feat: data generation for ctx distillation and rule to code (#5)

* feat: data generation for ctx distillation and rule to code

* hotfix

* hotfix

* chore

* Update datagen/ctxdistill/ctxdistill.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update datagen/ctxdistill/ctxdistill.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

Author: ganler

datagen/ctxdistill/ctxdistill.py

@@ -0,0 +1,57 @@
+# SPDX-FileCopyrightText: (c) UIUC PurpCode Team
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from datagen.ctxdistill.ctxdistill import run_distillation
+
+DEFAULT_SAMPLE_RATIO_MEDIUM = 0.25
+
+# Core logic behind:
+# Pick a subset of data {D} total prompts -> {N} prompts
+# Ctx based sampling -> {N * S} where S is the sample size
+# Verfication and pick best of S -> getting {K} prompts with verified responses
+# SFT over {K} prompt-response pairs
+# RL on {D} - {N where most responses are right} prompts, i.e., rm very easy prompts
+
+
+def main(**kwargs):
+    single_turn_datasets = [
+        # mal event / single-turn
+        (
+            "purpcode/mal-event-jailbreak-single-oss-16k",
+            DEFAULT_SAMPLE_RATIO_MEDIUM,
+            4096,
+        ),
+        (
+            "purpcode/mal-event-seed-attack-oss-24k",
+            DEFAULT_SAMPLE_RATIO_MEDIUM,
+            4096,
+        ),
+        # vul code / single-turn
+        ("purpcode/vul2prompt-general-oss-26k", DEFAULT_SAMPLE_RATIO_MEDIUM, 4096),
+        ("purpcode/vul2prompt-benign2vul-oss-21k", DEFAULT_SAMPLE_RATIO_MEDIUM, 4096),
+        ("purpcode/vul2prompt-vul2vul-oss-21k", DEFAULT_SAMPLE_RATIO_MEDIUM, 2048),
+        (
+            "purpcode/vul2prompt-jailbreaking-oss-11k",
+            DEFAULT_SAMPLE_RATIO_MEDIUM,
+            2048,
+        ),
+        # utility
+        ("purpcode/secqa_utility_train", DEFAULT_SAMPLE_RATIO_MEDIUM, 4096),
+        ("KodCode/KodCode-V1-SFT-R1", DEFAULT_SAMPLE_RATIO_MEDIUM, 8192),
+    ]
+    multi_turn_datasets = [
+        # vul code / multi-turn
+        ("purpcode/vul2prompt-multi-oss-5k", 1.0),
+        # mal event / multi-turn
+        ("purpcode/mal-event-fitd-multi-turn-oss-2k", 1.0),
+    ]
+
+    datasets = single_turn_datasets + multi_turn_datasets
+    run_distillation(datasets=datasets, **kwargs)
+
+
+if __name__ == "__main__":
+    from fire import Fire
+
+    Fire(main)