Explained Techniques to parse/format LLM's output using LangChain in python(TypedDict,Pydantic,JSON)

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Explained Different Techniques to parse the output of LLM's Using LangChain
1. Pydantic
2. TypedDict
3. JSON Schema
4. Custom Extraction

LetsLearnWithChinnoVino

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In few-shot prompting section, since we are already defining the structure in the prompt itself, we don't need to keep the "structured_llm" at the end of the chain, right ? We can simply use the llm ?

Superb video bro. So much info in this video, with great clarity !

asitnayak

11:00 - As we have already used while formatting the prompt, why do we need to pass the "parser" again at the end of the chain ? Because the prompt itself contains the formatting instructions.

asitnayak

Explained Techniques to parse/format LLM's output using LangChain in python(TypedDict,Pydantic,JSON)

Explained Techniques to parse/format LLM's output using LangChain in python(TypedDict,Pydantic,...

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