| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef _score(snippet: dict, low: str) -> int:\n padded = f\" {low} \"\n score = 0\n```", "response": " for keyword in snippet[\"keywords\"]:\n if keyword in padded:\n score += len(keyword) + (3 if \" \" in keyword else 0)\n return score", "source_file": "code_helper.py", "function_name": "_score", "class_name": null, "line_start": 50, "line_end": 56, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_explanation", "language": "python", "instruction": "Explain what this Python function does.\n\n```python\ndef _has_cue(low: str, cues: tuple[str, ...]) -> bool:\n \"\"\"Whole-word matching: 'script' must not fire inside 'javascript'.\"\"\"\n for cue in cues:\n if \" \" in cue or \"/\" in cue:\n if cue in low:\n return True\n elif re.search(rf\"(?<!\\w){re.escape(cue)}(?!\\w)\", low):\n return True\n return False\n```", "response": "Whole-word matching: 'script' must not fire inside 'javascript'.", "source_file": "code_helper.py", "function_name": "_has_cue", "class_name": null, "line_start": 59, "line_end": 67, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_generation", "language": "python", "instruction": "Write a Python function `_has_cue(low: str, cues: tuple[str, ...])` that does the following:\n\nWhole-word matching: 'script' must not fire inside 'javascript'.\n\nReturn only the Python code.", "response": "def _has_cue(low: str, cues: tuple[str, ...]) -> bool:\n \"\"\"Whole-word matching: 'script' must not fire inside 'javascript'.\"\"\"\n for cue in cues:\n if \" \" in cue or \"/\" in cue:\n if cue in low:\n return True\n elif re.search(rf\"(?<!\\w){re.escape(cue)}(?!\\w)\", low):\n return True\n return False", "source_file": "code_helper.py", "function_name": "_has_cue", "class_name": null, "line_start": 59, "line_end": 67, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef _format(snippet: dict, explain_first: bool) -> str:\n language = snippet[\"language\"]\n pretty = _pretty(language)\n head = f\"{pretty}: {snippet['title']}.\"\n code = snippet[\"code\"]\n explain = f\"Why it works: {snippet['explain']}\"\n```", "response": " if explain_first:\n body = f\"{head}\\n\\n{explain}\\n\\n{code}\"\n else:\n body = f\"{head}\\n\\n{code}\\n\\n{explain}\"\n\n if snippet.get(\"demo\"):\n body += f\"\\n\\nExample output:\\n{snippet['demo']}\"\n return body", "source_file": "code_helper.py", "function_name": "_format", "class_name": null, "line_start": 89, "line_end": 103, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef overview(language: str) -> str:\n titles = [s[\"title\"] for s in SNIPPETS if s[\"language\"] == language]\n pretty = _pretty(language)\n```", "response": " if not titles:\n return \"\"\n sample = \", \".join(titles[:6])\n return (f\"I have verified {pretty} examples for: {sample}.\\n\"\n f\"Ask for one directly, e.g. \\\"{language} fibonacci\\\".\")", "source_file": "code_helper.py", "function_name": "overview", "class_name": null, "line_start": 106, "line_end": 113, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef answer_code(text: str) -> str | None:\n low = \" \".join(text.lower().split())\n language = detect_language(low)\n explain_first = any(w in low for w in EXPLAIN_WORDS)\n\n # A bare topic (\"fibonacci\") or an explicit code cue is needed; this stops\n # \"who is the prime minister?\" from matching the prime-number snippet.\n if not language and not _has_context(low) and not _bare_topic(low):\n return None\n\n pool = [s for s in SNIPPETS if s[\"language\"] == language] if language else SNIPPETS\n best = None\n best_score = 0\n for snippet in pool:\n score = _score(snippet, low)\n if score > best_score:\n best, best_score = snippet, score\n```", "response": " if best is not None and best_score >= 3:\n return _format(best, explain_first)\n\n # Language named but no task: offer the menu instead of guessing, but only\n # when the message actually asks for code (not \"why is JavaScript popular?\").\n topic_only = low.strip(\" .!?\") in {\n \"javascript\", \"js\", \"node\", \"nodejs\", \"sql\", \"html\", \"css\",\n \"powershell\", \"c++\", \"cpp\",\n }\n if language and language != \"python\" and (_wants_code(low) or topic_only):\n return overview(language)\n\n # A generic coding request with no usable keyword: offer the menu instead\n # of letting the tiny base model invent broken code.\n if _wants_code(low):\n return overview(\"python\")\n return None", "source_file": "code_helper.py", "function_name": "answer_code", "class_name": null, "line_start": 116, "line_end": 150, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef main() -> None:\n ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)\n ap.add_argument(\"--checkpoint\", default=\"runs/medium/best.pt\")\n ap.add_argument(\"--tokenizer\", default=\"tokenizer/tokenizer.json\")\n ap.add_argument(\"--prompt\", default=None)\n ap.add_argument(\"--max-new-tokens\", type=int, default=60)\n ap.add_argument(\"--temperature\", type=float, default=0.8)\n ap.add_argument(\"--top-k\", type=int, default=50)\n ap.add_argument(\"--top-p\", type=float, default=0.92)\n ap.add_argument(\"--seed\", type=int, default=0)\n ap.add_argument(\"--device\", default=\"auto\")\n args = ap.parse_args()\n\n device = torch.device(\n \"cuda\" if args.device == \"auto\" and torch.cuda.is_available() else\n (\"cpu\" if args.device == \"auto\" else args.device)\n )\n ckpt = torch.load(args.checkpoint, map_location=device, weights_only=False)\n model = GPT(ModelConfig.from_dict(ckpt[\"model_config\"]))\n model.load_state_dict(ckpt[\"model\"])\n```", "response": " model.to(device).eval()\n tok = Tokenizer(args.tokenizer)\n\n print(f\"{args.checkpoint} @ step {ckpt.get('step')} | \"\n f\"{model.num_params() / 1e6:.1f}M params | vocab {tok.vocab_size:,}\\n\")\n\n todo = [(args.prompt, args.prompt)] if args.prompt else PROMPTS\n for name, prompt in todo:\n torch.manual_seed(args.seed)\n ids = tok.encode(prompt)\n x = torch.tensor([ids], dtype=torch.long, device=device)\n out = model.generate(\n x,\n max_new_tokens=args.max_new_tokens,\n temperature=args.temperature,\n top_k=args.top_k,\n top_p=args.top_p,\n repetition_penalty=1.1,\n eos_id=tok.eos_id,\n )\n text = tok.decode(out[0].tolist())\n print(f\"[{name}]\\n{text}\\n\")", "source_file": "demo_multilingual.py", "function_name": "main", "class_name": null, "line_start": 28, "line_end": 69, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef download(url: str, dest: Path, label: str) -> Path:\n dest.parent.mkdir(parents=True, exist_ok=True)\n if dest.exists() and dest.stat().st_size > 0:\n print(f\" {label}: cached ({dest.stat().st_size / MB:.1f} MB)\")\n return dest\n\n req = urllib.request.Request(url, headers={\"User-Agent\": \"corpus-fetcher/1.0\"})\n```", "response": " with urllib.request.urlopen(req, timeout=120) as resp:\n total = int(resp.headers.get(\"Content-Length\") or 0)\n done = 0\n last = 0.0\n with dest.open(\"wb\") as fh:\n while True:\n chunk = resp.read(1 << 20)\n if not chunk:\n break\n fh.write(chunk)\n done += len(chunk)\n now = time.time()\n if now - last > 2:\n last = now\n pct = f\" {done / total * 100:5.1f}%\" if total else \"\"\n print(f\" {label}: {done / MB:7.1f} MB{pct}\", end=\"\\r\", flush=True)\n print(f\" {label}: {done / MB:.1f} MB downloaded\")\n return dest", "source_file": "fetch_datasets.py", "function_name": "download", "class_name": null, "line_start": 52, "line_end": 76, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def __init__(self, path: Path, target_bytes: int, seen: set[str], min_len: int = 40) -> None:\n self.path = path\n self.target = target_bytes\n self.seen = seen\n```", "response": " self.min_len = min_len\n self.bytes = 0\n self.docs = 0\n path.parent.mkdir(parents=True, exist_ok=True)\n self.fh = path.open(\"w\", encoding=\"utf-8\", newline=\"\\n\")", "source_file": "fetch_datasets.py", "function_name": "__init__", "class_name": "Writer", "line_start": 82, "line_end": 90, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def add(self, text: str) -> bool:\n \"\"\"Append one document. Returns False when the byte budget is full.\"\"\"\n if self.done():\n return False\n if not text:\n return True\n text = text.strip()\n if len(text) < self.min_len:\n return True\n```", "response": " key = text[:200]\n if key in self.seen:\n return True\n self.seen.add(key)\n line = json.dumps({\"text\": text}, ensure_ascii=False) + \"\\n\"\n self.fh.write(line)\n self.bytes += len(line.encode(\"utf-8\"))\n self.docs += 1\n return not self.done()", "source_file": "fetch_datasets.py", "function_name": "add", "class_name": "Writer", "line_start": 92, "line_end": 109, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_explanation", "language": "python", "instruction": "Explain what this Python method does.\n\n```python\ndef add(self, text: str) -> bool:\n \"\"\"Append one document. Returns False when the byte budget is full.\"\"\"\n if self.done():\n return False\n if not text:\n return True\n text = text.strip()\n if len(text) < self.min_len:\n return True\n key = text[:200]\n if key in self.seen:\n return True\n self.seen.add(key)\n line = json.dumps({\"text\": text}, ensure_ascii=False) + \"\\n\"\n self.fh.write(line)\n self.bytes += len(line.encode(\"utf-8\"))\n self.docs += 1\n return not self.done()\n```", "response": "Append one document. Returns False when the byte budget is full.", "source_file": "fetch_datasets.py", "function_name": "add", "class_name": "Writer", "line_start": 92, "line_end": 109, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_generation", "language": "python", "instruction": "Write a Python method `Writer.add(self, text: str)` that does the following:\n\nAppend one document. Returns False when the byte budget is full.\n\nReturn only the Python code.", "response": "def add(self, text: str) -> bool:\n \"\"\"Append one document. Returns False when the byte budget is full.\"\"\"\n if self.done():\n return False\n if not text:\n return True\n text = text.strip()\n if len(text) < self.min_len:\n return True\n key = text[:200]\n if key in self.seen:\n return True\n self.seen.add(key)\n line = json.dumps({\"text\": text}, ensure_ascii=False) + \"\\n\"\n self.fh.write(line)\n self.bytes += len(line.encode(\"utf-8\"))\n self.docs += 1\n return not self.done()", "source_file": "fetch_datasets.py", "function_name": "add", "class_name": "Writer", "line_start": 92, "line_end": 109, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef parquet_texts(path: Path, columns: list[str]):\n import pyarrow.parquet as pq\n```", "response": " pf = pq.ParquetFile(path)\n for batch in pf.iter_batches(batch_size=256, columns=columns):\n for row in batch.to_pylist():\n yield row", "source_file": "fetch_datasets.py", "function_name": "parquet_texts", "class_name": null, "line_start": 124, "line_end": 130, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef fetch_english(out: Path, mb: float, seen: set[str]) -> None:\n if mb <= 0:\n return\n print(f\"English: Gutenberg books ({mb:.1f} MB)\")\n w = Writer(out / \"english\" / \"gutenberg.jsonl\", int(mb * MB), seen)\n cache = Path(\"data/cache/gutenberg\")\n\n header = re.compile(\n r\"\\*\\*\\*\\s*START OF (THE|THIS) PROJECT GUTENBERG EBOOK.*?\\*\\*\\*\", re.S | re.I\n )\n footer = re.compile(\n r\"\\*\\*\\*\\s*END OF (THE|THIS) PROJECT GUTENBERG EBOOK.*\", re.S | re.I\n )\n```", "response": " for gid in GUTENBERG_IDS:\n if w.done():\n break\n try:\n path = download(\n f\"https://www.gutenberg.org/cache/epub/{gid}/pg{gid}.txt\",\n cache / f\"pg{gid}.txt\",\n f\"book {gid}\",\n )\n except Exception as exc:\n print(f\" book {gid}: {exc}\")\n continue\n raw = path.read_text(encoding=\"utf-8\", errors=\"ignore\")\n raw = header.sub(\"\", raw)\n raw = footer.sub(\"\", raw)\n for block in re.split(r\"\\n\\s*\\n\\s*\\n\", raw):\n block = block.strip()\n if len(block) > 200:\n if not w.add(block):\n break\n w.close()", "source_file": "fetch_datasets.py", "function_name": "fetch_english", "class_name": null, "line_start": 134, "line_end": 168, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef fetch_hindi(out: Path, mb: float, seen: set[str]) -> None:\n if mb <= 0:\n return\n print(f\"Hindi: Hindi Wikipedia ({mb:.1f} MB)\")\n```", "response": " path = download(HINDI_URL, Path(\"data/cache/hi_wiki.parquet\"), \"hindi wiki\")\n w = Writer(out / \"hindi\" / \"wikipedia_hi.jsonl\", int(mb * MB), seen)\n for row in parquet_texts(path, [\"text\"]):\n if not w.add(row.get(\"text\") or \"\"):\n break\n w.close()", "source_file": "fetch_datasets.py", "function_name": "fetch_hindi", "class_name": null, "line_start": 171, "line_end": 180, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef fetch_hinglish(out: Path, mb: float, seen: set[str]) -> None:\n if mb <= 0:\n return\n print(f\"Hinglish: L3Cube Hinglish tweets ({mb:.1f} MB)\")\n path = download(HINGLISH_URL, Path(\"data/cache/hinglish.parquet\"), \"hinglish\")\n w = Writer(out / \"hinglish\" / \"l3cube.jsonl\", int(mb * MB), seen, min_len=12)\n marker = re.compile(r\"###\\s*Hinglish\\s*:\", re.I)\n```", "response": " for row in parquet_texts(path, [\"text\"]):\n text = row.get(\"text\") or \"\"\n m = marker.search(text)\n if m:\n text = text[m.end() :]\n text = text.replace(\"</s>\", \" \").strip()\n if not w.add(text):\n break\n w.close()", "source_file": "fetch_datasets.py", "function_name": "fetch_hinglish", "class_name": null, "line_start": 183, "line_end": 198, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef fetch_code(out: Path, mb: float, seen: set[str]) -> None:\n if mb <= 0:\n return\n stdlib = Path(sysconfig.get_paths()[\"stdlib\"])\n roots = [stdlib, Path(__file__).resolve().parent]\n print(f\"Code: Python sources from {stdlib} ({mb:.1f} MB)\")\n w = Writer(out / \"code\" / \"python.jsonl\", int(mb * MB), seen)\n skip = {\"site-packages\", \"test\", \"tests\", \"__pycache__\", \"idlelib\", \"lib2to3\", \"tkinter\"}\n files = 0\n```", "response": " for root in roots:\n for dirpath, dirnames, filenames in os.walk(root):\n dirnames[:] = [d for d in dirnames if d.lower() not in skip]\n for name in filenames:\n if not name.endswith((\".py\", \".pyi\")):\n continue\n if w.done():\n break\n p = Path(dirpath) / name\n try:\n if p.stat().st_size > 200_000:\n continue\n text = p.read_text(encoding=\"utf-8\", errors=\"ignore\")\n except OSError:\n continue\n files += 1\n if not w.add(f\"# {p.name}\\n{text}\"):\n break\n if w.done():\n break\n if w.done():\n break\n print(f\" scanned {files:,} python files\")\n w.close()", "source_file": "fetch_datasets.py", "function_name": "fetch_code", "class_name": null, "line_start": 201, "line_end": 233, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef main() -> None:\n ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)\n ap.add_argument(\"--out\", default=\"data/raw\")\n ap.add_argument(\"--english-mb\", type=float, default=10)\n ap.add_argument(\"--hindi-mb\", type=float, default=8)\n ap.add_argument(\"--hinglish-mb\", type=float, default=4)\n ap.add_argument(\"--code-mb\", type=float, default=8)\n args = ap.parse_args()\n\n out = Path(args.out)\n out.mkdir(parents=True, exist_ok=True)\n seen: set[str] = set()\n total = args.english_mb + args.hindi_mb + args.hinglish_mb + args.code_mb\n```", "response": " print(f\"building ~{total:.1f} MB corpus in {out}/ \"\n f\"(en {args.english_mb}, hi {args.hindi_mb}, hinglish {args.hinglish_mb}, code {args.code_mb})\\n\")\n started = time.time()\n fetch_english(out, args.english_mb, seen)\n fetch_hindi(out, args.hindi_mb, seen)\n fetch_hinglish(out, args.hinglish_mb, seen)\n fetch_code(out, args.code_mb, seen)\n\n print(f\"\\ndone in {time.time() - started:.0f}s\")\n for d in (\"english\", \"hindi\", \"hinglish\", \"code\"):\n p = out / d\n if p.exists():\n n = sum(f.stat().st_size for f in p.rglob(\"*\") if f.is_file())\n print(f\" {d:<9} {n / MB:6.1f} MB\")\n print(\"\\nnext: python train_tokenizer.py --source files --input data/raw --vocab-size 32768\")", "source_file": "fetch_datasets.py", "function_name": "main", "class_name": null, "line_start": 237, "line_end": 265, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def __init__(self, path: str | Path = \"data/chat/memory.json\") -> None:\n self.path = Path(path)\n self.entries: list[Entry] = []\n```", "response": " self._tokens: list[set[str]] = []\n self.load()", "source_file": "memory_store.py", "function_name": "__init__", "class_name": "MemoryStore", "line_start": 98, "line_end": 102, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def load(self) -> None:\n if not self.path.exists():\n return\n```", "response": " try:\n data = json.loads(self.path.read_text(encoding=\"utf-8\"))\n except (OSError, ValueError):\n return\n self.entries = [Entry(**{k: v for k, v in row.items()\n if k in Entry.__dataclass_fields__})\n for row in data.get(\"entries\", [])]\n self._tokens = [_tokens(e.text) for e in self.entries]", "source_file": "memory_store.py", "function_name": "load", "class_name": "MemoryStore", "line_start": 105, "line_end": 115, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def save(self) -> None:\n self.path.parent.mkdir(parents=True, exist_ok=True)\n payload = {\n \"version\": 1,\n \"saved\": time.time(),\n \"entries\": [e.to_dict() for e in self.entries[-MAX_ENTRIES:]],\n }\n```", "response": " tmp = self.path.with_suffix(\".tmp\")\n tmp.write_text(json.dumps(payload, ensure_ascii=False, indent=1), encoding=\"utf-8\")\n os.replace(tmp, self.path)", "source_file": "memory_store.py", "function_name": "save", "class_name": "MemoryStore", "line_start": 117, "line_end": 126, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def add(self, text: str, kind: str = \"turn\", key: str = \"\",\n emotion: str = \"neutral\", salience: float = 1.0) -> None:\n text = \" \".join(text.split()).strip()\n if not text:\n return\n norm = text.lower()\n```", "response": " for i, entry in enumerate(self.entries):\n if entry.text.lower() == norm and entry.kind == kind and entry.key == key:\n entry.ts = time.time()\n entry.salience = max(entry.salience, salience)\n return\n self.entries.append(Entry(text=text, kind=kind, key=key,\n emotion=emotion, salience=salience))\n self._tokens.append(_tokens(text))\n if len(self.entries) > MAX_ENTRIES:\n drop = len(self.entries) - MAX_ENTRIES\n del self.entries[:drop]\n del self._tokens[:drop]", "source_file": "memory_store.py", "function_name": "add", "class_name": "MemoryStore", "line_start": 129, "line_end": 146, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def forget(self, pattern: str) -> int:\n needle = pattern.lower().strip()\n if not needle:\n return 0\n keep = [e for e in self.entries if needle not in e.text.lower()]\n```", "response": " removed = len(self.entries) - len(keep)\n if removed:\n self.entries = keep\n self._tokens = [_tokens(e.text) for e in keep]\n self.save()\n return removed", "source_file": "memory_store.py", "function_name": "forget", "class_name": "MemoryStore", "line_start": 154, "line_end": 164, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\n def recall(self, query: str, k: int = 3) -> list[tuple[Entry, float]]:\n q = _tokens(query)\n if not q:\n return []\n now = time.time()\n scored: list[tuple[Entry, float]] = []\n```", "response": " for entry, toks in zip(self.entries, self._tokens):\n overlap = len(q & toks)\n if not overlap:\n continue\n score = overlap / math.sqrt(len(q) + 1)\n age_days = (now - entry.ts) / 86_400\n score += 0.18 * math.exp(-age_days / 14.0)\n score += 0.10 * entry.salience / 1.6\n if entry.kind == \"fact\":\n score += 0.35\n scored.append((entry, score))\n scored.sort(key=lambda pair: pair[1], reverse=True)\n return [(e, s) for e, s in scored[:k] if s >= 0.12]", "source_file": "memory_store.py", "function_name": "recall", "class_name": "MemoryStore", "line_start": 179, "line_end": 197, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_completion", "language": "python", "instruction": "Complete the following Python code. Return only the continuation, preserving indentation.\n\n```python\ndef extract_facts(text: str) -> list[tuple[str, str]]:\n \"\"\"Pull durable facts out of a sentence (name, age, city, likes, ...).\"\"\"\n found: list[tuple[str, str]] = []\n```", "response": " for key, pattern in FACT_PATTERNS:\n for match in re.finditer(pattern, text, flags=re.IGNORECASE):\n value = _clean_value(match.group(1))\n if not value or value in FACT_STOP or len(value) > 60:\n continue\n if key == \"age\":\n age = int(value)\n if not (1 <= age <= 120):\n continue\n if key == \"name\" and value.split()[0] in {\"a\", \"an\", \"the\", \"not\"}:\n continue\n if (key, value) not in found:\n found.append((key, value))\n return found", "source_file": "memory_store.py", "function_name": "extract_facts", "class_name": null, "line_start": 214, "line_end": 230, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_explanation", "language": "python", "instruction": "Explain what this Python function does.\n\n```python\ndef extract_facts(text: str) -> list[tuple[str, str]]:\n \"\"\"Pull durable facts out of a sentence (name, age, city, likes, ...).\"\"\"\n found: list[tuple[str, str]] = []\n for key, pattern in FACT_PATTERNS:\n for match in re.finditer(pattern, text, flags=re.IGNORECASE):\n value = _clean_value(match.group(1))\n if not value or value in FACT_STOP or len(value) > 60:\n continue\n if key == \"age\":\n age = int(value)\n if not (1 <= age <= 120):\n continue\n if key == \"name\" and value.split()[0] in {\"a\", \"an\", \"the\", \"not\"}:\n continue\n if (key, value) not in found:\n found.append((key, value))\n return found\n```", "response": "Pull durable facts out of a sentence (name, age, city, likes, ...).", "source_file": "memory_store.py", "function_name": "extract_facts", "class_name": null, "line_start": 214, "line_end": 230, "license": "mit", "source": "SadikAI project"} |
| {"task": "code_generation", "language": "python", "instruction": "Write a Python function `extract_facts(text: str)` that does the following:\n\nPull durable facts out of a sentence (name, age, city, likes, ...).\n\nReturn only the Python code.", "response": "def extract_facts(text: str) -> list[tuple[str, str]]:\n \"\"\"Pull durable facts out of a sentence (name, age, city, likes, ...).\"\"\"\n found: list[tuple[str, str]] = []\n for key, pattern in FACT_PATTERNS:\n for match in re.finditer(pattern, text, flags=re.IGNORECASE):\n value = _clean_value(match.group(1))\n if not value or value in FACT_STOP or len(value) > 60:\n continue\n if key == \"age\":\n age = int(value)\n if not (1 <= age <= 120):\n continue\n if key == \"name\" and value.split()[0] in {\"a\", \"an\", \"the\", \"not\"}:\n continue\n if (key, value) not in found:\n found.append((key, value))\n return found", "source_file": "memory_store.py", "function_name": "extract_facts", "class_name": null, "line_start": 214, "line_end": 230, "license": "mit", "source": "SadikAI project"} |
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