Langchain hub prompt not working. Issue: <RetrievalQA.
● Langchain hub prompt not working YAML, a human-readable data serialization standard, is used within LangChain to define prompts, making it crucial for developers to structure these prompts correctly for optimal performance. llms import ChatOpenAI template = """You are a customer service representative working for Amazon. If it's not, there might be an issue with the URL or your internet connection. llm import LLMChain from langchain. fromLLM method in the LangChainJS framework. We are working on adding support for more! If you have a specific request, please join the hub-feedback discord channel and let us know! Can I upload a prompt to the hub from a LangSmith Trace? Coming soon! Can LangChain Hub do ____? Maybe, and we'd love to hear from you! Please join the hub ReAct Agent Not Working With Huggingface Model When Using create_react_agent #18820. DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc. Please note that the _load_map_reduce_chain function does not take a prompt argument. If you try a different chain you may get it working. def load_prompt (path: Union [str, Path], encoding: Optional [str] = None)-> BasePromptTemplate: """Unified method for loading a prompt from LangChainHub or local fs. You can also create custom prompts with the PromptTemplate class by langchain. However, I'm facing an issue when testing prompts that involve OpenAI's function calls. I am trying to implement prompt caching in my rag system. If you would like to upload a prompt but don't have access to LangSmith fill out this form and we will expedite 🤖. I understand your issue with the RunnableLambda not supporting streaming in the LangChain framework. This could be a potential bug in the LangChain framework. There seems to be only one post on twitter regarding prompt caching in langchain. Who can help? You are a knowledgeable AI assistant specializing in extracting Try viewing the inputs into your prompt template using LangSmith or log statements to confirm they appear as expected. If the URL is accessible but the size of the loaded documents is still zero, it could be that the documents at the URL are not in a format that the RecursiveUrlLoader can handle. prompts import PromptTemplate bnb_config = BitsAndBytesConfig( load_in_4bit=True, # 4 bit quantization bnb_4bit_quant_type="nf4", # For I have not found any documentation for prompt caching in the langchain documentation. Based on the code you've provided, it seems like you're trying to use a custom prompt for the ConversationalRetrievalQAChain. If you are pulling a prompt from the LangChain Prompt Hub, try pulling and logging it or running it in isolation with a sample input to confirm that it is what you expect. Designed for composability and ease of integration into existing applications and services, OpaquePrompts is consumable via a simple Python library as well as through LangChain. chat import ChatPromptTemplate prompt = ChatPromptTemplate. Ensure all processing components in your chain can handle streaming for this to work effectively. So I'm trying to use Langsmith Hub for my prompts. memory import ConversationBufferMemory from langchain. Now I want to add my own system prompt, so I've forked the above, and edited the system prompt. prompts. chains import ConversationChain from langchain. Prompt hub Organize and manage prompts in LangSmith to streamline your LLM development workflow. I've also been using the Prompt Playground for testing by clicking the 'Try it' button located in the top-right corner. Create a prompt; Update a prompt; Manage prompts programmatically; LangChain Hub; Playground Quickly iterate on prompts and models in the LangSmith Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. langgraph tool calls not working #720. However, it seems like the truncate_word function is not correctly truncating the SQL command output to the specified max_string_length. The ConversationBufferMemory might not be returning the expected response due to a variety of reasons. The reason is how the prompts are treated internally by Langchain. Defaults to None. I searched the LangChain documentation with the integrated search. dcaputo-harmoni opened this issue Mar 8, 2024 · 2 comments Closed initialize_agent from langchain. LangChain Hub supports prompt versioning, allowing users to access previous versions of prompts. agents import initialize_agent, AgentType from langchain. Designing effective LangChain YAML prompts requires a deep understanding of both the LangChain framework and the specific language model you are working with. I've tested using: My script work fine. Don't worry, I'm here to guide you every step of the way. Hide child comments as well If the status code is 200, it means the URL is accessible. To start you should ALWAYS look at the tables in the database to see what you can query. You are having conversations with customers. Closed 5 tasks done. I used the GitHub search to find a similar question and didn't find it. prompts import PromptTemplate, MessagesPlaceholder from langchain. Hey @Rakin061, great to see you back!Hope everything's been going well on your end. com/docs/modules/agents/quick_start. prompts import PromptTemplate from langchain. What's cooking on your end? Based on the information you've provided and the context I found, it seems like the partial_variables is not working with I've been working with LangChain Hub and am familiar with pushing and pulling custom prompts. Args: path: Path to the prompt file. The official documentation highlights the importance of tailoring prompts to the specific model type you are working with, as different models have varying optimal prompting strategies. StructuredTool, tool from langchain import hub from langchain_core. Verify that tune_prompt, full_prompt, and metadata_prompt are set up properly. Get an API key for your Personal organization if you have not yet. (Soon, we'll be adding other artifacts like chains and agents). What is LangChain Hub? 📄️ Developer Setup. Notes: OP questions edited lightly for clarity. lastrei opened this issue Jun 20, 2024 · 13 comments Closed response_metadata={' token_usage ': {' completion_tokens ': 103 Creating effective prompts for LangChain Hub involves understanding the nuances of different models and their input and output schemas. This newly launched LangChain Hub simplifies prompt from langchain. from_chain_type with Issue you'd like to raise. 😊. Check the Prompt Template: Ensure your prompt templates are correctly defined with placeholders for inputs. Still learning LangChain here myself, but I will share the answers I've come up with in my own search. Instead, it uses the default implementation of the stream method provided by the Runnable base class, which calls the invoke method. from_template ("tell . It's possible that Structured Custom Tools not working with the react agent. """ if isinstance (path, str) and path Prompt Hub. Returns: A PromptTemplate object. encoding: Encoding of the file. Here is the code : def process_user_input(user_input): create_db() in Today, we're excited to launch LangChain Hub–a home for uploading, browsing, pulling, and managing your prompts. Hey there @hasansustcse13!Good to see you back around these parts. 🤖. Raises: RuntimeError: If the path is a Lang Chain Hub path. For more detailed guidance, consider checking LangChain's documentation or source code, especially regarding OpaquePrompts is a service that enables applications to leverage the power of language models without compromising user privacy. 💡Explore the Hub here LangChain Hub is built into LangSmith (more on that below) so there are 2 ways to start exploring LangChain MultiRouteChain not working as expected #9600. Instead, it takes question_prompt, combine_prompt, and collapse_prompt arguments. 📄️ Quick Start. RamishSiddiqui opened this issue Aug 22, 2023 · 5 comments Labels. These include support for For debugging your prompt templates in agent_executor, you can follow these steps:. This template is designed to identify assumptions in a given statement and suggest Recently, the LangChain Team launched the LangChain Hub, a platform that enables us to upload, browse, retrieve, and manage our prompts. Hello @aviramroi! 🙋♂️ I'm Dosu, a friendly bot here to assist you while our human maintainers are away. _models import ChatOpenAI from langchain. This guide will continue from the hub quickstart, using the Python or TypeScript SDK to interact with the hub instead of the Playground UI. Checked other resources I added a very descriptive title to this question. This is why the Hub currently only supports LangChain prompt objects. langchain. I am sure that this is a b Step-by-step guides that cover key tasks and operations for doing prompt engineering LangSmith. Perhaps more importantly, OpaquePrompts leverages the power 🤖. Try viewing the inputs into your prompt template using LangSmith or log statements to confirm they appear as expected. prompts import PromptTemplate from langchain. Please note that this is just a potential solution based on the information provided and the current implementation of the YoutubeLoader class in LangChain. I would recommend creating an issue in the LangChain repository detailing this problem so that the maintainers can investigate and potentially fix this 🤖. You can fork prompts to your personal organization, view the prompt's details, and run Based on the error message you provided, it seems like the OutputParserException is being raised because the output from your custom LLM is not being correctly parsed by the Step-by-step guides that cover key tasks and operations for doing prompt engineering LangSmith. com/docs/integrations/tools/tavily_search#usage) in Langchain, you will Head directly to https://smith. If you are pulling a prompt from the LangChain Prompt Hub, try The issue you're encountering with the duplicated prompt causing a context length error is likely due to the additional "ChatOpenAI" section and the "scratchpad" input in your prompt. Issue: <RetrievalQA. Do NOT skip this step. ) to the database. prompts import ChatPromptTemplate,MessagesPlaceholder from langchain. You can search for prompts by name, handle, use cases, descriptions, or models. llm_router import LLMRouterChain This setup uses Quart's Response and stream_with_context to yield data chunks as they're generated by the model, allowing for real-time streaming of chat responses. Specifically, the QA generator prompt. This is due to the RunnableLambda class not overriding the stream method from the Runnable base class. If someone wants me to deepen the explanation, please let me know. . If you want to customize the prompts used in the 🤖. chains. agents import create_react from langchain_google_genai import ChatGoogleGenerativeAI from langchain_core. Discover, share, and version control prompts in the Prompt Hub. Create a prompt; Update a When trying to run your first agent (https://js. I followed the process but faced Here you'll find all of the publicly listed prompts in the LangChain Hub. chains import create_history_aware_retriever, create_retrieval_chain from I searched the LangGraph/LangChain documentation with the integrated search. The hub will not work with your non-personal organization's api key! from langchain import hub from langchain. Invoke the Agent and Observe Outputs: Use the agent_executor to run a test input This change should ensure that the load method only attempts to translate an English transcript if the specified language is not English, which might resolve the issue you're experiencing. output_parsers import StrOutputParser from langchain_core. I tried to work on SQL cutsom prompt, but it didn't work and is still giving the wrong sql queries . Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. com/hub to start exploring. router. However, you're encountering an issue where the chain displays a default message instead of the custom prompt you've provided. I'm here to help you squash bugs, answer your questions, and get you up to speed on contributing to LangChain. pull(). Following this, the code pulls the “Assumption Checker” prompt template from LangChain Hub using hub. LangChain Hub is continuously evolving, and the development team is working on introducing several new features. These I was trying to follow the quickstart tutorial for agents for Langchain: https://js. One possibility could be that the conversation history is exceeding the maximum token limit, which is 12000 I hope this helps! If you have more information or if there's a specific method where the "prompt" parameter is used that you'd like me to look into, please let me know! Sources. Each time a prompt is committed, a new version is created, providing a clear history of changes. Based on the information you've provided, it seems like you're trying to combine the RAG model and Function Calling feature of OpenAI in LangChain for a chatbot that can handle follow-up questions and manage multiple arguments in the {context} part of the prompt without Checked other resources I added a very descriptive title to this issue. yagywmeejxpmunjuotnnorluhdwkiqtfdlbdrkhgojpyxtip