This project implements a Python client using OpenAIs Assistants API. An Assistant has instructions and can leverage models, tools, and knowledge to respond to user queries.
pip install -U openai
Note: Requires a OPENAI_API_KEY in .env and a paid plan for the Assistants API.
cat .env
OPENAI_API_KEY="sk-...."
python ./client.py -h
usage: client.py [-h] [-v] [-D]
OpenAI Assistant API Client (type 'exit' or CTRL-C to end).
options:
-h, --help show this help message and exit
-v, --verbose verbose
-D, --debug more verbose
The client.py creates a new assistant instance if none exists. The instructions prompt settings below are for some simple log file analysis use-case. The corresponding data set is in the files list and the data gets uploaded to your OpenAI assistant instance.
In assistant/client.py:
"""
Assistant level settings
- model: the OpenAI model of choice
- instructions: to guide the personality of the Assistant and define its goals (system prompt)
- functions: your own functions or third-party tools integration via a function calling
- files: tools access to your own domain data, upload your data here
- message_instructions: thread (message) level prompt
"""
tim_args = {
"name": "tim",
"instructions": """You are a root-cause analyst and your task is to
analyze system log files for software issues like failure events
or critical conditions and their initial root cause or trigger.
Task 1: Process files and look for this pattern, example,
ERROR rq.worker Traceback (most recent call last).
Task 2: After you find these patterns, correlate with any log
messages with a lower timestamp and with matching IP address.
Do not consider recurring log messages if they contain or represent a failure.
Task 3: Summarize the results in a bullet list containing timestamps
in ascending order and including data from the log message.""",
"model": "gpt-4-1106-preview",
"functions": [
"Schemas.getSummary",
"Schemas.getTimestampDelta",
"Schemas.getLogSeveritySubject",
"Schemas.getIpAddress",
],
"tools": [
{"type": "code_interpreter"},
{"type": "function", "function": Schemas.getSummary},
{"type": "function", "function": Schemas.getTimestampDelta},
{"type": "function", "function": Schemas.getLogSeveritySubject},
{"type": "function", "function": Schemas.getIpAddress},
],
"files": [
"/home/user/assistant/data/data.csv",
],
}
"""
Thread (message) level settings
- additional instructions specific to the assistent and message.
"""
message_instructions = "Analyze the input and format and structure the output."
python ./client.py
Existing assistants:
#0: asst_VxfQYPYeIs1e08DScbBA5tbz
Model: gpt-4-1106-preview
Name: tim
Files: ['file-fUG736fDSiOg1ycYTGd6i7jy']
Instructions: You are a root-cause analyst and your task is to
analyze system log files for software issues like failure events
or critical conditions and their initial root cause or trigger.
Task 1: Process files and look for this pattern, example,
ERROR rq.worker Traceback (most recent call last).
Task 2: After you find these patterns, correlate with any log
messages with a lower timestamp and with matching IP address.
Do not consider recurring log messages if they contain or represent a failure.
Task 3: Summarize the results in a bullet list containing timestamps
in ascending order and including data from the log message.
Select assistant [0..0] or create a new one [c]: 0
You> exit
Ending the conversation.
You> Please analyze the attached file for any software issues.
(00:07:58)> Here are the extracted messages from the logs that contain an `error` and `warnings`:
**Error Message:**
- "Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: ERROR rq.worker Traceback (most recent call last):"
**Warning Messages:**
- Multiple occurrences are reporting a "Not Found" error for a specific URL path (`/api-v1/node-manager/cluster/config`). This could be an indication of a misconfiguration or an issue with the node manager's cluster configuration endpoint.
It seems that apart from one error related to a traceback, the warnings are primarily related to the unavailability of a specific API endpoint. Based on this information, further investigation into the causes behind this warning and the error message would be warranted.
You> Can you show the log messages in the context of the error events you found?
(00:15:03)> Here are the full log messages in the context around the error event:
- INFO jobs.base Running job disk_space_low
- INFO jobs.base finished job disk_space_low in 0.03658160101622343 seconds
- INFO rq.worker default: Job OK (13fb1d9a-2cdf-4f7d-afce-e4aa3a830f27)
- INFO rq.worker default: execute() (387209b2-6b47-439e-97ef-141302a7df61)
- INFO jobs.base Running job certificate_expiration
- ERROR rq.worker Traceback (most recent call last):
- INFO rq.worker default: execute() (557aeda4-e5fe-407b-94fd-7debb4766a0f)
- INFO jobs.base Running job event_data_retention
- INFO events.models prune results=None
- INFO rq.worker default: Job OK (557aeda4-e5fe-407b-94fd-7debb4766a0f)
- INFO rq.worker default: execute() (7774fe50-f0f7-4426-a370-71dea0043246)
From the context provided by these log messages, it seems that the `ERROR` appears to be related to some kind of issue during the execution of a job. The logs indicate that jobs for "disk_space_low" and "certificate_expiration" were running prior to the error, followed by "event_data_retention".
The error message indicates that a traceback occurred, which suggests an exception was raised during job processing. Unfortunately, the actual exception and the stack trace are not included in the log line captured, but they would be critical to diagnose the precise issue. Typically, the traceback would provide the exact point of failure in the code.
The JSON debugs show the assistant dispatched calls to the configured tools. In most cases the code_interpreter found the correct information using pandas.
You> Please analyze the attached file for any software issues.
Assistant requests 6 tools.
2023-12-14T12:03:14.523 assistant INFO Assistant requested getSummary({'failure': 'failure'})
2023-12-14T12:03:14.523 assistant INFO Function call returning: {'failure': 'failure'}
2023-12-14T12:03:14.524 assistant INFO Assistant requested getSummary({'failure': 'error'})
2023-12-14T12:03:14.524 assistant INFO Function call returning: {'failure': 'error'}
2023-12-14T12:03:14.524 assistant INFO Assistant requested getSummary({'failure': 'warning'})
2023-12-14T12:03:14.524 assistant INFO Function call returning: {'failure': 'warning'}
2023-12-14T12:03:14.524 assistant INFO Assistant requested getSummary({'failure': 'exception'})
2023-12-14T12:03:14.524 assistant INFO Function call returning: {'failure': 'exception'}
2023-12-14T12:03:14.524 assistant INFO Assistant requested getSummary({'failure': 'critical'})
2023-12-14T12:03:14.525 assistant INFO Function call returning: {'failure': 'critical'}
2023-12-14T12:03:14.525 assistant INFO Assistant requested getSummary({'failure': 'fatal'})
2023-12-14T12:03:14.525 assistant INFO Function call returning: {'failure': 'fatal'}
(00:07:58)> Here are the extracted messages from the logs that contain an `error` and `warnings`:
**Error Message:**
- "Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: ERROR rq.worker Traceback (most recent call last):"
**Warning Messages:**
- Multiple occurrences are reporting a "Not Found" error for a specific URL path (`/api-v1/node-manager/cluster/config`). This could be an indication of a misconfiguration or an issue with the node manager's cluster configuration endpoint.
It seems that apart from one error related to a traceback, the warnings are primarily related to the unavailability of a specific API endpoint. Based on this information, further investigation into the causes behind this warning and the error message would be warranted.
Would you like to take any additional steps based on this analysis, such as examining specific log entries in more detail or extracting the timestamp difference between error logs?
2023-12-14T12:04:16.982 __main__ INFO Run steps:
{
"message_creation": {
"message_id": "msg_3lmq2i8pkkD2P8UJrfrceUEO"
},
"type": "message_creation"
}{
"tool_calls": [
{
"id": "call_hSJZTaWaVnM2SEKoBT0KNFeQ",
"code_interpreter": {
"input": "# Retrieve the actual log messages that contain the keywords 'error' and 'warning'\r\nerror_messages = issues['error']\r\nwarning_messages = issues['warning']\r\n\r\nerror_messages, warning_messages",
"outputs": [
{
"logs": "(['Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: ERROR rq.worker Traceback (most recent call last):'],\n ['Dec 18 23:54:02 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 18 23:55:03 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 18 23:56:03 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 18 23:57:02 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 18 23:58:03 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 18 23:59:03 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 19 00:00:02 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 19 00:01:03 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 19 00:02:03 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 19 00:03:02 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config',\n 'Dec 19 00:04:03 secpctbmgr1 aa95177baeb3[620]: WARNING django.request Not Found: /api-v1/node-manager/cluster/config'])",
"type": "logs"
}
]
},
"type": "code_interpreter"
}
],
"type": "tool_calls"
}{
"message_creation": {
"message_id": "msg_Fl0ISvFD9bxxfxUdjvqq8GTV"
},
"type": "message_creation"
}{
"tool_calls": [
{
"id": "call_4RteBs0e9yMo0zZMi29BcdeT",
"code_interpreter": {
"input": "# Define a function to search for specific keywords in the log messages and classify them\r\ndef extract_issues(log_messages, keywords):\r\n # Store the results\r\n issues = {keyword: [] for keyword in keywords}\r\n \r\n # Search each log entry for the keywords\r\n for message in log_messages:\r\n for keyword in keywords:\r\n if keyword.lower() in message.lower():\r\n issues[keyword].append(message)\r\n \r\n # Count the occurrences of each keyword\r\n issue_counts = {keyword: len(messages) for keyword, messages in issues.items()}\r\n \r\n return issues, issue_counts\r\n\r\n# Keywords related to software issues\r\nkeywords = [\"failure\", \"error\", \"warning\", \"exception\", \"critical\", \"fatal\"]\r\n\r\n# Extract issues and counts from the log messages\r\nissues, issue_counts = extract_issues(log_df['Message'], keywords)\r\n\r\nissue_counts",
"outputs": [
{
"logs": "{'failure': 0,\n 'error': 1,\n 'warning': 11,\n 'exception': 0,\n 'critical': 0,\n 'fatal': 0}",
"type": "logs"
}
]
},
"type": "code_interpreter"
}
],
"type": "tool_calls"
}{
"message_creation": {
"message_id": "msg_BgYlL5SjAKcArzl1b6zdVDSM"
},
"type": "message_creation"
}{
"tool_calls": [
{
"id": "call_Ri0kBvco6VVWDmsn9AuKv4PD",
"function": {
"arguments": "{\"failure\": \"failure\"}",
"name": "getSummary",
"output": "{\"failure\": \"failure\"}"
},
"type": "function"
},
{
"id": "call_iVtaMjoZyspXtcnVyJ9qHnts",
"function": {
"arguments": "{\"failure\": \"error\"}",
"name": "getSummary",
"output": "{\"failure\": \"error\"}"
},
"type": "function"
},
{
"id": "call_5NKKVxWHU5C1iDVH4LpnPAV1",
"function": {
"arguments": "{\"failure\": \"warning\"}",
"name": "getSummary",
"output": "{\"failure\": \"warning\"}"
},
"type": "function"
},
{
"id": "call_5RpZ9D8NIKLPdkiMiByoH2Qw",
"function": {
"arguments": "{\"failure\": \"exception\"}",
"name": "getSummary",
"output": "{\"failure\": \"exception\"}"
},
"type": "function"
},
{
"id": "call_TQfwyFar5kxpOgehECWaUC5K",
"function": {
"arguments": "{\"failure\": \"critical\"}",
"name": "getSummary",
"output": "{\"failure\": \"critical\"}"
},
"type": "function"
},
{
"id": "call_YM1r0QrcbbC3l1ZAvhA9mvpI",
"function": {
"arguments": "{\"failure\": \"fatal\"}",
"name": "getSummary",
"output": "{\"failure\": \"fatal\"}"
},
"type": "function"
}
],
"type": "tool_calls"
}{
"message_creation": {
"message_id": "msg_BAwcfo81IgXFuRl6S7KUbGpR"
},
"type": "message_creation"
}{
"tool_calls": [
{
"id": "call_JKA9QaQrIu2Ow1MUoY6Q2HHc",
"code_interpreter": {
"input": "import pandas as pd\r\n\r\n# Load the file into a pandas DataFrame to better analyze it\r\nlog_df = pd.read_csv(file_path)\r\n\r\n# Display basic information about the DataFrame and the first few rows to better understand its structure\r\nlog_info = log_df.info()\r\nlog_head = log_df.head()\r\n\r\nlog_info, log_head",
"outputs": [
{
"logs": "<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 200 entries, 0 to 199\nData columns (total 3 columns):\n # Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 Unnamed: 0 200 non-null int64 \n 1 UTC 200 non-null float64\n 2 Message 200 non-null object \ndtypes: float64(1), int64(1), object(1)\nmemory usage: 4.8+ KB\n(None,\n Unnamed: 0 UTC Message\n 0 23102 1.671408e+09 Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]:...\n 1 23103 1.671408e+09 Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]:...\n 2 23104 1.671408e+09 Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]:...\n 3 23105 1.671408e+09 Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]:...\n 4 23106 1.671408e+09 Dec 18 23:53:54 secpctbmgr1 aa95177baeb3[620]:...)",
"type": "logs"
}
]
},
"type": "code_interpreter"
}
],
"type": "tool_calls"
}{
"message_creation": {
"message_id": "msg_lxZGGgpRpUq0XqYeYaP3cY3t"
},
"type": "message_creation"
}{
"tool_calls": [
{
"id": "call_hDPchT7gaRq0izHKBbOj7zI4",
"code_interpreter": {
"input": "# First, let's check the content of the uploaded file to understand its structure\r\nfile_path = '/mnt/data/file-fUG736fDDiOg1ycNTGd6i7jy'\r\n\r\n# Let's try to read the first few lines of the file to determine its structure.\r\nwith open(file_path, 'r') as file:\r\n sample_content = [next(file) for _ in range(5)]\r\n\r\nsample_content",
"outputs": [
{
"logs": "[',UTC,Message\\n',\n '23102,1671407614.807,Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]: INFO updates.models attempting move from state: dl_checking\\n',\n '23103,1671407614.81,Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]: INFO jobs.base finished job updates in 0.01437351480126381 seconds\\n',\n '23104,1671407614.811,Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]: INFO rq.worker default: Job OK (cbbede5f-fb18-4cfb-8d10-9f9db714afad)\\n',\n '23105,1671407614.812,\"Dec 18 23:53:34 secpctbmgr1 6d23e148f79a[620]: INFO rq.worker Result will never expire, clean up result key manually\"\\n']",
"type": "logs"
}
]
},
"type": "code_interpreter"
}
],
"type": "tool_calls"
}{
"message_creation": {
"message_id": "msg_5rVLWdcBQ0rYFzxRthSVVmRl"
},
"type": "message_creation"
}
You> Can you show the log messages in the context of the error events you found?
(00:15:03)> Here are the full log messages in the context around the error event:
- INFO jobs.base Running job disk_space_low
- INFO jobs.base finished job disk_space_low in 0.03658160101622343 seconds
- INFO rq.worker default: Job OK (13fb1d9a-2cdf-4f7d-afce-e4aa3a830f27)
- INFO rq.worker default: execute() (387209b2-6b47-439e-97ef-141302a7df61)
- INFO jobs.base Running job certificate_expiration
- ERROR rq.worker Traceback (most recent call last):
- INFO rq.worker default: execute() (557aeda4-e5fe-407b-94fd-7debb4766a0f)
- INFO jobs.base Running job event_data_retention
- INFO events.models prune results=None
- INFO rq.worker default: Job OK (557aeda4-e5fe-407b-94fd-7debb4766a0f)
- INFO rq.worker default: execute() (7774fe50-f0f7-4426-a370-71dea0043246)
From the context provided by these log messages, it seems that the `ERROR` appears to be related to some kind of issue during the execution of a job. The logs indicate that jobs for "disk_space_low" and "certificate_expiration" were running prior to the error, followed by "event_data_retention".
The error message indicates that a traceback occurred, which suggests an exception was raised during job processing. Unfortunately, the actual exception and the stack trace are not included in the log line captured, but they would be critical to diagnose the precise issue. Typically, the traceback would provide the exact point of failure in the code.
If further investigation is needed, one could look into the job processing system's logs in more detail to understand what caused the error, especially by identifying the job or task that was running at the time of the error.
2023-12-14T12:55:25.880 __main__ INFO Run steps:
{
"message_creation": {
"message_id": "msg_vUMZLROBcG6N9tCr3kmwvuo2"
},
"type": "message_creation"
}{
"tool_calls": [
{
"id": "call_Ym3PzE4wbSdMnLrdqG9Gu4Or",
"code_interpreter": {
"input": "# Re-import pandas as the previous state has been reset\r\nimport pandas as pd\r\n\r\n# Define the file path\r\nfile_path = '/mnt/data/file-fUG736fDDiOg1ycNTGd6i7jy'\r\n\r\n# Re-load the file into a DataFrame\r\nlog_df = pd.read_csv(file_path)\r\n\r\n# Find the index of the error message in the DataFrame to get the entries before and after it\r\nerror_index = log_df[log_df['Message'].str.contains(\"ERROR\")].index[0]\r\n\r\n# Determine how many lines of context we want to show before and after the error\r\ncontext_lines = 5\r\n\r\n# Get the relevant slice of the DataFrame\r\nerror_context_df = log_df.iloc[max(error_index - context_lines, 0):min(error_index + context_lines + 1, len(log_df))]\r\n\r\n# Display the full messages for better context\r\nerror_context_full_messages = error_context_df['Message'].tolist()\r\nerror_context_full_messages",
"outputs": [
{
"logs": "['Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO jobs.base Running job disk_space_low',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO jobs.base finished job disk_space_low in 0.03658160101622343 seconds',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO rq.worker default: Job OK (13fb1d9a-2cdf-4f7d-afce-e4aa3a830f27)',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO rq.worker default: execute() (387209b2-6b47-439e-97ef-141302a7df61)',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO jobs.base Running job certificate_expiration',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: ERROR rq.worker Traceback (most recent call last):',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO rq.worker default: execute() (557aeda4-e5fe-407b-94fd-7debb4766a0f)',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO jobs.base Running job event_data_retention',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO events.models prune results=None',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO rq.worker default: Job OK (557aeda4-e5fe-407b-94fd-7debb4766a0f)',\n 'Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]: INFO rq.worker default: execute() (7774fe50-f0f7-4426-a370-71dea0043246)']",
"type": "logs"
}
]
},
"type": "code_interpreter"
}
],
"type": "tool_calls"
}{
"message_creation": {
"message_id": "msg_8GOhxkojn0Kcfl2vnhNuqfK6"
},
"type": "message_creation"
}{
"tool_calls": [
{
"id": "call_A3UK5i3ZobdqMrRKeYSPtxYp",
"code_interpreter": {
"input": "# The code execution state has been reset. Let's re-import the necessary libraries and re-read the file.\r\nimport pandas as pd\r\n\r\n# Re-load the log file\r\nfile_path = '/mnt/data/file-fUG736fDDiOg1ycNTGd6i7jy'\r\nlog_df = pd.read_csv(file_path)\r\n\r\n# Find the error message within the logs and get its index\r\nerror_message = \"ERROR\"\r\nerror_indexes = log_df[log_df['Message'].str.contains(error_message)].index\r\n\r\n# Display a few lines before and after the error message for context\r\ncontext_range = 5 # Define the range of lines before and after the error message to display\r\n\r\n# Get the logs context for each error message found\r\nerror_contexts = []\r\nfor error_index in error_indexes:\r\n start_index = max(error_index - context_range, 0)\r\n end_index = min(error_index + context_range + 1, len(log_df))\r\n error_contexts.append(log_df.iloc[start_index:end_index])\r\n\r\n# If multiple error messages exist, show the context for the first one for brevity\r\nerror_contexts[0] if error_contexts else \"No error messages found.\"",
"outputs": [
{
"logs": " Unnamed: 0 UTC \\\n113 23215 1.671408e+09 \n114 23216 1.671408e+09 \n115 23217 1.671408e+09 \n116 23218 1.671408e+09 \n117 23219 1.671408e+09 \n118 23220 1.671408e+09 \n119 23221 1.671408e+09 \n120 23222 1.671408e+09 \n121 23223 1.671408e+09 \n122 23224 1.671408e+09 \n123 23225 1.671408e+09 \n\n Message \n113 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n114 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n115 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n116 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n117 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n118 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n119 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n120 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n121 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n122 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... \n123 Dec 19 00:00:35 secpctbmgr1 6d23e148f79a[620]:... ",
"type": "logs"
}
]
},
"type": "code_interpreter"
}
],
"type": "tool_calls"
}{
"tool_calls": [
{
"id": "call_F6puHXYyOD9GhxImRy3hXFse",
"code_interpreter": {
"input": "# Find the index of the error message in the DataFrame to get the entries before and after it\r\nerror_index = log_df[log_df['Message'].isin(error_messages)].index[0]\r\n\r\n# Determine how many lines of context we want to show before and after the error\r\ncontext_lines = 5\r\n\r\n# Get the relevant slice of the DataFrame\r\nerror_context_df = log_df[max(error_index - context_lines, 0):min(error_index + context_lines + 1, len(log_df))]\r\n\r\nerror_context_df",
"outputs": []
},
"type": "code_interpreter"
}
],
"type": "tool_calls"
}{
"message_creation": {
"message_id": "msg_mMXLffx4968CgliOxTKw8hRn"
},
"type": "message_creation"
}
You>