Add ability to store row-level metadata

This metadata field allows non API parameters to be stored which could
be useful for when the results need to be associated with an external
source. For example, if the user has several rows of text data within a
database, and they want to calculate embeddings for each row, they can
now use the metadata field to save the row id so that when they parse
the results back, they know which embedding corresponds to which
database row.

examples/api_request_parallel_processor.py

@@ -31,8 +31,8 @@ python examples/api_request_parallel_processor.py \
 Inputs:
 - requests_filepath : str
     - path to the file containing the requests to be processed
-    - file should be a jsonl file, where each line is a json object with API parameters
-    - e.g., {"model": "text-embedding-ada-002", "input": "embed me"}
+    - file should be a jsonl file, where each line is a json object with API parameters and an optional metadata field
+    - e.g., {"model": "text-embedding-ada-002", "input": "embed me", "metadata": {"row_id": 1}}
     - as with all jsonl files, take care that newlines in the content are properly escaped (json.dumps does this automatically)
     - an example file is provided at examples/data/example_requests_to_parallel_process.jsonl
     - the code to generate the example file is appended to the bottom of this script
@@ -164,6 +164,7 @@ async def process_api_requests_from_file(
                             request_json=request_json,
                             token_consumption=num_tokens_consumed_from_request(request_json, api_endpoint, token_encoding_name),
                             attempts_left=max_attempts,
+                            metadata=request_json.pop("metadata", None)
                         )
                         status_tracker.num_tasks_started += 1
                         status_tracker.num_tasks_in_progress += 1
@@ -258,6 +259,7 @@ class APIRequest:
     request_json: dict
     token_consumption: int
     attempts_left: int
+    metadata: dict
     result: list = field(default_factory=list)
 
     async def call_api(
@@ -298,11 +300,21 @@ class APIRequest:
                 retry_queue.put_nowait(self)
             else:
                 logging.error(f"Request {self.request_json} failed after all attempts. Saving errors: {self.result}")
-                append_to_jsonl([self.request_json, [str(e) for e in self.result]], save_filepath)
+                data = (
+                    [self.request_json, [str(e) for e in self.result], self.metadata]
+                    if self.metadata
+                    else [self.request_json, [str(e) for e in self.result]]
+                )
+                append_to_jsonl(data, save_filepath)
                 status_tracker.num_tasks_in_progress -= 1
                 status_tracker.num_tasks_failed += 1
         else:
-            append_to_jsonl([self.request_json, response], save_filepath)
+            data = (
+                [self.request_json, response, self.metadata]
+                if self.metadata
+                else [self.request_json, response]
+            )
+            append_to_jsonl(data, save_filepath)
             status_tracker.num_tasks_in_progress -= 1
             status_tracker.num_tasks_succeeded += 1
             logging.debug(f"Request {self.task_id} saved to {save_filepath}")

examples/data/example_requests_to_parallel_process.jsonl

@@ -1,4 +1,4 @@
-{"model": "text-embedding-ada-002", "input": "0\n"}
+{"model": "text-embedding-ada-002", "input": "0\n", "metadata": {"row_id": 1}}
 {"model": "text-embedding-ada-002", "input": "1\n"}
 {"model": "text-embedding-ada-002", "input": "2\n"}
 {"model": "text-embedding-ada-002", "input": "3\n"}