extracted():\n if not reverse_buffers:\n return jsonify({'error': 'No files available'}), 400\n buffer = io.BytesIO()\n with zipfile.ZipFile(buffer, 'w', zipfile.ZIP_DEFLATED) as zip_file:\n for filepath, content in reverse_buffers.items():\n zip_file.writestr(filepath, content if isinstance(content, bytes) else content.encode('utf-8'))\n buffer.seek(0)\n return send_file(buffer, as_attachment=True, download_name=\"extracted_files.zip\", mimetype='application/zip')", "docstring": "", "dependencies": [ "send_file", "isinstance", "jsonify" ], "level": 1, "structural_vector": [ 1, 1, 0.9505494505494505, 0.04945054945054945 ], "semantic_embedding": [ -0.08526431769132614, 0.051278214901685715, -0.060333989560604095, 0.0046254051849246025, 0.035207830369472504, -0.1049981638789177, -0.014362798072397709, 0.05235745385289192, -0.021239038556814194, 0.037875816226005554, 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