mirror of
https://github.com/hwchase17/langchain
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141 lines
3.9 KiB
Plaintext
141 lines
3.9 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "6eaf7e66-f49c-42da-8d11-22ea13bef718",
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"metadata": {},
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"source": [
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"# Streaming with LLMs\n",
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"\n",
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"LangChain provides streaming support for LLMs. Currently, we only support streaming for the `OpenAI` LLM implementation, but streaming support for other LLM implementations is on the roadmap. To utilize streaming, use a [`CallbackHandler`](https://github.com/hwchase17/langchain/blob/master/langchain/callbacks/base.py) that implements `on_llm_new_token`. In this example, we are using [`StreamingStdOutCallbackHandler`]()."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "4ac0ff54-540a-4f2b-8d9a-b590fec7fe07",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"Verse 1\n",
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"I'm sippin' on sparkling water,\n",
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"It's so refreshing and light,\n",
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"It's the perfect way to quench my thirst,\n",
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"On a hot summer night.\n",
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"\n",
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"Chorus\n",
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"Sparkling water, sparkling water,\n",
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"It's the best way to stay hydrated,\n",
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"It's so refreshing and light,\n",
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"It's the perfect way to stay alive.\n",
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"\n",
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"Verse 2\n",
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"I'm sippin' on sparkling water,\n",
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"It's so bubbly and bright,\n",
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"It's the perfect way to cool me down,\n",
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"On a hot summer night.\n",
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"\n",
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"Chorus\n",
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"Sparkling water, sparkling water,\n",
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"It's the best way to stay hydrated,\n",
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"It's so refreshing and light,\n",
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"It's the perfect way to stay alive.\n",
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"\n",
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"Verse 3\n",
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"I'm sippin' on sparkling water,\n",
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"It's so crisp and clean,\n",
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"It's the perfect way to keep me going,\n",
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"On a hot summer day.\n",
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"\n",
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"Chorus\n",
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"Sparkling water, sparkling water,\n",
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"It's the best way to stay hydrated,\n",
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"It's so refreshing and light,\n",
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"It's the perfect way to stay alive."
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]
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}
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],
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"source": [
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"from langchain.llms import OpenAI\n",
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"from langchain.callbacks.base import CallbackManager\n",
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"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
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"\n",
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"\n",
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"llm = OpenAI(streaming=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), verbose=True, temperature=0)\n",
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"resp = llm(\"Write me a song about sparkling water.\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "61fb6de7-c6c8-48d0-a48e-1204c027a23c",
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"metadata": {
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"tags": []
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},
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"source": [
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"We still have access to the end `LLMResult` if using `generate`. However, `token_usage` is not currently supported for streaming."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "a35373f1-9ee6-4753-a343-5aee749b8527",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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"Q: What did the fish say when it hit the wall?\n",
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"A: Dam!"
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]
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},
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{
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"data": {
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"text/plain": [
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"LLMResult(generations=[[Generation(text='\\n\\nQ: What did the fish say when it hit the wall?\\nA: Dam!', generation_info={'finish_reason': 'stop', 'logprobs': None})]], llm_output={'token_usage': {}})"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"llm.generate([\"Tell me a joke.\"])"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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