LCEL Part 2: Chaining Chains, RunnableParallel, RunnableLambda and @chain
A straight line is the easy case. This post covers piping chains together, fanning out with RunnableParallel, wrapping your own functions, and drawing what you built.
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View allLCEL Part 1: The Pipe Operator, Batching, Streaming and the Runnable Protocol
A single pipe operator turns three objects into a pipeline that batches, streams and runs async for free. Here is how, plus the step that silently breaks streaming.
Structured Output: with_structured_output and When You Still Need a Parser
Free text is unusable in a pipeline. This post covers getting validated objects back with Pydantic, and the narrower cases where an output parser is still the right tool.
Model Inputs in LangChain: Messages, Prompt Templates and Few-Shot Examples
LangChain's first real abstraction is the input side: typed messages, reusable prompt templates, and few-shot examples that teach a model by showing instead of telling.
The OpenAI API Before LangChain: Roles, Temperature, Max Tokens and Streaming
Before reaching for a framework, call the API directly. System, user and assistant roles, a sarcastic chatbot, and what temperature and streaming actually control.
Tokens, Models and Prices: What an LLM Call Actually Costs
Tokens are the unit you are billed in, and they are not words. This post covers tokenization, counting before you send, model tiers, and how the costs really add up.
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AI & Tools
9 min read
LCEL Part 2: Chaining Chains, RunnableParallel, RunnableLambda and @chain
A straight line is the easy case. This post covers piping chains together, fanning out with RunnableParallel, wrapping your own functions, and drawing what you built.
AI & Tools
8 min read
LCEL Part 1: The Pipe Operator, Batching, Streaming and the Runnable Protocol
A single pipe operator turns three objects into a pipeline that batches, streams and runs async for free. Here is how, plus the step that silently breaks streaming.
AI & Tools
16 min read
Structured Output: with_structured_output and When You Still Need a Parser
Free text is unusable in a pipeline. This post covers getting validated objects back with Pydantic, and the narrower cases where an output parser is still the right tool.
AI & Tools
27 min read
Model Inputs in LangChain: Messages, Prompt Templates and Few-Shot Examples
LangChain's first real abstraction is the input side: typed messages, reusable prompt templates, and few-shot examples that teach a model by showing instead of telling.
AI & Tools
18 min read
The OpenAI API Before LangChain: Roles, Temperature, Max Tokens and Streaming
Before reaching for a framework, call the API directly. System, user and assistant roles, a sarcastic chatbot, and what temperature and streaming actually control.
AI & Tools
8 min read
Tokens, Models and Prices: What an LLM Call Actually Costs
Tokens are the unit you are billed in, and they are not words. This post covers tokenization, counting before you send, model tiers, and how the costs really add up.
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