{ "cells": [ { "cell_type": "markdown", "id": "ebeba428", "metadata": {}, "source": [ "# ✅ RAG JuJutsu PoC (Notebook with Joblib, FAISS, ChatGPT API)" ] }, { "cell_type": "code", "execution_count": null, "id": "8bdfd3c8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: ipywidgets==7.7.2 in /opt/anaconda3/lib/python3.11/site-packages (7.7.2)\n", "Requirement already satisfied: ipykernel>=4.5.1 in /opt/anaconda3/lib/python3.11/site-packages (from ipywidgets==7.7.2) (6.28.0)\n", "Requirement already satisfied: ipython-genutils~=0.2.0 in /opt/anaconda3/lib/python3.11/site-packages (from ipywidgets==7.7.2) (0.2.0)\n", "Requirement already satisfied: traitlets>=4.3.1 in /opt/anaconda3/lib/python3.11/site-packages (from ipywidgets==7.7.2) (5.7.1)\n", "Requirement already satisfied: widgetsnbextension~=3.6.0 in /opt/anaconda3/lib/python3.11/site-packages (from ipywidgets==7.7.2) (3.6.10)\n", "Requirement already satisfied: 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/opt/anaconda3/lib/python3.11/site-packages (from jsonschema[format-nongpl]>=4.18.0->jupyter-events>=0.6.0->jupyter-server<3,>=2.4.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets==7.7.2) (24.11.1)\n", "Requirement already satisfied: cffi>=1.0.1 in /opt/anaconda3/lib/python3.11/site-packages (from argon2-cffi-bindings->argon2-cffi->jupyter-server<3,>=2.4.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets==7.7.2) (1.16.0)\n", "Requirement already satisfied: soupsieve>1.2 in /opt/anaconda3/lib/python3.11/site-packages (from beautifulsoup4->nbconvert>=6.4.4->jupyter-server<3,>=2.4.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets==7.7.2) (2.5)\n", "Requirement already satisfied: pycparser in /opt/anaconda3/lib/python3.11/site-packages (from cffi>=1.0.1->argon2-cffi-bindings->argon2-cffi->jupyter-server<3,>=2.4.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets==7.7.2) (2.21)\n", "Requirement already satisfied: arrow>=0.15.0 in /opt/anaconda3/lib/python3.11/site-packages (from isoduration->jsonschema[format-nongpl]>=4.18.0->jupyter-events>=0.6.0->jupyter-server<3,>=2.4.0->notebook>=4.4.1->widgetsnbextension~=3.6.0->ipywidgets==7.7.2) (1.2.3)\n", "usage: jupyter [-h] [--version] [--config-dir] [--data-dir] [--runtime-dir]\n", " [--paths] [--json] [--debug]\n", " [subcommand]\n", "\n", "Jupyter: Interactive Computing\n", "\n", "positional arguments:\n", " subcommand the subcommand to launch\n", "\n", "options:\n", " -h, --help show this help message and exit\n", " --version show the versions of core jupyter packages and exit\n", " --config-dir show Jupyter config dir\n", " --data-dir show Jupyter data dir\n", " --runtime-dir show Jupyter runtime dir\n", " --paths show all Jupyter paths. Add --json for machine-readable\n", " format.\n", " --json output paths as machine-readable json\n", " --debug output debug information about paths\n", "\n", "Available subcommands: console dejavu events execute kernel kernelspec lab\n", "labextension labhub migrate nbconvert notebook qtconsole run server\n", "troubleshoot trust\n", "\n", "Jupyter command `jupyter-nbextension` not found.\n", "\u001b[32m[I 2025-06-14 22:49:12.578 ServerApp]\u001b[m Package notebook took 0.0000s to import\n", "\u001b[32m[I 2025-06-14 22:49:12.740 ServerApp]\u001b[m Package aext_assistant took 0.1621s to import\n", "\u001b[32m[I 2025-06-14 22:49:12.741 ServerApp]\u001b[m Package aext_core took 0.0011s to import\n", "\u001b[33m[W 2025-06-14 22:49:12.748 ServerApp]\u001b[m aext_panels | error adding extension (enabled: True): The module 'aext_panels' could not be found (cannot import name 'AuthConfig' from 'anaconda_cloud_auth.client' (/opt/anaconda3/lib/python3.11/site-packages/anaconda_cloud_auth/client.py)). Are you sure the extension is installed?\n", " Traceback (most recent call last):\n", " File \"/opt/anaconda3/lib/python3.11/site-packages/jupyter_server/extension/manager.py\", line 321, in add_extension\n", " extpkg = ExtensionPackage(name=extension_name, enabled=enabled)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/lib/python3.11/site-packages/jupyter_server/extension/manager.py\", line 185, in __init__\n", " self._load_metadata()\n", " File \"/opt/anaconda3/lib/python3.11/site-packages/jupyter_server/extension/manager.py\", line 200, in _load_metadata\n", " raise ExtensionModuleNotFound(msg) from None\n", " jupyter_server.extension.utils.ExtensionModuleNotFound: The module 'aext_panels' could not be found (cannot import name 'AuthConfig' from 'anaconda_cloud_auth.client' (/opt/anaconda3/lib/python3.11/site-packages/anaconda_cloud_auth/client.py)). Are you sure the extension is installed?\n", "\u001b[32m[I 2025-06-14 22:49:12.750 ServerApp]\u001b[m Package aext_share_notebook took 0.0009s to import\n", "\u001b[32m[I 2025-06-14 22:49:12.757 ServerApp]\u001b[m Package jupyter_lsp took 0.0074s to import\n", "\u001b[33m[W 2025-06-14 22:49:12.757 ServerApp]\u001b[m A `_jupyter_server_extension_points` function was not found in jupyter_lsp. Instead, a `_jupyter_server_extension_paths` function was found and will be used for now. This function name will be deprecated in future releases of Jupyter Server.\n", "\u001b[32m[I 2025-06-14 22:49:12.761 ServerApp]\u001b[m Package jupyter_server_terminals took 0.0035s to import\n", "\u001b[32m[I 2025-06-14 22:49:12.761 ServerApp]\u001b[m Package jupyterlab took 0.0000s to import\n", "\u001b[32m[I 2025-06-14 22:49:13.042 ServerApp]\u001b[m Package notebook_shim took 0.0000s to import\n", "\u001b[33m[W 2025-06-14 22:49:13.042 ServerApp]\u001b[m A `_jupyter_server_extension_points` function was not found in notebook_shim. Instead, a `_jupyter_server_extension_paths` function was found and will be used for now. This function name will be deprecated in future releases of Jupyter Server.\n", "\u001b[32m[I 2025-06-14 22:49:13.470 ServerApp]\u001b[m Package panel.io.jupyter_server_extension took 0.4273s to import\n", "\u001b[32m[I 2025-06-14 22:49:13.471 ServerApp]\u001b[m aext_assistant | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.471 ServerApp]\u001b[m aext_core | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.471 ServerApp]\u001b[m aext_share_notebook | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.471 ServerApp]\u001b[m jupyter_lsp | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.473 ServerApp]\u001b[m jupyter_server_terminals | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.474 ServerApp]\u001b[m jupyterlab | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.475 ServerApp]\u001b[m notebook | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.564 ServerApp]\u001b[m notebook_shim | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.564 ServerApp]\u001b[m panel.io.jupyter_server_extension | extension was successfully linked.\n", "\u001b[32m[I 2025-06-14 22:49:13.584 ServerApp]\u001b[m notebook_shim | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.585 ServerApp]\u001b[m Registered aext_assistant server extension\n", "\u001b[32m[I 2025-06-14 22:49:13.585 ServerApp]\u001b[m aext_assistant | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.585 ServerApp]\u001b[m Registered aext_core server extension\n", "\u001b[32m[I 2025-06-14 22:49:13.585 ServerApp]\u001b[m aext_core | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.585 ServerApp]\u001b[m Registered aext_share_notebook_server server extension\n", "\u001b[32m[I 2025-06-14 22:49:13.585 ServerApp]\u001b[m aext_share_notebook | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.586 ServerApp]\u001b[m jupyter_lsp | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.586 ServerApp]\u001b[m jupyter_server_terminals | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.588 LabApp]\u001b[m JupyterLab extension loaded from /opt/anaconda3/lib/python3.11/site-packages/jupyterlab\n", "\u001b[32m[I 2025-06-14 22:49:13.588 LabApp]\u001b[m JupyterLab application directory is /opt/anaconda3/share/jupyter/lab\n", "\u001b[32m[I 2025-06-14 22:49:13.589 LabApp]\u001b[m Extension Manager is 'pypi'.\n", "\u001b[32m[I 2025-06-14 22:49:13.606 ServerApp]\u001b[m jupyterlab | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.608 ServerApp]\u001b[m notebook | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.608 ServerApp]\u001b[m panel.io.jupyter_server_extension | extension was successfully loaded.\n", "\u001b[32m[I 2025-06-14 22:49:13.609 ServerApp]\u001b[m The port 8888 is already in use, trying another port.\n", "\u001b[32m[I 2025-06-14 22:49:13.609 ServerApp]\u001b[m The port 8889 is already in use, trying another port.\n", "\u001b[32m[I 2025-06-14 22:49:13.609 ServerApp]\u001b[m The port 8890 is already in use, trying another port.\n", "\u001b[32m[I 2025-06-14 22:49:13.610 ServerApp]\u001b[m Serving notebooks from local directory: /Users/ddiaz/Desktop/Proyectos_ImageMarker/POC-JuJitsu\n", "\u001b[32m[I 2025-06-14 22:49:13.610 ServerApp]\u001b[m Jupyter Server 2.10.0 is running at:\n", "\u001b[32m[I 2025-06-14 22:49:13.610 ServerApp]\u001b[m http://localhost:8891/tree?token=da5dcdce5100318c25020e1cce57e2b157f8243ee0051999\n", "\u001b[32m[I 2025-06-14 22:49:13.610 ServerApp]\u001b[m http://127.0.0.1:8891/tree?token=da5dcdce5100318c25020e1cce57e2b157f8243ee0051999\n", "\u001b[32m[I 2025-06-14 22:49:13.610 ServerApp]\u001b[m Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).\n", "\u001b[35m[C 2025-06-14 22:49:13.611 ServerApp]\u001b[m \n", " \n", " To access the server, open this file in a browser:\n", " file:///Users/ddiaz/Library/Jupyter/runtime/jpserver-72351-open.html\n", " Or copy and paste one of these URLs:\n", " http://localhost:8891/tree?token=da5dcdce5100318c25020e1cce57e2b157f8243ee0051999\n", " http://127.0.0.1:8891/tree?token=da5dcdce5100318c25020e1cce57e2b157f8243ee0051999\n", "\u001b[32m[I 2025-06-14 22:49:13.912 ServerApp]\u001b[m Skipped non-installed server(s): bash-language-server, dockerfile-language-server-nodejs, javascript-typescript-langserver, jedi-language-server, julia-language-server, pyright, python-language-server, r-languageserver, sql-language-server, texlab, typescript-language-server, unified-language-server, vscode-css-languageserver-bin, vscode-html-languageserver-bin, vscode-json-languageserver-bin, yaml-language-server\n", "0.00s - Debugger warning: It seems that frozen modules are being used, which may\n", "0.00s - make the debugger miss breakpoints. Please pass -Xfrozen_modules=off\n", "0.00s - to python to disable frozen modules.\n", "0.00s - Note: Debugging will proceed. Set PYDEVD_DISABLE_FILE_VALIDATION=1 to disable this validation.\n", "\u001b[33m[W 2025-06-14 22:49:15.430 ServerApp]\u001b[m wrote error: 'Forbidden'\n", " Traceback (most recent call last):\n", " File \"/opt/anaconda3/lib/python3.11/site-packages/tornado/web.py\", line 1786, in _execute\n", " result = await result\n", " ^^^^^^^^^^^^\n", " File \"/opt/anaconda3/lib/python3.11/site-packages/aext_assistant_server/handlers.py\", line 117, in get\n", " raise HTTPError(403, reason=\"missing nucleus_token\")\n", " tornado.web.HTTPError: HTTP 403: missing nucleus_token\n", "\u001b[33m[W 2025-06-14 22:49:15.432 ServerApp]\u001b[m 403 GET /aext_assistant_server/nucleus_token?1749962955366 (e1bb6698e462478ab1b1bdda87374748@::1) 2.68ms referer=http://localhost:8891/tree\n", "\u001b[33m[W 2025-06-14 22:49:31.915 ServerApp]\u001b[m wrote error: 'Forbidden'\n", " Traceback (most recent call last):\n", " File \"/opt/anaconda3/lib/python3.11/site-packages/tornado/web.py\", line 1786, in _execute\n", " result = await result\n", " ^^^^^^^^^^^^\n", " File \"/opt/anaconda3/lib/python3.11/site-packages/aext_assistant_server/handlers.py\", line 117, in get\n", " raise HTTPError(403, reason=\"missing nucleus_token\")\n", " tornado.web.HTTPError: HTTP 403: missing nucleus_token\n", "\u001b[33m[W 2025-06-14 22:49:31.915 ServerApp]\u001b[m 403 GET /aext_assistant_server/nucleus_token?1749962971861 (e1bb6698e462478ab1b1bdda87374748@::1) 1.29ms referer=http://localhost:8891/tree\n" ] } ], "source": [ "\n", "!pip install --quiet openai langchain faiss-cpu PyPDF2 sentence-transformers joblib\n", "!pip install ipywidgets==7.7.2\n", "!jupyter nbextension enable --py widgetsnbextension\n", "!jupyter notebook\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "49ee7721", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Loaded 329 chunks\n" ] } ], "source": [ "\n", "from PyPDF2 import PdfReader\n", "from langchain.text_splitter import RecursiveCharacterTextSplitter\n", "\n", "def load_pdf_chunks(pdf_path):\n", " reader = PdfReader(pdf_path)\n", " raw_text = \"\"\n", " for page in reader.pages:\n", " raw_text += page.extract_text() + \"\\n\"\n", "\n", " splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)\n", " return splitter.split_text(raw_text)\n", "\n", "chunks = load_pdf_chunks(\"JuJutsu-Contexto-Significado-Conexiones-Historia.pdf\")\n", "print(f\"Loaded {len(chunks)} chunks\")\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "371c637e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model, chunks, and index serialized to rag_model.joblib\n" ] } ], "source": [ "\n", "from sentence_transformers import SentenceTransformer\n", "import faiss\n", "import numpy as np\n", "import joblib\n", "\n", "model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')\n", "embeddings = model.encode(chunks)\n", "\n", "index = faiss.IndexFlatL2(embeddings.shape[1])\n", "index.add(np.array(embeddings))\n", "\n", "joblib.dump((model, chunks, index), \"rag_model.joblib\")\n", "print(\"Model, chunks, and index serialized to rag_model.joblib\")\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "28ce4963", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model, chunks, and index loaded from rag_model.joblib\n" ] } ], "source": [ "\n", "import joblib\n", "\n", "model, chunks, index = joblib.load(\"rag_model.joblib\")\n", "print(\"Model, chunks, and index loaded from rag_model.joblib\")\n" ] }, { "cell_type": "code", "execution_count": 7, "id": "51a89e77", "metadata": {}, "outputs": [], "source": [ "\n", "def search(query, k=3):\n", " query_vec = model.encode([query])\n", " scores, indices = index.search(np.array(query_vec), k)\n", " return [chunks[i] for i in indices[0]]\n" ] }, { "cell_type": "code", "execution_count": 23, "id": "34315775", "metadata": {}, "outputs": [], "source": [ "\n", "import os\n", "\n", "import openai\n", "from openai import OpenAI\n", "\n", "os.environ[\"OPENAI_API_KEY\"] = \"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\"\n", "\n", "\n", "client = OpenAI() # Uses env variable OPENAI_API_KEY\n", "\n", "def chat_no_rag(question):\n", " response = client.chat.completions.create(\n", " model=\"gpt-4o\",\n", " messages=[\n", " {\"role\": \"user\", \"content\": question}\n", " ],\n", " temperature=0.5,\n", " max_tokens=200, # 👈 Limit output to ~150-200 words\n", "\n", " )\n", " return response.choices[0].message.content\n", "\n", "def chat_with_rag(question, retrieved_chunks):\n", " context = \"\\n\".join(retrieved_chunks)\n", " prompt = f\"Usa el siguiente contexto para responder la pregunta:\\n\\n{context}\\n\\nPregunta: {question}\"\n", "\n", " response = client.chat.completions.create(\n", " model=\"gpt-4o\",\n", " messages=[\n", " {\"role\": \"user\", \"content\": prompt}\n", " ],\n", " temperature=0.3,\n", " max_tokens=200, # 👈 Limit output to ~150-200 words\n", " )\n", " return response.choices[0].message.content\n", "\n", "\n", "def chat_with_rag_enhanced(question, retrieved_chunks):\n", " context = \"\\n\".join(retrieved_chunks)\n", " prompt = (\n", " \"Eres un experto en historia marcial. \"\n", " \"Usa el siguiente contexto histórico para responder con precisión y detalle.\\n\\n\"\n", " f\"Contexto:\\n{context}\\n\\n\"\n", " f\"Pregunta: {question}\\nRespuesta:\"\n", " )\n", "\n", " response = client.chat.completions.create(\n", " model=\"gpt-4o\",\n", " messages=[\n", " {\"role\": \"user\", \"content\": prompt}\n", " ],\n", " temperature=0.2,\n", " max_tokens=200, # 👈 Limit output to ~150-200 words\n", " )\n", " return response.choices[0].message.content\n", "\n", "\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 25, "id": "900dfdfa", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "🔹 Sin RAG:\n" ] }, { "ename": "RateLimitError", "evalue": "Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mRateLimitError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[25], line 6\u001b[0m\n\u001b[1;32m 3\u001b[0m retrieved \u001b[38;5;241m=\u001b[39m search(query)\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m🔹 Sin RAG:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m----> 6\u001b[0m \u001b[38;5;28mprint\u001b[39m(chat_no_rag(query))\n\u001b[1;32m 8\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m🔹 Con RAG:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28mprint\u001b[39m(chat_with_rag(query, retrieved))\n", "Cell \u001b[0;32mIn[23], line 12\u001b[0m, in \u001b[0;36mchat_no_rag\u001b[0;34m(question)\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mchat_no_rag\u001b[39m(question):\n\u001b[0;32m---> 12\u001b[0m response \u001b[38;5;241m=\u001b[39m client\u001b[38;5;241m.\u001b[39mchat\u001b[38;5;241m.\u001b[39mcompletions\u001b[38;5;241m.\u001b[39mcreate(\n\u001b[1;32m 13\u001b[0m model\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgpt-4o\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 14\u001b[0m messages\u001b[38;5;241m=\u001b[39m[\n\u001b[1;32m 15\u001b[0m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrole\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muser\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent\u001b[39m\u001b[38;5;124m\"\u001b[39m: question}\n\u001b[1;32m 16\u001b[0m ],\n\u001b[1;32m 17\u001b[0m temperature\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0.5\u001b[39m,\n\u001b[1;32m 18\u001b[0m )\n\u001b[1;32m 19\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m response\u001b[38;5;241m.\u001b[39mchoices[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mcontent\n", "File \u001b[0;32m/opt/anaconda3/lib/python3.11/site-packages/openai/_utils/_utils.py:287\u001b[0m, in \u001b[0;36mrequired_args..inner..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 285\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMissing required argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquote(missing[\u001b[38;5;241m0\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 286\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[0;32m--> 287\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n", "File \u001b[0;32m/opt/anaconda3/lib/python3.11/site-packages/openai/resources/chat/completions/completions.py:925\u001b[0m, in \u001b[0;36mCompletions.create\u001b[0;34m(self, messages, model, audio, frequency_penalty, function_call, functions, logit_bias, logprobs, max_completion_tokens, max_tokens, metadata, modalities, n, parallel_tool_calls, prediction, presence_penalty, reasoning_effort, response_format, seed, service_tier, stop, store, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, web_search_options, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m 882\u001b[0m \u001b[38;5;129m@required_args\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m], [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m 883\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcreate\u001b[39m(\n\u001b[1;32m 884\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 922\u001b[0m timeout: \u001b[38;5;28mfloat\u001b[39m \u001b[38;5;241m|\u001b[39m httpx\u001b[38;5;241m.\u001b[39mTimeout \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m|\u001b[39m NotGiven \u001b[38;5;241m=\u001b[39m NOT_GIVEN,\n\u001b[1;32m 923\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ChatCompletion \u001b[38;5;241m|\u001b[39m Stream[ChatCompletionChunk]:\n\u001b[1;32m 924\u001b[0m validate_response_format(response_format)\n\u001b[0;32m--> 925\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_post(\n\u001b[1;32m 926\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/chat/completions\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 927\u001b[0m body\u001b[38;5;241m=\u001b[39mmaybe_transform(\n\u001b[1;32m 928\u001b[0m {\n\u001b[1;32m 929\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m: messages,\n\u001b[1;32m 930\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m: model,\n\u001b[1;32m 931\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maudio\u001b[39m\u001b[38;5;124m\"\u001b[39m: audio,\n\u001b[1;32m 932\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfrequency_penalty\u001b[39m\u001b[38;5;124m\"\u001b[39m: frequency_penalty,\n\u001b[1;32m 933\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfunction_call\u001b[39m\u001b[38;5;124m\"\u001b[39m: function_call,\n\u001b[1;32m 934\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfunctions\u001b[39m\u001b[38;5;124m\"\u001b[39m: functions,\n\u001b[1;32m 935\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlogit_bias\u001b[39m\u001b[38;5;124m\"\u001b[39m: logit_bias,\n\u001b[1;32m 936\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlogprobs\u001b[39m\u001b[38;5;124m\"\u001b[39m: logprobs,\n\u001b[1;32m 937\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmax_completion_tokens\u001b[39m\u001b[38;5;124m\"\u001b[39m: max_completion_tokens,\n\u001b[1;32m 938\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmax_tokens\u001b[39m\u001b[38;5;124m\"\u001b[39m: max_tokens,\n\u001b[1;32m 939\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmetadata\u001b[39m\u001b[38;5;124m\"\u001b[39m: metadata,\n\u001b[1;32m 940\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodalities\u001b[39m\u001b[38;5;124m\"\u001b[39m: modalities,\n\u001b[1;32m 941\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mn\u001b[39m\u001b[38;5;124m\"\u001b[39m: n,\n\u001b[1;32m 942\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mparallel_tool_calls\u001b[39m\u001b[38;5;124m\"\u001b[39m: parallel_tool_calls,\n\u001b[1;32m 943\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mprediction\u001b[39m\u001b[38;5;124m\"\u001b[39m: prediction,\n\u001b[1;32m 944\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpresence_penalty\u001b[39m\u001b[38;5;124m\"\u001b[39m: presence_penalty,\n\u001b[1;32m 945\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreasoning_effort\u001b[39m\u001b[38;5;124m\"\u001b[39m: reasoning_effort,\n\u001b[1;32m 946\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresponse_format\u001b[39m\u001b[38;5;124m\"\u001b[39m: response_format,\n\u001b[1;32m 947\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mseed\u001b[39m\u001b[38;5;124m\"\u001b[39m: seed,\n\u001b[1;32m 948\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mservice_tier\u001b[39m\u001b[38;5;124m\"\u001b[39m: service_tier,\n\u001b[1;32m 949\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstop\u001b[39m\u001b[38;5;124m\"\u001b[39m: stop,\n\u001b[1;32m 950\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstore\u001b[39m\u001b[38;5;124m\"\u001b[39m: store,\n\u001b[1;32m 951\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m: stream,\n\u001b[1;32m 952\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream_options\u001b[39m\u001b[38;5;124m\"\u001b[39m: stream_options,\n\u001b[1;32m 953\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtemperature\u001b[39m\u001b[38;5;124m\"\u001b[39m: temperature,\n\u001b[1;32m 954\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtool_choice\u001b[39m\u001b[38;5;124m\"\u001b[39m: tool_choice,\n\u001b[1;32m 955\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtools\u001b[39m\u001b[38;5;124m\"\u001b[39m: tools,\n\u001b[1;32m 956\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtop_logprobs\u001b[39m\u001b[38;5;124m\"\u001b[39m: top_logprobs,\n\u001b[1;32m 957\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtop_p\u001b[39m\u001b[38;5;124m\"\u001b[39m: top_p,\n\u001b[1;32m 958\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muser\u001b[39m\u001b[38;5;124m\"\u001b[39m: user,\n\u001b[1;32m 959\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mweb_search_options\u001b[39m\u001b[38;5;124m\"\u001b[39m: web_search_options,\n\u001b[1;32m 960\u001b[0m },\n\u001b[1;32m 961\u001b[0m completion_create_params\u001b[38;5;241m.\u001b[39mCompletionCreateParamsStreaming\n\u001b[1;32m 962\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m stream\n\u001b[1;32m 963\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m completion_create_params\u001b[38;5;241m.\u001b[39mCompletionCreateParamsNonStreaming,\n\u001b[1;32m 964\u001b[0m ),\n\u001b[1;32m 965\u001b[0m options\u001b[38;5;241m=\u001b[39mmake_request_options(\n\u001b[1;32m 966\u001b[0m extra_headers\u001b[38;5;241m=\u001b[39mextra_headers, extra_query\u001b[38;5;241m=\u001b[39mextra_query, extra_body\u001b[38;5;241m=\u001b[39mextra_body, timeout\u001b[38;5;241m=\u001b[39mtimeout\n\u001b[1;32m 967\u001b[0m ),\n\u001b[1;32m 968\u001b[0m cast_to\u001b[38;5;241m=\u001b[39mChatCompletion,\n\u001b[1;32m 969\u001b[0m stream\u001b[38;5;241m=\u001b[39mstream \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m 970\u001b[0m stream_cls\u001b[38;5;241m=\u001b[39mStream[ChatCompletionChunk],\n\u001b[1;32m 971\u001b[0m )\n", "File \u001b[0;32m/opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:1242\u001b[0m, in \u001b[0;36mSyncAPIClient.post\u001b[0;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[1;32m 1228\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(\n\u001b[1;32m 1229\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 1230\u001b[0m path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1237\u001b[0m stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m 1238\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[1;32m 1239\u001b[0m opts \u001b[38;5;241m=\u001b[39m FinalRequestOptions\u001b[38;5;241m.\u001b[39mconstruct(\n\u001b[1;32m 1240\u001b[0m method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpost\u001b[39m\u001b[38;5;124m\"\u001b[39m, url\u001b[38;5;241m=\u001b[39mpath, json_data\u001b[38;5;241m=\u001b[39mbody, files\u001b[38;5;241m=\u001b[39mto_httpx_files(files), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions\n\u001b[1;32m 1241\u001b[0m )\n\u001b[0;32m-> 1242\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrequest(cast_to, opts, stream\u001b[38;5;241m=\u001b[39mstream, stream_cls\u001b[38;5;241m=\u001b[39mstream_cls))\n", "File \u001b[0;32m/opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:1037\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[0;34m(self, cast_to, options, stream, stream_cls)\u001b[0m\n\u001b[1;32m 1034\u001b[0m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mread()\n\u001b[1;32m 1036\u001b[0m log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRe-raising status error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 1037\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_status_error_from_response(err\u001b[38;5;241m.\u001b[39mresponse) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1039\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[1;32m 1041\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m response \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcould not resolve response (should never happen)\u001b[39m\u001b[38;5;124m\"\u001b[39m\n", "\u001b[0;31mRateLimitError\u001b[0m: Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}" ] } ], "source": [ "\n", "# Example query\n", "query = \"¿Cuál es el origen del JuJutsu en Japón?\"\n", "retrieved = search(query)\n", "\n", "print(\"🔹 Sin RAG:\")\n", "print(chat_no_rag(query))\n", "\n", "print(\"\\n🔹 Con RAG:\")\n", "print(chat_with_rag(query, retrieved))\n", "\n", "print(\"\\n🔹 Con RAG + Prompt mejorado:\")\n", "print(chat_with_rag_enhanced(query, retrieved))\n" ] }, { "cell_type": "code", "execution_count": null, "id": "0b852f41-946b-4684-b3c8-5ee2b416710b", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.7" } }, "nbformat": 4, "nbformat_minor": 5 }