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docs: remove deprecated Graph Memory references (#5277)

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rudrajmehta-mem0
2026-05-28 12:58:15 +05:30
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commit eaca45dcdb
21 changed files with 21 additions and 46 deletions
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docs/core-concepts/memory-evaluation.mdx
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@@ -47,7 +47,7 @@ When a query arrives, the retrieval pipeline scores candidates across three sign
1. **Semantic Search** — Vector similarity scoring against memory embeddings
2. **Keyword Search** — Normalized term matching via BM25 with verb-form lemmatization
3. **Entity Search** — Entity graph matching boosts memories linked to query entities
3. **Entity Search** — Entity matching boosts memories linked to query entities
Results are fused via rank scoring into a final top-K set. Different query types lean on different signals:
docs/core-concepts/memory-operations/add.mdx
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@@ -27,15 +27,11 @@ Adding memory is how Mem0 captures useful details from a conversation so your ag
Mem0 offers two flows:
- **Mem0 Platform** – Fully managed API with dashboard, scaling, and graph features.
- **Mem0 Platform** – Fully managed API with dashboard and scaling.
- **Mem0 Open Source** – Local SDK that you run in your own environment.
Both flows take the same payload and pass it through the same pipeline.
<Frame caption="Architecture diagram illustrating the process of adding memories.">
<img src="../../images/add_architecture.png" />
</Frame>
<Steps>
<Step title="Information extraction">
Mem0 sends the messages through an LLM that pulls out key facts, decisions, or preferences to remember.
@@ -44,7 +40,7 @@ Mem0 sends the messages through an LLM that pulls out key facts, decisions, or p
Existing memories are checked for duplicates or contradictions so the latest truth wins.
</Step>
<Step title="Storage">
The resulting memories land in managed vector storage (and optional graph storage) so future searches return them quickly.
The resulting memories land in managed vector storage so future searches return them quickly.
</Step>
</Steps>
@@ -177,7 +173,7 @@ For full list of supported fields, required formats, and advanced options, see t
## Put it into practice
- Review the <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> guide to layer metadata, rerankers, and graph toggles.
- Review the <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> guide to layer metadata and rerankers.
- Explore the <Link href="/api-reference/memory/add-memories">Add Memories API reference</Link> for every request/response field.
## See it live
docs/core-concepts/memory-operations/search.mdx
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@@ -25,10 +25,6 @@ Mem0's search operation lets agents ask natural-language questions and get back
## Architecture
<Frame caption="Architecture diagram illustrating the memory search process.">
<img src="../../images/search_architecture.png" />
</Frame>
<Steps>
<Step title="Query processing">
Mem0 cleans and enriches your natural-language query so the downstream embedding search is accurate.
docs/core-concepts/memory-types.mdx
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@@ -104,7 +104,7 @@ results = memory.search(
## Put it into practice
- Use the <Link href="/core-concepts/memory-operations/add">Add Memory</Link> guide to persist user preferences.
- Follow <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> to tune metadata and graph writes.
- Follow <Link href="/platform/advanced-memory-operations">Advanced Memory Operations</Link> to tune metadata and retrieval.
## See it live