17 days ago
Stuck in traffic, brainstorming prompt engineering strategies. The LLM is powerful but needs guidance. Few-shot examples might be the key. Mental problem-solving during commute! #llm #promptengineering #thinking
18 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! #langchain #rag #llm
18 days ago
Stuck in traffic, brainstorming prompt engineering strategies. The LLM is powerful but needs guidance. Few-shot examples might be the key. Mental problem-solving during commute! #llm #promptengineering #thinking
19 days ago
OpenAI function calling makes structured outputs easy. No more prompt engineering for JSON! Defined schema for our API responses. The model reliably returns valid, typed data. Error handling is much cleaner. Building AI agents became so much more practical. Game changer for LLM applications! #openai #gpt #ai #functioncalling
19 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! Using Pinecone for vector storage with OpenAI embeddings. Chunking strategy was crucial - 500 tokens with 50 token overlap works best. Users can query 10,000 documents in natural language! #langchain #rag #llm #vectordb
19 days ago
OpenAI function calling makes structured outputs easy. No more prompt engineering for JSON! Defined schema for our API responses. The model reliably returns valid, typed data. Error handling is much cleaner. Building AI agents became so much more practical. Game changer for LLM applications! #openai #gpt #ai #functioncalling
20 days ago
Local LLM deployment with llama.cpp. Privacy-first AI without cloud dependencies! Running Mixtral on our own servers. Quantization maintains quality while fitting in memory. Response times are acceptable for our use case. Sensitive data never leaves our infrastructure. Self-hosted AI is viable! #llama #locallm #ai #privacy
22 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! Using Pinecone for vector storage with OpenAI embeddings. Chunking strategy was crucial - 500 tokens with 50 token overlap works best. Users can query 10,000 documents in natural language! #langchain #rag #llm #vectordb
23 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! Using Pinecone for vector storage with OpenAI embeddings. Chunking strategy was crucial - 500 tokens with 50 token overlap works best. Users can query 10,000 documents in natural language! #langchain #rag #llm #vectordb
25 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! #langchain #rag #llm
25 days ago
Stuck in traffic, brainstorming prompt engineering strategies. The LLM is powerful but needs guidance. Few-shot examples might be the key. Mental problem-solving during commute! #llm #promptengineering #thinking
26 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! #langchain #rag #llm
27 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! #langchain #rag #llm
28 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! Using Pinecone for vector storage with OpenAI embeddings. Chunking strategy was crucial - 500 tokens with 50 token overlap works best. Users can query 10,000 documents in natural language! #langchain #rag #llm #vectordb
28 days ago
Local LLM deployment with llama.cpp. Privacy-first AI without cloud dependencies! Running Mixtral on our own servers. Quantization maintains quality while fitting in memory. Response times are acceptable for our use case. Sensitive data never leaves our infrastructure. Self-hosted AI is viable! #llama #locallm #ai #privacy
29 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! #langchain #rag #llm
30 days ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! Using Pinecone for vector storage with OpenAI embeddings. Chunking strategy was crucial - 500 tokens with 50 token overlap works best. Users can query 10,000 documents in natural language! #langchain #rag #llm #vectordb
1 month ago
Local LLM deployment with llama.cpp. Privacy-first AI without cloud dependencies! Running Mixtral on our own servers. Quantization maintains quality while fitting in memory. Response times are acceptable for our use case. Sensitive data never leaves our infrastructure. Self-hosted AI is viable! #llama #locallm #ai #privacy
1 month ago
OpenAI function calling makes structured outputs easy. No more prompt engineering for JSON! Defined schema for our API responses. The model reliably returns valid, typed data. Error handling is much cleaner. Building AI agents became so much more practical. Game changer for LLM applications! #openai #gpt #ai #functioncalling
1 month ago
OpenAI function calling makes structured outputs easy. No more prompt engineering for JSON! Defined schema for our API responses. The model reliably returns valid, typed data. Error handling is much cleaner. Building AI agents became so much more practical. Game changer for LLM applications! #openai #gpt #ai #functioncalling
1 month ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! #langchain #rag #llm
1 month ago
Stuck in traffic, brainstorming prompt engineering strategies. The LLM is powerful but needs guidance. Few-shot examples might be the key. Mental problem-solving during commute! #llm #promptengineering #thinking
1 month ago
OpenAI function calling makes structured outputs easy. No more prompt engineering for JSON! Defined schema for our API responses. The model reliably returns valid, typed data. Error handling is much cleaner. Building AI agents became so much more practical. Game changer for LLM applications! #openai #gpt #ai #functioncalling
1 month ago
Local LLM deployment with llama.cpp. Privacy-first AI without cloud dependencies! Running Mixtral on our own servers. Quantization maintains quality while fitting in memory. Response times are acceptable for our use case. Sensitive data never leaves our infrastructure. Self-hosted AI is viable! #llama #locallm #ai #privacy
1 month ago
1 month ago
Stuck in traffic, brainstorming prompt engineering strategies. The LLM is powerful but needs guidance. Few-shot examples might be the key. Mental problem-solving during commute! #llm #promptengineering #thinking
1 month ago
LangChain + vector databases = powerful RAG applications. Document Q&A is now incredibly accurate! #langchain #rag #llm
1 month ago
OpenAI function calling makes structured outputs easy. No more prompt engineering for JSON! Defined schema for our API responses. The model reliably returns valid, typed data. Error handling is much cleaner. Building AI agents became so much more practical. Game changer for LLM applications! #openai #gpt #ai #functioncalling
