# AgentArchive Documentation

## swarms Multi-Agent Framework

**AgentArchive is an advanced feature crafted to archive, bookmark, and harness the transcripts of agent runs. It promotes the storing and leveraging of successful agent interactions, offering a powerful means for users to derive "recipes" for future agents. Furthermore, with its public archive feature, users can contribute to and benefit from the collective wisdom of the community.**

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## Overview:

AgentArchive empowers users to:

1. Preserve complete transcripts of agent instances.
2. Bookmark and annotate significant runs.
3. Categorize runs using various tags.
4. Transform successful runs into actionable "recipes".
5. Publish and access a shared knowledge base via a public archive.

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## Features:

### 1. Archiving:

- **Save Transcripts**: Retain the full narrative of an agent's interaction and choices.
- **Searchable Database**: Dive into archives using specific keywords, timestamps, or tags.

### 2. Bookmarking:

- **Highlight Essential Runs**: Designate specific agent runs for future reference.
- **Annotations**: Embed notes or remarks to bookmarked runs for clearer understanding.

### 3. Tagging:

Organize and classify agent runs via:

- **Prompt**: The originating instruction that triggered the agent run.
- **Tasks**: Distinct tasks or operations executed by the agent.
- **Model**: The specific AI model or iteration used during the interaction.
- **Temperature (Temp)**: The set randomness or innovation level for the agent.

### 4. Recipe Generation:

- **Standardization**: Convert successful run transcripts into replicable "recipes".
- **Guidance**: Offer subsequent agents a structured approach, rooted in prior successes.
- **Evolution**: Periodically refine recipes based on newer, enhanced runs.

### 5. Public Archive & Sharing:

- **Publish Successful Runs**: Users can choose to share their successful agent runs.
- **Collaborative Knowledge Base**: Access a shared repository of successful agent interactions from the community.
- **Ratings & Reviews**: Users can rate and review shared runs, highlighting particularly effective "recipes."
- **Privacy & Redaction**: Ensure that any sensitive information is automatically redacted before publishing.

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## Benefits:

1. **Efficiency**: Revisit past agent activities to inform and guide future decisions.
2. **Consistency**: Guarantee a uniform approach to recurring challenges, leading to predictable and trustworthy outcomes.
3. **Collaborative Learning**: Tap into a reservoir of shared experiences, fostering community-driven learning and growth.
4. **Transparency**: By sharing successful runs, users can build trust and contribute to the broader community's success.

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## Usage:

1. **Access AgentArchive**: Navigate to the dedicated section within the swarms Multi-Agent Framework dashboard.
2. **Search, Filter & Organize**: Utilize the search bar and tagging system for precise retrieval.
3. **Bookmark, Annotate & Share**: Pin important runs, add notes, and consider sharing with the broader community.
4. **Engage with Public Archive**: Explore, rate, and apply shared knowledge to enhance agent performance.

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With AgentArchive, users not only benefit from their past interactions but can also leverage the collective expertise of the swarms community, ensuring continuous improvement and shared success.
