Codes related to my LangChain playlist

Generate an optimal path on a map a la Traveling Salesman Problem to hit different landmarks in an input city using Cloudflare Workers AI (using LlaMA-3.1), LangChain (for prompt templates and comma separated list output parser), Mapbox to create a map and get information about cities and landmarks in those cities, and Folium to edit the map.

A custom chat agent implemented using Langchain, gpt-3.5 and Pinecone. Implements memory management for context, a custom prompt template, a custom output parser, and a QA tool.

This repository demonstrates structured output parsing techniques in LangChain using different output parsers including:

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Practical guide to LangChain output parsers. Convert raw LLM text into structured, validated data (JSON, lists, tables) with schemas, robust error handling, and retries. Build reliable pipelines that downstream tools can trust and automate.

Use LangChain's Output Parser to Extract Information from ChatGPT Prompt Response

Demonstrate flexible output parsing techniques using LangChain's powerful chaining and output parsing capabilities.

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Structured LLM output validation using LangChain Output Parsers, demonstrating JSON parsing, Pydantic schema enforcement, and multi-stage chain workflows.

Design robust structured outputs for LLM applications. Learn how to enforce schema-driven responses using TypedDict, Pydantic Output Parsers, and LangChain—especially for open-source LLMs that lack native structured output support.

I have used travel panner by using langchain chat_prompt_template, chat_model and output_parser and also use streamlit for UI.

Chatbot using Langchain, Ollama LLM, Prompt Template, Streamlit UI, Output Parser, and Chain, built and run in Jupyter Notebook. Demonstrates flexible, customizable, and efficient design.

This repository is dedicated for Langchain parser.. Basically idea is get the structured output so that it can able to communicate with other system like; database etc.

The AI CV Parser is an intelligent automation tool that utilizes Large Language Models (LLMs) to extract structured information from unstructured resumes. By combining Mistral-Nemo with LangChain's structured output parsing and Streamlit.

A ReACT-based chatbot agent leveraging LangChain, the Ollama LLM (llama3), and DuckDuckGo search integration. This project demonstrates how to build a conversational AI with a custom output parser to extract and present final answers cleanly.

Leveraging language model frameworks such as LangChain and LlamaIndex to create synthetic data for various journal entries across a few domains. Using Pydantic as the output parser that allows me, the AI engineer, to specify an arbitrary JSON schema and query LLMs for JSON outputs that conform to that schema.

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OutputParser

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Langchain Output Parser

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