feat: Add streaming only final aiter of agent (#6274)

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#### Add streaming only final async iterator of agent
This callback returns an async iterator and only streams the final
output of an agent.

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Tag maintainers/contributors who might be interested: @agola11

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langchain/callbacks/streaming_aiter_final_only.py

@@ -0,0 +1,88 @@
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional
+
+from langchain.callbacks.streaming_aiter import AsyncIteratorCallbackHandler
+from langchain.schema import LLMResult
+
+DEFAULT_ANSWER_PREFIX_TOKENS = ["Final", "Answer", ":"]
+
+
+class AsyncFinalIteratorCallbackHandler(AsyncIteratorCallbackHandler):
+    """Callback handler that returns an async iterator.
+    Only the final output of the agent will be iterated.
+    """
+
+    def append_to_last_tokens(self, token: str) -> None:
+        self.last_tokens.append(token)
+        self.last_tokens_stripped.append(token.strip())
+        if len(self.last_tokens) > len(self.answer_prefix_tokens):
+            self.last_tokens.pop(0)
+            self.last_tokens_stripped.pop(0)
+
+    def check_if_answer_reached(self) -> bool:
+        if self.strip_tokens:
+            return self.last_tokens_stripped == self.answer_prefix_tokens_stripped
+        else:
+            return self.last_tokens == self.answer_prefix_tokens
+
+    def __init__(
+        self,
+        *,
+        answer_prefix_tokens: Optional[List[str]] = None,
+        strip_tokens: bool = True,
+        stream_prefix: bool = False,
+    ) -> None:
+        """Instantiate AsyncFinalIteratorCallbackHandler.
+
+        Args:
+            answer_prefix_tokens: Token sequence that prefixes the answer.
+                Default is ["Final", "Answer", ":"]
+            strip_tokens: Ignore white spaces and new lines when comparing
+                answer_prefix_tokens to last tokens? (to determine if answer has been
+                reached)
+            stream_prefix: Should answer prefix itself also be streamed?
+        """
+        super().__init__()
+        if answer_prefix_tokens is None:
+            self.answer_prefix_tokens = DEFAULT_ANSWER_PREFIX_TOKENS
+        else:
+            self.answer_prefix_tokens = answer_prefix_tokens
+        if strip_tokens:
+            self.answer_prefix_tokens_stripped = [
+                token.strip() for token in self.answer_prefix_tokens
+            ]
+        else:
+            self.answer_prefix_tokens_stripped = self.answer_prefix_tokens
+        self.last_tokens = [""] * len(self.answer_prefix_tokens)
+        self.last_tokens_stripped = [""] * len(self.answer_prefix_tokens)
+        self.strip_tokens = strip_tokens
+        self.stream_prefix = stream_prefix
+        self.answer_reached = False
+
+    async def on_llm_start(
+        self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
+    ) -> None:
+        # If two calls are made in a row, this resets the state
+        self.done.clear()
+        self.answer_reached = False
+
+    async def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
+        if self.answer_reached:
+            self.done.set()
+
+    async def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
+        # Remember the last n tokens, where n = len(answer_prefix_tokens)
+        self.append_to_last_tokens(token)
+
+        # Check if the last n tokens match the answer_prefix_tokens list ...
+        if self.check_if_answer_reached():
+            self.answer_reached = True
+            if self.stream_prefix:
+                for t in self.last_tokens:
+                    self.queue.put_nowait(t)
+            return
+
+        # If yes, then put tokens from now on
+        if self.answer_reached:
+            self.queue.put_nowait(token)