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08fa1b6d08
* Remove deps on RetrieveAssistantAgent for getting human input * Terminate when no more context * Add deprecation warning message * Clean up RetrieveAssistantAgent, part 1 * Update version * Clean up docs and notebooks
102 lines
2.8 KiB
Python
Executable File
102 lines
2.8 KiB
Python
Executable File
#!/usr/bin/env python3 -m pytest
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import os
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import sys
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import pytest
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import autogen
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sys.path.append(os.path.join(os.path.dirname(__file__), "../../.."))
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from conftest import reason, skip_openai # noqa: E402
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sys.path.append(os.path.join(os.path.dirname(__file__), "../.."))
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from test_assistant_agent import KEY_LOC, OAI_CONFIG_LIST # noqa: E402
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try:
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import chromadb
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import openai
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from chromadb.utils import embedding_functions as ef
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from autogen import AssistantAgent
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from autogen.agentchat.contrib.retrieve_user_proxy_agent import (
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RetrieveUserProxyAgent,
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)
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except ImportError:
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skip = True
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else:
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skip = False
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reason = "do not run on MacOS or windows OR dependency is not installed OR " + reason
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@pytest.mark.skipif(
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sys.platform in ["darwin", "win32"] or skip or skip_openai,
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reason=reason,
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)
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def test_retrievechat():
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conversations = {}
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# autogen.ChatCompletion.start_logging(conversations) # deprecated in v0.2
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config_list = autogen.config_list_from_json(
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OAI_CONFIG_LIST,
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file_location=KEY_LOC,
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)
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assistant = AssistantAgent(
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name="assistant",
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system_message="You are a helpful assistant.",
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llm_config={
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"timeout": 600,
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"seed": 42,
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"config_list": config_list,
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},
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)
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sentence_transformer_ef = ef.SentenceTransformerEmbeddingFunction()
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ragproxyagent = RetrieveUserProxyAgent(
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name="ragproxyagent",
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human_input_mode="NEVER",
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max_consecutive_auto_reply=2,
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retrieve_config={
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"docs_path": "./website/docs",
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"chunk_token_size": 2000,
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"model": config_list[0]["model"],
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"client": chromadb.PersistentClient(path="/tmp/chromadb"),
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"embedding_function": sentence_transformer_ef,
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"get_or_create": True,
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},
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)
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assistant.reset()
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code_problem = "How can I use FLAML to perform a classification task, set use_spark=True, train 30 seconds and force cancel jobs if time limit is reached."
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ragproxyagent.initiate_chat(
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assistant, message=ragproxyagent.message_generator, problem=code_problem, search_string="spark", silent=True
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)
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print(conversations)
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@pytest.mark.skipif(
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sys.platform in ["darwin", "win32"] or skip,
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reason=reason,
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)
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def test_retrieve_config():
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# test warning message when no docs_path is provided
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ragproxyagent = RetrieveUserProxyAgent(
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name="ragproxyagent",
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human_input_mode="NEVER",
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max_consecutive_auto_reply=2,
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retrieve_config={
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"chunk_token_size": 2000,
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"get_or_create": True,
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},
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)
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assert ragproxyagent._docs_path is None
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if __name__ == "__main__":
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# test_retrievechat()
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test_retrieve_config()
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