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fix(reranker): align llm_reranker default model with SDK default (#6703)

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Kartik
2026-08-01 01:04:08 +05:30
committed by GitHub
parent 54328ffd97
commit cf3355e2ca
11 changed files with 26 additions and 26 deletions
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docs/components/rerankers/config.mdx
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@@ -52,7 +52,7 @@ All rerankers share these common configuration parameters:
| Parameter | Description | Type | Default |
| ---------------- | ------------------------------------------ | ------- | ---------------------- |
| `model` | LLM model to use for scoring | `str` | `"gpt-4o-mini"` |
| `model` | LLM model to use for scoring | `str` | `"gpt-5-mini"` |
| `provider` | LLM provider (`openai`, `anthropic`, etc.) | `str` | `"openai"` |
| `api_key` | API key for LLM provider | `str` | `None` |
| `temperature` | Temperature for LLM generation | `float` | `0.0` |
@@ -114,7 +114,7 @@ The self-hosted [TypeScript SDK](/open-source/features/reranker-search#typescrip
| `zero_entropy` | `pnpm add zeroentropy` | `zerank-1` | `apiKey`, `model`, `topK` |
| `sentence_transformer` | `pnpm add @huggingface/transformers` | `Xenova/ms-marco-MiniLM-L-6-v2` | `model`, `device`, `maxLength`, `normalize`, `topK` |
| `huggingface` | `pnpm add @huggingface/transformers` | `Xenova/bge-reranker-base` | `model`, `device`, `maxLength`, `normalize`, `topK` |
| `llm_reranker` | None (uses your LLM provider's own SDK) | `openai` / `gpt-4o-mini` | `provider`, `model`, `apiKey`, `llm` (nested override), `topK` |
| `llm_reranker` | None (uses your LLM provider's own SDK) | `openai` / `gpt-5-mini` | `provider`, `model`, `apiKey`, `llm` (nested override), `topK` |
```typescript
import { Memory } from "mem0ai/oss";
docs/components/rerankers/custom-prompts.mdx
+1 -1
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@@ -48,7 +48,7 @@ config = {
"provider": "llm_reranker",
"config": {
"provider": "openai",
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-openai-key",
"scoring_prompt": custom_prompt,
"top_k": 5
docs/components/rerankers/models/cohere.mdx
+1 -1
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@@ -101,7 +101,7 @@ os.environ["COHERE_API_KEY"] = "your-api-key"
# Initialize memory with Cohere reranker
config = {
"vector_store": {"provider": "chroma"},
"llm": {"provider": "openai", "config": {"model": "gpt-4o-mini"}},
"llm": {"provider": "openai", "config": {"model": "gpt-5-mini"}},
"rerank": {
"provider": "cohere",
"config": {
docs/components/rerankers/models/llm_reranker.mdx
+10 -10
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@@ -19,7 +19,7 @@ config = {
"provider": "llm_reranker",
"config": {
"provider": "openai",
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-openai-api-key"
}
}
@@ -33,7 +33,7 @@ m = Memory.from_config(config)
| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `provider` | str | `"openai"` | LLM provider (openai, anthropic, etc.) |
| `model` | str | `"gpt-4o-mini"` | LLM model to use for reranking |
| `model` | str | `"gpt-5-mini"` | LLM model to use for reranking |
| `api_key` | str | None | API key for the LLM provider |
| `top_k` | int | None | Number of top documents to return after reranking |
| `temperature` | float | 0.0 | LLM temperature for consistency |
@@ -69,7 +69,7 @@ config = {
## TypeScript (self-hosted)
The [TypeScript OSS SDK](/open-source/features/reranker-search#typescript-sdk) (`mem0ai/oss`) ships the LLM reranker under the provider name `llm_reranker`. It does **not** reuse the Memory's main `llm` instance; it builds its own LLM from the reranker's own config, defaulting to `openai` / `gpt-4o-mini`. Set `provider`/`model`/`apiKey` directly on `config`, or nest a fully separate `config.llm: { provider, config }` (its `provider`/`config` take priority over the top-level fields, which only backfill values missing from the nested config).
The [TypeScript OSS SDK](/open-source/features/reranker-search#typescript-sdk) (`mem0ai/oss`) ships the LLM reranker under the provider name `llm_reranker`. It does **not** reuse the Memory's main `llm` instance; it builds its own LLM from the reranker's own config, defaulting to `openai` / `gpt-5-mini`. Set `provider`/`model`/`apiKey` directly on `config`, or nest a fully separate `config.llm: { provider, config }` (its `provider`/`config` take priority over the top-level fields, which only backfill values missing from the nested config).
```typescript
import { Memory } from "mem0ai/oss";
@@ -114,7 +114,7 @@ config = {
"provider": "llm_reranker",
"config": {
"provider": "openai",
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-openai-api-key",
"temperature": 0.0
}
@@ -170,15 +170,15 @@ config = {
"provider": "llm_reranker",
"config": {
"provider": "azure_openai",
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-azure-api-key",
"llm": {
"provider": "azure_openai",
"config": {
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-azure-api-key",
"azure_endpoint": "https://your-resource.openai.azure.com/",
"azure_deployment": "gpt-4o-mini-deployment"
"azure_deployment": "gpt-5-mini-deployment"
}
}
}
@@ -232,7 +232,7 @@ config = {
"provider": "llm_reranker",
"config": {
"provider": "openai",
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-api-key",
"scoring_prompt": custom_prompt
}
@@ -351,7 +351,7 @@ fast_config = {
"provider": "llm_reranker",
"config": {
"provider": "openai",
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-api-key",
"top_k": 5,
"temperature": 0.0
@@ -444,7 +444,7 @@ fallback_config = {
"provider": "llm_reranker",
"config": {
"provider": "openai",
"model": "gpt-4o-mini",
"model": "gpt-5-mini",
"api_key": "your-api-key"
}
}
docs/components/rerankers/models/sentence_transformer.mdx
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@@ -36,7 +36,7 @@ config = {
"llm": {
"provider": "openai",
"config": {
"model": "gpt-4o-mini"
"model": "gpt-5-mini"
}
},
"rerank": {
@@ -113,7 +113,7 @@ from mem0 import Memory
# Initialize memory with local reranker
config = {
"vector_store": {"provider": "chroma"},
"llm": {"provider": "openai", "config": {"model": "gpt-4o-mini"}},
"llm": {"provider": "openai", "config": {"model": "gpt-5-mini"}},
"rerank": {
"provider": "sentence_transformer",
"config": {
docs/components/rerankers/models/zero_entropy.mdx
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@@ -34,7 +34,7 @@ config = {
"llm": {
"provider": "openai",
"config": {
"model": "gpt-4o-mini"
"model": "gpt-5-mini"
}
},
"rerank": {
@@ -98,7 +98,7 @@ os.environ["ZERO_ENTROPY_API_KEY"] = "your-api-key"
# Initialize memory with Zero Entropy reranker
config = {
"vector_store": {"provider": "chroma"},
"llm": {"provider": "openai", "config": {"model": "gpt-4o-mini"}},
"llm": {"provider": "openai", "config": {"model": "gpt-5-mini"}},
"rerank": {"provider": "zero_entropy", "config": {"model": "zerank-1"}}
}