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| # 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. | |