Metadata-Version: 2.3
Name: jipso
Version: 0.1.25
Summary: JIPSO framework for prompt orchestration and comparison
License: Apache-2.0
Keywords: jipso,ai
Author: JIPSO Foundation
Author-email: contact@jipso.org
Requires-Python: >=3.10
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Provides-Extra: all
Provides-Extra: byteplus
Provides-Extra: cloud
Provides-Extra: google
Provides-Extra: huggingface
Provides-Extra: local
Provides-Extra: ollama
Provides-Extra: tencent
Provides-Extra: xai
Requires-Dist: anthropic (>=0.18.0)
Requires-Dist: byteplus-python-sdk-v2 (>=0.1.0) ; extra == "byteplus" or extra == "cloud" or extra == "all"
Requires-Dist: google-generativeai (>=0.1.0) ; extra == "google" or extra == "cloud" or extra == "all"
Requires-Dist: httpx (>=0.24.0)
Requires-Dist: ollama (>=0.1.0) ; extra == "ollama" or extra == "local" or extra == "all"
Requires-Dist: openai (>=1.0.0)
Requires-Dist: pydantic (>=2.0.0)
Requires-Dist: python-dotenv (>=1.0.0)
Requires-Dist: tencentcloud-sdk-python (>=0.1.0) ; extra == "tencent" or extra == "all"
Requires-Dist: torch (>=0.1.0) ; extra == "huggingface" or extra == "local" or extra == "all"
Requires-Dist: transformers (>=0.1.0) ; extra == "huggingface" or extra == "local" or extra == "all"
Requires-Dist: typer (>=0.12.0)
Requires-Dist: ujson (>=5.0.0)
Requires-Dist: uvloop (>=0.17.0)
Requires-Dist: xai-sdk (>=0.1.0) ; extra == "xai" or extra == "cloud" or extra == "all"
Project-URL: Homepage, https://github.com/jipso-foundation/jipso-py
Project-URL: Repository, https://github.com/jipso-foundation/jipso-py
Description-Content-Type: text/markdown

<p align="center">
  <img width="300" src="https://cdn.jipso.org/logo/jipso_framework.svg" alt="JIPSO Framework Logo"/>
</p>

<p align="center">
  <a href="https://cdn.jipso.org/paper/en/main.pdf" title="JIPSO Framework Paper" target="_blank" rel="noopener"><span>📰 Paper</span></a>
  <a href="https://codecov.io/gh/jipso-foundation/jipso-py"><img src="https://codecov.io/gh/jipso-foundation/jipso-py/branch/main/graph/badge.svg" alt="Codecov"/></a>
  <a href="https://pypi.org/project/jipso"><img src="https://badge.fury.io/py/jipso.svg" alt="PyPI version"/></a>
  <a href="https://hub.docker.com/r/jipsofoundation/jipso"><img src="https://img.shields.io/docker/pulls/jipsofoundation/jipso" alt="Docker Pulls"/></a>
  <a href="https://jipso-py.readthedocs.io/en/latest"><img src="https://readthedocs.org/projects/jipso-py/badge/?version=latest" alt="Documentation Status"/></a>
  <!-- <a href="https://doi.org/10.5281/zenodo.1234567"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.1234567.svg" alt="DOI"/></a> -->
  <a href="https://app.fossa.com/projects/git%2Bgithub.com%2Fjipso-foundation%2Fjipso-py?ref=badge_shield"><img src="https://app.fossa.com/api/projects/git%2Bgithub.com%2Fjipso-foundation%2Fjipso-py.svg?type=shield" alt="FOSSA Status"/></a>
</p>


## 🛠️ INSTALL `jipso-py`

```bash
pip install jipso
```

## 🚀 QUICK START `jipso-py`

### Example 1

```python
import jipso
import os

os.environ['OPENAI_API_KEY'] = 'sk-proj-...'

prompt1 = 'Write leave request email'
prompt2 = 'Write formal leave request email with clear reason and timeline'
o_eval = jipso.pvp(prompt1, prompt2)
print(o_eval)

# ✅ **Function executed:** pvp("Write leave request email", "Write formal leave request email with clear reason and timeline"

# **Test Input Generated:** Employee needs 3 days off next week for medical appointment

# **Results:**
# - **P1 Output:** Generic leave request mentioning time off needed
# - **P2 Output:** Structured email with specific dates, medical reason, coverage arrangements, and professional formatting

# 📊 **Score:** P1 = 3.2/10 (P2 baseline = 5.0)
# 📝 **Reasoning:** P1 produces vague, incomplete emails missing key details like specific dates, reasons, and professional structure. P2's explicit requirements for "clear reason and timeline" generate comprehensive, actionable requests that managers can easily approve. P2 consistently outperforms P1 in completeness, professionalism, and practical utility.
```

### Example 2 (2235)

```python
import jipso

os.environ['ANTHROPIC_API_KEY'] = 'sk-ant-...'

p1 = jipso.Prompt('Collect sales figures this week')
print(p1.add('Customer trend analysis'))
# Collect sales figures this week and perform customer trend analysis

p2 = jipso.Prompt('Customer trend analysis')
p = p1 | p2
print(p)
# Collect sales figures this week and perform customer trend analysis

print(p > p2)
# True

p3 = p.enhance()
print(p3)
# Collect detailed sales figures for this week including revenue, units sold, and transaction counts by product category and customer segment, then perform comprehensive customer trend analysis identifying purchasing patterns, seasonal variations, and emerging opportunities with actionable insights and recommendations

print(set(p3))
# {
#   'Collect detailed sales figures for this week',
#   'Include revenue data', 
#   'Include units sold data',
#   'Include transaction counts',
#   'Categorize by product category',
#   'Categorize by customer segment', 
#   'Perform comprehensive customer trend analysis',
#   'Identify purchasing patterns',
#   'Identify seasonal variations', 
#   'Identify emerging opportunities',
#   'Provide actionable insights',
#   'Provide recommendations'
# }

print(dict(p3))
# {
#   "name": "comprehensive_sales_analysis",
#   "description": "Collect detailed sales data and perform customer trend analysis",
#   "data_collection": {
#     "timeframe": "this week",
#     "metrics": ["revenue", "units_sold", "transaction_counts"],
#     "segmentation": ["product_category", "customer_segment"]
#   },
#   "analysis": {
#     "type": "comprehensive_customer_trend_analysis",
#     "focus_areas": ["purchasing_patterns", "seasonal_variations", "emerging_opportunities"]
#   },
#   "output": {
#     "format": ["actionable_insights", "recommendations"],
#     "detail_level": "comprehensive"
#   }
# }
```

### Example 3

```python
import jipso

os.environ['GEMINI_API_KEY'] = 'sk-ant-...'

j = jipso.Judgement('models/gemini-1.5-flash')
i = 'Hi, I would like to ask about the Dell XPS 13 laptop. What is the current price and are there any promotions? Thank you!'
p = 'Please categorize this email into one of the following categories: Product Advice, Complaints, Technical Support, Orders, Other'
s = 'Based on the main content and purpose of the email. Choose only 1 category that best fits.'
o = j(i=i, p=p, s=s)
print(o)

# **Category: Product Advice**
# Reason: The email asks about current pricing and promotions for the Dell XPS 13 laptop, indicating the sender is researching to make a purchase decision — in the product consulting group.
```

### Example 4

```python
import jipso

os.environ['ALIBABACLOUD_API_KEY'] = 'sk-...'

compute = jipso.Compute(
  j = 'qwen-turbo',
  i = 'Hi, I would like to ask about the Dell XPS 13 laptop. What is the current price and are there any promotions? Thank you!',
  p = 'Please categorize this email into one of the following categories: Product Advice, Complaints, Technical Support, Orders, Other',
)
compute.s = 'Based on the main content and purpose of the email. Choose only 1 category that best fits.'
compute.exe()
print(compute.o)
```

## 🕌 ARCHITECT `jipso-stack`

|Pod|Docker Image|Engine|Role|
|--|--|--|--|
|Client Pod|-|jipso-py|Request jipso.Compute.exe()|
|Worker Pod|jipsofoundation/jipso|celery|Run jipso.Compute, wrap all AI model|
|Cache Pod|-| Redis GPU? (please build it or we will jipso-cache) | Cache VRAM |
|Proxy Pod| nginx| Nginx |Rate limiting |
|Broker Pod| bitnami/kafka | Kafka|Message Queue Broker|
|Database Pod|postgres|PostgreSQL|Database for jipso.Compute|
|Storage Pod|minio/minio|Minio, S3, CDN|Media content|
|Metric Pod| influxdb | InfluxDB| Metric: cost, SLA. Metric database and monitoring. Worker Pod proactive push|
|Auth Pod|keycloak/keycloak|Keycloak|Authentication, API key management|

- Self-Build: Deploy on top Kubernetes
- Multi-Vendor
  + AI Providers (OpenAI, Anthropic) and Individual: Worker Pod, Cache Pod, Proxy Pod
  + Cloud Providers (AWS, Alibaba Cloud): Broker Pod, Database Pod, Storage Pod, Metric Pod, Auth Pod
  + SME Partners: Client Pod with UI/UX

## 💰 SPONSORSHIP
This project has received no external funding, sponsorship, or investment. All development is fully volunteer-based at this stage.



<!-- ## 🧭 ROADMAP

The library currently only introduces concepts and abstract classes. JIPSO Foundation needs to work with **AI platforms** to innovate APIs in the JIPSO style, and requires funding to maintain the library.

Library Development Roadmap:
- ✅ v0.1: Establish CI/CD pipeline
- 👉 v0.2: JIPSO Foundation drafts abstract classes
- [ ] v0.3: JIPSO Foundation aligns with AI developers on abstract classes
- [ ] v0.4: Open for community contributions to build abstract classes
- [ ] v1.0: Alpha release with new APIs
- [ ] v1.1: Beta release with new APIs
- [ ] v1.2: Open for community contributions to development

**⚠️ Local AI Limitation**: The current Docker release does not support local AI providers (Ollama, HuggingFace) due to dependency overhead - local AI packages increase image size from ~300MB to ~4.5GB and require 16-32GB RAM. **JIPSO Foundation is actively collaborating with AI platform vendors** to develop lightweight client SDKs and hybrid deployment architectures. For immediate local AI needs, use development installation (`pip install jipso[local]`) or Docker Compose with separate inference containers.

## 👥 COMMUNITY DISCUSSION AND CONTRIBUTION (PLANNING)

### JIPSO Community Proposal
**JCP (JIPSO Community Proposal)** is a design document that provides information to the JIPSO community or describes a new feature, process, or enhancement for the JIPSO Framework. Similar to Python's PEP or LangChain's RFC, JCPs serve as the primary mechanism for proposing major changes, collecting community input, and documenting design decisions.

JCPs differ from traditional RFCs through their domain-expertise consensus model - admins from channels with the same technical specialty across different language regions must reach consensus (e.g., Privacy experts from English, Chinese, Russian, Indian, and Vietnamese channels collaborate; Enterprise specialists across all regions coordinate; Technical architecture experts form cross-language working groups). This ensures domain expertise alignment while maintaining global technical consistency, eliminating the need for full cross-domain consensus between unrelated specializations.

### Education Community (Microsoft Teams)
| Community | Admin |
|--|--|
[🇬🇧 JIPSO Education Global](https://teams.live.com/l/community/FEA2r9tFxkode6yegE) | vacancy |
[🇨🇳 JIPSO Education 中国](https://teams.live.com/l/community/FEA3iZADI16JNJ01gI) | vacancy |
[🇷🇺 JIPSO Education Россия](https://teams.live.com/l/community/FEA8Kbpi0O42WF1WgI) | vacancy |
[🇮🇳 JIPSO Education भारत](https://teams.live.com/l/community/FEAqZ2DW6oEYBMnYgI) | vacancy |
[🇻🇳 JIPSO Education Việt Nam](https://teams.live.com/l/community/FEANIvvgtmficCm6wE) | vacancy |
[Youtube]() | vacancy |
[Tiktok: @jipso.foundation](https://www.tiktok.com/@jipso.foundation) | vacancy |

### AI Developer Community (Discord)
| Community | Admin |
|--|--|
[🇬🇧 #ai-developer-community](https://discord.gg/vbBe8W5jqW) | vacancy |
[🇨🇳 #ai框架开发者社区](https://discord.gg/evCQQMF7Xd) | vacancy |
[🇷🇺 #разработчики-ai-фреймворков](https://discord.gg/eUBPHQsEAZN) | vacancy |
[🇮🇳 #ai-framework-विकासकर्ता](https://discord.gg/hDhnqw5TVn) | vacancy |
[🇩🇪 #ai-framework-entwickler](https://discord.gg/HcQvxqYpuZ) | vacancy |
[🇫🇷 #développeurs-framework-ia](https://discord.gg/BnhNNHNJC2) | vacancy |
[🇯🇵 #aiフレームワーク開発者](https://discord.gg/gYuAJBzBZf) | vacancy |
[🇰🇷 #ai프레임워크-개발자](https://discord.gg/yCkVfzKxg8) | vacancy |
[🇻🇳 #nhà-sáng-phát-triển-ai](https://discord.gg/jXXwFmgXrF) | vacancy |


### Content Creator Community (Discord)
| Community | Admin |
|--|--|
[🇬🇧 #content-creator-community](https://discord.gg/PUVcnMQnFx) | vacancy |
[🇨🇳 #内容创作者社区](https://discord.gg/kjpfv5SVp6) | vacancy |
[🇷🇺 #сообщество-контент-криэйторов](https://discord.gg/yuWuMVemVC) | vacancy |
[🇮🇳 #सामग्री-निर्माता-समुदाय](https://discord.gg/u8QmExRdCA) | vacancy |
[🇩🇪 #content-creator-gemeinschaft](https://discord.gg/PG8N8NpECY) | vacancy |
[🇫🇷 #communauté-créateurs-de-contenu](https://discord.gg/NR9DrDeU22) | vacancy |
[🇯🇵 #コンテンツ制作者コミュニティ](https://discord.gg/FdaWFtbzX5) | vacancy |
[🇰🇷 #콘텐츠-창작자-커뮤니티](https://discord.gg/8jtwVykkMC) | vacancy |
[🇻🇳 #nhà-sáng-tạo-nội-dung-số](https://discord.gg/yH7kZwPX4M) | vacancy |

### Game Text Based Community (Discord)
| Community | Admin |
|--|--|
[🇬🇧 #game-text-based-community](https://discord.gg/35gsJgjHNc) | vacancy |
[🇨🇳 #文字冒险游戏开发者](https://discord.gg/AZssCCP3mD) | vacancy |
[🇷🇺 #разработчики-текстовых-игр](https://discord.gg/9YXQFUjcB2) | vacancy |
[🇮🇳 #पाठ-आधारित-गेम-डेवलपर](https://discord.gg/e2TkzKRWu8) | vacancy |
[🇩🇪 #textbasierte-spieleentwickler](https://discord.gg/H42wAERmpv) | vacancy |
[🇫🇷 #développeurs-jeux-textuels](https://discord.gg/MB44uty7v2) | vacancy |
[🇯🇵 #テキストゲーム開発者](https://discord.gg/aYP2u2nYXU) | vacancy |
[🇰🇷 #텍스트-게임-개발자](https://discord.gg/84jYADk2HR) | vacancy |
[🇻🇳 #nhà-phát-triển-game-dạng-văn-bản](https://discord.gg/s3JzwFQcZZ) | vacancy |

### Social Community
| Community | Admin |
|--|--|
[Facebook]() | vacancy |
[X: jipsofoundation](https://x.com/jipsofoundation) | vacancy |
[Instagram: jipso_foundation](http://instagram.com/jipso_foundation) | vacancy |
[Threads: @jipso_foundation](https://www.threads.com/@jipso_foundation) | vacancy |

### Announcements Channel
- [🇬🇧 Slack]()
- [🇨🇳 DingTalk]()
- [🇷🇺 Telegram]()
- [🇮🇳 WhatsApp]()
- [🇻🇳 Zalo]()

### Official Contact
- [🌐 Website: jipso.org](https://jipso.org)
- [📬 Email: contact@jipso.org](mailto:contact@jipso.org)
- [🐛 #bug-reports](https://discord.gg/pb8aAMJG6t) -->


