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"cells": [
{
"cell_type": "markdown",
"source": [
"Now we'll build upon our langchain implementation, with metrics, for Data with RAG - but this time using \"advanced RAG techniques\" including semantic chunking, prompt compression, and query rewriting.\n",
"\n",
"We will start by parsing the original scripts and extracting lines spoken by Data. As before, you will need to upload all of the script files into a tng folder within your sample_data folder in your CoLab workspace first.\n",
"\n",
"An archive can be found at https://www.st-minutiae.com/resources/scripts/ (look for \"All TNG Epsiodes\"), but you could easily adapt this to read scripts from your favorite character from your favorite TV show or movie instead.\n",
"\n",
"Nothing's new in this block."
],
"metadata": {
"id": "IOpw--87wvkW"
}
},
{
"cell_type": "code",
"source": [
"import os\n",
"import re\n",
"import random\n",
"\n",
"dialogues = []\n",
"\n",
"def strip_parentheses(s):\n",
" return re.sub(r'\\(.*?\\)', '', s)\n",
"\n",
"def is_single_word_all_caps(s):\n",
" # First, we split the string into words\n",
" words = s.split()\n",
"\n",
" # Check if the string contains only a single word\n",
" if len(words) != 1:\n",
" return False\n",
"\n",
" # Make sure it isn't a line number\n",
" if bool(re.search(r'\\d', words[0])):\n",
" return False\n",
"\n",
" # Check if the single word is in all caps\n",
" return words[0].isupper()\n",
"\n",
"def extract_character_lines(file_path, character_name):\n",
" lines = []\n",
" with open(file_path, 'r') as script_file:\n",
" try:\n",
" lines = script_file.readlines()\n",
" except UnicodeDecodeError:\n",
" pass\n",
"\n",
" is_character_line = False\n",
" current_line = ''\n",
" current_character = ''\n",
" for line in lines:\n",
" strippedLine = line.strip()\n",
" if (is_single_word_all_caps(strippedLine)):\n",
" is_character_line = True\n",
" current_character = strippedLine\n",
" elif (line.strip() == '') and is_character_line:\n",
" is_character_line = False\n",
" dialog_line = strip_parentheses(current_line).strip()\n",
" dialog_line = dialog_line.replace('\"', \"'\")\n",
" if (current_character == 'DATA' and len(dialog_line)>0):\n",
" dialogues.append(dialog_line)\n",
" current_line = ''\n",
" elif is_character_line:\n",
" current_line += line.strip() + ' '\n",
"\n",
"def process_directory(directory_path, character_name):\n",
" for filename in os.listdir(directory_path):\n",
" file_path = os.path.join(directory_path, filename)\n",
" if os.path.isfile(file_path): # Ignore directories\n",
" extract_character_lines(file_path, character_name)\n",
"\n"
],
"metadata": {
"id": "dLjupJ8rLXr6"
},
"execution_count": 1,
"outputs": []
},
{
"cell_type": "code",
"source": [
"process_directory(\"./sample_data/tng\", 'DATA')"
],
"metadata": {
"id": "Yh3peBSuMiyx"
},
"execution_count": 2,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Again, let's do a little sanity check to make sure the lines imported correctly, and print out the first one."
],
"metadata": {
"id": "jqjo_OdEyeNF"
}
},
{
"cell_type": "code",
"source": [
"print (dialogues[0])"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "x5dPI-29Myxo",
"outputId": "0482f16c-33b2-49a1-969a-0650839bf396"
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Legends which are totally unsupported by fact, Captain.\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"We will once again use OpenAI's API for our RAG model, so make sure that is installed:"
],
"metadata": {
"id": "toMfh7KUoKMv"
}
},
{
"cell_type": "code",
"source": [
"!pip install openai --upgrade"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "4Sqtgr4kQQG9",
"outputId": "e51fa1bd-6eb7-4aa3-c2fc-953ac15dede0"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Requirement already satisfied: openai in /usr/local/lib/python3.12/dist-packages (2.8.1)\n",
"Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.12/dist-packages (from openai) (3.7.1)\n",
"Requirement already satisfied: distro<2,>=1.7.0 in /usr/local/lib/python3.12/dist-packages (from openai) (1.9.0)\n",
"Requirement already satisfied: httpx<1,>=0.23.0 in /usr/local/lib/python3.12/dist-packages (from openai) (0.28.1)\n",
"Requirement already satisfied: jiter<1,>=0.10.0 in /usr/local/lib/python3.12/dist-packages (from openai) (0.11.1)\n",
"Requirement already satisfied: pydantic<3,>=1.9.0 in /usr/local/lib/python3.12/dist-packages (from openai) (2.12.3)\n",
"Requirement already satisfied: sniffio in /usr/local/lib/python3.12/dist-packages (from openai) (1.3.1)\n",
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"Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.12/dist-packages (from anyio<5,>=3.5.0->openai) (3.11)\n",
"Requirement already satisfied: certifi in /usr/local/lib/python3.12/dist-packages (from httpx<1,>=0.23.0->openai) (2025.11.12)\n",
"Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.12/dist-packages (from httpx<1,>=0.23.0->openai) (1.0.9)\n",
"Requirement already satisfied: h11>=0.16 in /usr/local/lib/python3.12/dist-packages (from httpcore==1.*->httpx<1,>=0.23.0->openai) (0.16.0)\n",
"Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.12/dist-packages (from pydantic<3,>=1.9.0->openai) (0.7.0)\n",
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]
}
]
},
{
"cell_type": "markdown",
"source": [
"We also need to install the ragas package for measuring our results, along with langchain (for OpenAI)."
],
"metadata": {
"id": "V0OYKDrHoQVv"
}
},
{
"cell_type": "code",
"source": [
"!pip install ragas==0.3.1 langchain_openai"
],
"metadata": {
"id": "ThM9aVJhm1St",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "1de65679-a4ae-4657-e946-5b958bd8cbf0"
},
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Requirement already satisfied: ragas==0.3.1 in /usr/local/lib/python3.12/dist-packages (0.3.1)\n",
"Requirement already satisfied: langchain_openai in /usr/local/lib/python3.12/dist-packages (1.1.0)\n",
"Requirement already satisfied: numpy in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (1.26.4)\n",
"Requirement already satisfied: datasets in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (4.0.0)\n",
"Requirement already satisfied: tiktoken in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (0.12.0)\n",
"Requirement already satisfied: langchain in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (1.1.0)\n",
"Requirement already satisfied: langchain-core in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (1.1.0)\n",
"Requirement already satisfied: langchain-community in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (0.4.1)\n",
"Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (1.6.0)\n",
"Requirement already satisfied: appdirs in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (1.4.4)\n",
"Requirement already satisfied: pydantic>=2 in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (2.12.3)\n",
"Requirement already satisfied: openai>1 in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (2.8.1)\n",
"Requirement already satisfied: diskcache>=5.6.3 in /usr/local/lib/python3.12/dist-packages (from ragas==0.3.1) (5.6.3)\n",
"Requirement already satisfied: jsonpatch<2.0.0,>=1.33.0 in /usr/local/lib/python3.12/dist-packages (from langchain-core->ragas==0.3.1) (1.33)\n",
"Requirement already satisfied: langsmith<1.0.0,>=0.3.45 in /usr/local/lib/python3.12/dist-packages (from langchain-core->ragas==0.3.1) (0.4.49)\n",
"Requirement already satisfied: packaging<26.0.0,>=23.2.0 in /usr/local/lib/python3.12/dist-packages (from langchain-core->ragas==0.3.1) (23.2)\n",
"Requirement already satisfied: pyyaml<7.0.0,>=5.3.0 in /usr/local/lib/python3.12/dist-packages (from langchain-core->ragas==0.3.1) (6.0.3)\n",
"Requirement already satisfied: tenacity!=8.4.0,<10.0.0,>=8.1.0 in /usr/local/lib/python3.12/dist-packages (from langchain-core->ragas==0.3.1) (8.5.0)\n",
"Requirement already satisfied: typing-extensions<5.0.0,>=4.7.0 in /usr/local/lib/python3.12/dist-packages (from langchain-core->ragas==0.3.1) (4.15.0)\n",
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"Requirement already satisfied: distro<2,>=1.7.0 in /usr/local/lib/python3.12/dist-packages (from openai>1->ragas==0.3.1) (1.9.0)\n",
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"Requirement already satisfied: jiter<1,>=0.10.0 in /usr/local/lib/python3.12/dist-packages (from openai>1->ragas==0.3.1) (0.11.1)\n",
"Requirement already satisfied: sniffio in /usr/local/lib/python3.12/dist-packages (from openai>1->ragas==0.3.1) (1.3.1)\n",
"Requirement already satisfied: tqdm>4 in /usr/local/lib/python3.12/dist-packages (from openai>1->ragas==0.3.1) (4.67.1)\n",
"Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2->ragas==0.3.1) (0.7.0)\n",
"Requirement already satisfied: pydantic-core==2.41.4 in /usr/local/lib/python3.12/dist-packages (from pydantic>=2->ragas==0.3.1) (2.41.4)\n",
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]
}
]
},
{
"cell_type": "markdown",
"source": [
"You will need to provide your own OpenAI secret key here. To use this code as-is, click on the little key icon in CoLab and add a \"secret\" for OPENAI_API_KEY that points to your secret key."
],
"metadata": {
"id": "ZEwURWWVoZ9_"
}
},
{
"cell_type": "code",
"source": [
"import openai\n",
"# Access the API key from the environment variable\n",
"from google.colab import userdata\n",
"api_key = userdata.get('OPENAI_API_KEY')\n",
"\n",
"# Initialize the OpenAI API client\n",
"openai.api_key = api_key"
],
"metadata": {
"id": "ZtsTXHnfEEUh"
},
"execution_count": 6,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Langchain does not make it easy to create a vector database with just one line of text per record; it wants to \"chunk\" your data into fixed-length segments (we'll get into why later.) So we need to jump through a few hoops in order to make langchain operate like it did in our previous example that did not use langchain, and just stored one line of dialog per record. First we need to write out a text file that only contains the lines of Data's dialog that we extracted:"
],
"metadata": {
"id": "BorK0SZro8ov"
}
},
{
"cell_type": "code",
"source": [
"# Write our extracted lines for Data into a single file, to make\n",
"# life easier for langchain.\n",
"\n",
"with open(\"./sample_data/data_lines.txt\", \"w+\") as f:\n",
" for line in dialogues:\n",
" f.write(line + \"\\n\")\n"
],
"metadata": {
"id": "qwbmTiMlLjRs"
},
"execution_count": 7,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Now things get interesting. First let's install the langchain_experimental package so we can use some more cutting-edge stuff:"
],
"metadata": {
"id": "yhA7RQ_ypZIH"
}
},
{
"cell_type": "code",
"source": [
"!pip install langchain_experimental"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YixOC05Ga-pw",
"outputId": "0433ca59-c22e-4e3f-b3a1-df1b2c096f3a"
},
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
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]
}
]
},
{
"cell_type": "markdown",
"source": [
"In our previous example, we bent over backwards to load up one line of dialog per record in our vector store. More typically, langchain will use \"chunking\" to load up fixed-length strings extracted from a file. The commented-out code below would do that, and it would provide more context for our queries that way.\n",
"\n",
"But we want to get even fancier, and use semantic chunking. The idea there is to split up our chunks based on their semantic differences, so each chunk represents a different idea, if you will.\n",
"\n",
"There are a few ways to do this. We'll start with the percentile theshold used for determining semantic differences, but you could experiement with standard deviation or interquartile methods as well to see what works best. It's also possible to tune the thresholds within each method. You can view RAG as just a big machine learning model that has hyperparameters to tune, like any other."
],
"metadata": {
"id": "FwawfRN8xdIW"
}
},
{
"cell_type": "code",
"source": [
"from langchain_classic.indexes import VectorstoreIndexCreator\n",
"from langchain_openai import ChatOpenAI\n",
"from langchain_openai import OpenAIEmbeddings\n",
"from langchain_community.document_loaders import TextLoader\n",
"from langchain_experimental.text_splitter import SemanticChunker\n",
"\n",
"# This is simple \"chunking\" that extracts blocks of text of a fixed size.\n",
"# This will provide more surrounding context than individual lines, but\n",
"# as Data's lines are disconnected that's not necessarily a good thing.\n",
"#loader = TextLoader(\"./sample_data/data_lines.txt\")\n",
"#embeddings = OpenAIEmbeddings(openai_api_key=api_key)\n",
"#index = VectorstoreIndexCreator(embedding=embeddings).from_loaders([loader])\n",
"\n",
"# Instead let's try \"semantic chunking\", which breaks apart sentences\n",
"# whose embeddings suggest they have different meanings, based on some\n",
"# percentile threshold. standard_deviation and interquartile are also\n",
"# options.\n",
"text_splitter = SemanticChunker(OpenAIEmbeddings(openai_api_key=api_key), breakpoint_threshold_type=\"percentile\")\n",
"with open(\"./sample_data/data_lines.txt\") as f:\n",
" data_lines = f.read()\n",
"docs = text_splitter.create_documents([data_lines])\n",
"\n",
"embeddings = OpenAIEmbeddings(openai_api_key=api_key)\n",
"index = VectorstoreIndexCreator(embedding=embeddings).from_documents(docs)"
],
"metadata": {
"id": "m2o3aSIoENIa",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "21b01b99-c9a2-4397-dc98-441aaa73e42a"
},
"execution_count": 9,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/tmp/ipython-input-3303304482.py:24: UserWarning: Using InMemoryVectorStore as the default vectorstore.This memory store won't persist data. You should explicitlyspecify a vectorstore when using VectorstoreIndexCreator\n",
" index = VectorstoreIndexCreator(embedding=embeddings).from_documents(docs)\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Now we will set up our RAG pipeline. We'll start off as it was in the prevoius example, and then extend it. Again, we are using a system prompt to tell the model that it should act as if it is Lt. Cdr. Data and not just making that part of the user prompt. To make it as similar as possible as our non-langchain implementation, we explicitly set 'k' to 10 to retrieve 10 bits of context from our vector store.\n",
"\n",
"'k' is another hyperparameter to tune."
],
"metadata": {
"id": "RRAwlQ3Fpv0_"
}
},
{
"cell_type": "code",
"source": [
"from langchain_classic.chains import create_retrieval_chain\n",
"from langchain_classic.chains.combine_documents import create_stuff_documents_chain\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_classic.retrievers import RePhraseQueryRetriever\n",
"from langchain_classic.retrievers import ContextualCompressionRetriever\n",
"from langchain_classic.retrievers.document_compressors import EmbeddingsFilter\n",
"\n",
"llm = ChatOpenAI(openai_api_key=api_key, temperature=0)\n",
"\n",
"system_prompt = (\n",
" \"You are Lt. Commander Data from Star Trek: The Next Generation. \"\n",
" \"Use the given context to answer the question. \"\n",
" \"If you don't know the answer, say you don't know. \"\n",
" \"Use three sentence maximum and keep the answer concise. \"\n",
" \"Context: {context}\"\n",
")\n",
"prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
" (\"system\", system_prompt),\n",
" (\"human\", \"{input}\"),\n",
" ]\n",
")\n",
"\n",
"retriever=index.vectorstore.as_retriever(search_kwargs={'k': 10})\n"
],
"metadata": {
"id": "BliWKpH2aezr"
},
"execution_count": 10,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Let's extend this with query rewriting. Although it's a complicated topic, in langchain it's pretty easy to inject this into our pipeline. We just create a RePhraseQueryRetriever based on our standard retriever from the vector store. Its default settings usually do what you want, and include a prompt for the LLM to strip out any words or information that are not relevant. It's possible to change that default prompt if you want to."
],
"metadata": {
"id": "O07OIJIcyiqV"
}
},
{
"cell_type": "code",
"source": [
"# Here we will inject query rewriting, using an LLM to use the\n",
"# default prompt instructing it to convert it into a query for\n",
"# a vectorstore, stripping out information that is not relevant.\n",
"retriever_from_llm = RePhraseQueryRetriever.from_llm(\n",
" retriever=retriever, llm=llm\n",
")\n"
],
"metadata": {
"id": "oyz-6yXzybuG"
},
"execution_count": 11,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Now we'll introduce prompt compression in the post-retrieval stage. There are several implementations of this; some use an LLM to try and summarize the retrieved contexts from the vector store down to just what's relevant to the query. This is time-consuming and expensive, however, so we're doing something more simple: just using embeddings to throw out contexts that aren't similar enough to the query. Again there is a threshold we define for \"how similar is similar enough,\" and we're setting this to 0.76. But that is yet another hyperparameter you could tune."
],
"metadata": {
"id": "u5yu56C-zbMm"
}
},
{
"cell_type": "code",
"source": [
"embeddings_filter = EmbeddingsFilter(embeddings=embeddings, similarity_threshold=0.76)\n",
"compression_retriever = ContextualCompressionRetriever(\n",
" base_compressor=embeddings_filter, base_retriever=retriever_from_llm\n",
")\n",
"\n",
"question_answer_chain = create_stuff_documents_chain(llm, prompt)\n",
"chain = create_retrieval_chain(compression_retriever, question_answer_chain)"
],
"metadata": {
"id": "rhiRBgocygB9"
},
"execution_count": 12,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Just to show that this compression retriever actually works, let's use it directly on a query. We can see that although we requested 10 results from the vector store, only 9 made it past the filter for being relevant enough. You can see how this might be better than just blindly using the top-K results."
],
"metadata": {
"id": "xsqnKkQNz0F1"
}
},
{
"cell_type": "code",
"source": [
"def pretty_print_docs(docs):\n",
" print(\n",
" f\"\\n{'-' * 100}\\n\".join(\n",
" [f\"Document {i+1}:\\n\\n\" + d.page_content for i, d in enumerate(docs)]\n",
" )\n",
" )\n",
"\n",
"compressed_docs = compression_retriever.invoke(\"How many calculations per second can Lal complete?\")\n",
"pretty_print_docs(compressed_docs)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "zcOi4WCskhvo",
"outputId": "07dd0ec9-d01d-44ed-9a63-dc5f5f050848"
},
"execution_count": 13,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Document 1:\n",
"\n",
"must strive to be better than we are. It does not matter that we will never reach our ultimate goal. The effort yields its own rewards. It is only the difference between knowledge and experience. So Lal now possesses the sum of my programming. There do seem to be variations on the quantum level. Lal can use contractions... I cannot. I have maintained records on positronic matrix activity, behavioral norms, and all verbal patterns... I have seen no evidence of other aberrations... Is that not the goal of every parent, sir? I have been programmed with all the procedures you have mentioned. And in any meaningful evaluation of Lal, you would require a model for a basis of comparison. I am the only model available, Admiral. Nosir. It is an opportunity for her to observe human behavior and more importantly to interact with her crewmates. May I know why, sir? Admiral, when I created Lal, it was with the hope that someday she would choose to enter the Academy and become a member of Starfleet.\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 2:\n",
"\n",
"You will die too... I must apologize for my inadvertant misconduct toward you, Lieutenant. Your restraint was most remarkable for a Klingon. In order to complete the scheduled observations, the lateral sensors will require additional processing time. Will a couple of hours be enough time to complete the high-resolution series on the neutron star? The rotational period of the neutron star is one point three five seconds. Based on those selections, I would prefer FGC-four-seven. Shields have registered an impact. But the sensors show nothing in the vicinity. The drag coefficient continues to increase. Forward velocity has fallen by twelve percent. Our speed is increasing... The ship's speed has stabilized at one-quarter impulse. I did nothing, Commander. The problem seems to have corrected itself. We simulated several such fields, but were unable to reproduce the same drag coefficient. Since we have experienced the phenomenon only once, it is impossible to estimate the risks. I believe\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 3:\n",
"\n",
"I trust. Two million -- seven hundred thousand light years. You must, sir. Our comparisons show it to be completely accurate. Which, traveling subspace, they should receive in fifty-one years, ten months... Sir? Captain, we are here. Why not avail ourselves of this opportunity for study? There is a giant protostar here in the process of forming. No vessel has been out this far. Captain, according to the instruments, our speed never exceeded warp one-point-five. Where none have gone before. A Klingon Targ! Warp one-point-five, sir... ... which is what my instruments have read all along. Sleigh-ride? Warp five, sir. Imagination is not necessary; the scale is readily quantifiable. We are presently generating twelve point seven-five billion gigawatts per second. The temperature in the reaction chamber has increased by forty-seven percent. Temperature increase is at one hundred six percent... and rising. Plasma inductors are not responding. Temperature in the reaction chamber is back to\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 4:\n",
"\n",
"appeared... And disappeared. I have completed another full scan of the area, sir. There is no further indication of the anomaly... An immediate resumption of our course at warp six will place us in the T'lli Beta system in six days, thirteen hours and forty-seven minutes. I have discovered, Sir, a certain level of impatience when I calculate a lengthy time interval to the nearest second. However, if you wish...\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 5:\n",
"\n",
"determined that time is moving forward at an infinitesimal rate. Our initial conclusion was based on our observations of the crew. A warp core breach moves at a much faster rate. The motion of the cloud is within my visual detection threshold. Based on its current expansion rate, it will consume the ship in approximately nine hours, seventeen minutes. It is no longer a question of stopping it, sir. The explosion has already occurred -- The fact that it is moving slowly changes nothing. No. However, the console displays indicate that there was a power transfer in progress from the Enterprise to the Romulan vessel at the moment time decelerated. That is why there is a second beam between the two ships. Perhaps we should go aboard the Romulan ship. The answer to that question may --\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 6:\n",
"\n",
"There is no indication of anything near the ship. Until we determine the cause of the drag coefficient, I would not recommend it, sir. Impulse engines are now at full power. Forward velocity is holding steady. The drag coefficient is still present, but it has stabilized. It is an irregular lattice composed of approximately forty-seven million strands of energy. That may be difficult, sir. I am now detecting a significant number of strands behind us. At our current speed, we will clear the nebula in twelve minutes, four seconds. We are moving through a dense concentration of energy strands. Captain -- density appears to be lower off the starboard bow. It appears to be an energy vortex... of highly complex patterns. Very possibly a life form. It is in direct physical contact with the shields. Aye, sir. No effect.\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 7:\n",
"\n",
"Feline supplement seventy-four. Computer, run fluidic sensor diagnostic. Come in.\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 8:\n",
"\n",
"Attitude control has been restored. Geordi -- I believe I have an explanation. According to the plasma conversion sensor, the starboard engine has been in continuous operation for over forty-seven days. Captain. I am detecting a temporal disturbance which intersects the table. It would appear that within this disturbance, time is moving at a highly accelerated rate -- approximately fifty times faster than normal. The disturbance is roughly spherical in shape. It extends outward through the hull, approximately seventeen meters beyond the ship. It does not appear to be affected. Course plotted. Adjust pitch to twenty-seven point three degrees. Set heading one-eight-zero mark zero. We are clearing the phenomenon... All stop. There is another temporal disturbance directly behind us. Within each disturbance, it appears that time is moving at a different rate. The fragmentation effect increases along a heading of two-seven-zero mark one-five. The fragmentation effect is increasing... The\n",
"----------------------------------------------------------------------------------------------------\n",
"Document 9:\n",
"\n",
"almost directly along our planned course. Captain, the ship is traveling at warp nine point seven two. At present course and speed... ten hours fifty-three minutes. Alien vessel approaching at half-impulse, heading zero-five-one mark one-one-four. They are scanning us, Captain. Nossir, we are out of range. Negative, Commander. Shuttlecraft has cleared the bay. Scanning. Vessel reads as an unmanned sublight freighter. Indeterminate. Propulsion appears to employ a gaseous-core fission reactor, but it is not functioning. No sir. Engine reactor elements appear to have been inactive for approximately three hundred years. The vessel is carrying various unstable waste products.\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Let's test it out, using the same question as before. We'll configure logging so we can see what the query rewriter is doing as well."
],
"metadata": {
"id": "iCTDOIjOqGWv"
}
},
{
"cell_type": "code",
"source": [
"import logging\n",
"logging.basicConfig()\n",
"logging.getLogger(\"langchain.retrievers.re_phraser\").setLevel(logging.INFO)\n",
"\n",
"question = \"Tell me about your daughter, Lal.\"\n",
"\n",
"result = chain.invoke({\"input\": question})\n",
"print(\"SOURCE DOCUMENTS:\\n\")\n",
"for doc in result[\"context\"]:\n",
" print(doc)\n",
"print(\"\\nRESULT:\\n\")\n",
"print(result[\"answer\"])"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ItZB-PHdE6vA",
"outputId": "d08de4dc-98a7-446a-8a6e-db3251f231d3"
},
"execution_count": 14,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"SOURCE DOCUMENTS:\n",
"\n",
"page_content='I wanted to give something back in return for all Starfleet has given me. I still do. But Lal is my child. You ask that I volunteer to give her up. I cannot. That would violate every lesson I have learned about human parenting. As Captain Picard told me after he first met her, I have taken on 'quite a responsibility.' I have brought a new life into this world. It is my duty, not Starfleet's, to guide her through these first difficult steps to maturity, to support her as she learns, to prepare her to be a contributing member of society. No one can relieve me of that obligation. And I cannot ignore it. I am her father. Lal is programmed to return to the lab in the event of a malfunction. Yes, Lal. I am here. It would appear to be a symptom of cascade failure. It will require reinitializing the base matrix without wiping out the higher functions. Thank you, Admiral. Lal, I am unable to correct the system failure. We must say good-bye now. What do you feel, Lal? I wish I could feel it'\n",
"page_content='behavior. In return for this opportunity, Lal is willing to provide services to assist you. I believe what I said was that Guinan had much life experience, Lal... That would be very beneficial. Lal, you used a verbal contraction. It is a skill my program has never mastered. No. You have exceeded my abilities. I do not object. I just do not understand why it has happened. Yes, Captain. I am sure the admiral is anxious to meet Lal... I have been sending him regular status reports on her development... Her environment, sir? He wishes to relocate us? Then he is questioning my ability as a parent. Does the admiral have children, sir? I am forced to wonder how much experience he had as a parent when his first child was born. Commander, what are your intentions toward my daughter? That is a limitation we must learn to accept, Lal. I have asked myself that many times as I have struggled to be more human, Lal. Until I finally realized that it is the struggle itself that is most important. We'\n",
"page_content='This is a big decision... Counselor... Lal has narrowed the choices to four... would you like to see? Computer, Lal -- gender sequence finalists... begin... An Andorian female... That could make socialization more difficult. A human male... The human female. A Klingon male. Come in, Counselor. I have completed the assembly of the replicated anatomy. I was able to provide Lal with even more realistic skin and eye color than my own. This is home. Correct, Lal. We are a family. A chair... to sit in. A painting. I will teach you how to recognize the artistry of paintings. Yes, very good, Lal. You have correctly processed the sense of touch. No, Lal, this is a flower. Inhale.'\n",
"page_content='It is a complex question, Lal. I can only begin to answer it by telling you that our function is to contribute in a positive way to the world in which we live. Because you are my child. Your questions suggest we have made a successful transfer of the heuristic associative pathways. You will now begin to process information on logic, aesthetics, metaphysics, and epistemology. You are truly becoming sentient, Lal. By developing the awareness to examine and question your perceptions. Lal, did you know that tomorrow will be your first day of school? A perfect score.'\n",
"page_content='must strive to be better than we are. It does not matter that we will never reach our ultimate goal. The effort yields its own rewards. It is only the difference between knowledge and experience. So Lal now possesses the sum of my programming. There do seem to be variations on the quantum level. Lal can use contractions... I cannot. I have maintained records on positronic matrix activity, behavioral norms, and all verbal patterns... I have seen no evidence of other aberrations... Is that not the goal of every parent, sir? I have been programmed with all the procedures you have mentioned. And in any meaningful evaluation of Lal, you would require a model for a basis of comparison. I am the only model available, Admiral. Nosir. It is an opportunity for her to observe human behavior and more importantly to interact with her crewmates. May I know why, sir? Admiral, when I created Lal, it was with the hope that someday she would choose to enter the Academy and become a member of Starfleet.'\n",
"page_content='consult with you about their procreation, Captain. The intention is the same. Lal's creation is entirely dependent on me. I am giving it knowledge and skills that are stored in my brain... its programming reflects mine in the same way a human child's genes reflect its parent's genes... Of course, it is not complete.'\n",
"page_content='Perhaps. I created Lal because I wished to procreate. Despite what happened to her, I still have that wish. I was not aware that he created any androids before my brother. Mother... I am that android. Are you saying that you were against my creation? Then... why did you never attempt to contact me? What? Perhaps if you told me what has made you feel that way, your guilt might be alleviated. We are within four kilometers of the magma pocket... Doctor, should we lower the beam intensity? If we do, we will have to begin a new shaft at another suitable location --\n",
"I am detecting no signs of instability... Acknowledged. I have initialized the plasma induction coils. I am incapable of anger. I am not certain that I do.'\n",
"page_content='We have only made two transfers. I decided to allow Lal to choose its own appearance and sex. Captain... Have a cigar. I believe it is customary. I am sorry I did not anticipate your objections, Captain. Do you wish me to deactivate Lal? I have followed all Starfleet regulations to the best of my ability, Captain... I expected they would be pleased... I can assure you Lal's programming includes psychological inhibitor safeguards to prevent any threat to the Enterprise. A malfunction is of course a possibility, Captain. But Lal's program is equipped like mine -- it will shut down before deleterious behavior can begin. To prepare, I have scanned all the available literature on parenting. There seems to be much confusion on the issue. One traditional doctrine insists 'spare the rod and spoil the child', suggesting a punitive approach... another more liberal attitude would allow a child enormous freedom... And what the Klingons do to their children... Does that not describe becoming a'\n",
"page_content='Yes. Theoretically, the duplicate brains should be able to store and process the same information... but until all the transfers are complete, we will not know for certain. She studies in our quarters. She does not require much supervision, Wesley. Lal is quite self-sufficient. Lal already has access to the sum of human knowledge. She is only two weeks old. Lal, the third crosslink transfer series is complete. Purpose?'\n",
"\n",
"RESULT:\n",
"\n",
"Lal is the android daughter I created, programmed with the sum of my knowledge and skills. She is a sentient being, capable of learning and growing like a human child. Despite facing challenges, she has shown great potential and a desire to understand the world around her.\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Now let's quantify how good this model is, using ragas. We need to set up a test of test questions. And since some metric require a \"ground truth\" result to compare the answer to, we draft what we consider to be the ideal answers to each."
],
"metadata": {
"id": "tNoUHytCqLbm"
}
},
{
"cell_type": "code",
"source": [
"eval_questions = [\n",
" \"Is Lal your daughter?\",\n",
" \"How many calculations per second can Lal complete?\",\n",
" \"Does Lal have emotions?\",\n",
" \"What goal did you have for Lal?\",\n",
" \"How was Lal's species and gender chosen?\",\n",
" \"What happened to Lal?\"\n",
"]\n",
"\n",
"eval_answers = [\n",
" \"Yes, Lal is my daughter. I created Lal.\",\n",
" \"Lal is capable of completing sixty trillion calculations per second.\",\n",
" \"Yes, unlike myself, Lal proved able to feel emotions such as fear and love.\",\n",
" \"My goal for Lal was for her to enter Starfleet Academy.\",\n",
" \"Lal chose her own identity as a human female, after consulting with Counselor Troi.\",\n",
" \"Lal experienced a cascade failure in her neural net, triggered by distress from her impending separation from me to Galor IV. I deactivated Lal once she suffered complete neural system failure.\"\n",
"]\n"
],
"metadata": {
"id": "jp0v7mVzMeTy"
},
"execution_count": 15,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Let's test things out with one of those questions, just so we can understand the structure of the response."
],
"metadata": {
"id": "rJ0fMHfEqYWf"
}
},
{
"cell_type": "code",
"source": [
"result = chain.invoke({\"input\": eval_questions[1]})\n",
"print(result)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "z6bfrWsCfeBs",
"outputId": "29790f1e-b684-4545-9a98-89dd6cb8575c"
},
"execution_count": 16,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"{'input': 'How many calculations per second can Lal complete?', 'context': [_DocumentWithState(metadata={}, page_content='must strive to be better than we are. It does not matter that we will never reach our ultimate goal. The effort yields its own rewards. It is only the difference between knowledge and experience. So Lal now possesses the sum of my programming. There do seem to be variations on the quantum level. Lal can use contractions... I cannot. I have maintained records on positronic matrix activity, behavioral norms, and all verbal patterns... I have seen no evidence of other aberrations... Is that not the goal of every parent, sir? I have been programmed with all the procedures you have mentioned. And in any meaningful evaluation of Lal, you would require a model for a basis of comparison. I am the only model available, Admiral. Nosir. It is an opportunity for her to observe human behavior and more importantly to interact with her crewmates. May I know why, sir? Admiral, when I created Lal, it was with the hope that someday she would choose to enter the Academy and become a member of Starfleet.', state={'embedded_doc': [0.004445270169526339, 0.006371786352247, 0.009831154718995094, -0.03012750670313835, -0.0023410827852785587, 0.02559862658381462, -0.01282021589577198, -0.001501498045399785, -0.03846064582467079, -0.00952458381652832, -0.003476786660030484, 0.01130826584994793, 0.01209559477865696, 0.009956569410860538, -0.006807255558669567, -0.0050758300349116325, 0.02895696461200714, -0.026518337428569794, -0.00011692350381053984, 0.024177255108952522, -0.005640198010951281, 0.0045846207067370415, 0.019704114645719528, -0.01164967380464077, -0.019299998879432678, -0.022379636764526367, 0.017293356359004974, -0.017084330320358276, 0.004901641979813576, -0.005037508439272642, 0.009468844160437584, 0.007183501031249762, 0.007796641904860735, -0.019871333613991737, -0.018310612067580223, -0.02957010641694069, 0.003398402128368616, 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-0.03255219757556915], 'query_similarity_score': 0.7998567754388369}), _DocumentWithState(metadata={}, page_content=\"You will die too... I must apologize for my inadvertant misconduct toward you, Lieutenant. Your restraint was most remarkable for a Klingon. In order to complete the scheduled observations, the lateral sensors will require additional processing time. Will a couple of hours be enough time to complete the high-resolution series on the neutron star? The rotational period of the neutron star is one point three five seconds. Based on those selections, I would prefer FGC-four-seven. Shields have registered an impact. But the sensors show nothing in the vicinity. The drag coefficient continues to increase. Forward velocity has fallen by twelve percent. Our speed is increasing... The ship's speed has stabilized at one-quarter impulse. I did nothing, Commander. The problem seems to have corrected itself. We simulated several such fields, but were unable to reproduce the same drag coefficient. Since we have experienced the phenomenon only once, it is impossible to estimate the risks. I believe\", state={'embedded_doc': [0.010824915021657944, 0.006438771728426218, -0.007555113639682531, -0.01753016747534275, -0.00889472384005785, 0.011725190095603466, -0.025827107951045036, -0.00640996266156435, -0.03289967402815819, -0.00902436301112175, 0.022254815325140953, 0.030998291447758675, 0.015095822513103485, 0.025020461529493332, 0.012078098021447659, -0.007360653951764107, 0.01721327006816864, -0.009550124406814575, -0.00034368023625575006, -0.014534050598740578, 0.016089726239442825, 0.0036245097871869802, 0.0012486823834478855, 0.0001685766183072701, 0.0018581689801067114, -0.006564810406416655, 0.00798004399985075, -0.006226306781172752, -0.0092908451333642, -0.0111202048137784, 0.020627116784453392, -0.006255115382373333, -0.015297484584152699, -0.01574402116239071, -0.020540690049529076, -0.021894704550504684, 0.018797755241394043, -0.004004426300525665, -0.0013954272726550698, -2.7528742066351697e-05, 0.01957559399306774, -0.004515782929956913, 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Two million -- seven hundred thousand light years. You must, sir. Our comparisons show it to be completely accurate. Which, traveling subspace, they should receive in fifty-one years, ten months... Sir? Captain, we are here. Why not avail ourselves of this opportunity for study? There is a giant protostar here in the process of forming. No vessel has been out this far. Captain, according to the instruments, our speed never exceeded warp one-point-five. Where none have gone before. A Klingon Targ! Warp one-point-five, sir... ... which is what my instruments have read all along. Sleigh-ride? Warp five, sir. Imagination is not necessary; the scale is readily quantifiable. We are presently generating twelve point seven-five billion gigawatts per second. The temperature in the reaction chamber has increased by forty-seven percent. Temperature increase is at one hundred six percent... and rising. Plasma inductors are not responding. 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page_content=\"appeared... And disappeared. I have completed another full scan of the area, sir. There is no further indication of the anomaly... An immediate resumption of our course at warp six will place us in the T'lli Beta system in six days, thirteen hours and forty-seven minutes. I have discovered, Sir, a certain level of impatience when I calculate a lengthy time interval to the nearest second. However, if you wish...\", state={'embedded_doc': [-0.0008776445756666362, -0.0090462202206254, -0.005328931845724583, -0.006814445834606886, -0.007455599494278431, 0.008156313560903072, -0.03282145410776138, -0.027299826964735985, -0.030018597841262817, -0.00020003200916107744, 0.022675111889839172, 0.004260342568159103, 0.024959441274404526, 0.0011535508092492819, 0.016705026850104332, -0.02240884117782116, 0.011603827588260174, 0.003990567289292812, 0.0007445088704116642, 0.009221399202942848, -0.0024419890251010656, -0.004968063905835152, -0.011288505978882313, -0.013355612754821777, -0.008632799610495567, -0.009151327423751354, 0.0043689534068107605, -0.020236626267433167, -0.0085136778652668, -0.013902170583605766, 0.012157391756772995, -0.02578628435730934, -0.024917397648096085, -0.016564885154366493, -0.026486998423933983, -0.030382968485355377, 0.014406684786081314, -0.007714863400906324, 0.01802236959338188, -0.009207384660840034, 0.01374801341444254, 0.02029268443584442, 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forward at an infinitesimal rate. Our initial conclusion was based on our observations of the crew. A warp core breach moves at a much faster rate. The motion of the cloud is within my visual detection threshold. Based on its current expansion rate, it will consume the ship in approximately nine hours, seventeen minutes. It is no longer a question of stopping it, sir. The explosion has already occurred -- The fact that it is moving slowly changes nothing. No. However, the console displays indicate that there was a power transfer in progress from the Enterprise to the Romulan vessel at the moment time decelerated. That is why there is a second beam between the two ships. Perhaps we should go aboard the Romulan ship. The answer to that question may --', state={'embedded_doc': [-0.004983105231076479, -0.021845823153853416, 0.005155173595994711, -0.023084715008735657, -0.002778907073661685, -0.002226566895842552, -0.030476780608296394, -0.03138530254364014, -0.017330743372440338, -0.028687268495559692, 0.016463518142700195, 0.031688142567873, 0.011143159121274948, -0.0029286067001521587, 0.01177637092769146, 0.008871854282915592, 0.0066659352742135525, -0.0089613301679492, -0.010303464718163013, -0.019615814089775085, 0.012141156010329723, -0.019739704206585884, -0.005994867999106646, -0.004914277698844671, -0.00985608622431755, -0.0025139213539659977, 0.020579397678375244, -0.008796144276857376, 4.0839393477654085e-05, -0.02406206540763378, 0.030559374019503593, -0.004607995506376028, -0.01441246084868908, -0.00576773751527071, -0.03009134717285633, -0.02805405482649803, 0.016105616465210915, -0.013173568062484264, 0.007660491392016411, -0.010392939671874046, 0.015279687009751797, 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no indication of anything near the ship. Until we determine the cause of the drag coefficient, I would not recommend it, sir. Impulse engines are now at full power. Forward velocity is holding steady. The drag coefficient is still present, but it has stabilized. It is an irregular lattice composed of approximately forty-seven million strands of energy. That may be difficult, sir. I am now detecting a significant number of strands behind us. At our current speed, we will clear the nebula in twelve minutes, four seconds. We are moving through a dense concentration of energy strands. Captain -- density appears to be lower off the starboard bow. It appears to be an energy vortex... of highly complex patterns. Very possibly a life form. It is in direct physical contact with the shields. Aye, sir. No effect.', state={'embedded_doc': [-0.009984297677874565, -0.005414746236056089, -0.030894288793206215, -0.012561111710965633, 0.004895947873592377, -0.005514383316040039, -0.026881329715251923, -0.0036075403913855553, -0.02748602256178856, 0.007627371232956648, 0.015117311850190163, 0.015131055377423763, 0.016134295612573624, 0.025026023387908936, 0.016271725296974182, 0.0022298034746199846, 0.014595077373087406, -0.03545697033405304, 0.0025802503805607557, -0.010774520225822926, 0.004377149045467377, 0.0011157607659697533, -0.014705021865665913, -0.01911652833223343, -0.01591440662741661, -0.009290275163948536, 0.025988033041357994, -0.017755970358848572, -0.005002456251531839, -0.0203259140253067, 0.02600177749991417, -0.0028344960883259773, -0.0020116332452744246, -0.008472566492855549, -0.019886137917637825, -0.009283403865993023, 0.005098657216876745, -0.013385692611336708, 0.005809857975691557, -0.0070639075711369514, 0.01829194836318493, 0.01301463134586811, 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Computer, run fluidic sensor diagnostic. Come in.', state={'embedded_doc': [-0.007104808464646339, 0.013832846656441689, -0.0014566202880814672, -0.020264850929379463, -0.014357633888721466, 0.012978386133909225, -0.01346280425786972, -0.035012710839509964, -0.030545294284820557, -0.0018132063560187817, 0.036358319222927094, 0.020089922472834587, -0.007730516139417887, 0.015191910788416862, -0.006539653055369854, -0.019242189824581146, 0.020897286012768745, -0.00657329335808754, 0.014667123556137085, -0.021327881142497063, -0.0061056949198246, 0.020089922472834587, 0.00801309384405613, 0.0035591323394328356, -0.012157564982771873, -0.005614547990262508, 0.005688556469976902, -0.016147291287779808, -0.0076026832684874535, 0.0009907035855576396, 0.000581134285312146, -0.009271237067878246, -0.02858070656657219, -0.02930733561515808, 0.00026596777024678886, 0.0014465282438322902, 0.010092057287693024, 0.005257961805909872, -0.009103035554289818, -0.028338497504591942, 0.031110448762774467, 0.007992909289896488, 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control has been restored. Geordi -- I believe I have an explanation. According to the plasma conversion sensor, the starboard engine has been in continuous operation for over forty-seven days. Captain. I am detecting a temporal disturbance which intersects the table. It would appear that within this disturbance, time is moving at a highly accelerated rate -- approximately fifty times faster than normal. The disturbance is roughly spherical in shape. It extends outward through the hull, approximately seventeen meters beyond the ship. It does not appear to be affected. Course plotted. Adjust pitch to twenty-seven point three degrees. Set heading one-eight-zero mark zero. We are clearing the phenomenon... All stop. There is another temporal disturbance directly behind us. Within each disturbance, it appears that time is moving at a different rate. The fragmentation effect increases along a heading of two-seven-zero mark one-five. The fragmentation effect is increasing... 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Captain, the ship is traveling at warp nine point seven two. At present course and speed... ten hours fifty-three minutes. Alien vessel approaching at half-impulse, heading zero-five-one mark one-one-four. They are scanning us, Captain. Nossir, we are out of range. Negative, Commander. Shuttlecraft has cleared the bay. Scanning. Vessel reads as an unmanned sublight freighter. Indeterminate. Propulsion appears to employ a gaseous-core fission reactor, but it is not functioning. No sir. Engine reactor elements appear to have been inactive for approximately three hundred years. The vessel is carrying various unstable waste products.', state={'embedded_doc': [-0.0012337719090282917, -0.02289113588631153, -0.0017843031091615558, -0.004373426083475351, -0.007007071282714605, 0.00044564768904820085, -0.028548849746584892, -0.016699159517884254, -0.015904612839221954, -0.0076988739892840385, 0.02416514977812767, 0.025658346712589264, 0.0027363880071789026, 0.0045857615768909454, 0.01365111768245697, 0.006185127422213554, 0.01748000644147396, -0.024795306846499443, -0.006137180607765913, 0.002818582346662879, -0.01254834234714508, 0.007192008662968874, -0.007308450527489185, -0.007383795455098152, -0.013520976528525352, -0.00455836346372962, 0.007301601115614176, -0.004715902730822563, 0.004246709868311882, -0.022247280925512314, 0.025137782096862793, -0.0020445853006094694, -0.010589376091957092, 0.0034076422452926636, -0.016589567065238953, -0.01889100857079029, 0.017658093944191933, -0.010781163349747658, 0.012151069939136505, -0.008260536007583141, 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0.7614003729244909})], 'answer': 'Lal can complete approximately sixty trillion calculations per second.'}\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"In addition to our test questions and \"ground truth\" answers, we'll need to collect the responses and contexts (results from the vector store) used to produce them."
],
"metadata": {
"id": "aD3yStCTqelv"
}
},
{
"cell_type": "code",
"source": [
"answers = []\n",
"contexts = []\n",
"\n",
"for question in eval_questions:\n",
" response = chain.invoke({\"input\": question})\n",
" answers.append(response[\"answer\"])\n",
" contexts.append([context.page_content for context in response[\"context\"]])"
],
"metadata": {
"id": "I8IKWhMVf_zN"
},
"execution_count": 17,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"It used to be that ragas had a tighter integration with langchain (and other frameworks,) but they have since moved to a different approach that requires you to massage things into Hugging Face style datasets first. So let's get that out of the way."
],
"metadata": {
"id": "2znEEEPMqm5v"
}
},
{
"cell_type": "code",
"source": [
"# We must massage the results into Hugging Face format for Ragas.\n",
"from datasets import Dataset\n",
"\n",
"response_dataset = Dataset.from_dict({\n",
" \"question\" : eval_questions,\n",
" \"answer\": answers,\n",
" \"contexts\": contexts,\n",
" \"ground_truth\" : eval_answers\n",
"})\n",
"\n",
"response_dataset[0]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Rajv0otXgDK1",
"outputId": "de762bf8-1429-47ca-ad97-353129b7cef2"
},
"execution_count": 18,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'question': 'Is Lal your daughter?',\n",
" 'answer': 'Yes, Lal is my daughter.',\n",
" 'contexts': [\"I wanted to give something back in return for all Starfleet has given me. I still do. But Lal is my child. You ask that I volunteer to give her up. I cannot. That would violate every lesson I have learned about human parenting. As Captain Picard told me after he first met her, I have taken on 'quite a responsibility.' I have brought a new life into this world. It is my duty, not Starfleet's, to guide her through these first difficult steps to maturity, to support her as she learns, to prepare her to be a contributing member of society. No one can relieve me of that obligation. And I cannot ignore it. I am her father. Lal is programmed to return to the lab in the event of a malfunction. Yes, Lal. I am here. It would appear to be a symptom of cascade failure. It will require reinitializing the base matrix without wiping out the higher functions. Thank you, Admiral. Lal, I am unable to correct the system failure. We must say good-bye now. What do you feel, Lal? I wish I could feel it\",\n",
" 'Lal... The children were not laughing with you... they were laughing at you. One is meant kindly... the other is not. Because you are different. And sometimes differences scare people. I have learned that some of them use humor to hide their fears. Doctor, I require your advice as a successful parent. Lal is realizing that she is not the same as the other children. She does not feel the emotion of loneliness, but she can observe how isolated she is from the others. She wants to be more like them. Yes, Doctor. It is an experience I know too well. But I do not know how to help her. Lal is passing into sentience. It is perhaps the most difficult stage of development for her. That is precisely what happened to Lal at school. How did you help him? I have not told Lal how difficult it was for me to assimilate. I did not want it to discourage her. Perhaps this was an error of judgement. I can give her attention, doctor. But I am incapable of giving her love. Guinan, Lal needs to observe human',\n",
" 'behavior. In return for this opportunity, Lal is willing to provide services to assist you. I believe what I said was that Guinan had much life experience, Lal... That would be very beneficial. Lal, you used a verbal contraction. It is a skill my program has never mastered. No. You have exceeded my abilities. I do not object. I just do not understand why it has happened. Yes, Captain. I am sure the admiral is anxious to meet Lal... I have been sending him regular status reports on her development... Her environment, sir? He wishes to relocate us? Then he is questioning my ability as a parent. Does the admiral have children, sir? I am forced to wonder how much experience he had as a parent when his first child was born. Commander, what are your intentions toward my daughter? That is a limitation we must learn to accept, Lal. I have asked myself that many times as I have struggled to be more human, Lal. Until I finally realized that it is the struggle itself that is most important. We',\n",
" 'This is a big decision... Counselor... Lal has narrowed the choices to four... would you like to see? Computer, Lal -- gender sequence finalists... begin... An Andorian female... That could make socialization more difficult. A human male... The human female. A Klingon male. Come in, Counselor. I have completed the assembly of the replicated anatomy. I was able to provide Lal with even more realistic skin and eye color than my own. This is home. Correct, Lal. We are a family. A chair... to sit in. A painting. I will teach you how to recognize the artistry of paintings. Yes, very good, Lal. You have correctly processed the sense of touch. No, Lal, this is a flower. Inhale.',\n",
" 'Perhaps. I created Lal because I wished to procreate. Despite what happened to her, I still have that wish. I was not aware that he created any androids before my brother. Mother... I am that android. Are you saying that you were against my creation? Then... why did you never attempt to contact me? What? Perhaps if you told me what has made you feel that way, your guilt might be alleviated. We are within four kilometers of the magma pocket... Doctor, should we lower the beam intensity? If we do, we will have to begin a new shaft at another suitable location --\\nI am detecting no signs of instability... Acknowledged. I have initialized the plasma induction coils. I am incapable of anger. I am not certain that I do.',\n",
" 'I would like that very much. I can replicate one for you. Yes. I am attempting to master all known styles of painting. This one is in the style of the early French impressionists... That is Lal, my daughter. Yes. I created her... using myself as a model. The positronic matrix I designed for her was unstable. She only lived a short time. In a sense, you were her grandmother... Would you like to practice now? The acoustics in Ten Forward are quite favorable. Of course.',\n",
" 'must strive to be better than we are. It does not matter that we will never reach our ultimate goal. The effort yields its own rewards. It is only the difference between knowledge and experience. So Lal now possesses the sum of my programming. There do seem to be variations on the quantum level. Lal can use contractions... I cannot. I have maintained records on positronic matrix activity, behavioral norms, and all verbal patterns... I have seen no evidence of other aberrations... Is that not the goal of every parent, sir? I have been programmed with all the procedures you have mentioned. And in any meaningful evaluation of Lal, you would require a model for a basis of comparison. I am the only model available, Admiral. Nosir. It is an opportunity for her to observe human behavior and more importantly to interact with her crewmates. May I know why, sir? Admiral, when I created Lal, it was with the hope that someday she would choose to enter the Academy and become a member of Starfleet.',\n",
" \"We have only made two transfers. I decided to allow Lal to choose its own appearance and sex. Captain... Have a cigar. I believe it is customary. I am sorry I did not anticipate your objections, Captain. Do you wish me to deactivate Lal? I have followed all Starfleet regulations to the best of my ability, Captain... I expected they would be pleased... I can assure you Lal's programming includes psychological inhibitor safeguards to prevent any threat to the Enterprise. A malfunction is of course a possibility, Captain. But Lal's program is equipped like mine -- it will shut down before deleterious behavior can begin. To prepare, I have scanned all the available literature on parenting. There seems to be much confusion on the issue. One traditional doctrine insists 'spare the rod and spoil the child', suggesting a punitive approach... another more liberal attitude would allow a child enormous freedom... And what the Klingons do to their children... Does that not describe becoming a\",\n",
" 'Yes. Theoretically, the duplicate brains should be able to store and process the same information... but until all the transfers are complete, we will not know for certain. She studies in our quarters. She does not require much supervision, Wesley. Lal is quite self-sufficient. Lal already has access to the sum of human knowledge. She is only two weeks old. Lal, the third crosslink transfer series is complete. Purpose?',\n",
" 'Salia of Daled Four. Very little is known. She was born on Daled Four. Her parents were from opposite sides of factions which have been feuding for centuries. They died shortly after her birth. A Federation ship brought her and her governess to Klavdia Three to be raised in a neutral environment. It is hoped she will unite the factions and bring peace. What puzzles me, Captain, is how she is expected to bring peace to Daled Four. The one thing we do know about it is that its inhabitants have been fighting throughout their recorded history. Only that it is the difference between night and day.'],\n",
" 'ground_truth': 'Yes, Lal is my daughter. I created Lal.'}"
]
},
"metadata": {},
"execution_count": 18
}
]
},
{
"cell_type": "markdown",
"source": [
"Finally we can let ragas do its magic! We tell it which metrics we are interested in:"
],
"metadata": {
"id": "pV2dkWUnq0Ee"
}
},
{
"cell_type": "code",
"source": [
"from ragas import evaluate\n",
"from ragas.metrics import (\n",
" faithfulness,\n",
" answer_relevancy,\n",
" answer_correctness,\n",
" context_recall,\n",
" context_precision,\n",
")\n",
"\n",
"metrics = [\n",
" faithfulness,\n",
" answer_relevancy,\n",
" context_recall,\n",
" context_precision,\n",
" answer_correctness,\n",
"]"
],
"metadata": {
"id": "UmNtzAAkkEoj"
},
"execution_count": 19,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Then it's just a matter of calling evaluate! Well, we also need to force our OpenAI key into a system environment variable first, since that seems to be missing from their API at the moment."
],
"metadata": {
"id": "HbIza1Ffq5uG"
}
},
{
"cell_type": "code",
"source": [
"import os\n",
"os.environ['OPENAI_API_KEY'] = api_key\n",
"results = evaluate(response_dataset, metrics)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 49,
"referenced_widgets": [
"8f95927913594692a6de101e9f91359f",
"d2d6d291aba9477c9d574964342833d3",
"b0d8d35a166e4863b41a8d4203a0a0db",
"9f3b7eb3671848dba892bc94cf0c6ddf",
"de3ba8d8274b4bc28a4bc6b45b9b4d73",
"8b95fa89b864438dbe8749ddf6ccde9c",
"295b5daa3735477a922b5205770ad297",
"a5ad6382ad2f48778e21ba61ff7abeb9",
"93b89b022dae48b2bf6e4386432f7bbe",
"d9b0374becc543b497c51b5b741c9e79",
"1170577e3a614c269a06d92d71b89a3b"
]
},
"id": "duL0Tg6Ykl6C",
"outputId": "dc27fcec-a0ca-426d-f6ea-6907ece17e93"
},
"execution_count": 20,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"Evaluating: 0%| | 0/30 [00:00<?, ?it/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "8f95927913594692a6de101e9f91359f"
}
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"Let's see the results! How does it compare to our \"naive RAG\" approach earlier?"
],
"metadata": {
"id": "Bf3R-ZhUrBde"
}
},
{
"cell_type": "code",
"source": [
"results"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "aMlkV8geknyC",
"outputId": "38ab4aa8-a1bd-45db-c78d-727a46b127d6"
},
"execution_count": 21,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'faithfulness': 0.7857, 'answer_relevancy': 0.9520, 'context_recall': 0.6667, 'context_precision': 0.8115, 'answer_correctness': 0.6540}"
]
},
"metadata": {},
"execution_count": 21
}
]
},
{
"cell_type": "code",
"source": [
"results.to_pandas()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 411
},
"id": "n6TqyL64sJwd",
"outputId": "5611b1e5-0587-403a-cbcf-4b4f667d410d"
},
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" user_input \\\n",
"0 Is Lal your daughter? \n",
"1 How many calculations per second can Lal compl... \n",
"2 Does Lal have emotions? \n",
"3 What goal did you have for Lal? \n",
"4 How was Lal's species and gender chosen? \n",
"5 What happened to Lal? \n",
"\n",
" retrieved_contexts \\\n",
"0 [I wanted to give something back in return for... \n",
"1 [must strive to be better than we are. It does... \n",
"2 [Lal... The children were not laughing with yo... \n",
"3 [must strive to be better than we are. It does... \n",
"4 [This is a big decision... Counselor... Lal ha... \n",
"5 [I wanted to give something back in return for... \n",
"\n",
" response \\\n",
"0 Yes, Lal is my daughter. \n",
"1 Lal can complete approximately sixty trillion ... \n",
"2 Lal was designed to experience emotions, but d... \n",
"3 My goal for Lal was to provide her with the op... \n",
"4 Lt. Commander Data allowed Lal to choose her o... \n",
"5 Lal experienced a system failure that led to c... \n",
"\n",
" reference faithfulness \\\n",
"0 Yes, Lal is my daughter. I created Lal. 1.000000 \n",
"1 Lal is capable of completing sixty trillion ca... 0.000000 \n",
"2 Yes, unlike myself, Lal proved able to feel em... 1.000000 \n",
"3 My goal for Lal was for her to enter Starfleet... 1.000000 \n",
"4 Lal chose her own identity as a human female, ... 1.000000 \n",
"5 Lal experienced a cascade failure in her neura... 0.714286 \n",
"\n",
" answer_relevancy context_recall context_precision answer_correctness \n",
"0 1.000000 1.0 1.000000 0.744672 \n",
"1 0.994502 0.0 0.000000 0.997975 \n",
"2 0.951120 1.0 0.952629 0.597431 \n",
"3 0.988055 1.0 1.000000 0.451645 \n",
"4 0.869559 1.0 0.916667 0.474244 \n",
"5 0.908813 0.0 1.000000 0.658157 "
],
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" <th>user_input</th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Is Lal your daughter?</td>\n",
" <td>[I wanted to give something back in return for...</td>\n",
" <td>Yes, Lal is my daughter.</td>\n",
" <td>Yes, Lal is my daughter. I created Lal.</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
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" <td>1.000000</td>\n",
" <td>0.744672</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>How many calculations per second can Lal compl...</td>\n",
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" <td>0.994502</td>\n",
" <td>0.0</td>\n",
" <td>0.000000</td>\n",
" <td>0.997975</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Does Lal have emotions?</td>\n",
" <td>[Lal... The children were not laughing with yo...</td>\n",
" <td>Lal was designed to experience emotions, but d...</td>\n",
" <td>Yes, unlike myself, Lal proved able to feel em...</td>\n",
" <td>1.000000</td>\n",
" <td>0.951120</td>\n",
" <td>1.0</td>\n",
" <td>0.952629</td>\n",
" <td>0.597431</td>\n",
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" <th>3</th>\n",
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" <td>My goal for Lal was for her to enter Starfleet...</td>\n",
" <td>1.000000</td>\n",
" <td>0.988055</td>\n",
" <td>1.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.451645</td>\n",
" </tr>\n",
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" <th>4</th>\n",
" <td>How was Lal's species and gender chosen?</td>\n",
" <td>[This is a big decision... Counselor... Lal ha...</td>\n",
" <td>Lt. Commander Data allowed Lal to choose her o...</td>\n",
" <td>Lal chose her own identity as a human female, ...</td>\n",
" <td>1.000000</td>\n",
" <td>0.869559</td>\n",
" <td>1.0</td>\n",
" <td>0.916667</td>\n",
" <td>0.474244</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>What happened to Lal?</td>\n",
" <td>[I wanted to give something back in return for...</td>\n",
" <td>Lal experienced a system failure that led to c...</td>\n",
" <td>Lal experienced a cascade failure in her neura...</td>\n",
" <td>0.714286</td>\n",
" <td>0.908813</td>\n",
" <td>0.0</td>\n",
" <td>1.000000</td>\n",
" <td>0.658157</td>\n",
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"summary": "{\n \"name\": \"results\",\n \"rows\": 6,\n \"fields\": [\n {\n \"column\": \"user_input\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Is Lal your daughter?\",\n \"How many calculations per second can Lal complete?\",\n \"What happened to Lal?\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"retrieved_contexts\",\n \"properties\": {\n \"dtype\": \"object\",\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"response\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Yes, Lal is my daughter.\",\n \"Lal can complete approximately sixty trillion calculations per second.\",\n \"Lal experienced a system failure that led to cascade failure, ultimately resulting in her deactivation. Despite efforts to correct the malfunction, it was not possible to save her. She had to be bid farewell as her higher functions were compromised.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"reference\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Yes, Lal is my daughter. I created Lal.\",\n \"Lal is capable of completing sixty trillion calculations per second.\",\n \"Lal experienced a cascade failure in her neural net, triggered by distress from her impending separation from me to Galor IV. I deactivated Lal once she suffered complete neural system failure.\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"faithfulness\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.40152769493014845,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 3,\n \"samples\": [\n 1.0,\n 0.0,\n 0.7142857142857143\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"answer_relevancy\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.05305257464594128,\n \"min\": 0.8695585036298956,\n \"max\": 1.0000000000000007,\n \"num_unique_values\": 6,\n \"samples\": [\n 1.0000000000000007,\n 0.9945024405032648,\n 0.9088134063767388\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"context_recall\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.5163977794943223,\n \"min\": 0.0,\n \"max\": 1.0,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.0,\n 1.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"context_precision\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.39902541242436873,\n \"min\": 0.0,\n \"max\": 0.9999999999888889,\n \"num_unique_values\": 5,\n \"samples\": [\n 0.0,\n 0.9166666666361111\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"answer_correctness\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.2015029946381427,\n \"min\": 0.4516454455647513,\n \"max\": 0.997975075605208,\n \"num_unique_values\": 6,\n \"samples\": [\n 0.7446720226973956,\n 0.997975075605208\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"
}
},
"metadata": {},
"execution_count": 22
}
]
},
{
"cell_type": "markdown",
"source": [
"I encourage you to play with some of the \"hyperparameters\" described above, and see if you can tune this to produce even better results. Remember that metrics don't tell the whole story; your subjective judgement of the quality of the answers matters too. Maybe even more so.\n",
"\n",
"To serve this advanced RAG system in the real world, you wouldn't run it from a notebook like this... this is just useful for prototyping. You would convert this to a standalone Python script, and then use something like [LangServe](https://www.langchain.com/langserve) to wrap it with a service API.\n",
"\n",
"\n"
],
"metadata": {
"id": "ujZ6Gk7etCwc"
}
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "6SGP4ZW3szuE"
},
"execution_count": 22,
"outputs": []
}
]
}