Langchain agent without openai reddit. I don’t see OpenAI doing this.

Langchain agent without openai reddit And I found all the examples are OpenAI. cpp (both should work), and ollama. And because whatever OpenAI is using to store their assistant knowledge base sucks or at least it’s hard to get the agent to actually use it without extra prompts. I’m prototyping one now using a GPT and when it stops being stupid it gives really reliable SQL queries even without metadata on my db, only the tables and relations. I have an application that is currently based on 3 agents using LangChain and GPT4-turbo. (we're trying to fix this in LangChain as well - revamping the architecture to split out integrations, having langchain-core as a separate thing). They are not used to heavy frameworks such as Langchain. Thank you very much Hi LangChain community, I am trying to create a chatbot that excel not only in calling functions but also in having communications based on memory and on its prior knowledge to an extent. Langchain makes it fairly easy to do context augmented retrieval (i. In this example you find where sql_code is defined or created in the tool run, then send it to the run manager. #5 not to my knowledge, but you can look into langchain agents. Make a Reddit Application and initialize the Trying to use non-OpenAI models, but it seems like there's no equivalent to the get_openai_callback() function for other models, but the docs say it's only usable for OpenAI. If you built a specialized workflow, and now you want something similar, but with an LLM from Hugging Face instead of OpenAI, LangChain makes that change as simple as a few variables. It looks literally like the way to actually see what it's sending to openai is to use a logging http proxy? So if your choosing to implement an intelligent agent, LangChain is really your best bet currently. I am trying to switch to Open source LLM for this chatbot, has anyone used Langchain with LM studio? I was facing some issues using open source LLM from LM Studio for this task. They might have some off the shelf ones. OpenAI have changed their models many times, without affecting our community. i was doing some testing and manage to use a langchain pdf chat bot with the oobabooga-api, all run locally in my gpu. HuggingFaceHub without an API key? I'm interested in running the LLM locally. The platform aims to provide an easy way to create, upload, and manage these tools, giving you the power to LangChain is an open-source framework and developer toolkit that helps developers get LLM applications from prototype to production. I'm Harrison Chase, CEO and cofounder of LangChain–an open-source framework and developer toolkit that helps developers get LLM applications from prototype to production. questions over structured data. chains import RetrievalQA from langchain. All of these types of posts ignore or gloss over a LOT. They do affect us by changing their API with as little warning and documentation as they did. I plan to explore it more in the future. They've also started wrapping API endpoints with LLM interfaces. from With the big dogs openly focusing on Agent orchestration, function calling, and internal RAG integration it seems like this is inevitable. LangChain has a fairly decent async implementation which is wonderful when you switch from OpenAI to AzureOpenAI. Having started playing with it in its relative infancy and watched it grow (growing pains included), I’ve come to believe langchain is really suited more to very rapid prototyping and an eclectic selection of helpers for testing different implementations. In this example, we adapt existing code from the docs, and use ChatOpenAI to create an agent chain with memory. Assistants API also but slow. I'm also a bit hesitant/frustrated with Python in general, which makes Langchain. Then I compiled the code with the command "python3 nom_du_fichier ". OpenAI's mission is to ensure that artificial general Improving GPT-3. Langchain seems pretty messed up. Can you also get Langchain to use your own API with a private API Key? So for example if I wanted to create a Tool for my own API, can we have custom Tool/Plugin/Agent etc, not quite sure how that works. using this main code langchain-ask-pdf-local with the webui class in oobaboogas-webui-langchain_agent this is the The new releases from openai had me convinced to drop langchain, but then the concern of being locked in to a single LLM provider scared me too much to change course away from Langchain. e. We heard many people moving away from Langchain and building directly with OpenAI's API because of the unnecessary abstraction and the increased difficulty in debugging. Ready to support Yes, it is indeed possible to use the SemanticChunker in the LangChain framework with a different language model and set of embedders. And not hard to replicate. One funny story is we ran into an issue where the bot would always reply no matter what, so users would get into a "thanks, have a good day", "you too again", in an endless loop, so we had to implement a stop-code in the middleware. Also there is something like agent_executor so there are many terms that I am not sure which one is responsible about my customization. I mean that you're missing the case for LangChain if you try and develop an app that's LLM agnostic without it or some other library. Reading the documentation, it seems that the recommended Agent for Claude is the XML Agent. Or, it might be that AutoGPT leverages Langchain, I'm not sure. I’m building an agent with custom tools with Langchain and wanna know how to use different llms within it. I'd like to test Claude 3 in this context. agents import Tool, load_tools, initialize_agent, create_csv_agent, AgentType from langchain. openai. Any alternative on how we can do this without using langchain ? Same haha OpenAI + string formatting and you can already do 90% of what langchain does, without the black box aspect The langchain agent currently fetches results from tools and runs another round of LLM on the tool’s results which changes the I had this feeling only when I started with langchain after using OpenAI API for a while, 19 votes, 13 comments. Questions: Q1. from langchain_core. and have the better results that you'll get from reasoning. - The discord community is pretty inactive honestly so many unclosed queries still in the chat. Edit: Actually screw it, I'm just gonna use the api for each provider instead, seems way more straightforward and less of a hassle. So, LangChain (or Can you do without them, sure, but should you? Probably not depending on the scale LangChain gives you one standard interface for many use cases. The openai client works for openrouter but adding langchain in this way breaks generation. To run the example, add your reddit API access information and also get an OpenAI key from the OpenAI API. Has anyone had success using Langchain agents powered by an LLM other than the ones from OpenAI? I've specifically been working on understanding the differences between using I've played around with OpenAI's Function Calling and I've found it a lot faster and easier to use than the tools and agent options provided by LangChain. from langchain_huggingface import HuggingFacePipeline. Agreed. The problem with langchain is that it is not plug and play with different models. I will say tho that using langchain for RAG and agentic programs has had the best results for me. I don’t see OpenAI doing this. 17 votes, 16 comments. answering questions on the basis of documents, websites, repositories etc. Tool class. The problem is every LLM seems to have a different preference for the instruction format, and the response will be awful if I don't comply with that format. This loader fetches the text from the Posts of Subreddits or Reddit users, using the praw Python package. The MCAT (Medical College Admission Test) is offered by the AAMC and is a required exam for admission to medical schools in the USA and Canada. Although it's important to acknowledge that Huggingface's system is in beta, there seem to be fundamental issues in their agent management architecture or lack there of. I've been experimenting with combining LangChain agents with OpenAI's recently announced support for function calling. graph import StateGraph, END from typing import Annotated, Sequence, I was working on using gpt4all's open AI-like API backend to see if I could start phasing out the actual openai API to some extent. They mostly see LangChain as a shelf of ready-to-use apllication such as RAG and simple Agents. Hi folks, it seems to me that the current sentiment around AI agents is very negative as in that they're useless but I don't Working on a product that is on production . Here's an example. I use and develop the StreamLit/Langchain so much more because everything is just easier to develop and faster to manage and deploy. I'm trying to process different documents that have anywhere from 200 tokens to 2k tokens and consistently getting 20 I want to use an open source LLM as a RAG agent that also has memory of the current conversation (and eventually I want to work up to memory of previous conversations). I myself tried generating the answers by manually querying the DB, but the answer are like to the point, ie when the Agent thing worked for me, which was very rarely, it gave the answer more like a conversational manner whereas when I used Langchain to make an query and then run it on the DB manually myself, I got the answer which was just the fact. ). Agents work great with GPT4, with 3. Hi Reddit! Today is LangChain's first birthday and it's been incredibly exciting to see how far LLM app development has come in that time–and how much more there is to go. Reddit is an American social news aggregation, content rating, and discussion website. But GPTs and LangChain agents serve entirely different markets and those other models don't actually compete with GPT-4 There’s been a bit of time now for a few alternatives to come out to langchain. 5 is an idiot. Langchain execution agent too slow Anyone knows of an optimal solution to speed up langchain when using with vector db (pinecone in this case). I'm sure they went through dozens of iterations of each prompt to get the output right. I am using OpenAI_Multi_Functions agenttype currently and I wanna combine it with a conversational agent but I can't find anything relevant anywhere. The whole app comes crashing down, recovering states is a pain, etc. We are deployed without langchain on openrouter. I installed langchain[All] and the OpenAI import seemed to work. There are some custom agent tutorials but still they are not very easy to understand and I am not sure if this a situation to use custom agent or customize openai functions type agent. 10 votes, 12 comments. It's not An examples code to make langchain agents without openai API key (Google Gemini), Completely free unlimited and open source, run it yourself on website. LangGraph: LangGraph looks interesting. from_pretrained(model_id) model = AutoModelForCausalLM. Sorry I am new to langchain. There is no autonomous plug-in capabilities like OpenAi. from langchain. Asking GPT-4 questions without specifying the subject can cause it to answer based in its initial prompting. My issue was more around binding a tool to an agent_executor and then invoking it to just pass the tool output. It almost always fails with local models. It said something like CSV agent could not be installed because it was not compatible with the version of langchain. Web GPT4 was pretty good after uploading the document. A few months ago, most notably OpenAI DevDay (Nov 6, 2023), OpenAI added new functionality to both the API such as assistants and to ChatGPT such as custom GPTs. js). 5/4 and was considering using a framework such as LangChain. Tool Juggler is built on top of the Langchain library, and all custom tools are instances of the langchain. Also, Langchain’s main capability allows you to “chain” together operations. But in this jungle, how can you find some working stacks that uses OpenAI, LangChain and whatever else? Lets say I want an agent/bot that: * knows about my local workspace (git repo) but knows about it in REAL TIME * the agent or a sibling agent has access to all the latest documentation, say for example React Native Get the Reddit app Scan this I've also tried passing a list tools to an agent without the decorator using this method just in case it helped for some reason, messages, access smart devices with HomeAssistant etc. Their implementation of agents are also fairly easy and robust, with a lot of tools you can integrate into an agent and seamless usage between them, unlike ChatGPT with plugins. I'm working on a conversational agent Look for SystemMessage (in python it’s in langchain. 5-turbo-instruct can defeat chess engine Fairy-Stockfish 14 at level 5. Since you asked about possible alternatives, I’ll mention There are various language models that can be used to embed a sentence/paragraph into a vector. js attractive, but I'm concerne that Langchain. But I think in 2024 we will see the foundation models capable of Langchain type results and granularity. I was looking into conversational retrieval agents from Langchain (linked below), but it seems they only work with OpenAI models. Posted by u/Little-Meet4512 - 1 vote and 1 comment I replaced my old project with LangChain ReAct Agent tools with new OpenAI Functions and gotten better results The reasoning part got faster (maybe just because of improvements to gpt-3. Sure you can leverage LangChain to create an agent that works with other models as well. We use heavily OpenAI LLM to take decisions. I’m working with the gpt-4 model using azure OpenAI and get rate limit exceeded based on my subscription. Then you add it to the agent’s Does anyone knows how to add systemMessage to openai-functions agnet declared like We then use OpenAI Function Agent + Zep for memory and for the Vector Database. We already did a project with langchain agents before and it was very easy for us to use their agents. And in my opinion, for those using OpenAI's models, it's definitely the better option right OpenAI Functions is a separate fine-tuned model from OpenAI that you can send a list of functions and description to and get back which one to use based on your string query. BTW im not voting for any particular agent architecture, just pointing our two interesting concepts how important is the reasoning That you CAN have it even when using OpenAI functions (you need to play with the prompt to get it). The #1 social media platform for MCAT advice. . Say I have a function foo with parameters a, b, c. agent. vectorstores import FAISS from langchain. I tried reading and understanding the “WebGPT: Browser-assisted question OpenAI is an AI research and deployment company. But when they need to implement something more specific, they don't want to really understand how LangChain works under the hood to extend its functionality. However this documentation is referring to Claude 2 instead of No agent framework, Langchain or some other framework, is production ready unless your OpenAI or Microsoft (cost). GPT 4 is better but so, I don't think any other agent frameworks give you the same level of controllability We've also tried to learn from LangChain, and conciously keep LangGraph very low level and free of integrations. However, the open-source LLMs I used and agents I built with LangChain wrapper didn’t produce consistent, production-ready results. To utilize LangChain without an OpenAI API key, developers can leverage Is there a way to do a question and answer on multiple word documents, in a way that’s similar to what Langchain has, but to be run locally (without openai, without internet)? I’m ok with poorer quality outputs - it is more important to me that the model runs locally. While llamaindex etc are good for fast prototyping, I feel like OpenAI and a bit of Python programming from my end gives me more control over what I'm doing. As a demo I've put together an app that allows SecOps teams to autonomously find the domain registrar for malicious / LOL. The issue I ran into with assistant API from OpenAI is that it’s super slow. model_id = "microsoft/Phi-3-mini-4k-instruct" tokenizer = AutoTokenizer. Im not using langchain, just vanilla OpenAI with function calling. embeddings import OpenAIEmbeddings If you have developed such agent and can help me out, View community ranking In the Top 10% of largest communities on Reddit. This. I've been digging for hours. I have a second app on StreamLit with Langchain and pay $0. So I thought since Groq is ultra fast and rolled out the new tool calling feature, I’d give it a shot. Let's do this. Essentially, I wanted to use Langchain's ChatOpenAI(), but switch the OPENAI_BASE_URL, and put something random in for the key. Langchain Agent Search Returning Various Answers and Looping Question | Help 2023 Authors OpenAI Product, Announcements Starting today, all paying API customers have access to GPT-4. I believe strongly that there’s going to be at least one Explore Langchain's capabilities without needing an OpenAI API key, focusing on its features and functionalities. However all my agents are created using the function create_openai_tools_agent(). Langchain tries to be a horizontal layer which works with everything underneath so langchain obfuscate lot of stuff. You could also just append the sql code as a string/json to the output itself to return it in the typical agent How to make openai tools agent store tool messages I have the following code, memory does not store the intermediate steps in the tools calling, how can this be achieved? Or the funny bug in CrewAI, where you could never use OpenAI in your code, but if you have OPENAI_API_KEY set by accident, it will use it for embeddings without you knowing it until you see the money spent in your OpenAI report. Hosted on GCP Kubernetes. MessagesPlaceholder from langchain. Open-source AI Voice Agent with OpenAI Discussion How Apple Uses ML To Recognize People (Without Photos Leaving Your iPhone). In this notebook we will show how those parameters map to the LangGraph react agent executor using the create_react_agent prebuilt helper method. You can override on_tool_end() callback to send anything you want to your preferred callback, such as log files, apis, etc. Hey, I am building a simple chatbot where I use embeddings and OpenAI's completion (langchain. In the end, I built an agent without LangChain, using the OpenAI client, Python coroutines for async flow, and FastAPI for the web However, It's important to realize that Langchain's prompt engineering has been developed and tested against OpenAI's models and fine tuning / alignment data. I dm you! Has anyone created a langchain and/or autogen web scraping and crawling agent that on given a key word or series of keywords could scrape the web based on certain kpis. We are an unofficial community. So i tried to install langchain expiremental because the csv agent works for this one but for some reason after I installed the OpenAI import was greyed out again. The main reason I dropped langchain is that it's based on hopium and voodoo "prompt engineering" that kinda sometimes maybe works with OpenAI stuff. Then still return the sql output like normal. The ChatGPT Plugins cannot be used outside of ChatGPT. The LangChain framework is designed to be flexible and modular, allowing you to swap out Here’s a recent discussion (one of many) responding to a question about using LangChain in production, in the r/LocalLLama forum: Reddit - Dive into anything. This is the agents final reply: As an AI developed by OpenAI, I'm unable to directly modify files or execute code, including applying changes to API specifications or saving files. In general, as a rule, GPT 3. Here we focus on how to move from legacy LangChain agents to more flexible LangGraph agents. Has anyone successfully used LM Studio with Langchain agents? If so Hi all, I read in a thread about some frustrations in production and a few people chimed in with alternatives to LangChain that I wasn't aware of. 5), and the tool-picking part is more accurate. I have build Openai based chatbot that uses Langchain agents - wiki, dolphin, etc. utilities import BingSearchAPIWrapper from langchain import LLMMathChain from langchain. In March, we introduced the ChatGPT API, "LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning" Reddit. This helps solve the problem as tool nodes are seperated out of the model. Many times, we used langchain, set 'verbose' variable to true and directly took the resulting prompt in directly call to openai which provided better control and quality. - The documentation is subpar compared to what one can expect from a tool that can be used in production. Please share. The problem I'm facing is that I am using streaming, and in this case, we don't receive token usage in So it's very relevant even for people who never use actual OpenAI models or services. 5 Langchain Agents Video Share Add a Comment. Bite the bullet, and use OpenAI or some Exploring alternatives to OpenAI within the LangChain ecosystem opens up numerous possibilities for developers. agents import create_openai_tools_agent, Tool from langgraph. I would like to track token usage for every prompt. We are using a conversational chain in an agent with OpenAI functions as tools. schema module), and use it to create a System Message (this is what chat models use to give context to the LLM. Hello, do you know if it is possible to use langchain. Need OpenAI's new language model gpt-3. Langchain CSV agent had the worse performance of 3. I tried searching for what's the difference between chain and agent without getting a clear answer to it. agents import load_tools, AgentExecutor, initialize_agent. By leveraging both external providers and self-hosted models, one I’ve tried to use it, ended up building my own agent framework because LangChain is just crappy software imo. LangChain is an open-source framework and developer toolkit that helps developers get LLM ADMIN MOD Agent just outputs tool output without any editing . The lack of recovery on json parsing failures makes it unusable. I can see the prompt text, but not the function arguments (which are built from the tools provided to the create_openai_functions_agent factory method). Sure, you can approximate a GPT using the API. js will lag too far behind Langchain (python) and that I'll regret focusing on langchain js. This agent chain is able to pull information from Reddit and use these posts to respond to subsequent input. The actual function call requires all parameters, but I want the agent to recognize it should call foo, even if the user’s query I am looking to build a chatbot using GPT-3. OpenAI realized they didn't have a moat, so they tried to wall the garden by making the ecosystem more valuable with closed Plugins. prompts import PromptTemplate,# Load the model and tokenizer. OpenAI makes ChatGPT, GPT-4, and DALL·E 3. My problem is my agent is fine with doing this (I intentionally changed the "agent_scratchpad": lambda x: format_to_openai_function_messages(x["intermediate I tried to create a sarcastic AI chatbot that can mock the user with Ollama and Langchain, and I want to be able to change the LLM running in Ollama without changing my Langchain logic. com New models and developer products announced at DevDay Get the Reddit app Scan this without langchain , were i added a custom tool , here the process is different . LangChain seems very OpenAI-centric. I thought it would be good to have a thread detailing peoples experiences with those alternatives? I was using the LangChain python library and got slightly bamboozled by the number of abstractions. I was thinking of moving our dev servers though & will give all 3 a shot -- ollama, llama. Overall, I think your customer chatbot would benefit from augmented search instead of purely relying on a large chat context especially if you want to go off of a large customer support knowledge base (your question #2). 5 your better off using chains or other deterministic workflows. Note: you can of course use open source models without using OpenAI's API. Honestly, it's not hard to create custom classes in langchain via encapsulation and overriding whatever method or methods I need to be different for my purposes. . I've played with some external frameworks like Langchain and Llamaindex, and a bit of bare OpenAI's function calling. For example, I would say help me with Tesla information and choose 5-10 kpis from a predefined list such as valuation, assets, liability, share price , number of cars sold by model etc ? OpenAI is an AI research and deployment company. I want to be able to really understand how I can create an agent without using Langchain. But when i put these 2 chains into a langchain agent, Is there any way I can make the agent keep the answers as provided by the tools without modifying the answers by the central "router Sam Altman: ‘On a personal note, like four times now in the history of OpenAI, the most recent time was just in the last couple of OpenAI is an AI research and deployment company. 16 votes, 37 comments. true. However, we are integrating tools and we are thinking to use langchain agents for that. When I use the Langchain Agent it feels like a black box. Hey Guys, Anyone knows alternative Embedding Models with capabilities like the ada-002 model from openai? Bc the openai I have built an open-source AI agent which can handle voice calls and respond back in real-time. I would recommend using the OpenAI Functions Agent: https: The official Python community for Reddit! Stay up to date with the latest news, Without specific dates, it’s challenging to visualize the timeline you have in mind. It was time for a change "import openai" by "from langchain import PromptTemplate, OpenAI, LLMChain". Sort by: some with memory and some without, increased performance on my goal, which was more human-like responses. /r/MCAT is a place for MCAT practice, questions, discussion, advice, social networking, news, study tips and more. LangChain agents (the AgentExecutor in particular) have multiple configuration parameters. I'm specifically interested in low-memory LLMs. Does anyone know if there is a way to slow the number of times langchain agent calls OpenAI? Perhaps a parameter you can send. But I think the value of langchain is mainly on local OpenAI is an AI research and deployment company. Have people tried using other frameworks for local LLMs? Is so, what do you recommend? In particular I have trouble getting LangChain to work with quantized Vicuna (4-bit GPTQ). OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. qljbe pho qkdup vnxgq nyhjy wlmf trt gqpuq rtzy xpku