Mão_na_massa - Aula 1.ipynb

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      "Successfully built docx2txt pypika\n",
      "Installing collected packages: striprtf, sortedcontainers, schema, pypika, monotonic, filetype, durationpy, docx2txt, dirtyjson, appdirs, wsproto, uvloop, uvicorn, uv, types-requests, tomli-w, pytube, python-dotenv, pysbd, pyproject_hooks, pypdfium2, pypdf, protobuf, portalocker, parameterized, overrides, outcome, opentelemetry-util-http, nodeenv, mypy-extensions, mmh3, marshmallow, Mako, jsonref, json-repair, jiter, jedi, hyperframe, humanfriendly, httpx-sse, httptools, hpack, fastavro, deprecation, chroma-hnswlib, bcrypt, backoff, asgiref, watchfiles, typing-inspect, trio, tiktoken, starlette, pyright, pylance, posthog, opentelemetry-proto, httpx, h2, grpcio-tools, gptcache, docker, coloredlogs, build, alembic, trio-websocket, tokenizers, pyvis, pydantic-settings, pdfminer.six, opentelemetry-exporter-otlp-proto-common, openai, onnxruntime, llama-cloud, langsmith, lancedb, kubernetes, fastapi, dataclasses-json, transformers, selenium, qdrant-client, pdfplumber, opentelemetry-instrumentation, llama-index-core, litellm, langchain-core, instructor, cohere, auth0-python, opentelemetry-instrumentation-asgi, opentelemetry-exporter-otlp-proto-http, opentelemetry-exporter-otlp-proto-grpc, mem0ai, llama-parse, llama-index-readers-file, llama-index-llms-openai, llama-index-indices-managed-llama-cloud, llama-index-embeddings-openai, langchain-openai, opentelemetry-instrumentation-fastapi, llama-index-readers-llama-parse, llama-index-multi-modal-llms-openai, llama-index-llms-openai-like, llama_index.embeddings.huggingface, llama-index-cli, llama-index-agent-openai, langchain, llama-index-program-openai, llama-index-llms-groq, langchain-community, chromadb, llama-index-question-gen-openai, langchain-experimental, llama-index, langchain-cohere, embedchain, crewai-tools, crewai\n",
      "  Attempting uninstall: protobuf\n",
      "    Found existing installation: protobuf 4.25.5\n",
      "    Uninstalling protobuf-4.25.5:\n",
      "      Successfully uninstalled protobuf-4.25.5\n",
      "  Attempting uninstall: jiter\n",
      "    Found existing installation: jiter 0.8.2\n",
      "    Uninstalling jiter-0.8.2:\n",
      "      Successfully uninstalled jiter-0.8.2\n",
      "  Attempting uninstall: httpx\n",
      "    Found existing installation: httpx 0.28.1\n",
      "    Uninstalling httpx-0.28.1:\n",
      "      Successfully uninstalled httpx-0.28.1\n",
      "  Attempting uninstall: tokenizers\n",
      "    Found existing installation: tokenizers 0.21.0\n",
      "    Uninstalling tokenizers-0.21.0:\n",
      "      Successfully uninstalled tokenizers-0.21.0\n",
      "  Attempting uninstall: openai\n",
      "    Found existing installation: openai 1.57.4\n",
      "    Uninstalling openai-1.57.4:\n",
      "      Successfully uninstalled openai-1.57.4\n",
      "  Attempting uninstall: langsmith\n",
      "    Found existing installation: langsmith 0.2.3\n",
      "    Uninstalling langsmith-0.2.3:\n",
      "      Successfully uninstalled langsmith-0.2.3\n",
      "  Attempting uninstall: transformers\n",
      "    Found existing installation: transformers 4.47.0\n",
      "    Uninstalling transformers-4.47.0:\n",
      "      Successfully uninstalled transformers-4.47.0\n",
      "  Attempting uninstall: langchain-core\n",
      "    Found existing installation: langchain-core 0.3.25\n",
      "    Uninstalling langchain-core-0.3.25:\n",
      "      Successfully uninstalled langchain-core-0.3.25\n",
      "  Attempting uninstall: langchain\n",
      "    Found existing installation: langchain 0.3.12\n",
      "    Uninstalling langchain-0.3.12:\n",
      "      Successfully uninstalled langchain-0.3.12\n",
      "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "tensorflow 2.17.1 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 5.29.2 which is incompatible.\n",
      "tensorflow-metadata 1.13.1 requires protobuf<5,>=3.20.3, but you have protobuf 5.29.2 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0mSuccessfully installed Mako-1.3.8 alembic-1.14.0 appdirs-1.4.4 asgiref-3.8.1 auth0-python-4.7.2 backoff-2.2.1 bcrypt-4.2.1 build-1.2.2.post1 chroma-hnswlib-0.7.6 chromadb-0.5.23 cohere-5.13.3 coloredlogs-15.0.1 crewai-0.86.0 crewai-tools-0.17.0 dataclasses-json-0.6.7 deprecation-2.1.0 dirtyjson-1.0.8 docker-7.1.0 docx2txt-0.8 durationpy-0.9 embedchain-0.1.125 fastapi-0.115.6 fastavro-1.9.7 filetype-1.2.0 gptcache-0.1.44 grpcio-tools-1.68.1 h2-4.1.0 hpack-4.0.0 httptools-0.6.4 httpx-0.27.2 httpx-sse-0.4.0 humanfriendly-10.0 hyperframe-6.0.1 instructor-1.7.0 jedi-0.19.2 jiter-0.6.1 json-repair-0.32.0 jsonref-1.1.0 kubernetes-31.0.0 lancedb-0.17.0 langchain-0.3.13 langchain-cohere-0.3.3 langchain-community-0.3.13 langchain-core-0.3.27 langchain-experimental-0.3.3 langchain-openai-0.2.13 langsmith-0.1.147 litellm-1.55.6 llama-cloud-0.1.6 llama-index-0.12.6 llama-index-agent-openai-0.4.1 llama-index-cli-0.4.0 llama-index-core-0.12.7 llama-index-embeddings-openai-0.3.1 llama-index-indices-managed-llama-cloud-0.6.3 llama-index-llms-groq-0.3.1 llama-index-llms-openai-0.3.12 llama-index-llms-openai-like-0.3.3 llama-index-multi-modal-llms-openai-0.4.1 llama-index-program-openai-0.3.1 llama-index-question-gen-openai-0.3.0 llama-index-readers-file-0.4.1 llama-index-readers-llama-parse-0.4.0 llama-parse-0.5.18 llama_index.embeddings.huggingface-0.4.0 marshmallow-3.23.2 mem0ai-0.1.36 mmh3-5.0.1 monotonic-1.6 mypy-extensions-1.0.0 nodeenv-1.9.1 onnxruntime-1.20.1 openai-1.58.1 opentelemetry-exporter-otlp-proto-common-1.29.0 opentelemetry-exporter-otlp-proto-grpc-1.29.0 opentelemetry-exporter-otlp-proto-http-1.29.0 opentelemetry-instrumentation-0.50b0 opentelemetry-instrumentation-asgi-0.50b0 opentelemetry-instrumentation-fastapi-0.50b0 opentelemetry-proto-1.29.0 opentelemetry-util-http-0.50b0 outcome-1.3.0.post0 overrides-7.7.0 parameterized-0.9.0 pdfminer.six-20231228 pdfplumber-0.11.4 portalocker-2.10.1 posthog-3.7.4 protobuf-5.29.2 pydantic-settings-2.7.0 pylance-0.20.0 pypdf-5.1.0 pypdfium2-4.30.0 pypika-0.48.9 pyproject_hooks-1.2.0 pyright-1.1.391 pysbd-0.3.4 python-dotenv-1.0.1 pytube-15.0.0 pyvis-0.3.2 qdrant-client-1.12.1 schema-0.7.7 selenium-4.27.1 sortedcontainers-2.4.0 starlette-0.41.3 striprtf-0.0.26 tiktoken-0.7.0 tokenizers-0.20.3 tomli-w-1.1.0 transformers-4.46.3 trio-0.27.0 trio-websocket-0.11.1 types-requests-2.32.0.20241016 typing-inspect-0.9.0 uv-0.5.10 uvicorn-0.34.0 uvloop-0.21.0 watchfiles-1.0.3 wsproto-1.2.0\n"
     ]
    },
    {
     "data": {
      "application/vnd.colab-display-data+json": {
       "id": "53f9104d19a24a4fbd70df9d68db7e90",
       "pip_warning": {
        "packages": [
         "transformers"
        ]
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!pip install llama-index llama_index.embeddings.huggingface llama-index-readers-file llama-index-llms-groq crewai crewai-tools"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d57e8b24",
   "metadata": {
    "id": "FZAZrA0UhJoF"
   },
   "source": [
    "# Aula 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1b2eb66",
   "metadata": {
    "id": "KzK6I3AVipuM"
   },
   "outputs": [],
   "source": [
    "from llama_index.core import Settings\n",
    "from llama_index.llms.groq import Groq\n",
    "\n",
    "from google.colab import userdata\n",
    "groq = userdata.get('GROQ_API_KEY')\n",
    "\n",
    "\n",
    "llm = Groq(model=\"llama-3.3-70b-versatile\", api_key=groq)\n",
    "\n",
    "Settings.llm = llm\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "29d49469",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "QV5Aqe9zdMZU",
    "outputId": "6fc7a151-b67f-4d60-c5a0-7b44c2ab11d1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Título: Calling Carlos: Llamando a Carlos - Books\n",
      "Link: https://www.amazon.com/Calling-Carlos-Mar%C3%ADa-Victoria-Castillo/dp/1964792010\n",
      "\n",
      "Título: Calling Carlos: Llamando a Carlos (Paperback)\n",
      "Link: https://www.booksoup.com/book/9781964792019\n",
      "\n",
      "Título: Calling Carlos: Llamando a Carlos (Paperback)\n",
      "Link: https://www.avidbookshop.com/book/9781964792019\n",
      "\n",
      "Título: Llamando a Carlos by Castillo, MarÍa Victoria, Brand New ...\n",
      "Link: https://www.ebay.com/itm/196551782966\n",
      "\n",
      "Título: Calling Carlos: Llamando a Carlos\n",
      "Link: https://agendabookshop.com/products/calling-carlos-llamando-a-carlos?srsltid=AfmBOoqsbwFW2-tPfrPr-YIwM2eDbMtwjrxSAngrUhVgTrQfJkGi1v2b\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "\n",
    "def buscar_mencoes_sem_api(termo: str) -> str:\n",
    "    \"\"\"\n",
    "    Busca menções a um termo na web usando o Google Search (web scraping).\n",
    "\n",
    "    Args:\n",
    "        termo (str): O termo ou nome que você deseja buscar.\n",
    "\n",
    "    Returns:\n",
    "        str: Resultados encontrados (títulos e links) ou uma mensagem indicando que nada foi encontrado.\n",
    "    \"\"\"\n",
    "    # URL de busca no Google\n",
    "    url = f\"https://www.google.com/search?q={termo.replace(' ', '+')}\"\n",
    "\n",
    "    # Cabeçalhos para simular um navegador (necessário para evitar bloqueios simples)\n",
    "    headers = {\n",
    "        \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36\"\n",
    "    }\n",
    "\n",
    "    # Fazendo a requisição\n",
    "    response = requests.get(url, headers=headers)\n",
    "\n",
    "    if response.status_code != 200:\n",
    "        return \"Não foi possível acessar o Google. Tente novamente mais tarde.\"\n",
    "\n",
    "    # Parseando o HTML da página\n",
    "    soup = BeautifulSoup(response.text, \"html.parser\")\n",
    "\n",
    "    # Encontrando os resultados de busca\n",
    "    resultados = soup.find_all(\"div\", class_=\"tF2Cxc\")  # Classe específica dos resultados do Google\n",
    "\n",
    "    # Processando os resultados\n",
    "    lista_resultados = []\n",
    "    for resultado in resultados[:5]:  # Pegando apenas os 5 primeiros resultados\n",
    "        titulo = resultado.find(\"h3\").text if resultado.find(\"h3\") else \"Sem título\"\n",
    "        link = resultado.find(\"a\")[\"href\"] if resultado.find(\"a\") else \"Sem link\"\n",
    "        lista_resultados.append(f\"Título: {titulo}\\nLink: {link}\")\n",
    "\n",
    "    # Retornando os resultados formatados\n",
    "    if lista_resultados:\n",
    "        return \"\\n\\n\".join(lista_resultados)\n",
    "    else:\n",
    "        return \"Nenhuma menção encontrada.\"\n",
    "\n",
    "# Exemplo de uso\n",
    "print(buscar_mencoes_sem_api(\"Carlos Llamando\"))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dfb3983c",
   "metadata": {
    "id": "HTdJM0Hli4_y"
   },
   "outputs": [],
   "source": [
    "from llama_index.core.tools import FunctionTool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d515a74c",
   "metadata": {
    "id": "-fU8rCHSjurU"
   },
   "outputs": [],
   "source": [
    "ferramenta = FunctionTool.from_defaults(fn=buscar_mencoes_sem_api,name=\"Busca menções\",description=(\n",
    "    \"\"\"    Busca menções a um termo na web usando o Google Search (web scraping).\n",
    "\n",
    "    Args:\n",
    "        termo (str): O termo ou nome que você deseja buscar.\n",
    "\n",
    "    Returns:\n",
    "        str: Resultados encontrados (títulos e links) ou uma mensagem indicando que nada foi encontrado.\"\"\"\n",
    "    ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e12367d",
   "metadata": {
    "id": "CRNcLHJykaNO"
   },
   "outputs": [],
   "source": [
    "from llama_index.core.agent import FunctionCallingAgentWorker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a474a889",
   "metadata": {
    "id": "4SZuFE_ndjxr"
   },
   "outputs": [],
   "source": [
    "# Criando o agente\n",
    "agent_worker = FunctionCallingAgentWorker.from_tools(\n",
    "    tools=[ferramenta],\n",
    "    verbose=True,\n",
    "    allow_parallel_tool_calls=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4f6b37a7",
   "metadata": {
    "id": "trHU8MnUkdhO"
   },
   "outputs": [],
   "source": [
    "from llama_index.core.agent import AgentRunner"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9c5c8a53",
   "metadata": {
    "id": "1mofEG0ihH62"
   },
   "outputs": [],
   "source": [
    "agent = AgentRunner(agent_worker)\n",
    "\n",
    "# Consultando o agente\n",
    "response = agent.chat(\"Quais são as últimas menções sobre Carlos Llamando?\")"
   ]
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}