Petr Tsvetkov
commited on
Commit
β’
a3d6ea6
1
Parent(s):
9d14712
- Fix the grazie api
Browse files- Compute the average CM lengths for the dataset and for the production prompt
- Update the charts
api_wrappers/grazie_wrapper.py
CHANGED
@@ -11,7 +11,7 @@ import config
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client = GrazieApiGatewayClient(
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grazie_agent=GrazieAgent("grazie-toolformers", "v1.0"),
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url=GrazieApiGatewayUrls.STAGING,
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-
auth_type=AuthType.
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grazie_jwt_token=config.GRAZIE_API_JWT_TOKEN
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)
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client = GrazieApiGatewayClient(
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grazie_agent=GrazieAgent("grazie-toolformers", "v1.0"),
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url=GrazieApiGatewayUrls.STAGING,
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+
auth_type=AuthType.APPLICATION,
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grazie_jwt_token=config.GRAZIE_API_JWT_TOKEN
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)
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chart_processing.ipynb
CHANGED
The diff for this file is too large to render.
See raw diff
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generated_message_length_comparison.ipynb
CHANGED
@@ -15,23 +15,28 @@
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"id": "77d51d55b41735cf"
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},
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{
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-
"metadata": {
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"cell_type": "code",
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"source": [
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"!pip install grazie-api-gateway-client\n",
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"!pip install tqdm\n",
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"!pip install pandas\n",
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"!pip install datasets"
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],
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"id": "91fa273e8987f6f6",
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"outputs": [],
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-
"execution_count":
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-
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"start_time": "2024-
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}
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},
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"cell_type": "code",
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@@ -44,13 +49,13 @@
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],
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"id": "ce11a4c781c152e",
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"outputs": [],
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-
"execution_count":
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-
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"start_time": "2024-
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}
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},
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"cell_type": "code",
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@@ -62,25 +67,41 @@
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"\treturn PROD_PROMPT.replace(\"$diff\", diff).replace(\"$text\", \"\")\n",
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"\n",
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"def generate_commit_message_prod(diff):\n",
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-
"\
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],
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"id": "84a769c8765a7b64",
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"outputs": [],
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-
"execution_count":
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},
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{
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"metadata": {
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"cell_type": "code",
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"source": "generate_commit_message_prod(\"TEST\")",
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"id": "af2f20def94b0490",
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"outputs": [
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-
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"start_time": "2024-
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}
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},
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"cell_type": "code",
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@@ -90,6 +111,16 @@
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],
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"id": "a49cabf576c9d692",
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"outputs": [
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{
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"data": {
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"text/plain": [
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@@ -161,26 +192,39 @@
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"</div>"
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]
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},
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"execution_count":
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count":
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},
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{
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"metadata": {
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"cell_type": "code",
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"source": "DATA[\"prediction_prod\"] = DATA.progress_apply(lambda row: generate_commit_message_prod(str(row[\"diff\"])), axis=1)",
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"id": "9ded493e087f991d",
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"outputs": [
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-
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"start_time": "2024-
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}
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},
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"cell_type": "code",
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@@ -198,26 +242,52 @@
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]
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}
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],
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"execution_count":
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},
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{
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"metadata": {
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"cell_type": "code",
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"source": [
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"prod_avg_length = DATA[\"prediction_prod\"].str.len().mean()\n",
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"print(f\"Prod average length: {prod_avg_length}\")"
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],
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"id": "ec8b4412410794a4",
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"outputs": [
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{
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"metadata": {
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"cell_type": "code",
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"source": "print(f\"Length ratio (current / prod): {current_avg_length / prod_avg_length})\")",
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"id": "10f087784896eca3",
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"outputs": [
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}
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],
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"metadata": {
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"id": "77d51d55b41735cf"
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},
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{
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+
"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:09:07.968406Z",
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"start_time": "2024-06-20T16:09:07.955405Z"
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}
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},
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"cell_type": "code",
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"source": [
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"# !pip install grazie-api-gateway-client\n",
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"# !pip install tqdm\n",
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"# !pip install pandas\n",
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"# !pip install datasets"
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],
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"id": "91fa273e8987f6f6",
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"outputs": [],
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"execution_count": 1
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:09:10.353479Z",
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"start_time": "2024-06-20T16:09:07.970405Z"
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}
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},
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"cell_type": "code",
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],
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"id": "ce11a4c781c152e",
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"outputs": [],
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"execution_count": 2
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:09:10.368996Z",
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"start_time": "2024-06-20T16:09:10.354434Z"
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}
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},
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"cell_type": "code",
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"\treturn PROD_PROMPT.replace(\"$diff\", diff).replace(\"$text\", \"\")\n",
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"\n",
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"def generate_commit_message_prod(diff):\n",
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"\treturn generate_for_prompt(prod_prompt(diff))"
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],
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"id": "84a769c8765a7b64",
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"outputs": [],
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"execution_count": 3
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:09:10.384590Z",
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"start_time": "2024-06-20T16:09:10.371410Z"
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}
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},
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"cell_type": "code",
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"source": "generate_commit_message_prod(\"TEST\")",
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"id": "af2f20def94b0490",
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\"Certainly! I'll need to see the specific code differences (diffs) you would like to have summarized into a commit message. Please provide the diffs so I can assist you properly.\""
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 4
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:09:22.224167Z",
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"start_time": "2024-06-20T16:09:10.388409Z"
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}
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},
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"cell_type": "code",
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],
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"id": "a49cabf576c9d692",
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Using the latest cached version of the dataset since JetBrains-Research/lca-commit-message-generation couldn't be found on the Hugging Face Hub\n",
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"Found the latest cached dataset configuration 'commitchronicle-py-long' at cache\\JetBrains-Research___lca-commit-message-generation\\commitchronicle-py-long\\0.0.0\\58dcef83a63cccebacd3e786afd73181cc9175e5 (last modified on Sun Apr 7 11:16:22 2024).\n",
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"Using the latest cached version of the dataset since JetBrains-Research/lca-results couldn't be found on the Hugging Face Hub\n",
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"Found the latest cached dataset configuration 'cmg_gpt_4_0613' at cache\\JetBrains-Research___lca-results\\cmg_gpt_4_0613\\0.0.0\\4b56bbf7243da371b3e0a42a0c9db1f37af98c39 (last modified on Fri May 31 16:00:33 2024).\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"</div>"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 5
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:21:20.410778Z",
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"start_time": "2024-06-20T16:09:22.227258Z"
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}
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},
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"cell_type": "code",
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"source": "DATA[\"prediction_prod\"] = DATA.progress_apply(lambda row: generate_commit_message_prod(str(row[\"diff\"])), axis=1)",
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"id": "9ded493e087f991d",
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"100%|ββββββββββ| 163/163 [11:58<00:00, 4.41s/it]\n"
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]
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}
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],
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"execution_count": 6
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:21:20.426781Z",
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"start_time": "2024-06-20T16:21:20.414781Z"
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}
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"cell_type": "code",
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]
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}
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],
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"execution_count": 7
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:21:20.442017Z",
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"start_time": "2024-06-20T16:21:20.429913Z"
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}
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},
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"cell_type": "code",
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"source": [
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"prod_avg_length = DATA[\"prediction_prod\"].str.len().mean()\n",
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"print(f\"Prod average length: {prod_avg_length}\")"
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],
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"id": "ec8b4412410794a4",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Prod average length: 352.88957055214723\n"
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]
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}
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],
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"execution_count": 8
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-20T16:21:20.457884Z",
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"start_time": "2024-06-20T16:21:20.444852Z"
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}
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},
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"cell_type": "code",
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"source": "print(f\"Length ratio (current / prod): {current_avg_length / prod_avg_length})\")",
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"id": "10f087784896eca3",
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Length ratio (current / prod): 1.772691712591923)\n"
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]
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}
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],
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"execution_count": 9
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}
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],
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"metadata": {
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