Explore Neo4J RAG LLM pipeline using IBM BAM https://bam.res.ibm.com/
with custom chains and agents.
Run npm run watch:deploy
for a dev server. The application will automatically reload if you change any of the source files.
To interact with Langchain Express Server, head over to https://github.com/playground/mesh-genai
and clone the repo. Run ng serve
for a dev server. Hit this url http://localhost:4200/
to bring up the UI.
Navigate to Langchain JS
tab:
Settings: Provide Langchain Express URL(ex: http://localhost:3000).
Loader: Upload documents to be embedded and store in vector db (.pdf, .txt, .json, .csv)
Try Me:
Ask Me: Ask questions related to contents that have been uploaded by specifying the collection name
Ask Web: Ask questions by crawling the web with the provided url using retrieval chains/tools
Ask Agent: Coming soon
docker run -d --rm --name chromadb -p 8000:8000 -v ./chroma:/chroma/chroma -e IS_PERSISTENT=TRUE -e ANONYMIZED_TELEMETRY=TRUE chromadb/chroma:latest
To get around this error for the time being
Error [ERR_REQUIRE_ESM]: require() of ES Module /home/playground/langchain-express/node_modules/@xenova/transformers/src/transformers.js from /home/playground/langchain-express/node_modules/@langchain/community/dist/embeddings/hf_transformers.cjs not supported.
replace line #4 and #82 in /node_modules/@langchain/community/dist/embeddings/hf_transformers.cjs
with the following to dynamically import "@xenova/transformers"
Line #4
const transformers_1 = (async() => {
return await import('@xenova/transformers')
})();
Line #82
const pipe = await (this.pipelinePromise ??= (await import("@xenova/transformers")).pipeline("feature-extraction", this.modelName));
Explore Neo4J Knowledge Graph and custom Agents