Worker (#83)

* base llm

* ;)

* base llm

* llm

* more ideas around queues

* examples

* cleanup

* napper

* querent workers

* update the querent core to handle shutdown signals

* cleanup

* worker

* handle signaling

tests/llm_tests/mock_llm_test.py

@@ -0,0 +1,57 @@
+import asyncio
+import pytest
+from querent.common.types.querent_queue import QuerentQueue
+from querent.llm.base_llm import BaseLLM
+from querent.napper.querent import Querent
+
+
+# Define a simple mock LLM class for testing
+class MockLLM(BaseLLM):
+    async def process_tokens(self, data):
+        return f"Processed: {data}"
+
+    def validate(self):
+        return True
+
+
+@pytest.mark.asyncio
+async def test_querent_with_base_llm():
+    # Create input and output queues
+    input_queue = QuerentQueue()
+    output_queue = QuerentQueue()
+
+    # Create a list of mock LLM instances
+    num_llms = 3
+    llms = [MockLLM(input_queue, output_queue) for _ in range(num_llms)]
+
+    # Create a Querent instance
+    querent = Querent(llms, num_workers=num_llms, resource_manager=None)
+
+    # Start the Querent
+    await querent.start()
+
+    # Put some input data into the input queue
+    input_data = ["Data 1", "Data 2", "Data 3"]
+    for data in input_data:
+        await input_queue.put(data)
+
+    # Signal the Querent to stop by putting None into the input queue
+    await input_queue.close()
+
+    # Wait for the Querent to finish processing
+    await asyncio.gather(*llms)
+
+    # Check the output queue for results and store them in a list
+    results = []
+    async for result in output_queue:
+        results.append(result)
+    await output_queue.close()
+
+    # Assert that the results match the expected output
+    expected_output = ["Processed: Data 1", "Processed: Data 2", "Processed: Data 3"]
+    assert results == expected_output
+
+
+# Run the test
+if __name__ == "__main__":
+    pytest.main()