mirror of
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c4f8b1c761
* api_base -> base_url (#383) * InvalidRequestError -> BadRequestError (#389) * remove api_key_path; close #388 * close #402 (#403) * openai client (#419) * openai client * client test * _client -> client * _client -> client * extra kwargs * Completion -> client (#426) * Completion -> client * Completion -> client * Completion -> client * Completion -> client * support aoai * fix test error * remove commented code * support aoai * annotations * import * reduce test * skip test * skip test * skip test * debug test * rename test * update workflow * update workflow * env * py version * doc improvement * docstr update * openai<1 * add tiktoken to dependency * filter_func * async test * dependency * migration guide (#477) * migration guide * change in kwargs * simplify header * update optigude description * deal with azure gpt-3.5 * add back test_eval_math_responses * timeout * Add back tests for RetrieveChat (#480) * Add back tests for RetrieveChat * Fix format * Update dependencies order * Fix path * Fix path * Fix path * Fix tests * Add not run openai on MacOS or Win * Update skip openai tests * Remove unnecessary dependencies, improve format * Add py3.8 for testing qdrant * Fix multiline error of windows * Add openai tests * Add dependency mathchat, remove unused envs * retrieve chat is tested * bump version to 0.2.0b1 --------- Co-authored-by: Li Jiang <bnujli@gmail.com>
106 lines
3.2 KiB
Python
106 lines
3.2 KiB
Python
import os
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import sys
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import pytest
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from autogen.agentchat.contrib.retrieve_assistant_agent import RetrieveAssistantAgent
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from autogen import config_list_from_json
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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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from qdrant_client import QdrantClient
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from autogen.agentchat.contrib.qdrant_retrieve_user_proxy_agent import (
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create_qdrant_from_dir,
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QdrantRetrieveUserProxyAgent,
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query_qdrant,
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)
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import fastembed
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QDRANT_INSTALLED = True
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except ImportError:
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QDRANT_INSTALLED = False
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try:
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import openai
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OPENAI_INSTALLED = True
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except ImportError:
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OPENAI_INSTALLED = False
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test_dir = os.path.join(os.path.dirname(__file__), "../..", "test_files")
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@pytest.mark.skipif(
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sys.platform in ["darwin", "win32"] or not QDRANT_INSTALLED or not OPENAI_INSTALLED,
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reason="do not run on MacOS or windows or dependency is not installed",
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)
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def test_retrievechat():
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conversations = {}
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# ChatCompletion.start_logging(conversations) # deprecated in v0.2
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config_list = 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 = RetrieveAssistantAgent(
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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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client = QdrantClient(":memory:")
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ragproxyagent = QdrantRetrieveUserProxyAgent(
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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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"client": client,
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"docs_path": "./website/docs",
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"chunk_token_size": 2000,
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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(assistant, problem=code_problem, silent=True)
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print(conversations)
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@pytest.mark.skipif(not QDRANT_INSTALLED, reason="qdrant_client is not installed")
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def test_qdrant_filter():
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client = QdrantClient(":memory:")
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create_qdrant_from_dir(dir_path="./website/docs", client=client, collection_name="autogen-docs")
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results = query_qdrant(
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query_texts=["How can I use AutoGen UserProxyAgent and AssistantAgent to do code generation?"],
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n_results=4,
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client=client,
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collection_name="autogen-docs",
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# Return only documents with "AutoGen" in the string
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search_string="AutoGen",
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)
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assert len(results["ids"][0]) == 4
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@pytest.mark.skipif(not QDRANT_INSTALLED, reason="qdrant_client is not installed")
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def test_qdrant_search():
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client = QdrantClient(":memory:")
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create_qdrant_from_dir(test_dir, client=client)
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assert client.get_collection("all-my-documents")
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# Perform a semantic search without any filter
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results = query_qdrant(["autogen"], client=client)
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assert isinstance(results, dict) and any("autogen" in res[0].lower() for res in results.get("documents", []))
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if __name__ == "__main__":
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test_retrievechat()
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test_qdrant_filter()
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test_qdrant_search()
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