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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,84 @@ | ||
| import json | ||
| import shutil | ||
| import subprocess | ||
| import tempfile | ||
| from typing import * | ||
| import os | ||
| from core import Chunk, SourceTypes | ||
|
|
||
| CTAGS_LANGUAGES = {'py': "Python", 'ts': "Typescript", "tsx": "Typescript", "cpp": "C++", "c": "C"} | ||
|
|
||
| def compress_with_ctags(chunk: Chunk, extension: str) -> Chunk: | ||
| if chunk.text is None: | ||
| return Chunk(path=chunk.path, text=chunk.text, image=chunk.image, source_type=SourceTypes.UNCOMPRESSIBLE_CODE) | ||
| language = CTAGS_LANGUAGES[extension] | ||
| tmp_dir = tempfile.mkdtemp() | ||
| try: | ||
| file_path = os.path.join(tmp_dir, "tempfile")+'.'+extension | ||
| with open(file_path, 'w', encoding='utf-8') as tmp_file: | ||
| tmp_file.write(chunk.text) | ||
| # need custom options for ctags to work with typescript | ||
| if language == "Typescript": | ||
| cmd = [ | ||
| "./ctags", | ||
| f"--languages={language}", | ||
| "--output-format=json", | ||
| f"--options=./ts.ctags", | ||
| "-f", "-", | ||
| file_path | ||
| ] | ||
| else: | ||
| cmd = [ | ||
| "./ctags", | ||
| f"--languages={language}", | ||
| "--output-format=json", | ||
| "-f", "-", | ||
| file_path | ||
| ] | ||
| result = subprocess.run(cmd, capture_output=True, text=True) | ||
| if result.returncode != 0: | ||
| raise Exception(f"Error running ctags: {result.stderr}") | ||
| # write output to file | ||
| with open('ctags_output.json', 'w', encoding='utf-8') as f: | ||
| f.write(result.stdout) | ||
| # Process the JSON output | ||
| ctag_matches = [] | ||
| for line in result.stdout.strip().splitlines(): | ||
| tag = json.loads(line) | ||
| if 'pattern' in tag: | ||
| pattern_without_regex = tag['pattern'][2:-2] | ||
| ctag_matches.append(pattern_without_regex) | ||
| finally: | ||
| shutil.rmtree(tmp_dir) | ||
| # remove the json file | ||
| if os.path.exists('ctags_output.json'): | ||
| os.remove('ctags_output.json') | ||
| ctags_skeleton = '\n'.join(ctag_matches) | ||
| return Chunk(path=chunk.path, text=ctags_skeleton, image=chunk.image, source_type=SourceTypes.UNCOMPRESSIBLE_CODE) | ||
|
|
||
| def compress_chunks(chunks: List[Chunk]) -> List[Chunk]: | ||
| from llmlingua import PromptCompressor | ||
| llm_lingua = PromptCompressor(model_name="microsoft/llmlingua-2-xlm-roberta-large-meetingbank", use_llmlingua2=True) | ||
| new_chunks = [] | ||
| for chunk in chunks: | ||
| new_chunk = None | ||
| if chunk is None or chunk.text is None: | ||
| new_chunk = chunk | ||
| elif chunk.source_type == SourceTypes.COMPRESSIBLE_CODE: | ||
| extension = chunk.path.split('.')[-1] | ||
| new_chunk = compress_with_ctags(chunk, extension=extension) | ||
| elif chunk.source_type in {SourceTypes.PLAINTEXT, SourceTypes.PDF, SourceTypes.DOCX, SourceTypes.PPTX}: | ||
| # Compress the text with llmlingua | ||
| new_chunk_text = "" | ||
| WINDOW_SIZE = 500 | ||
| for i in range(0, len(chunk.text), WINDOW_SIZE): | ||
| window_text = chunk.text[i:i+WINDOW_SIZE] | ||
| result = llm_lingua.compress_prompt(window_text, rate=0.5) | ||
| new_window_text = result['compressed_prompt'] | ||
| new_chunk_text += new_window_text | ||
| new_chunk = Chunk(path=chunk.path, text=new_chunk_text, image=chunk.image, source_type=chunk.source_type) | ||
| else: | ||
| # if the chunk is not compressible, keep the original text | ||
| new_chunk = chunk | ||
| new_chunks.append(new_chunk) | ||
| return new_chunks |
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