pip install fetch-hive-sdk

export FETCH_HIVE_API_KEY=fhk_...

from fetch_hive_sdk import FetchHive

client = FetchHive()

client = FetchHive(api_key="fhk_...")

from fetch_hive_sdk import FetchHive

client = FetchHive()

reply = client.invoke_agent(
    agent="AGENT_UUID",
    message="Summarize the latest AI infrastructure trends",
)

print(reply["response"])

reply = client.invoke_agent(agent="AGENT_UUID", message="Hello")

print(reply["response"])      # final text
print(reply["model"])         # model identifier
print(reply["usage"])         # token usage breakdown
print(reply["request_id"])    # use this to look up the run in Logs
print(reply.get("tool_calls"))  # tool invocations made during the run

for chunk in client.invoke_agent_stream(
    agent="AGENT_UUID",
    message="Summarize the latest AI infrastructure trends",
    thread_id="user-456-support-session",
):
    if chunk.get("type") == "response":
        print(chunk.get("response", ""), end="", flush=True)
    elif chunk.get("type") == "tool":
        print(f"\n[Calling tool: {chunk.get('tool')}]")
    elif chunk.get("type") == "usage":
        print("\n\nUsage:", chunk["usage"])

import asyncio
from fetch_hive_sdk import FetchHive

async def main():
    client = FetchHive()
    async for chunk in client.ainvoke_agent_stream(
        agent="AGENT_UUID",
        message="Hello",
        thread_id="user-456-support-session",
    ):
        if chunk.get("type") == "response":
            print(chunk.get("response", ""), end="", flush=True)

asyncio.run(main())

client.invoke_agent(
    agent="AGENT_UUID",
    message="What are the main AI infrastructure trends right now?",
    thread_id="user-456-support-session",
)

client.invoke_agent(
    agent="AGENT_UUID",
    message="Which of those trends have the most enterprise adoption?",
    thread_id="user-456-support-session",
)

client.invoke_agent(
    agent="AGENT_UUID",
    message="Which of those trends have the most enterprise adoption?",
    messages=[
        {"role": "user", "content": "What are the main AI infrastructure trends right now?"},
        {"role": "assistant", "content": "Teams are focusing on evals, tool routing, and observability."},
    ],
)

result = client.invoke_agent(
    agent="vision-agent",
    message="Describe this image",
    attachments=["https://example.com/photo.jpg"],
)
print(result["response"])

client = FetchHive(
    api_key="fhk_...",
    base_url="https://api.fetchhive.com/v1",
    timeout=120,
)

import httpx

try:
    reply = client.invoke_agent(agent="AGENT_UUID", message="Hello")
except httpx.HTTPStatusError as exc:
    print("Fetch Hive returned", exc.response.status_code, exc.response.text)