{"id":25868416,"url":"https://github.com/md-emon-hasan/langchain","last_synced_at":"2026-06-08T12:32:39.976Z","repository":{"id":277388687,"uuid":"932269707","full_name":"Md-Emon-Hasan/LangChain","owner":"Md-Emon-Hasan","description":"Powerful framework for building applications with Large Language Models (LLMs), enabling seamless integration with memory, agents, and external data sources.","archived":false,"fork":false,"pushed_at":"2025-02-13T16:58:17.000Z","size":755,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-02T04:38:10.512Z","etag":null,"topics":["ai-chatbot","chromadb","custom-llm","document-processing","faiss","fine-tuning-llms","generative-ai","huggingface","knowledge-graph","langchain","large-language-models","llm-agents","llm-applications","multi-modal-ai","prompt-engineering","rag-pipeline","retrieval-augmented-generation","semantic-search","text-embedding","vector-search"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Md-Emon-Hasan.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-02-13T16:38:00.000Z","updated_at":"2025-02-14T14:55:11.000Z","dependencies_parsed_at":"2025-02-13T17:50:35.576Z","dependency_job_id":"b107034a-053c-43af-b79c-8a8196bffc0d","html_url":"https://github.com/Md-Emon-Hasan/LangChain","commit_stats":null,"previous_names":["md-emon-hasan/langchain"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Md-Emon-Hasan/LangChain","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Md-Emon-Hasan%2FLangChain","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Md-Emon-Hasan%2FLangChain/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Md-Emon-Hasan%2FLangChain/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Md-Emon-Hasan%2FLangChain/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Md-Emon-Hasan","download_url":"https://codeload.github.com/Md-Emon-Hasan/LangChain/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Md-Emon-Hasan%2FLangChain/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34063150,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-08T02:00:07.615Z","response_time":111,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai-chatbot","chromadb","custom-llm","document-processing","faiss","fine-tuning-llms","generative-ai","huggingface","knowledge-graph","langchain","large-language-models","llm-agents","llm-applications","multi-modal-ai","prompt-engineering","rag-pipeline","retrieval-augmented-generation","semantic-search","text-embedding","vector-search"],"created_at":"2025-03-02T04:38:12.115Z","updated_at":"2026-06-08T12:32:39.951Z","avatar_url":"https://github.com/Md-Emon-Hasan.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# LangChain\n![Image](https://github.com/user-attachments/assets/eabf0a00-b5ee-4e89-bc0c-0609b1542c66)\n\n## Overview\nLangChain is a cutting-edge open-source framework designed to streamline the development of applications leveraging Large Language Models (LLMs). It provides robust tools for seamless integration with external data sources, memory management, and agent-based decision-making, empowering developers to build sophisticated AI-powered applications efficiently.\n\n## Key Features\n- **Seamless LLM Integration**: Effortlessly connect with models such as OpenAI, Hugging Face, Cohere, and others.\n- **Advanced Prompt Engineering**: Optimize and refine prompts for improved model interactions.\n- **Persistent Memory Management**: Store and retrieve conversation history to enhance contextual awareness.\n- **Intelligent Agents and Tools**: Automate decision-making workflows with flexible agents.\n- **Efficient Vector Databases**: Implement state-of-the-art knowledge indexing and retrieval.\n\n## Installation\nTo get started with LangChain, install the necessary dependencies:\n```bash\npip install langchain\npip install openai  # If using OpenAI models\npip install chromadb  # For vector storage\npip install faiss-cpu  # Alternative vector store\n```\n\n## Quick Start Guide\n### 1. Basic LLM Usage\n```python\nfrom langchain.llms import OpenAI\n\nllm = OpenAI(model_name=\"text-davinci-003\", openai_api_key=\"your-api-key\")\nresponse = llm.predict(\"What is LangChain?\")\nprint(response)\n```\n\n### 2. Creating a Conversational AI with Memory\n```python\nfrom langchain.memory import ConversationBufferMemory\nfrom langchain.chains import ConversationChain\nfrom langchain.llms import OpenAI\n\nmemory = ConversationBufferMemory()\nllm = OpenAI(model_name=\"gpt-3.5-turbo\", openai_api_key=\"your-api-key\")\nconversation = ConversationChain(llm=llm, memory=memory)\n\nprint(conversation.predict(input=\"Hello!\"))\nprint(conversation.predict(input=\"How are you today?\"))\n```\n\n### 3. Utilizing Vector Databases (ChromaDB)\n```python\nfrom langchain.vectorstores import Chroma\nfrom langchain.embeddings import OpenAIEmbeddings\n\nembeddings = OpenAIEmbeddings(openai_api_key=\"your-api-key\")\nvectorstore = Chroma(embedding_function=embeddings)\nvectorstore.add_texts([\"LangChain is a powerful framework for LLM applications.\"])\n\nquery = \"What is LangChain?\"\nresults = vectorstore.similarity_search(query)\nprint(results)\n```\n\n### 4. Implementing an AI Agent with Custom Tools\n```python\nfrom langchain.agents import AgentType, initialize_agent\nfrom langchain.llms import OpenAI\nfrom langchain.tools import Tool\n\ndef custom_tool(query):\n    return f\"Processed query: {query}\"\n\ntools = [Tool(name=\"CustomTool\", func=custom_tool, description=\"A sample tool\")] \nllm = OpenAI(model_name=\"gpt-3.5-turbo\", openai_api_key=\"your-api-key\")\nagent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)\n\nresponse = agent.run(\"Use CustomTool to process 'Hello World'\")\nprint(response)\n```\n\n## Advanced Topics\n- **Fine-tuning LangChain with Hugging Face Models**\n- **Building a Retrieval-Augmented Generation (RAG) Pipeline**\n- **Deploying LangChain Applications with Streamlit and FastAPI**\n\n## Best Practices\n- Implement caching mechanisms to optimize API costs.\n- Use prompt engineering techniques like few-shot learning to improve performance.\n- Secure API keys by leveraging environment variables.\n\n## Resources\n- [LangChain Official Documentation](https://python.langchain.com/)\n- [LangChain GitHub Repository](https://github.com/hwchase17/langchain)\n- [Community Support and Discussions](https://discord.com/invite/langchain)\n\n## Contributing\nContributions are highly encouraged! Feel free to submit issues, feature requests, or pull requests to help enhance this repository.\n\n## Contact Information\nFor any inquiries or collaboration opportunities, feel free to reach out:\n- **Email:** [iconicemon01@gmail.com](mailto:iconicemon01@gmail.com)\n- **WhatsApp:** [+8801834363533](https://wa.me/8801834363533)\n- **GitHub:** [Md-Emon-Hasan](https://github.com/Md-Emon-Hasan)\n- **LinkedIn:** [Md Emon Hasan](https://www.linkedin.com/in/md-emon-hasan)\n- **Facebook:** [Md Emon Hasan](https://www.facebook.com/mdemon.hasan2001/)\n\n## License\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmd-emon-hasan%2Flangchain","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmd-emon-hasan%2Flangchain","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmd-emon-hasan%2Flangchain/lists"}