Comparison
promptsource vs Awesome-AIGC-Tutorials
Verdict
Pick promptsource if promptSource aids in creating, sharing, and using natural language prompts for large language models; pick Awesome-AIGC-Tutorials if awesome-AIGC-Tutorials supplies specialized guidance on Large Language Models and AI-generated artistry.
Markdown twin · promptsource alternatives · Awesome-AIGC-Tutorials alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | promptsource | Awesome-AIGC-Tutorials |
|---|---|---|
| Maintenance | Dormant (1027d since push) As of 1w · github_public_v1 | Dormant (848d since push) As of 4w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Organization account As of 4w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- promptsource
- Toolkit for creating, sharing and using natural language prompts
- Awesome-AIGC-Tutorials
- Curated tutorials and resources for Large Language Models, AI Painting, and more
Stars
- promptsource
- 3.0k
- Awesome-AIGC-Tutorials
- 4.5k
Forks
- promptsource
- 375
- Awesome-AIGC-Tutorials
- 303
Open issues
- promptsource
- 43
- Awesome-AIGC-Tutorials
- 10
Language
- promptsource
- Python
- Awesome-AIGC-Tutorials
- -
Adopt for
- promptsource
- PromptSource aids in creating, sharing, and using natural language prompts for large language models.
- Awesome-AIGC-Tutorials
- Awesome-AIGC-Tutorials supplies specialized guidance on Large Language Models and AI-generated artistry.
Persona
- promptsource
- -
- Awesome-AIGC-Tutorials
- -
Runtime
- promptsource
- -
- Awesome-AIGC-Tutorials
- -
License
- promptsource
- Apache-2.0
- Awesome-AIGC-Tutorials
- MIT license allows for free use in both open-source and proprietary products, with attribution required to the authors.
Last pushed
- promptsource
- Oct 23, 2023
- Awesome-AIGC-Tutorials
- Mar 31, 2024
Categories
- promptsource
- Developer Tools, Model Training
- Awesome-AIGC-Tutorials
- Developer Tools, LLM Frameworks, Model Training
Trust and health
Days since push
- promptsource
- 1027d
- Awesome-AIGC-Tutorials
- 848d
Open issues (now)
- promptsource
- 43
- Awesome-AIGC-Tutorials
- 10
Stars delta
- promptsource
- +2 (30d)
- Awesome-AIGC-Tutorials
- Unknown
Open issues delta
- promptsource
- -1 (30d)
- Awesome-AIGC-Tutorials
- Unknown
Full report
- promptsource
- Trust report
- Awesome-AIGC-Tutorials
- Trust report
Shared compatibility
- Python · promptsource: Python runtime · Awesome-AIGC-Tutorials: Python runtime
Choose promptsource if…
- License: promptsource is Apache-2.0, Awesome-AIGC-Tutorials is MIT.
- Tags unique to promptsource: few-shot, fine-tuning, language-models, machine-learning.
- When you need to create reusable prompts for multiple datasets with a focus on simplicity through a templating language called Jinja.
When NOT to use promptsource
- Avoid if you require complex prompt customization beyond what simple templating can offer, as PromptSource is not designed for intricate configurations.
- Not suitable for users focused on real-time interaction with prompts, since it lacks dynamic features for immediate adjustments.
Choose Awesome-AIGC-Tutorials if…
- License: Awesome-AIGC-Tutorials is MIT, promptsource is Apache-2.0.
- Requirements: No specific technical prerequisites are listed. Basic understanding of AI concepts like LLMs and NLP is beneficial..
- Tags unique to Awesome-AIGC-Tutorials: ai, aigc, chatgpt, deep-learning.
- Also covers LLM Frameworks.
- If you aim to deepen your understanding of prompt engineering for models like MidJourney or Stable Diffusion, this repository offers focused tutorials and resources.
When NOT to use Awesome-AIGC-Tutorials
- Avoid if you are looking for a one-stop-shop coding platform, as Awesome-AIGC-Tutorials provides theoretical knowledge and tutorials rather than practical code samples.
- Not suitable if your focus is solely on the commercial deployment of large language models; this repository does not cover market-specific insights or competitive analysis.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (bigscience-workshop/promptsource) · observed Aug 15, 2026
- GitHub forks (bigscience-workshop/promptsource) · observed Aug 15, 2026
- Last push (bigscience-workshop/promptsource) · observed Oct 23, 2023
- License file (Apache-2.0) · observed Aug 15, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (luban-agi/Awesome-AIGC-Tutorials) · observed Jul 28, 2026
- GitHub forks (luban-agi/Awesome-AIGC-Tutorials) · observed Jul 28, 2026
- Last push (luban-agi/Awesome-AIGC-Tutorials) · observed Mar 31, 2024
- License file (MIT) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: promptsource 3.0k · Awesome-AIGC-Tutorials 4.5k (synced Aug 15, 2026).
Common questions
- What is the difference between promptsource and Awesome-AIGC-Tutorials?
- promptsource: Toolkit for creating, sharing and using natural language prompts. Awesome-AIGC-Tutorials: Curated tutorials and resources for Large Language Models, AI Painting, and more. See the comparison table for live GitHub stats and shared categories.
- When should I choose promptsource over Awesome-AIGC-Tutorials?
- Choose promptsource over Awesome-AIGC-Tutorials when License: promptsource is Apache-2.0, Awesome-AIGC-Tutorials is MIT; Tags unique to promptsource: few-shot, fine-tuning, language-models, machine-learning; When you need to create reusable prompts for multiple datasets with a focus on simplicity through a templating language called Jinja.
- When should I choose Awesome-AIGC-Tutorials over promptsource?
- Choose Awesome-AIGC-Tutorials over promptsource when License: Awesome-AIGC-Tutorials is MIT, promptsource is Apache-2.0; Requirements: No specific technical prerequisites are listed. Basic understanding of AI concepts like LLMs and NLP is beneficial.; Tags unique to Awesome-AIGC-Tutorials: ai, aigc, chatgpt, deep-learning; Also covers LLM Frameworks; If you aim to deepen your understanding of prompt engineering for models like MidJourney or Stable Diffusion, this repository offers focused tutorials and resources.
- When should I avoid promptsource?
- Avoid if you require complex prompt customization beyond what simple templating can offer, as PromptSource is not designed for intricate configurations. Not suitable for users focused on real-time interaction with prompts, since it lacks dynamic features for immediate adjustments.
- When should I avoid Awesome-AIGC-Tutorials?
- Avoid if you are looking for a one-stop-shop coding platform, as Awesome-AIGC-Tutorials provides theoretical knowledge and tutorials rather than practical code samples. Not suitable if your focus is solely on the commercial deployment of large language models; this repository does not cover market-specific insights or competitive analysis.
- Is promptsource or Awesome-AIGC-Tutorials more popular on GitHub?
- Awesome-AIGC-Tutorials has more GitHub stars (4,522 vs 3,029). Stars measure visibility, not whether either tool fits your constraints.
- Are promptsource and Awesome-AIGC-Tutorials open source?
- Yes - both are open-source projects on GitHub (promptsource: Apache-2.0, Awesome-AIGC-Tutorials: MIT).
- Where can I find alternatives to promptsource or Awesome-AIGC-Tutorials?
- GraphCanon lists graph-backed alternatives at promptsource alternatives and Awesome-AIGC-Tutorials alternatives (promptsource markdown twin, Awesome-AIGC-Tutorials markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, promptsource or Awesome-AIGC-Tutorials?
- promptsource: Dormant. Awesome-AIGC-Tutorials: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for promptsource and Awesome-AIGC-Tutorials?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: promptsource trust report; Awesome-AIGC-Tutorials trust report.