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docs: rebrand Keywords AI integration to Respan (#5098)

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Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: Kartik <kartik.labhshetwar@mem0.ai>
This commit is contained in:
fran3cc
2026-06-20 10:40:15 -07:00
committed by GitHub
parent ca86a164bd
commit e615cc66de
4 changed files with 29 additions and 28 deletions
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docs/docs.json
+1 -1
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@@ -441,7 +441,7 @@
"integrations/flowise",
"integrations/langchain-tools",
"integrations/agentops",
"integrations/keywords",
"integrations/respan",
"integrations/raycast"
]
}
docs/integrations.mdx
+6 -4
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@@ -309,19 +309,21 @@ Here are the available integrations for Mem0:
</Card>
<Card
title="Keywords AI"
title="Respan"
icon={
<svg
xmlns="http://www.w3.org/2000/svg"
width="24"
height="24"
viewBox="0 0 24 24"
viewBox="0 0 200 200"
fill="none"
>
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<path d="M2.00635 190.234V9.76584H53.3558V29.5101H26.7223V170.562H53.3558V190.234H2.00635Z" fill="currentColor"></path>
<path d="M120.692 160.902C116.383 160.902 112.691 159.387 109.612 156.357C106.535 153.327 105.02 149.633 105.067 145.277C105.02 141.016 106.535 137.37 109.612 134.34C112.691 131.309 116.383 129.794 120.692 129.794C124.859 129.794 128.481 131.309 131.559 134.34C134.684 137.37 136.27 141.016 136.317 145.277C136.27 148.166 135.512 150.793 134.045 153.161C132.624 155.528 130.73 157.422 128.362 158.842C126.042 160.216 123.486 160.902 120.692 160.902Z" fill="currentColor"></path>
<path d="M197.993 9.76584V190.234H146.643V170.562H173.278V29.5101H146.643V9.76584H197.993Z" fill="currentColor"></path>
</svg>
}
href="/integrations/keywords"
href="/integrations/respan"
>
Build AI applications with persistent memory and comprehensive LLM observability.
</Card>
docs/integrations/keywords.mdx → docs/integrations/respan.mdx
+21 -22
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@@ -1,22 +1,22 @@
---
title: Keywords AI
description: "Combine Mem0 persistent memory with Keywords AI observability for tracked, cost-optimized AI applications."
title: Respan
description: "Combine Mem0 persistent memory with Respan observability for tracked, cost-optimized AI applications."
---
Build AI applications with persistent memory and comprehensive LLM observability by integrating Mem0 with Keywords AI.
Build AI applications with persistent memory and comprehensive LLM observability by integrating Mem0 with Respan.
## Overview
Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users. Keywords AI provides complete LLM observability.
Mem0 is a self-improving memory layer for LLM applications, enabling personalized AI experiences that save costs and delight users. Respan (formerly Keywords AI) provides complete LLM observability.
Combining Mem0 with Keywords AI allows you to:
Combining Mem0 with Respan allows you to:
1. Add persistent memory to your AI applications
2. Track interactions across sessions
3. Monitor memory usage and retrieval with Keywords AI observability
3. Monitor memory usage and retrieval with Respan observability
4. Optimize token usage and reduce costs
<Note>
You can get your Mem0 API key from the <a href="https://app.mem0.ai/?utm_source=oss&utm_medium=integration-keywords" rel="nofollow">Mem0 dashboard</a>.
You can get your Mem0 API key from the <a href="https://app.mem0.ai/?utm_source=oss&utm_medium=integration-respan" rel="nofollow">Mem0 dashboard</a>.
</Note>
## Setup and Configuration
@@ -24,7 +24,7 @@ You can get your Mem0 API key from the <a href="https://app.mem0.ai/?utm_source=
Install the necessary libraries:
```bash
pip install mem0ai keywordsai-sdk
pip install mem0ai openai
```
Set up your environment variables:
@@ -34,13 +34,13 @@ import os
# Set your API keys
os.environ["MEM0_API_KEY"] = "your-mem0-api-key"
os.environ["KEYWORDSAI_API_KEY"] = "your-keywords-api-key"
os.environ["KEYWORDSAI_BASE_URL"] = "https://api.keywordsai.co/api/"
os.environ["RESPAN_API_KEY"] = "your-respan-api-key"
os.environ["RESPAN_BASE_URL"] = "https://api.respan.ai/api/"
```
## Basic Integration Example
Here's a simple example of using Mem0 with Keywords AI:
Here's a simple example of using Mem0 with Respan:
```python
from mem0 import Memory
@@ -48,17 +48,17 @@ import os
# Configuration
api_key = os.getenv("MEM0_API_KEY")
keywordsai_api_key = os.getenv("KEYWORDSAI_API_KEY")
base_url = os.getenv("KEYWORDSAI_BASE_URL") # "https://api.keywordsai.co/api/"
respan_api_key = os.getenv("RESPAN_API_KEY")
base_url = os.getenv("RESPAN_BASE_URL") # "https://api.respan.ai/api/"
# Set up Mem0 with Keywords AI as the LLM provider
# Set up Mem0 with Respan as the LLM provider
config = {
"llm": {
"provider": "openai",
"config": {
"model": "gpt-5-mini",
"temperature": 0.0,
"api_key": keywordsai_api_key,
"api_key": respan_api_key,
"openai_base_url": base_url,
},
}
@@ -79,7 +79,7 @@ print(result)
## Advanced Integration with OpenAI SDK
For more advanced use cases, you can integrate Keywords AI with Mem0 through the OpenAI SDK:
For more advanced use cases, you can integrate Respan with Mem0 through the OpenAI SDK:
```python
from openai import OpenAI
@@ -88,8 +88,8 @@ import json
# Initialize client
client = OpenAI(
api_key=os.environ.get("KEYWORDSAI_API_KEY"),
base_url=os.environ.get("KEYWORDSAI_BASE_URL"),
api_key=os.environ.get("RESPAN_API_KEY"),
base_url=os.environ.get("RESPAN_BASE_URL"),
)
# Sample conversation messages
@@ -118,18 +118,18 @@ response = client.chat.completions.create(
print(json.dumps(response.model_dump(), indent=4))
```
For detailed information on this integration, refer to the official [Keywords AI Mem0 integration documentation](https://docs.keywordsai.co/integration/development-frameworks/mem0).
For detailed information on this integration, refer to the official [Respan Mem0 integration documentation](https://www.respan.ai/docs/integrations/mem0).
## Key Features
1. **Memory Integration**: Store and retrieve relevant information from past interactions
2. **LLM Observability**: Track memory usage and retrieval patterns with Keywords AI
2. **LLM Observability**: Track memory usage and retrieval patterns with Respan
3. **Session Persistence**: Maintain context across multiple user sessions
4. **Cost Optimization**: Reduce token usage through efficient memory retrieval
## Conclusion
Integrating Mem0 with Keywords AI provides a powerful combination for building AI applications with persistent memory and comprehensive observability. This integration enables more personalized user experiences while providing insights into your application's memory usage.
Integrating Mem0 with Respan provides a powerful combination for building AI applications with persistent memory and comprehensive observability. This integration enables more personalized user experiences while providing insights into your application's memory usage.
<CardGroup cols={2}>
<Card title="OpenAI Agents SDK" icon="cube" href="/integrations/openai-agents-sdk">
@@ -139,4 +139,3 @@ Integrating Mem0 with Keywords AI provides a powerful combination for building A
Monitor agent performance with AgentOps
</Card>
</CardGroup>
docs/llms.txt
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@@ -286,7 +286,7 @@ If the user is on a pre-current major (Python < 2, TS < 3, or Platform `output_f
- [Dify](https://docs.mem0.ai/integrations/dify) [Both]: Use when the user is on Dify LLMOps.
- [Flowise](https://docs.mem0.ai/integrations/flowise) [Both]: Use when the user is on Flowise no-code.
- [AgentOps](https://docs.mem0.ai/integrations/agentops) [Both]: Use when tracking agent observability with memory metadata.
- [Keywords AI](https://docs.mem0.ai/integrations/keywords) [Both]: Use when monitoring with Keywords AI.
- [Respan](https://docs.mem0.ai/integrations/respan) [Both]: Use when monitoring Mem0 with Respan (formerly Keywords AI) LLM observability.
- [Raycast](https://docs.mem0.ai/integrations/raycast) [Both]: Use when the user wants quick memory access via Raycast.
## Cookbooks