https://github.com/es7/langchain-for-llms
https://github.com/es7/langchain-for-llms
Last synced: over 1 year ago
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- Host: GitHub
- URL: https://github.com/es7/langchain-for-llms
- Owner: ES7
- License: mit
- Created: 2024-05-21T15:50:53.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-23T08:41:16.000Z (about 2 years ago)
- Last Synced: 2024-05-23T09:40:06.759Z (about 2 years ago)
- Language: Jupyter Notebook
- Size: 16.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LangChain-for-LLMs
LangChain is a framework designed for developing applications powered by language models. It provides a set of tools and abstractions that make it easier to build complex applications that leverage the capabilities of large language models (LLMs) like OpenAI's GPT-4. LangChain is especially useful for tasks that require integrating language models with other systems, managing interactions, and handling the flow of data.
**`1. Model_Prompt_Parser.ipynb` :-** In this notebook we will see the models used in langchain, what are prompt templates, and what is parsing in langchain.
**`2. Memory.ipynb` :-** In this notebook we will see the different ways to store the history of conversation in langchain.
**`3. Chains.ipynb` :-** In this notebook we will see what are chains and its types and how to use it.
**`4. QnA.ipynb` :-** In this notebook we will pass a document and ask questions to the langauge model via Chains, we will also see some methods to perform this task.
**`5. Evaluation.ipynb` :-** In this notebook we will see how can we evaluate our code using LangChain.
**`6. Agents.ipynb` :-** In this notebook we will see what are agents in langchain and how to use it.