SqliteChannel Quickstart

from swarms import Agent, SqliteChannel

channel = SqliteChannel("channels.db", name="ev-batteries")

researcher = Agent(
    agent_name="Researcher",
    system_prompt="You gather facts and figures. Answer in a short bullet list.",
    model_name="gpt-5.4",
    max_loops=1,
    channel=channel,
)
writer = Agent(
    agent_name="Writer",
    system_prompt="You turn the facts in the conversation into a short report.",
    model_name="gpt-5.4",
    max_loops=1,
    channel=channel,
)

task = "Report on the EV battery market."
researcher.run(task)
writer.run(task)

for row in channel.fetch_messages():
    print(f"#{row['id']} {row['created_at']} {row['agent_name']}")

from swarms import Agent, ConcurrentWorkflow, SqliteChannel

angles = ["technology", "regulation", "supply chain"]
agents = [
    Agent(
        agent_name=f"{angle.title().replace(' ', '-')}-Analyst",
        system_prompt=f"Analyse the task from the {angle} angle only.",
        model_name="gpt-5.4",
        max_loops=1,
    )
    for angle in angles
]

channel = SqliteChannel("channels.db", name="q3-ev-outlook")

workflow = ConcurrentWorkflow(agents=agents, channel=channel)
workflow.run("What will shape the EV battery market over the next five years?")

for message in channel.messages():
    print(f"\n[{message['agent_name']}]\n{message['content']}")

from swarms import Agent, MixtureOfAgents, SqliteChannel

workers = [
    Agent(agent_name="Bull", system_prompt="Make the strongest case for the investment.", model_name="gpt-5.4", max_loops=1),
    Agent(agent_name="Bear", system_prompt="Make the strongest case against the investment.", model_name="gpt-5.4", max_loops=1),
    Agent(agent_name="Quant", system_prompt="Assess the numbers only.", model_name="gpt-5.4", max_loops=1),
]
aggregator = Agent(
    agent_name="Portfolio-Manager",
    system_prompt="Weigh the analysts' views and give a final recommendation.",
    model_name="gpt-5.4",
    max_loops=1,
)

channel = SqliteChannel("investments.db", name="nvda-2026-11")

moa = MixtureOfAgents(
    agents=workers,
    aggregator_agent=aggregator,
    layers=2,
    channel=channel,
)
print(moa.run("Should we add to our NVIDIA position this quarter?"))

# Only the Bear's arguments, latest last.
for row in channel.fetch_messages():
    if row["agent_name"].startswith("Bear"):
        print(row["agent_name"], row["content"][:120])

from swarms import Agent, SqliteChannel

DB = "support.db"

tickets = {
    "support-1042": "My invoice shows the wrong plan.",
    "support-1043": "I cannot reset my password.",
}

for ticket, text in tickets.items():
    agent = Agent(
        agent_name="Support-Agent",
        system_prompt="Draft a short, friendly first reply to the customer.",
        model_name="gpt-5.4",
        max_loops=1,
        channel=SqliteChannel(DB, name=ticket),
    )
    agent.run(text)

print(SqliteChannel.list_conversations(DB))
# ['support-1042', 'support-1043']

followup = Agent(
    agent_name="Support-Agent",
    model_name="gpt-5.4",
    max_loops=1,
    channel=SqliteChannel(DB, name="support-1042"),
)
followup.run("The customer says they were charged twice. Update your reply.")

import sqlite3

from swarms import Agent, MajorityVoting, SqliteChannel

voters = [
    Agent(agent_name=f"Reviewer-{i}", model_name="gpt-5.4", max_loops=1)
    for i in range(1, 4)
]

channel = SqliteChannel("votes.db", name="rust-vs-go")

vote = MajorityVoting(agents=voters, channel=channel)
vote.run("Should our new ingestion service be written in Rust or Go? Answer with one word, then one sentence.")

rows = sqlite3.connect("votes.db").execute(
    "SELECT agent_name, substr(content, 1, 60) FROM messages WHERE channel = ? ORDER BY id",
    ("rust-vs-go",),
)
for agent_name, preview in rows:
    print(f"{agent_name:18} {preview}")

channel.clear()  # Deletes this conversation's rows; other names are untouched
channel.close()  # Closes the connection; the file keeps everything else