⚠️ Disclaimer: This project is open sourced to solve problems that are critical to some users, and the functions provided may not be natively provided by GitHub Copilot. Therefore the contents, opinions and views expressed in this project are solely mine do not necessarly refect the views of my employer, These are my personal notes based on myunderstanding of the code and trial deployments to GitHub Copilot. If anything is wrong with this article, please let me know through the issues. l appreciate your help in correcting my understanding.
⚠️ Risk Warning: This project provides metrics on individual dimensions that Copilot's original metrics do not have, which may cause potential developer stress and mental pressure. Please use it with caution ONLY for research purposes, do not use it for performance evaluation or other purposes that may cause harm to developers.
| Version | Update Notes | Date |
|---|---|---|
| 1.0 | Add the feature of recording completions and telemetry of Copilot. | 20241208 |
| 1.1 | - By default, telemetry logs are not saved. - Added parsing of the content fields of request and response in completion |
20241225 |
| 1.1 | Feature: Read proxy authentication informatio and save the log to the corresponding subdirectory according to the URL containing "copilot-codex/completions" or "chat/completions", otherwise skip the record. | 20241226 |
| 1.2 | Feature: Enhance proxy_addons.py to track usage metrics and save to separate files; refactor logging paths and update metrics handling |
20241228 |
| 1.3 | - Feature: Add filtering for meaningless requests to ensure that only valuable data is calculated - Feature: Add auth |
20241229 |
| 1.4 | Fixed the verification logic bug of basic authentication; adjusted the proxy server side log format and added emoji🙂 to make the log very clear | 20241230 |
| 1.5 | Add functionality to load and save usernames from a JSON file, In order to avoid the problem that sometimes requests do not carry Authorization, that cause requests to be dropped | 20250108 |
| 1.6 | Different event types have been added to logging and metrics, including nes, agent, edits, chat-inline, chat-panel. |
20250224 |
| 1.7 | 1. Added model tracking in metrics - now records which AI models are used within each editor version for more detailed analytics. 2. Visualization with Grafana & Elasticsearch. 3. Deploy Guides |
20250312 |
| 1.8 | 1. Add support for segmentation of inline chat event types: fix/explain/docs/tests. Added tracking for the new metrics and implemented corresponding log updates.2. Copilot MCP compatible metrics |
20250314 |
Because according to the official Copilot document REST API endpoints for Copilot metrics - GitHub Enterprise Cloud Docs:
This endpoint will only return results for a given day if the team had five or more members with active Copilot licenses on that day, as evaluated at the end of that day.
So, if you want to view the usage of Copilot, the smallest granularity is Teams, and it is a Team with at least 5 members. if this is OK for you, just follow Copilot Usage Advanced Dashboard to visualize it.
But, if you are an admin of your Enterprise/Organizations/Teams with GitHub Copilot enabled, and you want to know the usage details of every users, models, Chat types, and the use of Extensions, try this project. this is why built this.
- A proxy plugin to capture and log HTTP requests and responses between your IDE and GitHub Copilot APIs.
- Save the usage details data of every user, and generate user-dimensional metrics.
- Whitelisting of allowed users, supports basic authentication
- Support for multiple IDEs, including JetBrains and VSCode
- Visualization of the metrics for every user, model, chat types, and extensions with Grafana & Elasticsearch
- link: copilot-metrics-for-everyuser
- username：
demouser - password：
demouser
- These are general guidelines for Copilot block:
- Do not change any GitHub Copilot HTTP headers on network
- Do not share GitHub accounts and GitHub Copilot access
- GitHub personal account can not be shared, GitHub can block those shared accounts.
- GitHub Copilot access can not be shared between multiple users.
- Maintain a single GitHub Copilot access network outbound so one user do not access GitHub Copilot from different locations at the same time
- Do not use a program to generate Copilot token, the token needs to be requested from the official GitHub Copilot IDE extension
- GitHub does not recommend customers on solutions that are not part of GitHub's product, in the case of internet proxy officially GitHub support will not support issues on proxy or advise which proxy to use.
-
Proxy traffic. For a network-isolated development environment.
-
Prompts Recording. Captures HTTP requests and responses and logs the details to files, this will let you know exactly what the code snippets (prompts) sent by Copilot are.
- Copilot Metrics for Every User. Supports basic authentication, this allows you to get the data of the user dimension, deeper than team dimension.
- Visualization (Optional) of the metrics for every user, model, chat types, and extensions with Grafana & Elasticsearch (All yellow services can be deployed on the same machine,
mfe2esis short for Metrics For Everyuser To ElasticSearch).
- Prepare an intermediary server, with IP address
a.b.c.d(The following diagrams and documents all use127.0.0.1as an example. Please replace it with your actual IP address). - Follow the doc to install mitmproxy. If you use pip to install mitmproxy on Windows, you need to add the exe path to the environment variable.
- There are some key parameters to configure in
proxy_addons.py, mitmproxy will automatically reload the script once it has been modified.# Conditional judgment, It is recommended to set it to True, which will perform rule checks on all requests to ensure that the number of chats and completions are not counted multiple times. conditional_judgment = True # False True # if you want to use advanced feature, set this to True. This requires that the user must configure basic authentication is_proxy_auth_needed = True # False True # This value is very sensitive, please change it to a value that only you know. This is the key parameter used to calculate the password. random_seed = 123456 # Limit access to only these users # All users you allow to use Copilot through this proxy can be customized, and they do not need to be the same as the username used to log in to Copilot. # This plugin will automatically generate passwords and save them in logs/user_auth.json. As an administrator, please protect this file and tell each user their generated passwords. allowed_usernames = [ "satomic", "xuefeng", ]
- run command in console
mitmdump --listen-host 0.0.0.0 --listen-port 8080 --set block_global=false -s proxy_addons.py
- The contents of the automatically generated
auditlogs/user_auth.jsonare as follows{ "satomic": "961aa8753b", "xuefeng": "1b3ecfa5aa" } - Tell these users their usernames and passwords
- Before you start this section, strongly recommend you to read the Copilot Usage Advanced Dashboard Special Notes first. And strongly recommend you to deploy the Copilot Usage Advanced Dashboard first, and then deploy this project. Then you can reuse the same Docker, Elasticsearch and Grafana, and you don't need to deploy them again. Your architecture will look like this:
- If you don't want to deploy the Copilot Usage Advanced Dashboard, you can also follow the guide to deploy Docker, Elasticsearch and Grafana, and then deploy this project. The only difference is that you need to deploy the
mfe2escontainer separately, and themfe2escontainer will be used to send the metrics data to Elasticsearch.
Put all the work in the /srv directory, click download zip archive, unzip and rename the folder to copilot-metrics-4-every-user, or directly git clone
cd /srv
git clone https://github.com/satomic/copilot-metrics-4-every-user.git
cd copilot-metrics-4-every-userAssure that you have Elasticsearch running and accessible. Please refer to the previous steps here.
- Confirm that you are in the correct path
cd /srv/copilot-metrics-4-every-user - Execute the script and create an index
The following content is obtained, indicating ok
bash create_es_indexes.sh
{"acknowledged":true,"shards_acknowledged":true,"index":"copilot_completions"} {"acknowledged":true,"shards_acknowledged":true,"index":"copilot_chat"} {"acknowledged":true,"shards_acknowledged":true,"index":"copilot_extension"} - verify
The following content is obtained, indicating ok
curl -X GET http://localhost:9200/_cat/indices?vhealth status index uuid pri rep docs.count docs.deleted store.size pri.store.size dataset.size yellow open copilot_completions XrOEfAngTS60VsuUz3Lbrw 1 1 0 0 227b 227b 227b yellow open copilot_chat xE6tkg5GQEOP-EP8pwAkYg 1 1 0 0 227b 227b 227b yellow open copilot_extension 6R_1cdlIQQOCv4BoHPqXCw 1 1 0 0 227b 227b 227b
Assure that you have Grafana running and accessible. Please refer to the previous steps here.
- Confirm that you are in the correct path
cd /srv/copilot-metrics-4-every-user - Run the script to add data sources
bash add_grafana_data_sources.sh
- Visit the Grafana UI to confirm that the addition was successful
- Confirm that you are in the correct path
cd /srv/copilot-metrics-4-every-user - Execute the script to generate a Grafana json model. Execute one of the following two commands
Get the output
# Generate Copilot Metrics for Every User Dashboard python3 gen_grafana_model.py --template=grafana/dashboard-template.json
Model saved to grafana/dashboard-model-2024-12-17.json, please import it to Grafana
- Download the generated file to your local computer
scp root@<PUBLIC_IP_OF_YOUR_VM>:/srv/copilot-metrics-4-every-user/grafana/dashboard-model-*.json . dashboard-model-2024-12-17.json 100% 157KB 243.8KB/s 00:00 dashboard-model-data_sources_name_uid_mapping-2024-12-17.json 100% 210 1.1KB/s 00:00
- Copy the generated json file and import it into Grafana
- Congratulations, you now have a complete dashboard, but there should be no data yet. Next, run the core program.
is the abbreviation of the first characters of Metrics For Everyuser To ElasticSearch
Parameter description
LOG_PATH: Log storage location, not recommended to modify. If modified, you need to modify the-vdata volume mapping simultaneously.EXECUTION_INTERVAL: Update interval, the default is to update the program every1minutes.
docker run -itd \
--net=host \
--restart=always \
--name mfe2es \
-e LOG_PATH="logs" \
-e EXECUTION_INTERVAL=1 \
-e ELASTICSEARCH_URL="http://localhost:9200" \
-v /srv/auditlogs:/app/auditlogs \
satomic/copilot-metrics-4-everyuserCongratulations! now you can visit the Grafana UI and see the data in the dashboard. The data will be updated every minute, and you can also set the update interval in the docker run command.
- now you can set the proxy in your IDE (VSCode as example here, if you are using JetBrains, after set proxy, you need to restart the JetBrains IDE), and the IP address is
127.0.0.1as an example, please change it to your actual IP address.-
for normal features, set the proxy like:
http://127.0.0.1:8080, only if the Admin setis_proxy_auth_needed = Falsein Server side.
-
for advanced features, set the proxy like:
http://your_username:your_passoword@127.0.0.1:8080(the username issatomicand pwd is961aa8753bas an sample).
or in
settings.json"http.proxy": "http://satomic:961aa8753b@127.0.0.1:8080"
-
- However, at this time, IDE will prompt certificate errors, so a certificate needs to be installed. The certificate download requires access to mitm.it, and the prerequisite for normal access is that mitmproxy is functioning normally. Therefore, before enabling the proxy, only requests that go through the proxy will return normal web pages.
- If you encounter the TLS error, please visit Configuring network settings for GitHub Copilot for help or raise a issue here.
- Now you can use the Copilot to generate code, and the request and response will be saved in the
auditlogsfolder.- The
metricsfolder stores daily usage metrics statistics. - The
usagefolder is a subdirectory with the user name, which records the detailed data ofchatandcompletionsrespectively.
- The
[10:13:13.823] ====================================================================================================
[10:13:13.824] ✅ http_connect flow.request.url: proxy.enterprise.githubcopilot.com:443
[10:13:13.824] ✅ Obtained Proxy-Authorization, username: xuefeng
[10:13:13.881][127.0.0.1:57302] server connect proxy.enterprise.githubcopilot.com:443 (52.175.140.176:443)
127.0.0.1:57302: POST https://proxy.enterprise.githubcopilot.com/v1/engines/copilot-codex/completions HTTP/2.0
<< HTTP/2.0 200 OK 5.3k
[10:13:14.186] ✅🤖🚗 Processing completions response: https://proxy.enterprise.githubcopilot.com/v1/engines/copilot-codex/completions
[10:13:14.192] 😄 Log saved logs\usage\xuefeng\completions/2024-12-30T02-13-14.189603_4ce93ec3b2_127.0.0.1_JetBrains-PC-243.22562.220.json
[10:13:14.196] 😆 Metrics saved logs\metrics\copilot-usage_2024-12-30.json
[10:13:15.363][127.0.0.1:57302] client disconnect
[10:13:15.364][127.0.0.1:57302] server disconnect proxy.enterprise.githubcopilot.com:443 (52.175.140.176:443)
[10:13:15.371][127.0.0.1:57306] client connect
[10:13:30.482] ====================================================================================================
[10:13:30.482] ✅ http_connect flow.request.url: api.enterprise.githubcopilot.com:443
[10:13:30.483] ✅ Obtained Proxy-Authorization, username: xuefeng
[10:13:30.487][127.0.0.1:57319] server connect api.enterprise.githubcopilot.com:443 (140.82.113.22:443)
[10:13:30.638][127.0.0.1:56773] server disconnect telemetry.enterprise.githubcopilot.com:443 (140.82.113.21:443)
[10:13:31.139][127.0.0.1:57317] Client TLS handshake failed. The client disconnected during the handshake. If this happens consistently for telemetry.enterprise.githubcopilot.com, this may indicate that the client does not trust the proxy's certificate.
[10:13:31.143][127.0.0.1:57317] client disconnect
[10:13:31.146][127.0.0.1:57317] server disconnect telemetry.enterprise.githubcopilot.com:443 (140.82.113.22:443)
[10:13:31.224][127.0.0.1:57319] Client TLS handshake failed. The client disconnected during the handshake. If this happens consistently for api.enterprise.githubcopilot.com, this may indicate that the client does not trust the proxy's certificate.
[10:13:31.228][127.0.0.1:57319] client disconnect
[10:13:31.229][127.0.0.1:57319] server disconnect api.enterprise.githubcopilot.com:443 (140.82.113.22:443)
127.0.0.1:57306: POST https://telemetry.enterprise.githubcopilot.com/telemetry HTTP/2.0
<< HTTP/2.0 200 OK 62b
127.0.0.1:57241: POST https://api.enterprise.githubcopilot.com/chat/completions HTTP/2.0
<< HTTP/2.0 200 OK 7.6k
[10:13:32.198] ✅💬👄 Processing chat response: https://api.enterprise.githubcopilot.com/chat/completions
[10:13:32.205] 😄 Log saved logs\usage\xuefeng\chat/2024-12-30T02-13-32.203524_4ce93ec3b2_127.0.0.1_JetBrains-PC-243.22562.220.json
[10:13:32.208] 😆 Metrics saved logs\metrics\copilot-usage_2024-12-30.json
[10:13:32.223][127.0.0.1:57325] client connect
[10:13:32.225] ====================================================================================================
[10:13:32.225] ✅ http_connect flow.request.url: api.enterprise.githubcopilot.com:443
[10:13:32.225] ✅ Obtained Proxy-Authorization, username: xuefeng
[10:13:32.231][127.0.0.1:57325] server connect api.enterprise.githubcopilot.com:443 (140.82.113.22:443)
[10:13:32.974][127.0.0.1:57325] Client TLS handshake failed. The client disconnected during the handshake. If this happens consistently for api.enterprise.githubcopilot.com, this may indicate that the client does not trust the proxy's certificate.
[10:13:32.977][127.0.0.1:57325] client disconnect
[10:13:32.979][127.0.0.1:57325] server disconnect api.enterprise.githubcopilot.com:443 (140.82.113.22:443)
127.0.0.1:57241: POST https://api.enterprise.githubcopilot.com/chat/completions HTTP/2.0
<< HTTP/2.0 200 OK 6.7k
[10:13:33.671] ✅💬👄 Processing chat response: https://api.enterprise.githubcopilot.com/chat/completions
[10:13:33.679] ⚠️ Skipping invalid chat response, cuz last_role_in_messages is not type of `user`: system
[10:13:34.328][127.0.0.1:57327] client connect
Different event types are now visible in metrics, including nes, agent, edits, chat-inline, chat-panel, etc. Additionally, statistics are now tracked by model type, recording the number of times different AI models are used within each editor version.
Below is a detailed explanation of the metrics JSON file structure:
{
"day": "2025-03-11", // Current date
"total_chat_turns": 162, // Total chat turns from all users for the day
"total_completions_count": 0, // Total code completions from all users for the day
"usage": { // Usage data grouped by users
"satomic": { // Username
"chat_turns": 162, // Total chat turns for this user
"chat": { // Chat-related data, grouped by action type
"chat-panel": { // Chat panel interactions
"chat_turns": 31, // Number of chat turns for this action type
"editor_version": { // Grouped by editor version
"vscode-1.98.0-insider": { // Editor version
"count": 31, // Usage count for this editor version
"models": { // Statistics grouped by model
"claude-3.7-sonnet-thought": 15, // Model name and usage count
"gpt-4o": 16 // Model name and usage count
}
}
}
},
"nes": {
"chat_turns": 101,
"editor_version": {
"simulation-tests-editor-1.85": {
"count": 101,
"models": {
"copilot-nes-v": 101
}
}
}
}
// Other action types...
},
"completions_count": 14,
"completions": {
"vscode-1.98.1": {
"count": 14,
"models": {
"gpt-4o-copilot": {
"count": 14,
"languages": {
"python": 14
}
}
}
}
},
"extension_count": 4,
"extension": {
"roulette-play": {
"count": 1,
"editor_version": {
"vscode-1.99.0-insider": {
"count": 2,
"models": {
"gpt-4o": 2
}
}
}
},
"cute-cat-assistant": {
"count": 2,
"editor_version": {
"vscode-1.98.1": {
"count": 2,
"models": {
"gpt-4o": 1,
"gemini-2.0-flash-001": 1
}
}
}
}
}
}
}
}This structure allows you to analyze data across multiple dimensions:
- Usage analysis by user
- Differentiation between chat functions and code completion features
- Grouping by action type (chat panel, inline chat, edits, etc.)
- Analysis by editor version
- Analysis by AI model type
- For code completion features, analysis by programming language
This multi-dimensional statistical data can help you gain deep insights into the Copilot usage patterns of each team member.
Logging is supported for different types of chat, including nes, agent, edits...
├─auditlogs
│ ├─metrics
│ └─usage
│ ├─anonymous
│ │ ├─chat-panel
│ │ └─completions
│ ├─rin
│ │ ├─chat-panel
│ │ └─completions
│ ├─satomic
│ │ ├─chat-inline
│ │ ├─chat-panel
│ │ ├─completions
│ │ ├─edits
│ │ ├─nes
│ │ └─other
│ └─xuefeng
│ ├─chat-inline
│ ├─chat-panel
│ └─completions
{
"proxy-authorization": "satomic:123",
"timestamp": "2024-12-28T14:50:18.214725",
"proxy-time-consumed": "188.35ms",
"request": {
"url": "https://proxy.enterprise.githubcopilot.com/v1/engines/copilot-codex/completions",
"method": "POST",
"headers": {
"authorization": "Bearer tid=5e1e32dca6b1cccb036ab1bd2d7d444d;ol=ea9395b9a9248c05ee6847cbd24355ed,fa25d2808d3f1461923caba5bbaa7673,679c1c3c27523244c3c3ad04ef88d2f0;exp=1735398336;sku=copilot_enterprise_seat;proxy-ep=proxy.enterprise.githubcopilot.com;st=dotcom;ssc=1;chat=1;cit=1;malfil=1;ccr=1;8kp=1;ip=156.59.13.4;asn=AS21859:f9c792ae49b6494b595fc62854ed0a10a78e624d849112f33114fefde749863b",
"x-request-id": "2e177ccd-029e-46f1-bf59-3d366bdb5e55",
"openai-organization": "github-copilot",
"vscode-sessionid": "d680c0d9-d9ef-43b5-a272-86ad27f0b04e1735381508063",
"vscode-machineid": "4ce93ec3b250003c9580aba5d1a71685fe7df281ac090fa58018e5b6a3017bf9",
"x-github-api-version": "2024-12-15",
"editor-version": "vscode/1.96.2",
"editor-plugin-version": "copilot/1.254.0",
"copilot-language-server-version": "1.254.0",
"annotations-enabled": "true",
"code-quote-enabled": "true",
"openai-intent": "copilot-ghost",
"content-type": "application/json",
"user-agent": "GithubCopilot/1.254.0",
"content-length": "306",
"accept": "*/*",
"accept-encoding": "gzip,deflate,br"
},
"content": {
"prompt": "# Path: tryit.py\n\n\n\ndef add(x, y):\n return x + y",
"suffix": "",
"max_tokens": 500,
"temperature": 0,
"top_p": 1,
"n": 1,
"stop": [
"\n"
],
"nwo": "satomic/copilot-proxy-insight",
"stream": true,
"extra": {
"language": "python",
"next_indent": 0,
"trim_by_indentation": true,
"prompt_tokens": 18,
"suffix_tokens": 0
}
}
},
"response": {
"status_code": 200,
"headers": {
"azureml-model-deployment": "d071-20241226110228",
"content-security-policy": "default-src 'none'; sandbox",
"content-type": "text/event-stream",
"openai-processing-ms": "33.6402",
"strict-transport-security": "max-age=31536000",
"x-request-id": "2e177ccd-029e-46f1-bf59-3d366bdb5e55",
"content-length": "356",
"date": "Sat, 28 Dec 2024 14:50:18 GMT",
"x-github-backend": "Kubernetes",
"x-github-request-id": "8566:18E3C2:19397A5:1A0ECB8:67700FE2"
},
"content": [
{
"id": "cmpl-AjSQstOuqLSedY7J3Vg6Op6Khvcnl",
"created": 1735397418,
"model": "gpt-35-turbo",
"choices": [
{
"index": 0,
"finish_reason": null,
"logprobs": null,
"p": "aaaaaaa"
}
]
},
{
"id": "cmpl-AjSQstOuqLSedY7J3Vg6Op6Khvcnl",
"created": 1735397418,
"model": "gpt-35-turbo",
"choices": [
{
"index": 0,
"finish_reason": "stop",
"logprobs": null,
"p": "aaaaaaa"
}
]
},
""
]
}
}{
"proxy-authorization": "xuefeng",
"timestamp": "2024-12-29T04:48:23.295551",
"proxy-time-consumed": "1164.14ms",
"request": {
"url": "https://api.enterprise.githubcopilot.com/chat/completions",
"method": "POST",
"headers": {
"authorization": "Bearer tid=5e1e32dca6b1cccb036ab1bd2d7d444d;ol=ea9395b9a9248c05ee6847cbd24355ed,fa25d2808d3f1461923caba5bbaa7673,679c1c3c27523244c3c3ad04ef88d2f0;exp=1735448320;sku=copilot_enterprise_seat;proxy-ep=proxy.enterprise.githubcopilot.com;st=dotcom;ssc=1;chat=1;cit=1;malfil=1;ccr=1;8kp=1;ip=156.59.13.4;asn=AS21859:40c14fca83ab35817c1ce79ed932afc124f02ccc760f5f4555cd2e5f29189fbd",
"x-request-id": "36098736-8ce8-4f30-8088-7c6bca56e77c",
"openai-organization": "github-copilot",
"vscode-sessionid": "ecdf0705-5c33-44f9-9c50-3c88d2f3a1e51735394608543",
"vscode-machineid": "4ce93ec3b250003c9580aba5d1a71685fe7df281ac090fa58018e5b6a3017bf9",
"editor-version": "JetBrains-PC/243.22562.220",
"editor-plugin-version": "copilot-intellij/1.5.30.8388-242-nightly",
"copilot-language-server-version": "1.250.0",
"x-github-api-version": "2023-07-07",
"openai-intent": "conversation-panel",
"content-type": "application/json",
"user-agent": "GithubCopilot/1.250.0",
"content-length": "6962",
"accept": "*/*",
"accept-encoding": "gzip,deflate,br"
},
"content": {
"messages": [
{
"role": "system",
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"content": "Consider the following conversation history:\n1) User: what's wrong with you\nGitHub Copilot: I am here to assist you with your coding questions. How can I help you with your project today?\n\n2) User: 你能给我什么帮助\nGitHub Copilot: 我可以帮助你解决与编程相关的问题，例如调试代码、优化代码、解释代码片段、提供示例代码等。你可以告诉我你目前遇到的具体问题或需要的帮助，我会尽力为你提供支持。\n\n3) User: 你在想什么呢？\nGitHub Copilot: 我在这里帮助你解决与编程相关的问题。如果你有任何代码问题或需要帮助，请告诉我。\n\n4) User: 你是什么模型？\nGitHub Copilot: 我是 GitHub Copilot，一个由 OpenAI 的 GPT-4 模型驱动的编程助手。我的目的是帮助你解决编程相关的问题。你有什么需要帮助的吗？\n\n5) User: 你是什么模型？\nGitHub Copilot: I am GitHub Copilot, a programming assistant powered by OpenAI's GPT-4 model. My purpose is to help you with coding-related questions and tasks. How can I assist you today?\n\nConsider the additional context:\nMetadata about the current git repository:\n- Current branch name: main\nCode excerpt from file `patient-management/src/patient.py`:\n```python\nclass Patient:\n \"\"\"\n This class represents a patient with personal information, medical history, and current condition.\n \"\"\"\n\n def __init__(self, name, age, gender, height):\n self.name = name\n self.age = age\n self.gender = gender\n self.height = height\n self.medical_history = []\n self.current_condition = None\n\n # 将记录添加到病史中\n def add_record(self, record):\n self.medical_history.append(record)\n\n def set_current_condition(self, condition):\n self.current_condition = condition\n\n # 用漂亮的格式打印病人的信息\n def print_info(self):\n info = f\"\"\"\n 病人信息:\n 姓名: {self.name}\n 年龄: {self.age}\n 性别: {self.gender}\n 身高: {self.height} cm\n 病史: {', '.join(self.medical_history) if self.medical_history else '无'}\n 当前病情: {self.current_condition if self.current_condition else '无'}\n \"\"\"\n print(info)\n\n\n\n\n```\nThe developer is working on a project with the following characteristics (languages, frameworks):\n- python\n- javascript\nCode excerpt from the currently open file `patient-management/src/main.py`:\n```python\nfrom patient import Patient\n\n# 创建一个名为张三的病人信息实例\npatient = Patient(\"张三\", 30, \"男\", 175)\npatient.set_current_condition(\"头疼脑热\")\npatient.add_record(\"感冒\")\npatient.print_info()\n\n\n\n\ndef sum(a, b):\n return a + b\n\ndef subtract(a, b):\n return a - b\n\n\ndef multiply(a, b):\n return a * b\n\ndef divide(a, b):\n return a / b\n```"
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