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Fix: add note regarding llama

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Harshith Mullapudi 2025-06-30 23:35:58 +05:30
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commit 13d0c1462e
3 changed files with 25 additions and 24 deletions
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46
README.md
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@ -4,8 +4,6 @@
</a> </a>
</div> </div>
## C.O.R.E. ## C.O.R.E.
**Contextual Observation & Recall Engine** **Contextual Observation & Recall Engine**
@ -17,9 +15,11 @@ C.O.R.E is built for two reasons:
1. To give you complete ownership of your memory, stored locally and accessible across any app needing LLM context. 1. To give you complete ownership of your memory, stored locally and accessible across any app needing LLM context.
2. To help SOL (your AI assistant) access your context, facts, and preferences for more relevant and personalized responses. 2. To help SOL (your AI assistant) access your context, facts, and preferences for more relevant and personalized responses.
## Demo Video > **Note:** We are actively working on improving support for Llama models. At the moment, C.O.R.E does not provide optimal results with Llama-based models, but we are making progress to ensure better compatibility and output in the near future.
[Check C.O.R.E Demo](https://youtu.be/iANZ32dnK60)
## Demo Video
[Check C.O.R.E Demo](https://youtu.be/iANZ32dnK60)
## How is C.O.R.E different from other Memory Providers? ## How is C.O.R.E different from other Memory Providers?
@ -37,7 +37,6 @@ With C.O.R.E, you see exactly what prices changed, who approved them, the contex
Or ask: “What does Mike know about Project Phoenix?” and get a timeline of meetings, decisions, and facts Mike was involved in, with full traceability to those specific events. Or ask: “What does Mike know about Project Phoenix?” and get a timeline of meetings, decisions, and facts Mike was involved in, with full traceability to those specific events.
## C.O.R.E Cloud Setup ## C.O.R.E Cloud Setup
1. Sign up to [Core Cloud](https://core.heysol.ai) and start building your memory graph. 1. Sign up to [Core Cloud](https://core.heysol.ai) and start building your memory graph.
@ -97,30 +96,31 @@ Or ask: “What does Mike know about Project Phoenix?” and get a timeline of m
2. In Cursor, go to: Settings → Tools & Integrations → New MCP Server. 2. In Cursor, go to: Settings → Tools & Integrations → New MCP Server.
3. Add the CORE MCP server using the configuration format below. Be sure to replace the API_TOKEN value with the token you generated in step 1. 3. Add the CORE MCP server using the configuration format below. Be sure to replace the API_TOKEN value with the token you generated in step 1.
MCP configuration to add in Cursor MCP configuration to add in Cursor
``` json ```json
{ {
"mcpServers": { "mcpServers": {
"memory": { "memory": {
"command": "npx", "command": "npx",
"args": ["-y", "@redplanethq/core-mcp"], "args": ["-y", "@redplanethq/core-mcp"],
"env": { "env": {
"API_TOKEN": "YOUR_API_TOKEN_HERE", "API_TOKEN": "YOUR_API_TOKEN_HERE",
"API_BASE_URL": "https://core.heysol.ai", "API_BASE_URL": "https://core.heysol.ai",
"SOURCE": "cursor" "SOURCE": "cursor"
} }
} }
} }
} }
``` ```
4. Go to Settings-> User rules -> New Rule -> and add the below rule to ensure all your chat interactions are being stored in CORE memory 4. Go to Settings-> User rules -> New Rule -> and add the below rule to ensure all your chat interactions are being stored in CORE memory
``` ```
After every interaction, update the memory with the user's query and the assistant's After every interaction, update the memory with the user's query and the assistant's
response to core-memory mcp. sessionId should be the uuid of the conversation response to core-memory mcp. sessionId should be the uuid of the conversation
``` ```
## Connecting to the API ## Connecting to the API
You can also interact with C.O.R.E. programmatically via its APIs. You can also interact with C.O.R.E. programmatically via its APIs.

2
mcp/package.json
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@ -1,6 +1,6 @@
{ {
"name": "@redplanethq/core-mcp", "name": "@redplanethq/core-mcp",
"version": "0.1.3", "version": "0.1.5",
"type": "module", "type": "module",
"main": "dist/index.js", "main": "dist/index.js",
"bin": { "bin": {

1
mcp/src/operations/graph.ts
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@ -14,6 +14,7 @@ export async function ingestKnowledgeGraph(args: IngestKG) {
const response = await axiosInstance.post(`/ingest`, { const response = await axiosInstance.post(`/ingest`, {
episodeBody: args.message, episodeBody: args.message,
source: process.env.SOURCE, source: process.env.SOURCE,
referenceTime: new Date().toISOString(),
sessionId: undefined, sessionId: undefined,
}); });
return response.data; return response.data;