fix dockerfile not building due to PEP517 error (#106)

Dockerfile.app

@@ -8,6 +8,8 @@ RUN apt-get update && apt-get install -y git gcc
 ENV PYTHONDONTWRITEBYTECODE 1
 ENV PYTHONUNBUFFERED 1
 
+RUN pip install --upgrade pip
+
 # Install Poetry
 RUN pip install poetry==1.8.1
 
@@ -17,6 +19,12 @@ WORKDIR /usr/src/app
 
 COPY pyproject.toml poetry.lock ./
 
+# fix error:
+# KeyError: 'PEP517_BUILD_BACKEND'
+# Note: This error originates from the build backend, and is likely not a problem with poetry but with paginate (0.5.6) not supporting PEP 517 builds. You can verify this by running 'pip wheel --no-cache-dir --use-pep517 "paginate (==0.5.6)"'.
+RUN poetry run pip install --upgrade pip setuptools wheel
+RUN poetry run python -m pip install paginate==0.5.6 --no-cache-dir --no-use-pep517 
+
 # Install dependencies
 RUN poetry config virtualenvs.create false \
     && poetry install --no-interaction --no-ansi --no-root --with label-studio

adala/runtimes/_openai.py

@@ -367,10 +367,10 @@ async def batch_to_batch(
                     # check for errors - if any, append to outputs and continue
                     if response.get("error"):
                         # FIXME if we collect failed and succeeded outputs in the same list -> df, we end up with an awkward schema like this:
-                            # output error message details
-                            # ---------------------------
-                            # output1 nan    nan      nan
-                            # nan     true   message2 details2
+                        # output error message details
+                        # ---------------------------
+                        # output1 nan    nan      nan
+                        # nan     true   message2 details2
                         # we are not going to send the error response to lse
                         # outputs.append(response)
                         if self.verbose:
@@ -392,7 +392,7 @@ async def batch_to_batch(
         # TODO: note that this doesn't work for multiple output fields e.g. `Output {output1} and Output {output2}`
         output_df = InternalDataFrame(outputs)
         # return output dataframe indexed as input batch.index, assuming outputs are in the same order as inputs
-        return output_df.set_index('index')
+        return output_df.set_index("index")
 
     async def record_to_record(
         self,