1-models_prompts_parsers.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"!pip install -q langchain openai","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:26:27.829859Z","iopub.execute_input":"2023-10-22T04:26:27.830237Z","iopub.status.idle":"2023-10-22T04:26:56.734988Z","shell.execute_reply.started":"2023-10-22T04:26:27.830208Z","shell.execute_reply":"2023-10-22T04:26:56.733889Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"code","source":"!pip install tiktoken","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:27:08.704542Z","iopub.execute_input":"2023-10-22T04:27:08.705057Z","iopub.status.idle":"2023-10-22T04:27:20.188541Z","shell.execute_reply.started":"2023-10-22T04:27:08.705005Z","shell.execute_reply":"2023-10-22T04:27:20.187356Z"},"trusted":true},"execution_count":4,"outputs":[{"name":"stdout","text":"Requirement already satisfied: tiktoken in /opt/conda/lib/python3.10/site-packages (0.5.1)\nRequirement already satisfied: regex>=2022.1.18 in /opt/conda/lib/python3.10/site-packages (from tiktoken) (2023.6.3)\nRequirement already satisfied: requests>=2.26.0 in /opt/conda/lib/python3.10/site-packages (from tiktoken) (2.31.0)\nRequirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (3.1.0)\nRequirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (3.4)\nRequirement already satisfied: urllib3<3,>=1.21.1 in /opt/conda/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (1.26.15)\nRequirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (2023.7.22)\n","output_type":"stream"}]},{"cell_type":"markdown","source":"## Prompts","metadata":{}},{"cell_type":"code","source":"# text prompt template\nfrom langchain.prompts import PromptTemplate\n\ntemplate = \"\"\"You will provided with the sample text. \\\nYour task is to rewrite the text to be gramatically correct. \\\nSample text: ```{sample_text}``` \\\nOutput: \n\"\"\"\nprompt_template = PromptTemplate.from_template(template = template)\n\nsample_text = \"Me likes cats not dogs. They jumps high so much!\"\nfinal_prompt = prompt_template.format(sample_text = sample_text)\nprint(final_prompt)","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:27:20.192319Z","iopub.execute_input":"2023-10-22T04:27:20.192851Z","iopub.status.idle":"2023-10-22T04:27:20.616881Z","shell.execute_reply.started":"2023-10-22T04:27:20.192797Z","shell.execute_reply":"2023-10-22T04:27:20.615471Z"},"trusted":true},"execution_count":5,"outputs":[{"name":"stdout","text":"You will provided with the sample text. Your task is to rewrite the text to be gramatically correct. Sample text: ```Me likes cats not dogs. They jumps high so much!``` Output: \n\n","output_type":"stream"}]},{"cell_type":"code","source":"# chat prompt template\nfrom langchain.prompts import SystemMessagePromptTemplate, HumanMessagePromptTemplate, ChatPromptTemplate\n\nsystem_template = \"\"\"You will provided with the sample text. \\\nYour task is to translate the text into {output_language} language \\\nand summarize the translated text in at most {max_words} words. \\ \n\"\"\"\nsystem_message_prompt_template = SystemMessagePromptTemplate.from_template(system_template)\nhuman_template = \"{sample_text}\"\nhuman_message_prompt_template = HumanMessagePromptTemplate.from_template(human_template)\nchat_prompt_template = ChatPromptTemplate.from_messages([system_message_prompt_template, human_message_prompt_template])\n\nfinal_prompt = chat_prompt_template.format_prompt(\n    output_language=\"English\", \n    max_words=15,\n    sample_text=\"Estoy deseando que llegue el fin de semana.\"\n).to_messages()\nprint(final_prompt)","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:27:20.618859Z","iopub.execute_input":"2023-10-22T04:27:20.620094Z","iopub.status.idle":"2023-10-22T04:27:20.632241Z","shell.execute_reply.started":"2023-10-22T04:27:20.620048Z","shell.execute_reply":"2023-10-22T04:27:20.631208Z"},"trusted":true},"execution_count":6,"outputs":[{"name":"stdout","text":"[SystemMessage(content='You will provided with the sample text. Your task is to translate the text into English language and summarize the translated text in at most 15 words. \\\\ \\n'), HumanMessage(content='Estoy deseando que llegue el fin de semana.')]\n","output_type":"stream"}]},{"cell_type":"markdown","source":"## Models","metadata":{}},{"cell_type":"code","source":"# LLMs\nfrom langchain.llms import OpenAI\nfrom langchain.prompts import PromptTemplate\n\nimport os\nos.environ[\"OPENAI_API_KEY\"] = \"Enter your api key\"\n\nllm = OpenAI(model_name= \"gpt-3.5-turbo\" , temperature= 0)\ntempalte = \"\"\"You will provided with the sample text. \\\nYour task is to rewrite the text to be gramatically correct. \\\nSample text: ```{sample_text}``` \\\nOutput: \n\"\"\"\n\nprompt_template = PromptTemplate.from_template(template=template)\n\nsample_text = \"Me likes cats not dogs. They jumps high so much!\"\nfinal_prompt = prompt_template.format(sample_text=sample_text)\n\ncompletion = llm(final_prompt)\nprint(completion)","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:27:49.534237Z","iopub.execute_input":"2023-10-22T04:27:49.534709Z","iopub.status.idle":"2023-10-22T04:27:52.371351Z","shell.execute_reply.started":"2023-10-22T04:27:49.534670Z","shell.execute_reply":"2023-10-22T04:27:52.369699Z"},"trusted":true},"execution_count":8,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/langchain/llms/openai.py:216: UserWarning: You are trying to use a chat model. This way of initializing it is no longer supported. Instead, please use: `from langchain.chat_models import ChatOpenAI`\n  warnings.warn(\n/opt/conda/lib/python3.10/site-packages/langchain/llms/openai.py:811: UserWarning: You are trying to use a chat model. This way of initializing it is no longer supported. Instead, please use: `from langchain.chat_models import ChatOpenAI`\n  warnings.warn(\n","output_type":"stream"},{"name":"stdout","text":"I like cats, not dogs. They jump so high!\n","output_type":"stream"}]},{"cell_type":"code","source":"# Chat models\nfrom langchain.chat_models import ChatOpenAI\nfrom langchain.prompts import SystemMessagePromptTemplate, HumanMessagePromptTemplate, ChatPromptTemplate\nimport os \n\nos.environ[\"OPENAI_API_KEY\"] = \"Enter your api key\"\n\nchat = ChatOpenAI(temperature=0)\nsystem_template = \"\"\"You will provided with the sample text. \\\nYour task is to translate the text into {output_language} language \\\nand summarize the translated text in at most {max_words} words. \\ \n\"\"\"\n\nsystem_message_prompt_template = SystemMessagePromptTemplate.from_template(system_template)\nhuman_template = \"{sample_text}\"\nhuman_message_prompt_template = HumanMessagePromptTemplate.from_template(human_template)\nchat_prompt_template = ChatPromptTemplate.from_messages([system_message_prompt_template, human_message_prompt_template])\nfinal_prompt = chat_prompt_template.format_prompt(\n  output_language=\"English\",\n  max_words=15,\n  sample_text=\"Estoy deseando que llegue el fin de semana.\"\n).to_messages()\n\ncompletion = chat(final_prompt)\nprint(completion)","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:27:55.958765Z","iopub.execute_input":"2023-10-22T04:27:55.959140Z","iopub.status.idle":"2023-10-22T04:27:57.739061Z","shell.execute_reply.started":"2023-10-22T04:27:55.959109Z","shell.execute_reply":"2023-10-22T04:27:57.738012Z"},"trusted":true},"execution_count":9,"outputs":[{"name":"stdout","text":"content=\"I'm looking forward to the weekend. (6 words)\"\n","output_type":"stream"}]},{"cell_type":"code","source":"# Text embeddings\nfrom langchain.embeddings import OpenAIEmbeddings\n\nos.environ[\"OPENAI_API_KEY\"] = \"Enter your api key\"\n\nembeddings = OpenAIEmbeddings(model = \"text-embedding-ada-002\")\ntext = \"It is imperative that we work towards sustainable practices, reducing waste and conserving resources.\"\n\nembedded_text = embeddings.embed_query(text)\nprint(embedded_text)","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:28:02.002216Z","iopub.execute_input":"2023-10-22T04:28:02.002604Z","iopub.status.idle":"2023-10-22T04:28:04.915869Z","shell.execute_reply.started":"2023-10-22T04:28:02.002574Z","shell.execute_reply":"2023-10-22T04:28:04.914590Z"},"collapsed":true,"jupyter":{"outputs_hidden":true},"trusted":true},"execution_count":10,"outputs":[{"name":"stdout","text":"[-0.004131294766797781, -0.006632752684219078, 0.00993454824017149, 0.00423174163127087, -0.002243859915304053, 0.00940315048284666, 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\nos.environ[\"OPEN_AI_KEY\"] = \"Enter your api key\"\n\ngift_schema = ResponseSchema(\n    name = \"gift\",\n    description=\"Was the item purchased\\\n    as a gift or somene else?\\\n    Answer True if yes,\\\n    False if not or unknown.\"\n)\n\ndelivery_days_schema = ResponseSchema(\n    name = \"delivery_days\",\n    description = \"How many days\\\n    did it take for the product\\\n    to arrive? If this \\\n    information is not found,\\\n    output -1.\"\n)\n\nprice_value_schema = ResponseSchema(\n    name=\"price_value\",\n    description=\"Extract any\\\n    sentences about the value or \\\n    price, and output them as a \\\n    comma separated Python list.\"\n)\n\nresponse_schemas = [\n    gift_schema,\n    delivery_days_schema,\n    price_value_schema\n]","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:36:05.697039Z","iopub.execute_input":"2023-10-22T04:36:05.697415Z","iopub.status.idle":"2023-10-22T04:36:05.705188Z","shell.execute_reply.started":"2023-10-22T04:36:05.697386Z","shell.execute_reply":"2023-10-22T04:36:05.703953Z"},"trusted":true},"execution_count":12,"outputs":[]},{"cell_type":"code","source":"output_parser = StructuredOutputParser.from_response_schemas(response_schemas)\nformat_instructions = output_parser.get_format_instructions()\nprint(format_instructions)","metadata":{"execution":{"iopub.status.busy":"2023-10-22T04:36:43.238347Z","iopub.execute_input":"2023-10-22T04:36:43.238756Z","iopub.status.idle":"2023-10-22T04:36:43.244772Z","shell.execute_reply.started":"2023-10-22T04:36:43.238721Z","shell.execute_reply":"2023-10-22T04:36:43.243667Z"},"trusted":true},"execution_count":14,"outputs":[{"name":"stdout","text":"The output should be a markdown code snippet formatted in the following schema, including the leading and trailing \"```json\" and \"```\":\n\n```json\n{\n\t\"gift\": string  // Was the item purchased    as a gift or somene else?    Answer True if yes,    False if not or unknown.\n\t\"delivery_days\": string  // How many days    did it take for the product    to arrive? If this     information is not found,    output -1.\n\t\"price_value\": string  // Extract any    sentences about the value or     price, and output them as a     comma separated Python list.\n}\n```\n","output_type":"stream"}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}