Thank you. JAX works at the NumPy level. So we can't actually compare it with Pytorch which is a framework with high-level APIs. Regarding the advantages, have already mentioned them in the thread.
CODE
-
Community Contributions and Open Source Engagement Welcomed
By
–
Again, we're really excited to see how this develops! We are extremely open to contributions and suggestions – please open PRs, file issues, DM us, or get in touch on the discord:
-
LangChain Buffer Memory: Essential Tool for AI Agents
By
–
Memory Buffer Memory: https://
hwchase17.github.io/langchainjs/do
cs/modules/memory/buffer_memory
… -
MRKL agents and Hub loading in LangChain
By
–
Agents MRKL: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/load_from_hub
… Load from Hub: https://
hwchase17.github.io/langchainjs/do
cs/modules/agents/load_from_hub
… -
LangChain Chains: LLM, Vector DB QA, Conversation Guide
By
–
Chains (just a selection) LLM Chain: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/llm_chain
… Vector DB QA: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/vector_db_qa
… Conversation Chain: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/conversation_chain
… Load from Hub: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/load_from_hub
… -
OpenAI LLMs and LangChain Integration Guide
By
–
LLMs OpenAI: https://
hwchase17.github.io/langchainjs/do
cs/modules/llms/openai
… -
LangChain JS Indexes: Text Splitter, Embeddings, Vectorstores
By
–
Indexes Text Splitter: https://
hwchase17.github.io/langchainjs/do
cs/modules/indexes/text_splitter
… Embeddings: https://
hwchase17.github.io/langchainjs/do
cs/modules/indexes/embeddings
… Vectorstores: https://
hwchase17.github.io/langchainjs/do
cs/modules/indexes/vectorstore
… -
LangChain JS Prompt Templates and Few Shot Examples Guide
By
–
Prompts: Prompt Templates: https://
hwchase17.github.io/langchainjs/do
cs/modules/prompts/prompt_template
… Few Shot Examples: https://
hwchase17.github.io/langchainjs/do
cs/modules/prompts/few_shot_examples
… Load from Hub: https://
hwchase17.github.io/langchainjs/do
cs/modules/prompts/load_from_hub
… -
Cross-language AI abstractions with shared serializable formats
By
–
Relationship to Python Package We built the same abstractions (prompts, LLMs, etc) we had in Python In particular, we built them in a way where they share the same serializable format This means you can load the same prompt, chain, agent in both languages
-
LLM abstractions now natively available in JavaScript
By
–
HighLights All the same abstractions (prompts, LLMs, textsplitters, embeddings, vectorstores, chains, agents, memory) are now natively available in js There is a common serializable format for cross-language sharing This was only doable with community support