Langchain sql agent github
Langchain sql agent github. from_uri (). History. This is demonstrated in the test_agent_with_callbacks function in the test_agent_async. In your code, you're using the astream method of the AgentExecutor class, which is an asynchronous method. agent_toolkits import SQLDatabaseToolkit: from langchain. sql_database import SQLDatabase: from langchain. llm ( BaseLanguageModel) – Language model to use for the agent. I would like to use SQL Agent to query database. Lastly, we add the FewShotPromptTemplate to the agent_executor. Just a note on your code - the second snippet will naturally be faster as your SELECT query is only returning 10 rows - on the other hand the first snippet is importing a table. 5-turbo model. llms Dec 6, 2023 · I'm using langchain sql database agent and python REPL tool. The issue has been resolved by me, who provided a detailed response explaining the likely cause of the errors and suggested alternative packages to use. If you want to add this to an existing project, you can just run: langchain app add sql-ollama. What I would like to do is to be SQL. from_agent_and_tools() doesn't use kwargs, but rather agent_executor_kwargs. Integrate with hundreds of third-party providers. Jul 13, 2023 · Is there any approach other than tool description by which we can make the agent use the correct tool. You switched accounts on another tab or window. Enterprise data is often stored in SQL databases. 🤖. Jun 23, 2023 · edited. prompts Apr 13, 2024 · I think langchain team should accept the PR raised by you because, though, the function calling is being done, but for some reason gpt-4-turbo ignores it for responding in particular way, and the ellipsis is not required in this case because its just an empty string, so as you provided a default value, its a quick fix, because that solves the issue. gguf". agents. orm import sessionmaker from pandas import DataFrame # Assuming you have a dataframe to insert from libs. This will allow the agent_executor to use the FewShotPromptTemplate when generating responses. chat_models import ChatOpenAI llm = ChatOpenAI(model_name="gpt-3. Based on your requirements, it seems like you want to modify the create_sql_agent function to return only the SQL query to reduce the latency caused by high completion tokens when generating HTML tables and summaries with LLM (GPT-4). # Create a language model llm = ChatOpenAI ( model="gpt-3. Cannot retrieve latest commit at this time. sql_database import SQLDatabase # Step 1: Create an SQLDatabase instance for a SQLite Nov 25, 2023 · Langchain SQL Agent with local RAG. 22 lines (17 loc) · 749 Bytes. While we wait for human maintainers, I'll do my best to help you with your issue. /openhermes-2. While the LangChain framework does not currently provide built-in functionality for integrating GPTCache with SQL Agent, it The docs describe how to create an SQL agent using OpenAI as an example but implying that the approach is generic. dosubot bot added Ɑ: agent 🔌: postgres 🤖:improvement labels last month. agents import create_spark_sql_agent from langchain_community. agent_types import AgentType from langchain. Today, DOCKER_BUILDKIT=1 docker build --target=runtime . Dec 8, 2023 · When utilizing custom_table_info in the sqldatabase instance while employing the create_sql_agent function, it appears that there is an issue where it disregards the sql_db_schema. May 14, 2023 · You would do something like this: from langchain. Note that you'll need to ensure this method is called appropriately when the agent finishes its output, which might require additional integration depending on how the agent signals completion. ''' FORMAT_INSTRUCTIONS = """Please use the following LangChain comes with a number of built-in chains and agents that are compatible with any SQL dialect supported by SQLAlchemy (e. import { OpenAI } from "langchain/llms/openai"; import { SqlDatabase } from "langchain/sql_db"; import { createSqlAgent, SqlToolkit } from "langchain/agents"; Nov 21, 2023 · One thing you could try is to debug the agent execution process. When using database agent this is how I am initiating things: `db = SQLDatabase. SQLDatabaseToolkit¶ class langchain_community. This README provides a step-by-step guide on how to set up and use the SQL Database Agent. I am able to use create_sql_query_chain just fine against either an OpenAI LLM or Jan 26, 2024 · You should initialize the handler as an instance of SQLHandler before passing it to the invoke method: handler = SQLHandler () response = agent_executor. Please help the community. Aug 26, 2023 · Issue with current documentation: from langchain. sql into the created databse in step 3. The agent takes a dbengine object which is tied to one connection alone. Jul 11, 2023 · If you alter the structure of the prompt, the language model might struggle to generate the correct output, and the SQLDatabaseChain might have difficulty parsing the output. Configure . n_gpu_layers = 1 # Change this value based on your model and your GPU VRAM pool. Mar 3, 2024 · I need to query the database to get the total sales per country. Thank you for bringing this to our attention. These systems will allow us to ask a question about the data in a SQL database and get back a natural language answer. py and base. The issue is langchain's sql database toolkit somehow is unable to query the clickhouse database, it works fine for the chinook db sqlite file. It's defined in the class GPTCache which inherits from the BaseCache class. _DEFAULT_TEMPLATE = """Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. The create_sql Tutorial to LangChain SQL Agent. I hope our previous interaction was helpful! Let's dive into your new challenge. ArtistId WHERE Artist. Jun 21, 2023 · danielvi1787 commented on May 30, 2023. The function takes several parameters including tools, llm, agent, callback_manager, agent_path, agent_kwargs, tags, and **kwargs. It seems like the create_sql_agent function in LangChain is indeed ignoring the custom prefix and suffix when the agent_type is set to "zero-shot-react-description". You have access to a Microsoft SQL Server database. langchain_community. LangChain is a framework for developing applications powered by large language models (LLMs). 7343056 Nov 14, 2023 · from langchain. Based on the context you've provided, it seems you want to use a GPT4 model to query SQL tables/views and use the returned data for answering while maintaining the chat in memory. AlbumId JOIN Artist ON Album. @hwchase17 Thanks. This works because in this file, it's apparent that AgentExecutor. All it needs a SQL-based schema, and it can perform any read and write action to that schema. Apr 29, 2023 · From what I understand, you were having trouble using the SQL Database Agent with the OpenAI gpt-3. prompt import PromptTemplate. agents import create_sql_agent from langchain. environ ["OPENAI_API_KEY"] = "sk-xxxxxxxxxxxxxx" db = SQLDatabase. Logs for Apr 6, 2024 · create_sql_agent with mistral instruct model Checked other resources I added a very descriptive title to this question. toolkit ( Optional[SQLDatabaseToolkit]) – SQLDatabaseToolkit for the However, when working with the SQL agent on Oracle Database, I provide the UserID, Password, Server name, Host, and Port in the connection string (provided code in example). Apr 5, 2023 · Hi, @praysml!I'm Dosu, and I'm here to help the LangChain team manage our backlog. spark_sql import SparkSQL from langchain_openai import ChatOpenAI Hi, I am in the process of developing an agent and a toolkit to query mongodb databases, and to do this I simulated SQL Database Agent code with implementations for mongodb, I created this function to create the agent: def create_mongodb Season the chicken with salt and pepper to taste. Currently the flat query_checker_prompt would send the resulting sql back to llm to verify it's correct. This method takes an early_stopping_method parameter. openai import OpenAI Apr 27, 2023 · It looks like the main issue is with the fact that table_1 is taking a while to import or there is performance issue with the SQL Database Agent itself. py files, and received assistance from me, who provided potential solutions involving modifying the create_sql_agent function and passing inputs as a dictionary You signed in with another tab or window. For these applications, LangChain simplifies the entire application lifecycle: Open-source libraries: Build your applications using LangChain's modular building blocks and components. Let's get started. Add 8 ounces of fresh spinach and cook until wilted, about 3 minutes. Here's an example code snippet demonstrating these steps: from sqlalchemy import create_engine from sqlalchemy. py file to ensure that the SQL agent uses the correct table names when generating SQL queries. This process is computationally intensive and depends on the complexity of the underlying embedding model and the hardware Jul 18, 2023 · This makes sure that the agent does not randomly rewrite the query but first again looks at the schema of the database using the info_sql_data_baase_tool and then builds on the top of it to rewrite the query, This helps avoid the loop that you were mentioning. Originally posted by @axtsoi in #18761 (comment) 👍 1. 5-turbo") # Set up the SQL database connection Jul 26, 2023 · Based on my understanding, you are experiencing an OutputParserException when using a SQL Agent connected to BigQuery. llms import OpenAI from langchain. I used the GitHub search to find a similar question and didn't find it. The connection is established successfully, but the SQL agent encounters an issue in recognizing the tables. One of these columns is a timestamp column with the value 672457193. Invoking: `sql_db_schema` with `Track`. SQLDatabaseToolkit [source] ¶ Bases: BaseToolkit. For example the query will use a limit clause instead of top. Run the docker container using docker-compose (Recommended) Edit the Command in docker-compose with target streamlit app. Toolkit for interacting with SQL databases. Interested in your specific use case. From what I understand, you were trying to add memory to an agent using the create_csv_agent or create_sql_agent methods, but it seems that these methods do not currently support memory. Save the context in memory with user input query and result from chain. Additionally, a group of University of Toronto students has expressed interest in working on the issue for an assignment and plans to make a pull request. These are compatible with any SQL dialect supported by SQLAlchemy (e. This could be the cause of the issue. llms. The llm agent is able to get the data from the database successfully, however when i request the agent to plot the data its failing with In LangChain, there is a method called return_stopped_response that is used when the agent has been stopped due to max iterations. utilities import SQLDatabase from langchain. base import SQLDatabaseChain from langchain. agent_toolkits import SQLDatabaseToolkit from langchain. This is due to the hardcoded values in the from langchain. You signed out in another tab or window. To create a new LangChain project and install this as the only package, you can do: langchain app new my-app --package sql-ollama. from_uri (sql_uri) model_path = ". 5-turbo" to the OpenAI attributes, but it didn't work for you. They enable use cases such as: Generating queries that will be run based on natural language questions, Creating chatbots that can answer questions based on Feb 22, 2024 · Guys, the key to adapt it its to create the full prompt from scratch, following this format: This is a printscreen from the original source of the langchain "create_sql_agent" method, it creates the prompt if no prompt is provided, but if it is, the prompt must be complete and in proper form, different from the "openai_tools" method that gets your prompt and insert it in the ReAct prompt somehow. Example Code. py file: from sql_ollama import chain as sql_ollama_chain add_routes ( app Uses LangChain as a wrapper for interacting with Azure OpenAI , vector stores, constructing prompts and creating agents. agents import create_sql_agent: from langchain. Create a new model by parsing and validating input data from keyword arguments. The function create_sql_agent you've used in your code is designed to construct a SQL agent from a language model and a toolkit or database. Action Input: SELECT country, SUM(sales) FROM orders GROUP BY country ORDER BY SUM(sales) DESC; sql\_db\_query is not a valid tool, try one of [sql_db_query, sql_db_schema, sql_db_list Langchain based SQL Agent. import psycopg2 from langchain_experimental. base. agents import AgentExecutor, create_sql_agent. I downloaded the chinook database in MySQL , I made the connection successfully and got good answers from this database using the SQLDataBase agent tutorial. from_uri ("mysql://user:password@localhost:db_port/db_name Mar 9, 2012 · It looks like you encountered a "ModuleNotFoundError" for 'MySQLdb' and 'ConfigParser' while trying to run the SQL Database Agent example in Langchain. MIT Mar 10, 2011 · Expected behavior. It is particularly focused on financial data analysis, offering insights into how natural language processing (NLP) can be utilized to simplify data querying processes. You mentioned that you tried different approaches, including adding model_name="gpt-3. , MySQL, PostgreSQL, Oracle SQL, Databricks, SQLite). However, the create_sql_agent function doesn't directly support the integration of FewShotPromptTemplate as it's not designed to work with prompts in this way. Zep: Zep: A long-term memory store for LLM / Chatbot applications ; Langchain Decorators: a layer on the top of LangChain that provides syntactic sugar 🍭 for writing custom langchain prompts and chains Feb 20, 2024 · To use Google BigQuery, you would need to create an instance of SQLDatabase that connects to your Google BigQuery database. ArtistId = Artist. py", line 26, in agent_executor = create_sql_agent( AttributeError: type object 'QueryCheckerTool' has no attribute 'llm' Mar 18, 2024 · I'm using Langchain SQL-agent to connect a LLM to a existing database. I wanted to let you know that we are marking this issue as stale. py file. LangChain offers SQL Chains and Agents to build and run SQL queries based on natural language prompts. . Apr 23, 2023 · From what I understand, you are seeking guidance on connecting a LangChain agent to a MongoDB database and have received several comments from other users offering potential solutions. Install and launch MySQL database server in your local env. Create the prompt value with as usual, with required variables along with history = memory. Action: sql\_db\_query. Construct a SQL agent from an LLM and toolkit or database. Jun 21, 2023 · SELECT SUM(Milliseconds) FROM Track JOIN Album ON Track. agent_toolkits. Based on the information you've provided and the context from the LangChain repository, the 'suffix' parameter in the create_sql_agent function should be an optional string (Optional[str]). Based on the LangChain framework, it is indeed correct to assign a custom callback handler to an Agent Executor object after its initialization. To use Google BigQuery, you would need to create an instance of SQLDatabase that To add memory to the SQL agent in LangChain, you can use the save_context method of the ConversationBufferMemory class. In a large skillet, melt 2 tablespoons of unsalted butter over medium heat. Here's how you can run the chain without manually formatting the prompt: sql_prompt = PromptTemplate ( input_variables= [ "input", "table_info", "dialect" ], template=sql Based on the information you've provided, it seems like you're trying to integrate FewShotPromptTemplate into the create_sql_agent function in the LangChain framework. This method allows you to save the context of a conversation, which can be used to respond to queries, retain history, and remember context for subsequent queries. Run the docker container directly; docker run -d --name langchain-streamlit-agent -p 8051:8051 langchain-streamlit-agent:latest . But also I would like to use CromaDB to save embeddings with local knowledge of the database structure, columns content, So this means thy I would like to create chain that would extend LLM with this local knowledge, and then pass this as LLM fro Hey @Abe410, great to see you back here diving into some intricate LangChain work! 👾. Sep 1, 2023 · from langchain. And add the following code to your server. Sep 12, 2023 · Initializing the LangChain Agent. Hi, I was struggling with this too, but I could resolve it, on Azure AI Studio you can create a Deployment with a name different to the model name, if you do this, the code line llm = AzureOpenAI (deployment_name="deployment name", model_name="model name") fails with the Resource not found error, if you Apr 21, 2023 · File "C:\Users\Stef\Documents\ChatGPT-Tabular-Data\mysqlUI - Agent. In this example, we first create an SQL database with a ‘countries’ table, and Sep 5, 2023 · In the LangChain codebase, we have two types of agents you mentioned: the Pandas Dataframe agent and the CSV agent. openai import OpenAI from l Nov 24, 2023 · I am using local LLM with langchain: openhermes-2. I am sure that this is a bug in LangChain rather than my code. GPTCache: This module provides methods for initializing the GPTCache, looking up data from the cache, updating the cache, and clearing the cache. agents import create_sql_agent, initialize_agent, create_spark_sql_agent from langchain. sql import SQLDatabaseChain from langchain. Hello @NISHANTSHRIVASTAV!Good to see you again. sql. py. Reload to refresh your session. agent is defined as follows: `toolkit = SQLDatabaseToolkit(db=db, llm=llm) toolkit. If the table is slightly bigger with complex question, It throws InvalidRequestError: This model's maximum context length is 4097 tokens, however you requested 13719 tokens (13463 in your prompt; 256 for the completion). You signed in with another tab or window. chains import LLMChain from langchain. agent_types import AgentType # Set up the OpenAI LLM: llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY, model_name = "gpt-3. Hello @rajesh-b-rao!I'm Dosu, a bot here to assist you. Topics """LangChain SQL Agent. I am working on creating an agent which based on input query will decide whether to use doc retrieval or sql tool. . gguf. This instance would then be passed as the db argument to the create_sql_agent function. openai import OpenAI os. The main difference between the two is that our agent can query the database in a loop as many time as it needs to answer the May 2, 2023 · Using create_sql_agent(), specify agent_executor_kwargs like so: agent_executor_kwargs={"return_intermediate_steps": True}. mrkl import prompt as react_prompt line of code. Identify which tables can be used to answer the user's question and write and execute a SQL query accordingly. Aug 28, 2023 · As for your question, yes, the LangChain framework does support connections to Microsoft SQL Server databases. LLMs make it possible to interact with SQL databases using natural langugae. agents import create_sql_agent from langchain. n_batch = 512 # Should be between 1 Dec 6, 2023 · 🤖. agent_toolkits import SQLDatabaseToolkit, SparkSQLToolkit from langchain. load_memory_variable ( {}) ['history'] Pass prompt value to SQLDatabaseChain, get the results. invoke ({ "input": prompt }, { "callbacks": [ handler ]})[ 'output'] This should allow the on_agent_action method in your SQLHandler class to capture the SQL query when the sql_db_query tool The Medium_LangChain_Demo. create_sql_agent. agent_toolkits import create_sql_agent from langchain_openai import ChatOpenAI from langchain import OpenAI, SQLDatabase import cx_Oracle import openai from langchain_openai import OpenAIEmbeddings from langchain. However, you're not awaiting the astream method in your generate_response function. This repo contains code snippets and datasets used in my Medium article "A Beginners Guide to LLM Agents and Toolkits". The idea being that this function is passed the generated sql and could sanity check it before it is executed. prompts. agents. Multi-Lingual (ingests, indexes and understand any language) Multi-Index -> multiple search indexes; Tabular Data Q&A with CSV files and SQL flavor Databases langchain_sql_agent. get_tools() PREFIX = '''You are a SQL expert. In the below example, when using mssql data source type. llms. from langchain. It seems Sync documents from SaaS tools to a SQL or vector database, where they can be easily queried by AI applications like ChatGPT. Mar 22, 2024 · Provide a component that can extract and generate sql from dialogue questions and answers like langchain sql agent, obtain data in relational databases, and use LLM to perform statistical analysis on the data. However, when I try to do sql query using the OpenAI function agent it fails. Jul 1, 2023 · +1 , NoSQL db queries have become more and more enterprise use cases, and I am very much looking forward to the launch of mongoDB Agent in langchain 👍 6 gururise, DevinRC, linznin, RichardHruby, Alexmhack, and userr2232 reacted with thumbs up emoji This could be due to the FastAPI endpoint returning before the async operation has finished. The resulting queries are not valid mssql queries. agent_toolkits import SQLDatabaseToolkit from langchain. I provided a response suggesting a modification to the get_schema function in the chain. sql_database import SQLDatabase from langchain. Note: Please use your OpenAI key for this, which should be kept private. Here is how you can use this method: 🦜🔗 Build context-aware reasoning applications. Apr 11, 2023 · import os from langchain. Contribute to langchain-ai/langchain development by creating an account on GitHub. llms import HuggingFacePipeline Jul 19, 2023 · I am following the tutorial of OpenAI function Agent . 5-turbo", temperature=0 ) Jul 21, 2023 · Based on my understanding, you were encountering errors when trying to implement memory with the SQL agent toolkit in the LangChain framework. , MySQL, PostgreSQL, Oracle SQL, Databricks The SQL Database Agent is a tool designed to interact with SQL databases using natural language queries. AlbumId = Album. You can do this by adding print statements or logging in the agent's code to see exactly where it's getting stuck. This issue occurs specifically when the option view_support=True is used in SQLDatabase. example. /. Code. This database has multiple tables, columns and rows. agent_toolkits import SQLDatabaseToolkit. The SQLDatabase toolkit should be able to query the clickhouse database as I have installed and provided the right dialect and connecting directly via sqlalchemy works fine. I got the following error: Nov 9, 2023 · Regarding the initialize_agent function in the LangChain framework, it is used to load an agent executor given a set of tools and a language model. However, I wasn't able to find any information on whether the create_sql_agent function in LangChain supports the addition of a FewShotPromptTemplate directly. 5-turbo") toolkit = SQLDatabaseToolkit(db=db,llm=llm) agent_executor = create_sql_agent( llm=llm, toolkit=toolkit, verbose=True ) and it works for me. You made changes to the Prompt. If the early_stopping_method is set to "force", the agent will stop immediately and return a constant string. Import students. 4 days ago · langchain_community. Q8_0. sql_database import SQLDatabase from langchain_experimental. sql_database import SQLDatabase from langchain_community. It's possible that this GitHub community articles Repositories. llm) agent_executor = create_sql_agent(prefix=MSSQL_AGENT_PREFIX, Create a memory object. May 7, 2023 · If I ask straightforward question on a tiny table that has only 5 records, Then the agent is running well. After that, I can identify the country whose customers spent the most. I searched the LangChain documentation with the integrated search. Here's the code to initialize the LangChain Agent and connect it to your SQL database. Create a new database students. Maybe the right solution is working multiple agents in parallel with the same prompt across different data s Based on the code you've provided and the context given, the slow response times you're experiencing when using the create_sql_agent function could be due to the process of embedding the query into a vector representation. In this guide we'll go over the basic ways to create a Q&A chain and agent over a SQL database. 5-mistral-7b. Apr 3, 2023 · @konrad-cadlabs: Not with the current implementation. Both the indexed documents and tables in DB have data of similar context, Hence the tool description is not that helpful in this I agreed with most users - token counting is one of the fundamental and crucial features by LangChain but this doesn't seem to be treated as a high priority. This could help you identify if the issue is with the Claude v2 model, the AWS Bedrock integration, or the SQL execution process. toolkit = SQLDatabaseToolkit(db=db, llm=self. It seems to be related to parsing the output of the agent. Add 1 small diced onion and 2 minced garlic cloves, and cook until softened, about 3-4 minutes. It works for me too Oct 27, 2023 · I'm here to assist you with your question about integrating SQL data retrieval with the ConversationalChatAgent in the LangChain framework. Mar 27, 2024 · A new method on_llm_endis introduced to handle the end of the agent's output, where it streams the content of the buffer and then clears it. -t langchain-streamlit-agent:latest. By leveraging the power of LangChain, SQL Agents, and OpenAI’s Large Language Models (LLMs) like ChatGPT, we have created an application that enables users to query databases using NLP. Another user suggested editing the prompt of the SQL agent, which seemed to work Oct 27, 2023 · From what I understand, you raised an issue regarding the SQL agent not retrieving the database schema and attempting to query non-existent table names. agent_toolkits import SparkSQLToolkit from langchain_community. sql_database import SQLDatabase from langchain. Blame. #13846. Currently, it only utilizes either the custom_table_info or the sql_db_schema. Jun 21, 2023 · from langchain. ¶. Describe the solution you'd like May 17, 2023 · hi, I was looking to add an additional function that could be passed to the SQLDatabaseChain. Name != 'AC/DC'; Instead it tries the following (abbreviated output): Invoking: `sql_db_list_tables` with `{}`. Jun 8, 2023 · > Entering new AgentExecutor chain Action: list_tables_sql_db Action Input: Observation: users, organizations, plans, workspace_members, curated_topic_details, subscription_modifiers, workspace_member_roles, receipts, workspaces, domain_information, alembic_version, blog_post, subscriptions Thought:I need to check the schema of the blog_post table to find the relevant columns for social . ipynb notebook is designed for AI architects and ML engineers interested in exploring the capabilities of LangChain in conjunction with SQL databases. This is because LangChain uses SQLAlchemy as its database toolkit, which supports a variety of SQL databases, including Microsoft SQL Server. community. env. 2 days ago · langchain_community. g. Used Libraries and Tools. If agent_type is “tool-calling” then llm is expected to support tool calling. The function returns an agent executor. Python: Sqlite3; LangChain; License. app. toolkit. Sep 26, 2023 · You signed in with another tab or window. docker Yes, it is indeed possible to create an SQL agent in the latest version of LangChain to query tables on Google BigQuery. Dec 4, 2023 · In my previous blog, we explored the Langchain tool and its remarkable create_sql_agent function, which enables the creation of a powerful SQL Agent with just a few lines of code. Contribute to snchelluri/langchain-agent-sql development by creating an account on GitHub. May 22, 2023 · Using this one: from langchain. The Pandas Dataframe agent is designed to facilitate the interaction between language models and pandas dataframes. chains import LLMChain. Feb 22, 2024 · from langchain. However, there is no SQL Agent in the current version of LangChain. How to use. utilities. env with your valid OpenAI API key in your local env following the example . It provides a set of functions to generate This example shows how to load and use an agent with a SQL toolkit. dx lj yl ju ee up ma yt av rd