mirror of
https://github.com/hwchase17/langchain
synced 2024-11-04 06:00:26 +00:00
560 lines
213 KiB
Plaintext
560 lines
213 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "812a4dbc-fe04-4b84-bdf9-390045e30806",
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"metadata": {},
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"source": [
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"# Use Case\n",
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"\n",
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"Many documents contain a mixture of content types: \n",
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"\n",
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"* `Semi-structured data`: text and tables\n",
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"* `Image`: images contain valuable information \n",
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"\n",
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"Here, we show how `Unstructured` can be used to partition all 3 types from documents. \n",
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"\n",
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"We generate summaries of each content type, using an open source multi-modal model (LLaVA) for image summaries.\n",
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"\n",
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"We embed summaries and store them w/ the raw table and text chunks. \n",
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"\n",
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"For images, we embed and store the summaries only; future work could store the images for final answer generation."
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]
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},
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{
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"attachments": {
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"28d8b949-8001-4b94-be3f-a64995390935.png": {
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"image/png": 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"
|
|
}
|
|
},
|
|
"cell_type": "markdown",
|
|
"id": "7ea70aa4-9a53-4e17-8f11-1d14a0ac9b43",
|
|
"metadata": {},
|
|
"source": [
|
|
"![img_flow.png](attachment:28d8b949-8001-4b94-be3f-a64995390935.png)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "74b56bde-1ba0-4525-a11d-cab02c5659e4",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Data Loading\n",
|
|
"\n",
|
|
"### Partition PDF tables, text, and images\n",
|
|
" \n",
|
|
"* `LLaVA` Paper: https://arxiv.org/pdf/2304.08485.pdf\n",
|
|
"* Use `Unstructured` to partition elements"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"id": "4aa9055d-1243-4b5a-aca0-2c6f8fb34143",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Some weights of the model checkpoint at microsoft/table-transformer-structure-recognition were not used when initializing TableTransformerForObjectDetection: ['model.backbone.conv_encoder.model.layer3.0.downsample.1.num_batches_tracked', 'model.backbone.conv_encoder.model.layer2.0.downsample.1.num_batches_tracked', 'model.backbone.conv_encoder.model.layer4.0.downsample.1.num_batches_tracked']\n",
|
|
"- This IS expected if you are initializing TableTransformerForObjectDetection from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
|
|
"- This IS NOT expected if you are initializing TableTransformerForObjectDetection from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import pandas as pd\n",
|
|
"from lxml import html\n",
|
|
"from pydantic import BaseModel\n",
|
|
"from typing import Any, Optional\n",
|
|
"from unstructured.partition.pdf import partition_pdf\n",
|
|
"\n",
|
|
"# Path to save images\n",
|
|
"path = \"/Users/rlm/Desktop/Papers/LLaVA/\"\n",
|
|
"\n",
|
|
"# Get elements\n",
|
|
"raw_pdf_elements = partition_pdf(filename=path+\"LLaVA.pdf\",\n",
|
|
" # Using pdf format to find embedded image blocks\n",
|
|
" extract_images_in_pdf=True,\n",
|
|
" # Use layout model (YOLO-X) to get bounding boxes (for tables) and find titles\n",
|
|
" # Titles are any sub-section of the document \n",
|
|
" infer_table_structure=True, \n",
|
|
" # Post processing to aggregate text once we have the title \n",
|
|
" chunking_strategy=\"by_title\",\n",
|
|
" # Chunking params to aggregate text blocks\n",
|
|
" # Attempt to create a new chunk 3800 chars\n",
|
|
" # Attempt to keep chunks > 2000 chars \n",
|
|
" # Hard max on chunks\n",
|
|
" max_characters=4000, \n",
|
|
" new_after_n_chars=3800, \n",
|
|
" combine_text_under_n_chars=2000,\n",
|
|
" image_output_dir_path=path)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"id": "7cdba921-5419-4471-b234-d93af3859b6f",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"{\"<class 'unstructured.documents.elements.CompositeElement'>\": 31,\n",
|
|
" \"<class 'unstructured.documents.elements.Table'>\": 3}"
|
|
]
|
|
},
|
|
"execution_count": 2,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Create a dictionary to store counts of each type\n",
|
|
"category_counts = {}\n",
|
|
"\n",
|
|
"for element in raw_pdf_elements:\n",
|
|
" category = str(type(element))\n",
|
|
" if category in category_counts:\n",
|
|
" category_counts[category] += 1\n",
|
|
" else:\n",
|
|
" category_counts[category] = 1\n",
|
|
"\n",
|
|
"# Unique_categories will have unique elements\n",
|
|
"# TableChunk if Table > max chars set above\n",
|
|
"unique_categories = set(category_counts.keys())\n",
|
|
"category_counts"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "5f660305-e165-4b6c-ada3-a67a422defb5",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"3\n",
|
|
"31\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"class Element(BaseModel):\n",
|
|
" type: str\n",
|
|
" text: Any\n",
|
|
"\n",
|
|
"# Categorize by type\n",
|
|
"categorized_elements = []\n",
|
|
"for element in raw_pdf_elements:\n",
|
|
" if \"unstructured.documents.elements.Table\" in str(type(element)):\n",
|
|
" categorized_elements.append(Element(type=\"table\", text=str(element)))\n",
|
|
" elif \"unstructured.documents.elements.CompositeElement\" in str(type(element)):\n",
|
|
" categorized_elements.append(Element(type=\"text\", text=str(element)))\n",
|
|
"\n",
|
|
"# Tables\n",
|
|
"table_elements = [e for e in categorized_elements if e.type == \"table\"]\n",
|
|
"print(len(table_elements))\n",
|
|
"\n",
|
|
"# Text\n",
|
|
"text_elements = [e for e in categorized_elements if e.type == \"text\"]\n",
|
|
"print(len(text_elements))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "0aa7f52f-bf5c-4ba4-af72-b2ccba59a4cf",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Multi-vector retriever\n",
|
|
"\n",
|
|
"Use [multi-vector-retriever](https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector#summary).\n",
|
|
"\n",
|
|
"### Text and Table summaries"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "523e6ed2-2132-4748-bdb7-db765f20648d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from langchain.chat_models import ChatOllama\n",
|
|
"from langchain.prompts import ChatPromptTemplate\n",
|
|
"from langchain.schema.output_parser import StrOutputParser"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "22c22e3f-42fb-4a4a-a87a-89f10ba8ab99",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Prompt \n",
|
|
"prompt_text=\"\"\"You are an assistant tasked with summarizing tables and text. \\ \n",
|
|
"Give a concise summary of the table or text. Table or text chunk: {element} \"\"\"\n",
|
|
"prompt = ChatPromptTemplate.from_template(prompt_text) \n",
|
|
"\n",
|
|
"# Summary chain \n",
|
|
"model = ChatOllama(model=\"llama2:13b-chat\")\n",
|
|
"summarize_chain = {\"element\": lambda x:x} | prompt | model | StrOutputParser()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"id": "0e1ba7ba-d209-424a-8f05-6a95d6d32bb2",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Apply to text\n",
|
|
"texts = [i.text for i in text_elements if i.text != \"\"]\n",
|
|
"text_summaries = summarize_chain.batch(texts, {\"max_concurrency\": 5})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a419123a-6038-4264-9ee0-bfb2a2df7153",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Apply to tables\n",
|
|
"tables = [i.text for i in table_elements]\n",
|
|
"table_summaries = summarize_chain.batch(tables, {\"max_concurrency\": 5})"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "d52641eb-762e-4460-80c7-3ac3ddd93621",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Image summaries \n",
|
|
"\n",
|
|
"Use [llama.cpp](https://github.com/ggerganov/llama.cpp/pull/3436): \n",
|
|
"\n",
|
|
"* Download `mmproj-model-f16.gguf` and one of `ggml-model-[f16|q5_k|q4_k].gguf` from [LLaVA 7b repo](https://huggingface.co/mys/ggml_llava-v1.5-7b/tree/main)\n",
|
|
"* Clone `llama.cpp` repo\n",
|
|
"* Build\n",
|
|
"```\n",
|
|
"mkdir build && cd build && cmake ..\n",
|
|
"cmake --build .\n",
|
|
"```\n",
|
|
"\n",
|
|
"For [better performance](https://github.com/ggerganov/llama.cpp/issues/3602):\n",
|
|
"\n",
|
|
"* It appears `7b` is currently better than `13b` in the above LLaVA repo.\n",
|
|
"* Use `--temp 0.1`"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "646a6874-008e-46aa-809d-1d59df36858b",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"%%bash\n",
|
|
"\n",
|
|
"# Define the directory containing the images\n",
|
|
"IMG_DIR=~/Desktop/Papers/LLaVA/\n",
|
|
"\n",
|
|
"# Loop through each image in the directory\n",
|
|
"for img in \"${IMG_DIR}\"*.jpg; do\n",
|
|
" # Extract the base name of the image without extension\n",
|
|
" base_name=$(basename \"$img\" .jpg)\n",
|
|
"\n",
|
|
" # Define the output file name based on the image name\n",
|
|
" output_file=\"${IMG_DIR}${base_name}.txt\"\n",
|
|
"\n",
|
|
" # Execute the command and save the output to the defined output file\n",
|
|
" /Users/rlm/Desktop/Code/llama.cpp/bin/llava -m ../models/llava-7b/ggml-model-q5_k.gguf --mmproj ../models/llava-7b/mmproj-model-f16.gguf --temp 0.1 -p \"Describe the image in detail. Be specific about graphs, such as bar plots.\" --image \"$img\" > \"$output_file\"\n",
|
|
"\n",
|
|
"done"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "da8a8c94-3df7-446f-9a69-703295f50f02",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os, glob\n",
|
|
"\n",
|
|
"# Get all .txt files in the directory\n",
|
|
"file_paths = glob.glob(os.path.expanduser(os.path.join(path, \"*.txt\")))\n",
|
|
"\n",
|
|
"# Read each file and store its content in a list\n",
|
|
"img_summaries = []\n",
|
|
"for file_path in file_paths:\n",
|
|
" with open(file_path, 'r') as file:\n",
|
|
" img_summaries.append(file.read())\n",
|
|
"\n",
|
|
"cleaned_img_summary = [s.split(\"clip_model_load: total allocated memory: 201.27 MB\\n\\n\", 1)[1].strip() for s in img_summaries]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "67b030d4-2ac5-41b6-9245-fc3ba5771d87",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Add to vectorstore\n",
|
|
"\n",
|
|
"Use [Multi Vector Retriever](https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector#summary) with summaries."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"id": "64a5df0c-8193-407e-a83f-8fc17caff3e4",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Found model file at /Users/rlm/.cache/gpt4all/ggml-all-MiniLM-L6-v2-f16.bin\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"objc[42078]: Class GGMLMetalClass is implemented in both /Users/rlm/miniforge3/envs/llama2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libreplit-mainline-metal.dylib (0x31f870208) and /Users/rlm/miniforge3/envs/llama2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libllamamodel-mainline-metal.dylib (0x31fc9c208). One of the two will be used. Which one is undefined.\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import uuid\n",
|
|
"from langchain.vectorstores import Chroma\n",
|
|
"from langchain.storage import InMemoryStore\n",
|
|
"from langchain.schema.document import Document\n",
|
|
"from langchain.embeddings import GPT4AllEmbeddings\n",
|
|
"from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
|
|
"\n",
|
|
"# The vectorstore to use to index the child chunks\n",
|
|
"vectorstore = Chroma(\n",
|
|
" collection_name=\"summaries\",\n",
|
|
" embedding_function=GPT4AllEmbeddings()\n",
|
|
")\n",
|
|
"\n",
|
|
"# The storage layer for the parent documents\n",
|
|
"store = InMemoryStore()\n",
|
|
"id_key = \"doc_id\"\n",
|
|
"\n",
|
|
"# The retriever (empty to start)\n",
|
|
"retriever = MultiVectorRetriever(\n",
|
|
" vectorstore=vectorstore, \n",
|
|
" docstore=store, \n",
|
|
" id_key=id_key,\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "d643cc61-827d-4f3c-8242-7a7c8291ed8a",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Add texts\n",
|
|
"doc_ids = [str(uuid.uuid4()) for _ in texts]\n",
|
|
"summary_texts = [Document(page_content=s,metadata={id_key: doc_ids[i]}) for i, s in enumerate(text_summaries)]\n",
|
|
"retriever.vectorstore.add_documents(summary_texts)\n",
|
|
"retriever.docstore.mset(list(zip(doc_ids, texts)))\n",
|
|
"\n",
|
|
"# Add tables\n",
|
|
"table_ids = [str(uuid.uuid4()) for _ in tables]\n",
|
|
"summary_tables = [Document(page_content=s,metadata={id_key: table_ids[i]}) for i, s in enumerate(table_summaries)]\n",
|
|
"retriever.vectorstore.add_documents(summary_tables)\n",
|
|
"retriever.docstore.mset(list(zip(table_ids, tables)))\n",
|
|
"\n",
|
|
"# Add images\n",
|
|
"img_ids = [str(uuid.uuid4()) for _ in cleaned_img_summary]\n",
|
|
"summary_img = [Document(page_content=s,metadata={id_key: img_ids[i]}) for i, s in enumerate(cleaned_img_summary)]\n",
|
|
"retriever.vectorstore.add_documents(summary_img)\n",
|
|
"retriever.docstore.mset(list(zip(img_ids, cleaned_img_summary))) # Store the image summary as the raw document"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "4b45fb81-46b1-426e-aa2c-01aed4eac700",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Sanity Check"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "3dbb23d5-ae66-444d-8f5f-b24107fb9c57",
|
|
"metadata": {},
|
|
"source": [
|
|
"Image:"
|
|
]
|
|
},
|
|
{
|
|
"attachments": {
|
|
"227da97f-e1ae-4252-b577-03a873a321e9.jpg": {
|
|
"image/jpeg": 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"
|
|
}
|
|
},
|
|
"cell_type": "markdown",
|
|
"id": "329fd4ee-4a68-4f3b-b157-a676f13ba587",
|
|
"metadata": {},
|
|
"source": [
|
|
"![figure-8-1.jpg](attachment:227da97f-e1ae-4252-b577-03a873a321e9.jpg)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "6fde6f17-d244-4270-b759-68e1858d399f",
|
|
"metadata": {},
|
|
"source": [
|
|
"We can retrieve this image summary:"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "6f52ee1e-ed46-4a81-834a-3608a1cf90ce",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"'The image features a close-up of a tray filled with various pieces of fried chicken. The chicken pieces are arranged in a way that resembles a map of the world, with some pieces placed in the shape of continents and others as countries. The arrangement of the chicken pieces creates a visually appealing and playful representation of the world, making it an interesting and creative presentation.\\n\\nmain: image encoded in 865.20 ms by CLIP ( 1.50 ms per image patch)'"
|
|
]
|
|
},
|
|
"execution_count": 17,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"retriever.get_relevant_documents(\"Images / figures with playful and creative examples\")[0]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "69060724-e390-4dda-8250-5f86025c874a",
|
|
"metadata": {},
|
|
"source": [
|
|
"## RAG\n",
|
|
"\n",
|
|
"Run [RAG pipeline](https://python.langchain.com/docs/expression_language/cookbook/retrieval)."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"id": "771a47fa-1267-4db8-a6ae-5fde48bbc069",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from operator import itemgetter\n",
|
|
"from langchain.schema.runnable import RunnablePassthrough\n",
|
|
"\n",
|
|
"# Prompt template\n",
|
|
"template = \"\"\"Answer the question based only on the following context, which can include text and tables:\n",
|
|
"{context}\n",
|
|
"Question: {question}\n",
|
|
"\"\"\"\n",
|
|
"prompt = ChatPromptTemplate.from_template(template)\n",
|
|
"\n",
|
|
"# RAG pipeline\n",
|
|
"chain = (\n",
|
|
" {\"context\": retriever, \"question\": RunnablePassthrough()} \n",
|
|
" | prompt \n",
|
|
" | model \n",
|
|
" | StrOutputParser()\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"id": "ea8414a8-65ee-4e11-8154-029b454f46af",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"\" Based on the provided context, LLaVA's performance across multiple image domains/subjects is not explicitly mentioned. However, we can infer some information about its performance based on the given text:\\n\\n1. LLaVA achieves an accuracy of 90.92% on the ScienceQA dataset, which is close to the current SoTA (91.68%).\\n2. When prompted with a 2-shot in-context learning task using GPT-4, it achieves an accuracy of 82.69%, indicating a 7.52% absolute gain compared to GPT-3.5.\\n3. For a substantial number of questions, GPT-4 fails due to insufficient context such as images or plots.\\n\\nBased on these points, we can infer that LLaVA performs well across multiple image domains/subjects, but its performance may be limited by the quality and availability of the input images. Additionally, its ability to recognize visual content and provide detailed responses is dependent on the specific task and dataset being used.\""
|
|
]
|
|
},
|
|
"execution_count": 20,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"chain.invoke(\"What is the performance of LLaVa across across mutiple image domains / subjects?\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1b7aeb57-2ab8-496c-b909-0734ccc5da5f",
|
|
"metadata": {},
|
|
"source": [
|
|
"We can check the [trace](https://smith.langchain.com/public/ab90fb1c-5949-4fc6-a002-56a6056adc6b/r) to review retrieval."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 22,
|
|
"id": "1ad375c5-8aef-4be3-9a12-8ad953fa2d14",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"' Sure, I\\'d be happy to help! Based on the provided context, here are some playful and creative explanations for the images/figures mentioned in the paper:\\n\\n1. \"The image features a close-up of a tray filled with various pieces of fried chicken. The chicken pieces are arranged in a way that resembles a map of the world, with some pieces placed in the shape of continents and others as countries.\"\\n\\nPlayful explanation: \"Look, ma! The fried chicken is mapping out the world one piece at a time! Who needs Google Maps when you have crispy chicken wings to guide the way?\"\\n\\nCreative explanation: \"The arrangement of the fried chicken pieces creates a visual representation of the world that\\'s both appetizing and adventurous. It\\'s like a culinary globe-trotting experience!\"\\n\\n2. \"The image is a screenshot of a conversation between two people, likely discussing a painting.\"\\n\\nPlayful explanation: \"The painting is getting a double take - these two people are having a chat about it and we get to eavesdrop on their art-loving banter!\"\\n\\nCreative explanation: \"This image captures the dynamic exchange of ideas between two art enthusiasts. It\\'s like we\\'re peeking into their creative brainstorming session, where the painting is the catalyst for a lively discussion.\"\\n\\n3. \"The image features a text-based representation of a scene with a person holding onto a rope, possibly a woman, and a boat in the background.\"\\n\\nPlayful explanation: \"This image looks like a page from a choose-your-own-adventure book! Is our brave protagonist about to embark on a thrilling boat ride or hold tight for a wild journey?\"\\n\\nCreative explanation: \"The text-based representation of the scene creates an intriguing narrative that invites the viewer to fill in the blanks. It\\'s like we\\'re reading a visual storybook, where the person holding onto the rope is the hero of their own adventure.\"\\n\\n4. \"Figure 5: LLaVA recognizes the famous art work, Mona Lisa, by Leonardo da Vinci.\"\\n\\nPlayful explanation: \"Mona Lisa is getting a digital spotlight - look at her smile now that she\\'s part of this cool image recognition tech!\"\\n\\nCreative explanation: \"This playful recognition of the Mona Lisa painting highlights the advanced technology used in image analysis. It\\'s like LLaVA is giving the famous artwork a modern makeover, showcasing its timeless beauty and relevance in the digital age.\"\\n\\nOverall, these images/figures offer unique opportunities for creative and playful explanations that can capture the viewer\\'s attention while highlighting the technology and narratives presented in the paper.'"
|
|
]
|
|
},
|
|
"execution_count": 22,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"chain.invoke(\"Explain any images / figures in the paper with playful and creative examples.\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "1da79644-4046-45b0-8c25-01aa73587b22",
|
|
"metadata": {},
|
|
"source": [
|
|
"We can check the [trace](https://smith.langchain.com/public/c6d3b7d5-0f40-4905-ab8f-3a2b77c39af4/r) to review retrieval."
|
|
]
|
|
}
|
|
],
|
|
"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": "3.9.16"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|