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6e25591eee
Co-authored-by: Shubham Naik <shub@letta.com> Co-authored-by: Shubham Naik <shub@memgpt.ai>
133 lines
4.1 KiB
Python
133 lines
4.1 KiB
Python
import os
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import threading
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import time
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import pytest
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from dotenv import load_dotenv
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from letta_client import AgentState, Letta, LlmConfig, MessageCreate
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from letta.schemas.message import Message
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def run_server():
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load_dotenv()
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from letta.server.rest_api.app import start_server
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print("Starting server...")
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start_server(debug=True)
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@pytest.fixture(
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scope="module",
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)
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def client(request):
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# Get URL from environment or start server
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api_url = os.getenv("LETTA_API_URL")
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server_url = os.getenv("LETTA_SERVER_URL", f"http://localhost:8283")
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if not os.getenv("LETTA_SERVER_URL"):
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print("Starting server thread")
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thread = threading.Thread(target=run_server, daemon=True)
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thread.start()
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time.sleep(5)
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print("Running client tests with server:", server_url)
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# Overide the base_url if the LETTA_API_URL is set
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base_url = api_url if api_url else server_url
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# create the Letta client
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yield Letta(base_url=base_url, token=None)
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# Fixture for test agent
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@pytest.fixture(scope="module")
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def agent(client: Letta):
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agent_state = client.agents.create(
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name="test_client",
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memory_blocks=[{"label": "human", "value": ""}, {"label": "persona", "value": ""}],
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model="letta/letta-free",
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embedding="letta/letta-free",
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)
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yield agent_state
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# delete agent
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client.agents.delete(agent_state.id)
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@pytest.mark.parametrize(
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"stream_tokens,model",
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[
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(True, "openai/gpt-4o-mini"),
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(True, "anthropic/claude-3-sonnet-20240229"),
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(False, "openai/gpt-4o-mini"),
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(False, "anthropic/claude-3-sonnet-20240229"),
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],
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)
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def test_streaming_send_message(
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disable_e2b_api_key,
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client: Letta,
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agent: AgentState,
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stream_tokens: bool,
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model: str,
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):
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# Update agent's model
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config = client.agents.retrieve(agent_id=agent.id).llm_config
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config_dump = config.model_dump()
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config_dump["model"] = model
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config = LlmConfig(**config_dump)
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client.agents.modify(agent_id=agent.id, llm_config=config)
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# Send streaming message
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user_message_otid = Message.generate_otid()
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response = client.agents.messages.create_stream(
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agent_id=agent.id,
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messages=[
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MessageCreate(
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role="user",
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content="This is a test. Repeat after me: 'banana'",
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otid=user_message_otid,
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),
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],
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stream_tokens=stream_tokens,
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)
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# Tracking variables for test validation
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inner_thoughts_exist = False
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inner_thoughts_count = 0
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send_message_ran = False
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done = False
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last_message_id = client.agents.messages.list(agent_id=agent.id, limit=1)[0].id
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letta_message_otids = [user_message_otid]
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assert response, "Sending message failed"
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for chunk in response:
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# Check chunk type and content based on the current client API
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if hasattr(chunk, "message_type") and chunk.message_type == "reasoning_message":
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inner_thoughts_exist = True
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inner_thoughts_count += 1
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if chunk.message_type == "tool_call_message" and hasattr(chunk, "tool_call") and chunk.tool_call.name == "send_message":
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send_message_ran = True
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if chunk.message_type == "assistant_message":
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send_message_ran = True
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if chunk.message_type == "usage_statistics":
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# Validate usage statistics
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assert chunk.step_count == 1
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assert chunk.completion_tokens > 10
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assert chunk.prompt_tokens > 1000
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assert chunk.total_tokens > 1000
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done = True
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else:
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letta_message_otids.append(chunk.otid)
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print(chunk)
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# If stream tokens, we expect at least one inner thought
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assert inner_thoughts_count >= 1, "Expected more than one inner thought"
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assert inner_thoughts_exist, "No inner thoughts found"
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assert send_message_ran, "send_message function call not found"
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assert done, "Message stream not done"
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messages = client.agents.messages.list(agent_id=agent.id, after=last_message_id)
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assert [message.otid for message in messages] == letta_message_otids
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