mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
2667ddc686
**Description: a description of the change**
Fixed `make docs_build` and related scripts which caused errors. There
are several changes.
First, I made the build of the documentation and the API Reference into
two separate commands. This is because it takes less time to build. The
commands for documents are `make docs_build`, `make docs_clean`, and
`make docs_linkcheck`. The commands for API Reference are `make
api_docs_build`, `api_docs_clean`, and `api_docs_linkcheck`.
It looked like `docs/.local_build.sh` could be used to build the
documentation, so I used that. Since `.local_build.sh` was also building
API Rerefence internally, I removed that process. `.local_build.sh` also
added some Bash options to stop in error or so. Futher more added `cd
"${SCRIPT_DIR}"` at the beginning so that the script will work no matter
which directory it is executed in.
`docs/api_reference/api_reference.rst` is removed, because which is
generated by `docs/api_reference/create_api_rst.py`, and added it to
.gitignore.
Finally, the description of CONTRIBUTING.md was modified.
**Issue: the issue # it fixes (if applicable)**
https://github.com/hwchase17/langchain/issues/6413
**Dependencies: any dependencies required for this change**
`nbdoc` was missing in group docs so it was added. I installed it with
the `poetry add --group docs nbdoc` command. I am concerned if any
modifications are needed to poetry.lock. I would greatly appreciate it
if you could pay close attention to this file during the review.
**Tag maintainer**
- General / Misc / if you don't know who to tag: @baskaryan
If this PR needs any additional changes, I'll be happy to make them!
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
424 lines
186 KiB
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424 lines
186 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "8d10861f-a550-4443-bc63-4ce2ae13b841",
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"metadata": {},
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"source": [
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"# Infino - LangChain LLM Monitoring Example\n",
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"\n",
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"This example shows how one can track the following while calling OpenAI models via LangChain and [Infino](https://github.com/infinohq/infino):\n",
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"\n",
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"* prompt input,\n",
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"* response from chatgpt or any other LangChain model,\n",
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"* latency,\n",
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"* errors,\n",
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"* number of tokens consumed"
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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": "3a5a0976-9953-41d8-880c-eb3f2992e936",
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"metadata": {},
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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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"Requirement already satisfied: matplotlib in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (3.7.1)\n",
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"Requirement already satisfied: contourpy>=1.0.1 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (1.0.7)\n",
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"Requirement already satisfied: cycler>=0.10 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (0.11.0)\n",
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"Requirement already satisfied: fonttools>=4.22.0 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (4.39.4)\n",
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"Requirement already satisfied: kiwisolver>=1.0.1 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (1.4.4)\n",
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"Requirement already satisfied: numpy>=1.20 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (1.24.3)\n",
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"Requirement already satisfied: packaging>=20.0 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (23.1)\n",
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"Requirement already satisfied: pillow>=6.2.0 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (9.5.0)\n",
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"Requirement already satisfied: pyparsing>=2.3.1 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (3.0.9)\n",
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"Requirement already satisfied: python-dateutil>=2.7 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from matplotlib) (2.8.2)\n",
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"Requirement already satisfied: six>=1.5 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
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"Requirement already satisfied: infinopy in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (0.0.1)\n",
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"Requirement already satisfied: docker in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from infinopy) (6.1.3)\n",
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"Requirement already satisfied: requests in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from infinopy) (2.31.0)\n",
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"Requirement already satisfied: packaging>=14.0 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from docker->infinopy) (23.1)\n",
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"Requirement already satisfied: urllib3>=1.26.0 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from docker->infinopy) (2.0.2)\n",
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"Requirement already satisfied: websocket-client>=0.32.0 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from docker->infinopy) (1.5.2)\n",
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"Requirement already satisfied: charset-normalizer<4,>=2 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from requests->infinopy) (3.1.0)\n",
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"Requirement already satisfied: idna<4,>=2.5 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from requests->infinopy) (3.4)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in /Users/vinaykakade/.pyenv/versions/3.10.11/lib/python3.10/site-packages (from requests->infinopy) (2023.5.7)\n"
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]
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}
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],
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"source": [
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"# Install necessary dependencies.\n",
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"!pip install infinopy\n",
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"!pip install matplotlib\n",
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"\n",
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"# Remove the (1) import sys and sys.path.append(..) and (2) uncomment `!pip install langchain` after merging the PR for Infino/LangChain integration.\n",
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"import sys\n",
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"\n",
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"sys.path.append(\"../../../../../langchain\")\n",
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"#!pip install langchain\n",
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"\n",
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"\n",
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"import datetime as dt\n",
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"from infinopy import InfinoClient\n",
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"import json\n",
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"from langchain.llms import OpenAI\n",
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"from langchain.callbacks import InfinoCallbackHandler\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib.dates as md\n",
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"import os\n",
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"import time\n",
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"import sys"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "9f90210d-c805-4a0c-81e4-d5298942afc4",
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"metadata": {},
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"source": [
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"## Start Infino server, initialize the Infino client\n"
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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": 10,
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"id": "748b9858-5145-4351-976a-ca2d54e836a6",
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"metadata": {},
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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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"497a621125800abdd19f57ce7e033349b3cf83ca8cea6a74e8e28433a42ecadd\n"
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]
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}
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],
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"source": [
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"# Start server using the Infino docker image.\n",
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"!docker run --rm --detach --name infino-example -p 3000:3000 infinohq/infino:latest\n",
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"\n",
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"# Create Infino client.\n",
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"client = InfinoClient()"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "b6b81cda-b841-43ee-8c5e-b1576555765f",
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"metadata": {},
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"source": [
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"## Read the questions dataset"
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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": 17,
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"id": "b659fd0c-0d8c-470e-8b6c-867a117f2a27",
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"metadata": {},
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"outputs": [],
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"source": [
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"# These are a subset of questions from Stanford's QA dataset -\n",
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"# https://rajpurkar.github.io/SQuAD-explorer/\n",
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"data = \"\"\"In what country is Normandy located?\n",
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"When were the Normans in Normandy?\n",
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"From which countries did the Norse originate?\n",
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"Who was the Norse leader?\n",
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"What century did the Normans first gain their separate identity?\n",
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"Who gave their name to Normandy in the 1000's and 1100's\n",
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"What is France a region of?\n",
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"Who did King Charles III swear fealty to?\n",
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"When did the Frankish identity emerge?\n",
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"Who was the duke in the battle of Hastings?\n",
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"Who ruled the duchy of Normandy\n",
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"What religion were the Normans\n",
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"What type of major impact did the Norman dynasty have on modern Europe?\n",
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"Who was famed for their Christian spirit?\n",
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"Who assimilted the Roman language?\n",
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"Who ruled the country of Normandy?\n",
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"What principality did William the conquerer found?\n",
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"What is the original meaning of the word Norman?\n",
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"When was the Latin version of the word Norman first recorded?\n",
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"What name comes from the English words Normans/Normanz?\"\"\"\n",
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"\n",
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"questions = data.split(\"\\n\")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "dce1b820-3f1a-4b94-b848-4c6032cadc18",
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"metadata": {},
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"source": [
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"## LangChain OpenAI Q&A; Publish metrics and logs to Infino"
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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": 18,
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"id": "d5cebf35-2d10-48b8-ab11-c4a574c595d2",
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"metadata": {},
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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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"In what country is Normandy located?\n",
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"generations=[[Generation(text='\\n\\nNormandy is located in France.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 16, 'completion_tokens': 9, 'prompt_tokens': 7}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('8de21639-acec-4bd1-a12d-8124de1e20da'))\n",
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"When were the Normans in Normandy?\n",
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"generations=[[Generation(text='\\n\\nThe Normans first settled in Normandy in the late 9th century.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 24, 'completion_tokens': 16, 'prompt_tokens': 8}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('cf81fc86-250b-4e6e-9d92-2df3bebb019a'))\n",
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"From which countries did the Norse originate?\n",
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"generations=[[Generation(text='\\n\\nThe Norse originated from Scandinavia, which includes modern-day Norway, Sweden, and Denmark.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 29, 'completion_tokens': 21, 'prompt_tokens': 8}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('50f42f5e-b4a4-411a-a049-f92cb573a74f'))\n",
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"Who was the Norse leader?\n",
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"generations=[[Generation(text='\\n\\nThe most famous Norse leader was the legendary Viking king Ragnar Lodbrok. He is believed to have lived in the 9th century and is renowned for his exploits in England and France.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 45, 'completion_tokens': 39, 'prompt_tokens': 6}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('e32f31cb-ddc9-4863-8e6e-cb7a281a0ada'))\n",
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"What century did the Normans first gain their separate identity?\n",
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"generations=[[Generation(text='\\n\\nThe Normans first gained their separate identity in the 11th century.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 28, 'completion_tokens': 16, 'prompt_tokens': 12}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('da9d8f73-b3b3-4bc5-8495-da8b11462a51'))\n",
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"Who gave their name to Normandy in the 1000's and 1100's\n",
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"generations=[[Generation(text='\\n\\nThe Normans, a people from northern France, gave their name to Normandy in the 1000s and 1100s. The Normans were descended from Viking settlers who had come to the region in the late 800s.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 58, 'completion_tokens': 45, 'prompt_tokens': 13}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('bb5829bf-b6a6-4429-adfa-414ac5be46e5'))\n",
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"What is France a region of?\n",
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"generations=[[Generation(text='\\n\\nFrance is a region of Europe.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 16, 'completion_tokens': 9, 'prompt_tokens': 7}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('6943880b-b4e4-4c74-9ca1-8c03c10f7e9c'))\n",
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"Who did King Charles III swear fealty to?\n",
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"generations=[[Generation(text='\\n\\nKing Charles III swore fealty to Pope Innocent III.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 23, 'completion_tokens': 13, 'prompt_tokens': 10}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('c91fd663-09e6-4d00-b746-4c7fd96f9ceb'))\n",
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"When did the Frankish identity emerge?\n",
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"generations=[[Generation(text='\\n\\nThe Frankish identity began to emerge in the late 5th century, when the Franks began to expand their power and influence in the region. The Franks were a Germanic tribe that had migrated to the area from the east and had established a kingdom in what is now modern-day France. The Franks were eventually able to establish a powerful kingdom that lasted until the 10th century.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 86, 'completion_tokens': 78, 'prompt_tokens': 8}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('23f86775-e592-4cb8-baa3-46ebe74305b2'))\n",
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"Who was the duke in the battle of Hastings?\n",
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"generations=[[Generation(text='\\n\\nThe Duke of Normandy, William the Conqueror, was the leader of the Norman forces at the Battle of Hastings in 1066.', generation_info={'finish_reason': 'stop', 'logprobs': None})]] llm_output={'token_usage': {'total_tokens': 39, 'completion_tokens': 28, 'prompt_tokens': 11}, 'model_name': 'text-davinci-003'} run=RunInfo(run_id=UUID('ad5b7984-8758-4d95-a5eb-ee56e0218f6b'))\n"
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]
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}
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],
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"source": [
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"# Set your key here.\n",
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"# os.environ[\"OPENAI_API_KEY\"] = \"YOUR_API_KEY\"\n",
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"\n",
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"# Create callback handler. This logs latency, errors, token usage, prompts as well as prompt responses to Infino.\n",
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"handler = InfinoCallbackHandler(\n",
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" model_id=\"test_openai\", model_version=\"0.1\", verbose=False\n",
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")\n",
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"\n",
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"# Create LLM.\n",
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"llm = OpenAI(temperature=0.1)\n",
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"\n",
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"# Number of questions to ask the OpenAI model. We limit to a short number here to save $$ while running this demo.\n",
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"num_questions = 10\n",
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"\n",
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"questions = questions[0:num_questions]\n",
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"for question in questions:\n",
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" print(question)\n",
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"\n",
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" # We send the question to OpenAI API, with Infino callback.\n",
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" llm_result = llm.generate([question], callbacks=[handler])\n",
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" print(llm_result)"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "b68ec697-c922-4fd9-aad1-f49c6ac24e8a",
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"metadata": {},
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"source": [
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"## Create Metric Charts\n",
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"\n",
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"We now use matplotlib to create graphs of latency, errors and tokens consumed."
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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": 19,
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"id": "f078c612-89e0-4a1d-b1a8-bf36b664a10e",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
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"text/plain": [
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"<Figure size 600x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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",
|
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"text/plain": [
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"<Figure size 600x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
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"image/png": 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",
|
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"text/plain": [
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"<Figure size 600x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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",
|
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"text/plain": [
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"<Figure size 600x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
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"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 600x400 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Helper function to create a graph using matplotlib.\n",
|
|
"def plot(data, title):\n",
|
|
" data = json.loads(data)\n",
|
|
"\n",
|
|
" # Extract x and y values from the data\n",
|
|
" timestamps = [item[\"time\"] for item in data]\n",
|
|
" dates = [dt.datetime.fromtimestamp(ts) for ts in timestamps]\n",
|
|
" y = [item[\"value\"] for item in data]\n",
|
|
"\n",
|
|
" plt.rcParams[\"figure.figsize\"] = [6, 4]\n",
|
|
" plt.subplots_adjust(bottom=0.2)\n",
|
|
" plt.xticks(rotation=25)\n",
|
|
" ax = plt.gca()\n",
|
|
" xfmt = md.DateFormatter(\"%Y-%m-%d %H:%M:%S\")\n",
|
|
" ax.xaxis.set_major_formatter(xfmt)\n",
|
|
"\n",
|
|
" # Create the plot\n",
|
|
" plt.plot(dates, y)\n",
|
|
"\n",
|
|
" # Set labels and title\n",
|
|
" plt.xlabel(\"Time\")\n",
|
|
" plt.ylabel(\"Value\")\n",
|
|
" plt.title(title)\n",
|
|
"\n",
|
|
" plt.show()\n",
|
|
"\n",
|
|
"\n",
|
|
"response = client.search_ts(\"__name__\", \"latency\", 0, int(time.time()))\n",
|
|
"plot(response.text, \"Latency\")\n",
|
|
"\n",
|
|
"response = client.search_ts(\"__name__\", \"error\", 0, int(time.time()))\n",
|
|
"plot(response.text, \"Errors\")\n",
|
|
"\n",
|
|
"response = client.search_ts(\"__name__\", \"prompt_tokens\", 0, int(time.time()))\n",
|
|
"plot(response.text, \"Prompt Tokens\")\n",
|
|
"\n",
|
|
"response = client.search_ts(\"__name__\", \"completion_tokens\", 0, int(time.time()))\n",
|
|
"plot(response.text, \"Completion Tokens\")\n",
|
|
"\n",
|
|
"response = client.search_ts(\"__name__\", \"total_tokens\", 0, int(time.time()))\n",
|
|
"plot(response.text, \"Total Tokens\")"
|
|
]
|
|
},
|
|
{
|
|
"attachments": {},
|
|
"cell_type": "markdown",
|
|
"id": "c3d61822-1781-4bc6-97a2-2abc5c2b2e75",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Full text query on prompt or prompt outputs."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"id": "a0f051f0-e2bc-44e7-8dfb-bfd5bbd0fc9f",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Results for normandy : [{\"time\":1686821979,\"fields\":{\"prompt\":\"In what country is Normandy located?\"},\"text\":\"In what country is Normandy located?\"},{\"time\":1686821982,\"fields\":{\"prompt_response\":\"\\n\\nNormandy is located in France.\"},\"text\":\"\\n\\nNormandy is located in France.\"},{\"time\":1686821984,\"fields\":{\"prompt_response\":\"\\n\\nThe Normans first settled in Normandy in the late 9th century.\"},\"text\":\"\\n\\nThe Normans first settled in Normandy in the late 9th century.\"},{\"time\":1686821993,\"fields\":{\"prompt\":\"Who gave their name to Normandy in the 1000's and 1100's\"},\"text\":\"Who gave their name to Normandy in the 1000's and 1100's\"},{\"time\":1686821997,\"fields\":{\"prompt_response\":\"\\n\\nThe Normans, a people from northern France, gave their name to Normandy in the 1000s and 1100s. The Normans were descended from Viking settlers who had come to the region in the late 800s.\"},\"text\":\"\\n\\nThe Normans, a people from northern France, gave their name to Normandy in the 1000s and 1100s. The Normans were descended from Viking settlers who had come to the region in the late 800s.\"}]\n",
|
|
"===\n",
|
|
"Results for king charles III : [{\"time\":1686821998,\"fields\":{\"prompt\":\"Who did King Charles III swear fealty to?\"},\"text\":\"Who did King Charles III swear fealty to?\"},{\"time\":1686822000,\"fields\":{\"prompt_response\":\"\\n\\nKing Charles III swore fealty to Pope Innocent III.\"},\"text\":\"\\n\\nKing Charles III swore fealty to Pope Innocent III.\"}]\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Search for a particular prompt text.\n",
|
|
"query = \"normandy\"\n",
|
|
"response = client.search_log(query, 0, int(time.time()))\n",
|
|
"print(\"Results for\", query, \":\", response.text)\n",
|
|
"\n",
|
|
"print(\"===\")\n",
|
|
"\n",
|
|
"query = \"king charles III\"\n",
|
|
"response = client.search_log(\"king charles III\", 0, int(time.time()))\n",
|
|
"print(\"Results for\", query, \":\", response.text)"
|
|
]
|
|
},
|
|
{
|
|
"attachments": {},
|
|
"cell_type": "markdown",
|
|
"id": "4b171074-c775-48e0-a4b3-f550e2c8eccb",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Step 5: Stop infino server"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"id": "147663cb-b88f-4cfb-9726-7231dbec7cc1",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"infino-example\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"!docker rm -f infino-example"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "86f36c49-53a3-460d-b74b-995cda7726b3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.9.4"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|