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Documentation Index

Fetch the complete documentation index at: https://docs.memvid.com/llms.txt

Use this file to discover all available pages before exploring further.

Memvid uses local models for semantic search (embeddings), reranking, visual search (CLIP), Logic‑Mesh entity extraction (NER), and local enrichment workflows. Models are cached under MEMVID_MODELS_DIR (default ~/.memvid/models). Some models are installed explicitly via memvid models install, while embedding/reranker models are auto-downloaded on first use (unless offline).

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Quick Start

# See what's available / installed (no downloads)
memvid models list

# Install optional CLIP + NER models
memvid models install --clip mobileclip-s2
memvid models install --ner distilbert-ner

# Install optional local LLM for enrichment (GGUF)
memvid models install phi-3.5-mini

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Model Types

TypeHow it’s fetchedUsed by
EmbeddingAuto-download on first useput --embedding, find --mode sem/auto, ask --mode sem/hybrid
RerankerAuto-download on first useHybrid ask/find (disable with --no-rerank)
CLIPmemvid models install --clip …put --clip, find --mode clip
NERmemvid models install --ner …put --logic-mesh, follow …
LLM (Enrich)memvid models install …enrich, put --contextual --contextual-model local
WhisperAuto-download on first useput --transcribe

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Embedding Models (Text Vectors)

Select the default embedding model with the global -m/--embedding-model flag. It can appear before or after the subcommand: 
memvid put knowledge.mv2 --input docs/ --embedding -m bge-small
memvid -m openai-small put knowledge.mv2 --input docs/ --embedding

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Common choices

ModelDimensionsNotes
bge-small384Default local model (fastembed)
bge-base768Higher quality local model
nomic768High accuracy local model
gte-large1024Best local semantic depth
openai-small1536OPENAI_API_KEY required
openai-large3072OPENAI_API_KEY required
openai3072Alias for openai-large
openai-ada1536Legacy OpenAI model

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External embedding APIs

export OPENAI_API_KEY=sk-...
memvid put knowledge.mv2 --input docs/ --embedding -m openai-small
ask/find auto-detect the correct embedding runtime from the .mv2 when vectors are present. Use --query-embedding-model (or global -m) only when you need an explicit override.

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Reranking (Hybrid Precision)

memvid ask may use a cross-encoder reranker (auto-downloaded on first use). Disable it in gated/offline environments: 
memvid ask knowledge.mv2 --question "…" --no-rerank
Install a CLIP model: 
memvid models install --clip mobileclip-s2
memvid models install --clip mobileclip-s2-fp16
memvid models install --clip siglip-base
Use it during ingestion and search: 
memvid put photos.mv2 --input ./images --clip
memvid find photos.mv2 --query "sunset over ocean" --mode clip

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NER Model (Logic‑Mesh)

Install NER: 
memvid models install --ner distilbert-ner
Enable Logic‑Mesh during ingestion: 
memvid put graph.mv2 --input docs/ --logic-mesh
memvid follow graph.mv2 traverse --start "Microsoft" --hops 2

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Enrichment LLM Models

These are local GGUF models used by enrichment workflows (not by memvid ask): 
memvid models install phi-3.5-mini
memvid models install phi-3.5-mini-q8
For memvid ask, choose a synthesis model with --use-model (e.g. --use-model openai, --use-model gemini-2.0-flash, or --use-model "ollama:qwen2.5:1.5b"). See Local Models with Ollama.

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List / Verify / Remove

# Filter model list
memvid models list --model-type embedding
memvid models list --model-type clip --json

# Verify installed enrichment LLM models (phi-3.5-*)
memvid models verify
memvid models verify phi-3.5-mini

# Remove an enrichment LLM model
memvid models remove phi-3.5-mini --yes

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Offline Mode

Set MEMVID_OFFLINE=1 to prevent downloads. In offline mode:
  • memvid models install … fails (it can’t download).
  • Embedding/reranker auto-download is blocked; run a semantic command once while online to populate caches.

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Environment Variables

VariablePurpose
MEMVID_MODELS_DIRModel cache directory (default ~/.memvid/models)
MEMVID_OFFLINESkip downloads/network (1 to enable)
MEMVID_CLIP_MODELDefault local CLIP model (e.g. mobileclip-s2)
OPENAI_API_KEYOpenAI embeddings / CLIP / LLM providers
GEMINI_API_KEYGemini providers
ANTHROPIC_API_KEYClaude providers
COHERE_API_KEYCohere embeddings
VOYAGE_API_KEYVoyage embeddings