forked from phoenix/litellm-mirror
121 lines
3.1 KiB
Python
121 lines
3.1 KiB
Python
import sys
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import os
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import io
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sys.path.insert(0, os.path.abspath("../.."))
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from litellm import completion
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import litellm
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litellm.failure_callback = ["lunary"]
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litellm.success_callback = ["lunary"]
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litellm.set_verbose = True
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def test_lunary_logging():
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try:
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response = completion(
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model="gpt-3.5-turbo",
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messages=[{"role": "user", "content": "what llm are u"}],
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max_tokens=10,
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temperature=0.2,
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user="test-user",
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)
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print(response)
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except Exception as e:
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print(e)
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# test_lunary_logging()
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def test_lunary_template():
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import lunary
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try:
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template = lunary.render_template("test-template", {"question": "Hello!"})
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response = completion(**template)
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print(response)
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except Exception as e:
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print(e)
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# test_lunary_template()
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def test_lunary_logging_with_metadata():
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try:
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response = completion(
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model="gpt-3.5-turbo",
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messages=[{"role": "user", "content": "what llm are u"}],
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max_tokens=10,
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temperature=0.2,
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metadata={
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"run_name": "litellmRUN",
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"project_name": "litellm-completion",
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},
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)
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print(response)
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except Exception as e:
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print(e)
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#test_lunary_logging_with_metadata()
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def test_lunary_with_tools():
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import litellm
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messages = [{"role": "user", "content": "What's the weather like in San Francisco, Tokyo, and Paris?"}]
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_current_weather",
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"description": "Get the current weather in a given location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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},
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"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
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},
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"required": ["location"],
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},
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},
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}
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]
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response = litellm.completion(
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model="gpt-3.5-turbo-1106",
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messages=messages,
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tools=tools,
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tool_choice="auto", # auto is default, but we'll be explicit
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)
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response_message = response.choices[0].message
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print("\nLLM Response:\n", response.choices[0].message)
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#test_lunary_with_tools()
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def test_lunary_logging_with_streaming_and_metadata():
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try:
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response = completion(
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model="gpt-3.5-turbo",
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messages=[{"role": "user", "content": "what llm are u"}],
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max_tokens=10,
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temperature=0.2,
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metadata={
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"run_name": "litellmRUN",
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"project_name": "litellm-completion",
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},
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stream=True,
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)
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for chunk in response:
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continue
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except Exception as e:
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print(e)
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# test_lunary_logging_with_streaming_and_metadata()
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