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1b8d65df0a
* Re-added missing notebook * Test installing postgres * Error handle the connection. * Fixed import. * Fixed import. * Fixed creation of collection without client. * PGVector portion working. OpenAI untested. * Fixed prints. * Added output. * Fixed pre-commits. * Run pgvector notebook * Improve efficiency of get_collection * Fix delete_collection * Fixed issues with pytests and validated functions. * Validated pytests. * Fixed pre-commits * Separated extra_requires to allow more logic. Retrieve_chat base dependencies included on pgvector and qdrant. * Fixed extra newline. * Added username and password fields. * URL Encode the connection string parameters to support symbols like % * Fixed pre-commits. * Added pgvector service * pgvector doesn't have health intervals. * Switched to colon based key values. * Run on Ubuntu only. Linux is only option with container service support. * Using default credentials instead. * Fix postgres setup * Fix postgres setup * Don't skip tests on win and mac * Fix command error * Try apt install postgresql * Assert table does not exist when deleted. * Raise value error on a empty list or None value provided for IDs * pre-commit * Add install pgvector * Add install pgvector * Reorg test files, create a separate job for test pgvector * Fix format * Fix env format * Simplify job name, enable test_retrieve_config * Fix test_retrieve_config * Corrected behavior for get_docs_by_ids with no ids returning all docs. * Corrected behavior for get_docs_by_ids with no ids returning all docs. * Fixed pre-commits. * Added return values for all functions. * Validated distance search is implemented correctly. * Validated all pytests * Removed print. * Added default clause. * Make ids optional * Fix test, make it more robust * Bump version of openai for the vector_store support * Added support for choosing the sentence transformer model. * Added error handling for model name entered. * Updated model info. * Added model_name db_config param. * pre-commit fixes and last link fix. * Use secrets password. * fix: link fixed * updated tests * Updated config_list. * pre-commit fix. * Added chat_result to all output. Unable to re-run notebooks. * Pre-commit fix detected this requirement. * Fix python 3.8 and 3.9 not supported for macos * Fix python 3.8 and 3.9 not supported for macos * Fix format * Reran notebook with MetaLlama3Instruct7BQ4_k_M * added gpt model. * Reran notebook --------- Co-authored-by: Li Jiang <bnujli@gmail.com> Co-authored-by: Hk669 <hrushi669@gmail.com>
104 lines
2.8 KiB
Python
Executable File
104 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.agentchat.contrib.retrieve_assistant_agent import (
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RetrieveAssistantAgent,
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)
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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 = 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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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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