forked from phoenix/litellm-mirror
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No EOL
7.6 KiB
Text
Vendored
226 lines
No EOL
7.6 KiB
Text
Vendored
{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"# [STREAMING] OpenAI, Anthropic, Replicate, Cohere using liteLLM\n",
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"In this tutorial:\n",
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"Note: All inputs/outputs are in the format used by `gpt-3.5-turbo`\n",
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"\n",
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"- Call all models in the same input format [**with streaming**]:\n",
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"\n",
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" `completion(model, messages, stream=True)`\n",
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"- All streaming generators are accessed at `chunk['choices'][0]['delta']`\n",
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"\n",
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"The following Models are covered in this tutorial\n",
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"- [GPT-3.5-Turbo](https://platform.openai.com/docs/models/gpt-3-5)\n",
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"- [Claude-2](https://www.anthropic.com/index/claude-2)\n",
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"- [StableLM Tuned Alpha 7B](https://replicate.com/stability-ai/stablelm-tuned-alpha-7b)\n",
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"- [A16z infra-LLAMA-2 7B Chat](https://replicate.com/a16z-infra/llama-2-7b-chat)\n",
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"- [Vicuna 13B](https://replicate.com/replicate/vicuna-13b)\n",
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"- [Cohere - Command Nightly]()\n",
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"\n",
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"\n",
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"\n"
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],
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"metadata": {
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"id": "YV6L5fNv7Kep"
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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": null,
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"metadata": {
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"id": "TO-EdF84O9QT"
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},
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"outputs": [],
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"source": [
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"# install liteLLM\n",
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"!pip install litellm==0.1.369"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"## Imports & Set ENV variables\n",
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"Get your API Keys\n",
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"\n",
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"https://platform.openai.com/account/api-keys\n",
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"\n",
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"https://replicate.com/account/api-tokens\n",
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"\n",
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"https://console.anthropic.com/account/keys\n",
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"\n",
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"https://dashboard.cohere.ai/api-keys\n"
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],
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"metadata": {
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"id": "mpHTbTqQ8fey"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"from litellm import completion\n",
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"import os\n",
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"\n",
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"os.environ['OPENAI_API_KEY'] = '' # @param\n",
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"os.environ['REPLICATE_API_TOKEN'] = '' # @param\n",
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"os.environ['ANTHROPIC_API_KEY'] = '' # @param\n",
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"os.environ['COHERE_API_KEY'] = '' # @param"
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],
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"metadata": {
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"id": "kDbgfcU8O-dW"
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},
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"execution_count": 8,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"### Set Messages"
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],
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"metadata": {
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"id": "1KmkOdzLSOmJ"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"user_message = \"Hello, whats the weather in San Francisco??\"\n",
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"messages = [{ \"content\": user_message,\"role\": \"user\"}]"
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],
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"metadata": {
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"id": "xIEeOhVH-oh6"
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},
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"execution_count": 4,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"## Calling Models using liteLLM Streaming -\n",
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"\n",
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"## `completion(model, messages, stream)`"
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],
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"metadata": {
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"id": "9SOCVRC1L-G3"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"# replicate models #######\n",
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"stability_ai = \"stability-ai/stablelm-tuned-alpha-7b:c49dae362cbaecd2ceabb5bd34fdb68413c4ff775111fea065d259d577757beb\"\n",
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"llama_2_7b = \"a16z-infra/llama-2-7b-chat:4f0b260b6a13eb53a6b1891f089d57c08f41003ae79458be5011303d81a394dc\"\n",
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"vicuna = \"replicate/vicuna-13b:6282abe6a492de4145d7bb601023762212f9ddbbe78278bd6771c8b3b2f2a13b\"\n",
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"\n",
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"models = [\"gpt-3.5-turbo\", \"claude-2\", stability_ai, llama_2_7b, vicuna, \"command-nightly\"] # command-nightly is Cohere\n",
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"for model in models:\n",
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" replicate = (model == stability_ai or model==llama_2_7b or model==vicuna) # let liteLLM know if a model is replicate, using this optional param, `replicate=True`\n",
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" response = completion(model=model, messages=messages, stream=True, replicate=replicate)\n",
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" print(f\"####################\\n\\nResponse from {model}\")\n",
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" for i, chunk in enumerate(response):\n",
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" if i < 5: # NOTE: LIMITING CHUNKS FOR THIS DEMO\n",
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" print((chunk['choices'][0]['delta']))\n"
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],
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "XJ4nh4SnRzHP",
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"outputId": "26b9fe10-b499-4a97-d60d-a8cb8f8030b8"
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},
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"execution_count": 13,
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"text": [
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"####################\n",
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"\n",
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"Response from gpt-3.5-turbo\n",
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"{\n",
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" \"role\": \"assistant\",\n",
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" \"content\": \"\"\n",
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"}\n",
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"{\n",
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" \"content\": \"I\"\n",
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"}\n",
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"{\n",
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" \"content\": \"'m\"\n",
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"}\n",
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"{\n",
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" \"content\": \" sorry\"\n",
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"}\n",
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"{\n",
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" \"content\": \",\"\n",
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"}\n",
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"####################\n",
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"\n",
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"Response from claude-2\n",
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"{'role': 'assistant', 'content': ' Unfortunately'}\n",
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"{'role': 'assistant', 'content': ' I'}\n",
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"{'role': 'assistant', 'content': ' don'}\n",
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"{'role': 'assistant', 'content': \"'t\"}\n",
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"{'role': 'assistant', 'content': ' have'}\n",
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"####################\n",
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"\n",
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"Response from stability-ai/stablelm-tuned-alpha-7b:c49dae362cbaecd2ceabb5bd34fdb68413c4ff775111fea065d259d577757beb\n",
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"{'role': 'assistant', 'content': \"I'm\"}\n",
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"{'role': 'assistant', 'content': ' sorry,'}\n",
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"{'role': 'assistant', 'content': ' I'}\n",
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"{'role': 'assistant', 'content': ' cannot'}\n",
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"{'role': 'assistant', 'content': ' answer'}\n",
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"####################\n",
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"\n",
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"Response from a16z-infra/llama-2-7b-chat:4f0b260b6a13eb53a6b1891f089d57c08f41003ae79458be5011303d81a394dc\n",
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"{'role': 'assistant', 'content': ''}\n",
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"{'role': 'assistant', 'content': ' Hello'}\n",
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"{'role': 'assistant', 'content': '!'}\n",
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"{'role': 'assistant', 'content': ' I'}\n",
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"{'role': 'assistant', 'content': \"'\"}\n",
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"####################\n",
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"\n",
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"Response from replicate/vicuna-13b:6282abe6a492de4145d7bb601023762212f9ddbbe78278bd6771c8b3b2f2a13b\n",
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"{'role': 'assistant', 'content': 'Comment:'}\n",
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"{'role': 'assistant', 'content': 'Hi! '}\n",
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"{'role': 'assistant', 'content': 'How '}\n",
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"{'role': 'assistant', 'content': 'are '}\n",
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"{'role': 'assistant', 'content': 'you '}\n",
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"####################\n",
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"\n",
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"Response from command-nightly\n",
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"{'role': 'assistant', 'content': ' Hello'}\n",
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"{'role': 'assistant', 'content': '!'}\n",
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"{'role': 'assistant', 'content': ' '}\n",
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"{'role': 'assistant', 'content': ' I'}\n",
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"{'role': 'assistant', 'content': \"'m\"}\n"
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]
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}
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]
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},
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{
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"cell_type": "code",
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"source": [],
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"metadata": {
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"id": "t7WMRuL-8NrO"
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},
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"execution_count": null,
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"outputs": []
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}
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]
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} |