Repository: truera/trulens
Issue: [BUG] Running feedback functions with a base url
Root cause: Documentation Deficiency

I wrote the feedback functions but it is not available, the dashboard shows that "No feedback functions found." and the feedback functions are not performed actually. My code is following:
import os

os.environ["OPENAI_API_BASE"] =
os.environ["OPENAI_API_KEY"] = 
from trulens.core import TruSession, FeedbackMode

session = TruSession()
session.reset_database()
import os
import urllib.request

url = "https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt"
file_path = "data/paul_graham_essay.txt"

if not os.path.exists("data"):
    os.makedirs("data")

if not os.path.exists(file_path):
    urllib.request.urlretrieve(url, file_path)
from llama_index.core import Settings
from llama_index.core import SimpleDirectoryReader
from llama_index.core import VectorStoreIndex
from llama_index.llms.openai import OpenAI

Settings.chunk_size = 128
Settings.chunk_overlap = 16
Settings.llm = OpenAI()

documents = SimpleDirectoryReader("data").load_data()
index = VectorStoreIndex.from_documents(documents)

query_engine = index.as_query_engine(similarity_top_k=3)
# response = query_engine.query("What did the author do growing up?")
# print(response)
import numpy as np
from trulens.apps.llamaindex import TruLlama
from trulens.core import Feedback
from trulens.providers.openai import OpenAI

# Initialize provider class
provider = OpenAI()

# select context to be used in feedback. the location of context is app specific.

context = TruLlama.select_context(query_engine)

# Define a groundedness feedback function
f_groundedness = (
    Feedback(
        provider.groundedness_measure_with_cot_reasons, name="Groundedness"
    )
    .on(context.collect())  # collect context chunks into a list
    .on_output()
)

# Question/answer relevance between overall question and answer.
f_answer_relevance = Feedback(
    provider.relevance_with_cot_reasons, name="Answer Relevance"
).on_input_output()
# Question/statement relevance between question and each context chunk.
f_context_relevance = (
    Feedback(
        provider.context_relevance_with_cot_reasons, name="Context Relevance"
    )
    .on_input()
    .on(context)
    .aggregate(np.mean)
)
tru_query_engine_recorder = TruLlama(
    query_engine,
    app_name="LlamaIndex_App",
    app_version="base",
    feedbacks=[f_groundedness, f_answer_relevance, f_context_relevance],
    feedback_mode=FeedbackMode.WITH_APP_THREAD
)
# or as context manager
from trulens_eval import Tru
tru = Tru()
tru.run_dashboard()
from trulens.dashboard.display import get_feedback_result
with tru_query_engine_recorder as recording:
    query_engine.query("What did the author do growing up?")



@0930mcx pls rotate you key, it's exposed. We removed it from your issue in the meantime.

Hey @0930mcx - you can initialize your provider with the base URL like this:

```python
from trulens.providers.openai.provider import OpenAI

feedback_provider = OpenAI(
    model_engine="glm-4v-9b",
    base_url="http://0.0.0.0:8000/v1/",
    api_key="your_api_key"
)
```

@0930mcx any success changing the base model like I'm showing above?

Hey @0930mcx - closing this for now but please re-open if issues persist.