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update sql, neo4j arango examples
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‎examples/data-qa/sql-chat/sql_chat.py‎

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@@ -191,6 +191,7 @@ def main(
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show_stats=False,
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context_descriptions=context_descriptions, # Add context descriptions to the config
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use_schema_tools=schema_tools,
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addressing_prefix=SEND_TO,
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llm=OpenAIGPTConfig(
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chat_model=OpenAIChatModel.GPT4,
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),

‎examples/kg-chat/chat-arangodb.py‎

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"""
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Single-agent to use to chat with an existing ArangoDB knowledge-graph (KG) on cloud,
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or locally.
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If you have an existing ArangoDB instance, you can
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chat with it by specifying its URL, username, password, and database name in the dialog.
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Run like this (--model is optional, defaults to GPT4o):
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python3 examples/kg-chat/chat-arangodb.py --model litellm/claude-3-5-sonnet-20241022
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If using litellm, remember to install langroid with the litellm extra, e.g.
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pip install "langroid[litellm]"
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See these guides for info on setting up langroid to use Open/Local LLMs
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and other non-OpenAI LLMs:
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- https://langroid.github.io/langroid/tutorials/local-llm-setup/
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- https://langroid.github.io/langroid/tutorials/non-openai-llms/
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"""
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import typer
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import os
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from typing import Optional
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from dotenv import load_dotenv
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from rich import print
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from rich.console import Console
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from rich.prompt import Prompt
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import langroid.language_models as lm
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from langroid import TaskConfig
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from langroid.agent.special.arangodb.arangodb_agent import (
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ArangoChatAgentConfig,
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ArangoChatAgent,
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ArangoSettings,
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)
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from langroid.utils.constants import SEND_TO
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from langroid.agent.chat_document import ChatDocument
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from langroid.agent.task import Task
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from langroid.utils.configuration import Settings, set_global
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from adb_cloud_connector import get_temp_credentials
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from arango.client import ArangoClient
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from arango_datasets import Datasets
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import logging
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logging.basicConfig(
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level=logging.INFO,
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
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force=True, # Add this
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)
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root_logger = logging.getLogger()
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root_logger.setLevel(logging.INFO) # Add this
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logger = logging.getLogger(__name__)
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console = Console()
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app = typer.Typer()
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class MyArangoChatAgent(ArangoChatAgent):
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def user_response(
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self,
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msg: Optional[str | ChatDocument] = None,
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) -> Optional[ChatDocument]:
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response = super().user_response(msg)
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if response.content == "r":
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self.clear_history(1) # remove all msgs after system msg
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n_msgs = len(self.message_history)
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assert n_msgs == 1
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logger.warning("Reset Agent history, only system msg remains")
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# prompt user again
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return super().user_response(msg)
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return response
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@app.command()
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def main(
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debug: bool = typer.Option(False, "--debug", "-d", help="debug mode"),
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model: str = typer.Option("", "--model", "-m", help="model name"),
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no_stream: bool = typer.Option(False, "--nostream", "-ns", help="no streaming"),
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nocache: bool = typer.Option(False, "--nocache", "-nc", help="don't use cache"),
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) -> None:
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set_global(
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Settings(
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debug=debug,
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cache=nocache,
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stream=not no_stream,
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)
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)
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print(
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"""
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[blue]Welcome to ArangoDB Knowledge Graph RAG chatbot!
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Enter x or q to quit at any point.
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"""
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)
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load_dotenv()
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url = Prompt.ask(
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"ArangoDB URL (enter 'got' for Game of Thrones dataset) ",
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default="https://db.catalog.igvf.org",
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)
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username = Prompt.ask(
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"ArangoDB username ",
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default="guest",
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)
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db = Prompt.ask(
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"ArangoDB database ",
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default="igvf",
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)
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pw = Prompt.ask(
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"ArangoDB password ",
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default="",
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)
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pw = pw or os.getenv("ARANGODB_PASSWORD")
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if url == "got":
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print(
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"""
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No URL supplied, using Game of Thrones dataset from cloud, see here:
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https://docs.arangodb.com/3.11/components/tools/arango-datasets/
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"""
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)
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connection = get_temp_credentials(tutorialName="langroid")
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client = ArangoClient(hosts=connection["url"])
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db = client.db(
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connection["dbName"],
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connection["username"],
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connection["password"],
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verify=True,
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)
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datasets = Datasets(db)
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ArangoChatAgent.cleanup_graph_db(db)
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assert len(datasets.list_datasets()) > 0, "No datasets found"
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DATASET = "GAME_OF_THRONES" # a small dataset
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info = datasets.dataset_info(DATASET)
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assert info["label"] == DATASET
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datasets.load(DATASET, batch_size=100, preserve_existing=False)
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arango_settings = ArangoSettings(db=db, client=client)
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else:
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arango_settings = ArangoSettings(
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url=url,
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username=username,
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database=db,
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password=pw,
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)
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arango_agent = MyArangoChatAgent(
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ArangoChatAgentConfig(
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name="Arango",
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chat_mode=True,
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arango_settings=arango_settings,
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prepopulate_schema=True,
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use_functions_api=False,
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use_tools=True,
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database_created=True,
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llm=lm.OpenAIGPTConfig(
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chat_model=model or lm.OpenAIChatModel.GPT4o,
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chat_context_length=128_000,
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),
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human_prompt=(
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"Human (respond, or x/q to quit, r to reset history, "
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"or hit enter to continue)"
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),
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)
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)
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task_config = TaskConfig(addressing_prefix=SEND_TO)
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arango_task = Task(
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arango_agent,
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# user not awaited, UNLESS LLM explicitly addresses user via recipient_tool
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interactive=False,
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config=task_config,
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)
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arango_task.run()
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# The above runs the app in a continuous chat.
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# Alternatively, to set up a task to answer a single query and quit when done:
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# set up arango_agent above with chat_mode=False, set up arango_task as above,
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# then run the task with a single query, e.g.:
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# result = arango_task.run("What is the location of the gene BRCA1?")
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# You can have this in a loop with the user, like so:
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# while True:
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# query = Prompt.ask("Enter your query")
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# if query in ["x", "q"]:
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# break
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# result = arango_task.run(query)
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# print(result.content)
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if __name__ == "__main__":
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app()

‎examples/kg-chat/chat-neo4j.py‎

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If you have an existing Neo4j db on Aura (or possibly elsewhere, e.g. locally), you can
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chat with it by specifying its URI, username, password, and database name in the dialog.
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7-
If you don't have an existing Neo4j db, and want to try this script, you can populate
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You can chose the defaults in the dialog, in which case it will use the
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freely available Movies database.
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Or, you can populate
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an empty Neo4j db with the cypher queries in the file `movies.cypher` in this folder.
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See info on getting setup with Neo4j here:
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uri = Prompt.ask(
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"Neo4j URI ",
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default="neo4j+s://8d105d28.databases.neo4j.io",
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default="neo4j+s://demo.neo4jlabs.com",
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)
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username = Prompt.ask(
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"No4j username ",
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default="neo4j",
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default="movies",
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)
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db = Prompt.ask(
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"Neo4j database ",
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default="neo4j",
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default="movies",
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)
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pw = Prompt.ask(
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"Neo4j password ",
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default="",
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default="movies",
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)
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pw = pw or os.getenv("NEO4J_PASSWORD")
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neo4j_settings = Neo4jSettings(uri=uri, username=username, database=db, password=pw)
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neo4j_config = Neo4jChatAgentConfig(
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neo4j_settings=neo4j_settings,
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llm=llm_config,
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chat_mode=True,
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)
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neo4j_agent = Neo4jChatAgent(neo4j_config)

‎examples/kg-chat/dependency_chatbot.py‎

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dependency_agent = DependencyGraphAgent(
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config=Neo4jChatAgentConfig(
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chat_mode=True,
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neo4j_settings=neo4j_settings,
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show_stats=False,
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use_tools=tools,

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