Comparison
promptsource vs agents-from-scratch
Verdict
Pick promptsource if promptSource aids in creating, sharing, and using natural language prompts for large language models; pick agents-from-scratch if agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies.
Markdown twin · promptsource alternatives · agents-from-scratch alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | promptsource | agents-from-scratch |
|---|---|---|
| Maintenance | Dormant (1027d since push) As of 1w · github_public_v1 | Active (18d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Personal account As of 1w · 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
- agents-from-scratch
- Build AI agents locally without relying on frameworks or cloud APIs.
Stars
- promptsource
- 3.0k
- agents-from-scratch
- 954
Forks
- promptsource
- 375
- agents-from-scratch
- 240
Open issues
- promptsource
- 43
- agents-from-scratch
- 3
Language
- promptsource
- Python
- agents-from-scratch
- Python
Adopt for
- promptsource
- PromptSource aids in creating, sharing, and using natural language prompts for large language models.
- agents-from-scratch
- agents-from-scratch is for those who want absolute control over their AI agent development using only local resources and Python, focusing on deep learning without relying on external frameworks or cloud dependencies.
Persona
- promptsource
- -
- agents-from-scratch
- -
Runtime
- promptsource
- -
- agents-from-scratch
- -
License
- promptsource
- Apache-2.0
- agents-from-scratch
- MIT License: Permissive licensing allowing free use and distribution for both commercial and non-commercial purposes.
Last pushed
- promptsource
- Oct 23, 2023
- agents-from-scratch
- Jul 25, 2026
Categories
- promptsource
- Developer Tools, Model Training
- agents-from-scratch
- AI Agents, Developer Tools
Trust and health
Maintenance
- promptsource
- Dormant (18%)
- agents-from-scratch
- Active (82%)
Days since push
- promptsource
- 1027d
- agents-from-scratch
- 18d
Open issues (now)
- promptsource
- 43
- agents-from-scratch
- 3
Stars delta
- promptsource
- +2 (30d)
- agents-from-scratch
- Unknown
Open issues delta
- promptsource
- -1 (30d)
- agents-from-scratch
- Unknown
Owner type
- promptsource
- Organization
- agents-from-scratch
- User
Full report
- promptsource
- Trust report
- agents-from-scratch
- Trust report
Shared compatibility
- Python · promptsource: Python runtime · agents-from-scratch: Python runtime
Choose promptsource if…
- License: promptsource is Apache-2.0, agents-from-scratch is MIT.
- Tags unique to promptsource: few-shot, fine-tuning, language-models, machine-learning.
- Also covers Model Training.
- 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 agents-from-scratch if…
- License: agents-from-scratch is MIT, promptsource is Apache-2.0.
- Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs..
- Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm.
- Also covers AI Agents.
- You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture.
When NOT to use agents-from-scratch
- You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks.
- If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure.
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 (pguso/agents-from-scratch) · observed Aug 12, 2026
- GitHub forks (pguso/agents-from-scratch) · observed Aug 12, 2026
- Last push (pguso/agents-from-scratch) · observed Jul 25, 2026
- License file (MIT) · observed Aug 12, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: promptsource 3.0k · agents-from-scratch 954 (synced Aug 15, 2026).
Common questions
- What is the difference between promptsource and agents-from-scratch?
- promptsource: Toolkit for creating, sharing and using natural language prompts. agents-from-scratch: Build AI agents locally without relying on frameworks or cloud APIs.. See the comparison table for live GitHub stats and shared categories.
- When should I choose promptsource over agents-from-scratch?
- Choose promptsource over agents-from-scratch when License: promptsource is Apache-2.0, agents-from-scratch is MIT; Tags unique to promptsource: few-shot, fine-tuning, language-models, machine-learning; Also covers Model Training; 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 agents-from-scratch over promptsource?
- Choose agents-from-scratch over promptsource when License: agents-from-scratch is MIT, promptsource is Apache-2.0; Requirements: Min 8 GB RAM; Local large language model availability is critical as the tool does not utilize any cloud APIs.; Tags unique to agents-from-scratch: agent-architecture, ai-agents, llm, local-llm; Also covers AI Agents; You plan to teach yourself or others about the fundamentals of creating AI agents from ground zero with complete transparency into each layer of architecture.
- 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 agents-from-scratch?
- You are working on an application that needs to be deployed quickly. The tool's approach from first principles can be time-consuming compared to using established frameworks. If you need scalability or cloud capabilities such as easy scaling with demand, this tool will not provide these features since it strictly operates on local infrastructure.
- Is promptsource or agents-from-scratch more popular on GitHub?
- promptsource has more GitHub stars (3,029 vs 954). Stars measure visibility, not whether either tool fits your constraints.
- Are promptsource and agents-from-scratch open source?
- Yes - both are open-source projects on GitHub (promptsource: Apache-2.0, agents-from-scratch: MIT).
- Where can I find alternatives to promptsource or agents-from-scratch?
- GraphCanon lists graph-backed alternatives at promptsource alternatives and agents-from-scratch alternatives (promptsource markdown twin, agents-from-scratch 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 agents-from-scratch?
- promptsource: Dormant. agents-from-scratch: Active. 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 agents-from-scratch?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: promptsource trust report; agents-from-scratch trust report.