only stream results for the same request id. this allows multiple concurrent requests on the same LLM without overlapping interference in the streamed outputs

exo/api/chatgpt_api.py

@@ -285,9 +285,9 @@ class ChatGPTAPI:
         )
         await response.prepare(request)
 
-        async def stream_result(request_id: str, tokens: List[int], is_finished: bool):
-          prev_last_tokens_len = self.prev_token_lens.get(request_id, 0)
-          self.prev_token_lens[request_id] = max(prev_last_tokens_len, len(tokens))
+        async def stream_result(_request_id: str, tokens: List[int], is_finished: bool):
+          prev_last_tokens_len = self.prev_token_lens.get(_request_id, 0)
+          self.prev_token_lens[_request_id] = max(prev_last_tokens_len, len(tokens))
           new_tokens = tokens[prev_last_tokens_len:]
           finish_reason = None
           eos_token_id = tokenizer.special_tokens_map.get("eos_token_id") if hasattr(tokenizer, "_tokenizer") and isinstance(tokenizer._tokenizer,
@@ -317,7 +317,7 @@ class ChatGPTAPI:
             if DEBUG >= 2: traceback.print_exc()
 
         def on_result(_request_id: str, tokens: List[int], is_finished: bool):
-          self.stream_tasks[request_id] = asyncio.create_task(stream_result(request_id, tokens, is_finished))
+          if _request_id == request_id: self.stream_tasks[_request_id] = asyncio.create_task(stream_result(_request_id, tokens, is_finished))
 
           return _request_id == request_id and is_finished