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https://github.com/NirDiamant/RAG_Techniques.git
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Merge pull request #69 from moshe-shelly/test_bedrock_simple_rag
Tested simple_rag with Bedrock
This commit is contained in:
@@ -78,33 +78,27 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"c:\\Users\\N7\\PycharmProjects\\llm_tasks\\RAG_TECHNIQUES\\.venv\\Lib\\site-packages\\deepeval\\__init__.py:45: UserWarning: You are using deepeval version 0.21.70, however version 0.21.73 is available. You should consider upgrading via the \"pip install --upgrade deepeval\" command.\n",
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" warnings.warn(\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import os\n",
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"import sys\n",
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"from dotenv import load_dotenv\n",
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"\n",
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"\n",
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"sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '..'))) # Add the parent directory to the path since we work with notebooks\n",
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"from helper_functions import *\n",
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"from evaluation.evalute_rag import *\n",
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"\n",
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"# Load environment variables from a .env file\n",
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"load_dotenv()\n",
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"\n",
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"# Set the OpenAI API key environment variable\n",
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"os.environ[\"OPENAI_API_KEY\"] = os.getenv('OPENAI_API_KEY')"
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"# Set the OpenAI API key environment variable (comment out if not using OpenAI)\n",
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"if not os.getenv('OPENAI_API_KEY'):\n",
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" os.environ[\"OPENAI_API_KEY\"] = input(\"Please enter your OpenAI API key: \")\n",
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"else:\n",
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" os.environ[\"OPENAI_API_KEY\"] = os.getenv('OPENAI_API_KEY')\n",
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"\n",
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"sys.path.append(os.path.abspath(os.path.join(os.getcwd(), '..'))) # Add the parent directory to the path since we work with notebooks\n",
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"from helper_functions import *\n",
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"from evaluation.evalute_rag import *\n"
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]
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},
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{
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@@ -132,7 +126,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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@@ -160,8 +154,11 @@
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" texts = text_splitter.split_documents(documents)\n",
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" cleaned_texts = replace_t_with_space(texts)\n",
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"\n",
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" # Create embeddings and vector store\n",
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" # Create embeddings (Tested with OpenAI and Amazon Bedrock)\n",
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" embeddings = get_langchain_embedding_provider(EmbeddingProvider.OPENAI)\n",
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" #embeddings = get_langchain_embedding_provider(EmbeddingProvider.AMAZON_BEDROCK)\n",
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"\n",
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" # Create vector store\n",
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" vectorstore = FAISS.from_documents(cleaned_texts, embeddings)\n",
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"\n",
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" return vectorstore"
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@@ -271,6 +268,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"#Note - this currently works with OPENAI only\n",
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"evaluate_rag(chunks_query_retriever)"
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]
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}
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@@ -291,7 +289,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.0"
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"version": "3.12.3"
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}
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},
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"nbformat": 4,
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