add maritalk (#10925)

docs/examples/llm/maritalk.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a href=\"https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/llm/maritalk.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>\n",
+    "\n",
+    "# Maritalk\n",
+    "\n",
+    "## Introduction\n",
+    "\n",
+    "MariTalk is an assistant developed by the Brazilian company [Maritaca AI](www.maritaca.ai).\n",
+    "MariTalk is based on language models that have been specially trained to understand Portuguese well.\n",
+    "\n",
+    "This notebook demonstrates how to use MariTalk with llama-index through a simple example."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Installation\n",
+    "If you're opening this Notebook on colab, you will probably need to install LlamaIndex."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install llama-index-llms-maritalk\n",
+    "!pip install llama-index"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## API Key\n",
+    "You will need an API key that can be obtained from chat.maritaca.ai (\"Chaves da API\" section)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Usage\n",
+    "\n",
+    "### Chat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from llama_index.core.llms import ChatMessage\n",
+    "from llama_index.llms.maritalk import Maritalk\n",
+    "\n",
+    "# To customize your API key, do this\n",
+    "# otherwise it will lookup MARITALK_API_KEY from your env variable\n",
+    "# llm = Maritalk(api_key=\"<your_maritalk_api_key>\")\n",
+    "\n",
+    "llm = Maritalk()\n",
+    "\n",
+    "# Call chat with a list of messages\n",
+    "messages = [\n",
+    "    ChatMessage(\n",
+    "        role=\"system\",\n",
+    "        content=\"You are an assistant specialized in suggesting pet names. Given the animal, you must suggest 4 names.\",\n",
+    "    ),\n",
+    "    ChatMessage(role=\"user\", content=\"I have a dog.\"),\n",
+    "]\n",
+    "\n",
+    "response = llm.chat(messages)\n",
+    "print(response)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### Few-shot examples\n",
+    "\n",
+    "We recommend using the `llm.complete()` method when using the model with few-shot examples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "prompt = \"\"\"Classifique a resenha de filme como \"positiva\" ou \"negativa\".\n",
+    "\n",
+    "Resenha: Gostei muito do filme, é o melhor do ano!\n",
+    "Classe: positiva\n",
+    "\n",
+    "Resenha: O filme deixa muito a desejar.\n",
+    "Classe: negativa\n",
+    "\n",
+    "Resenha: Apesar de longo, valeu o ingresso..\n",
+    "Classe:\"\"\"\n",
+    "\n",
+    "response = llm.complete(prompt, stopping_tokens=[\"\\n\"])\n",
+    "print(response)"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

docs/module_guides/models/llms/modules.md

@@ -150,6 +150,15 @@ maxdepth: 1
 /examples/llm/localai.ipynb
 ```
 
+## MariTalk
+
+```{toctree}
+---
+maxdepth: 1
+---
+/examples/llm/maritalk.ipynb
+```
+
 ## MistralAI
 
 ```{toctree}

llama-index-integrations/llms/llama-index-llms-maritalk/.gitignore

+llama_index/_static
+.DS_Store
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+bin/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+etc/
+include/
+lib/
+lib64/
+parts/
+sdist/
+share/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+.ruff_cache
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+notebooks/
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+pyvenv.cfg
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# Jetbrains
+.idea
+modules/
+*.swp
+
+# VsCode
+.vscode
+
+# pipenv
+Pipfile
+Pipfile.lock
+
+# pyright
+pyrightconfig.json

llama-index-integrations/llms/llama-index-llms-maritalk/BUILD

+poetry_requirements(
+    name="poetry",
+)

llama-index-integrations/llms/llama-index-llms-maritalk/Makefile

+GIT_ROOT ?= $(shell git rev-parse --show-toplevel)
+
+help:	## Show all Makefile targets.
+	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}'
+
+format:	## Run code autoformatters (black).
+	pre-commit install
+	git ls-files | xargs pre-commit run black --files
+
+lint:	## Run linters: pre-commit (black, ruff, codespell) and mypy
+	pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files
+
+test:	## Run tests via pytest.
+	pytest tests
+
+watch-docs:	## Build and watch documentation.
+	sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/

llama-index-integrations/llms/llama-index-llms-maritalk/README.md

+# LlamaIndex Llms Integration: Maritalk

llama-index-integrations/llms/llama-index-llms-maritalk/llama_index/llms/maritalk/BUILD

+python_sources()

llama-index-integrations/llms/llama-index-llms-maritalk/llama_index/llms/maritalk/__init__.py

+from llama_index.llms.maritalk.base import Maritalk
+
+
+__all__ = ["Maritalk"]

llama-index-integrations/llms/llama-index-llms-maritalk/llama_index/llms/maritalk/base.py

+from typing import Any, Optional, Sequence
+from llama_index.core.base.llms.types import (
+    ChatMessage,
+    ChatResponse,
+    ChatResponseAsyncGen,
+    ChatResponseGen,
+    CompletionResponse,
+    CompletionResponseAsyncGen,
+    CompletionResponseGen,
+    LLMMetadata,
+    MessageRole,
+)
+from llama_index.core.bridge.pydantic import Field, PrivateAttr
+from llama_index.core.llms.llm import LLM
+from llama_index.core.llms.callbacks import (
+    llm_chat_callback,
+    llm_completion_callback,
+)
+import requests
+import os
+
+
+class Maritalk(LLM):
+    api_key: Optional[str] = Field(default=None, description="Your MariTalk API key.")
+    temperature: float = Field(
+        default=0.7,
+        gt=0.0,
+        lt=1.0,
+        description="Run inference with this temperature. Must be in the"
+        "closed interval [0.0, 1.0].",
+    )
+    max_tokens: int = Field(
+        default=512,
+        gt=0,
+        description="The maximum number of tokens to" "generate in the reply.",
+    )
+    do_sample: bool = Field(
+        default=True,
+        description="Whether or not to use sampling; use `True` to enable.",
+    )
+    top_p: float = Field(
+        default=0.95,
+        gt=0.0,
+        lt=1.0,
+        description="Nucleus sampling parameter controlling the size of"
+        " the probability mass considered for sampling.",
+    )
+    system_message_workaround: bool = Field(
+        default=True,
+        description="Whether to include a workaround for system"
+        " message by adding it as a user message.",
+    )
+
+    _endpoint: str = PrivateAttr("https://chat.maritaca.ai/api/chat/inference")
+
+    def __init__(self, **kwargs) -> None:
+        super().__init__(**kwargs)
+        # If an API key is not provided during instantiation,
+        # fall back to the MARITALK_API_KEY environment variable
+        self.api_key = self.api_key or os.getenv("MARITALK_API_KEY")
+        if not self.api_key:
+            raise ValueError(
+                "An API key must be provided or set in the "
+                "'MARITALK_API_KEY' environment variable."
+            )
+
+    @classmethod
+    def class_name(cls) -> str:
+        return "Maritalk"
+
+    @property
+    def metadata(self) -> LLMMetadata:
+        return LLMMetadata(
+            model_name="maritalk",
+            context_window=self.max_tokens,
+            is_chat_model=True,
+        )
+
+    @llm_chat_callback()
+    def chat(self, messages: Sequence[ChatMessage], **kwargs: Any) -> ChatResponse:
+        # Prepare the data payload for the Maritalk API
+        formatted_messages = [
+            {
+                "role": "user" if msg.role == MessageRole.USER else "assistant",
+                "content": msg.content,
+            }
+            for msg in messages
+        ]
+
+        data = {
+            "messages": formatted_messages,
+            "do_sample": self.do_sample,
+            "max_tokens": self.max_tokens,
+            "temperature": self.temperature,
+            "top_p": self.top_p,
+        }
+
+        # Update data payload with additional kwargs if any
+        data.update(kwargs)
+
+        headers = {"authorization": f"Key {self.api_key}"}
+
+        response = requests.post(self._endpoint, json=data, headers=headers)
+        if response.status_code == 429:
+            return ChatResponse(
+                message=ChatMessage(
+                    role=MessageRole.SYSTEM,
+                    content="Rate limited, please try again soon",
+                ),
+                raw=response.text,
+            )
+        elif response.ok:
+            answer = response.json()["answer"]
+            return ChatResponse(
+                message=ChatMessage(role=MessageRole.ASSISTANT, content=answer),
+                raw=response.json(),
+            )
+        else:
+            response.raise_for_status()  # noqa: RET503
+
+    @llm_completion_callback()
+    def complete(
+        self, prompt: str, formatted: bool = False, **kwargs: Any
+    ) -> CompletionResponse:
+        # Prepare the data payload for the Maritalk API
+        data = {
+            "messages": prompt,
+            "do_sample": self.do_sample,
+            "max_tokens": self.max_tokens,
+            "temperature": self.temperature,
+            "top_p": self.top_p,
+            "chat_mode": False,
+        }
+
+        # Update data payload with additional kwargs if any
+        data.update(kwargs)
+
+        headers = {"authorization": f"Key {self.api_key}"}
+
+        response = requests.post(self._endpoint, json=data, headers=headers)
+        if response.status_code == 429:
+            return CompletionResponse(
+                text="Rate limited, please try again soon",
+                raw=response.text,
+            )
+        elif response.ok:
+            answer = response.json()["answer"]
+            return CompletionResponse(
+                text=answer,
+                raw=response.json(),
+            )
+        else:
+            response.raise_for_status()  # noqa: RET503
+
+    def stream_chat(
+        self, messages: Sequence[ChatMessage], **kwargs: Any
+    ) -> ChatResponseGen:
+        raise NotImplementedError(
+            "Maritalk does not currently support streaming completion."
+        )
+
+    def stream_complete(
+        self, prompt: str, formatted: bool = False, **kwargs: Any
+    ) -> CompletionResponseGen:
+        raise NotImplementedError(
+            "Maritalk does not currently support streaming completion."
+        )
+
+    @llm_chat_callback()
+    async def achat(
+        self, messages: Sequence[ChatMessage], **kwargs: Any
+    ) -> ChatResponse:
+        return self.chat(messages, **kwargs)
+
+    @llm_completion_callback()
+    async def acomplete(
+        self, prompt: str, formatted: bool = False, **kwargs: Any
+    ) -> CompletionResponse:
+        return self.complete(prompt, formatted, **kwargs)
+
+    @llm_chat_callback()
+    async def astream_chat(
+        self, messages: Sequence[ChatMessage], **kwargs: Any
+    ) -> ChatResponseAsyncGen:
+        raise NotImplementedError(
+            "Maritalk does not currently support streaming completion."
+        )
+
+    @llm_completion_callback()
+    async def astream_complete(
+        self, prompt: str, formatted: bool = False, **kwargs: Any
+    ) -> CompletionResponseAsyncGen:
+        raise NotImplementedError(
+            "Maritalk does not currently support streaming completion."
+        )

llama-index-integrations/llms/llama-index-llms-maritalk/pyproject.toml

+[build-system]
+build-backend = "poetry.core.masonry.api"
+requires = ["poetry-core"]
+
+[tool.codespell]
+check-filenames = true
+check-hidden = true
+# Feel free to un-skip examples, and experimental, you will just need to
+# work through many typos (--write-changes and --interactive will help)
+skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb"
+
+[tool.llamahub]
+contains_example = false
+import_path = "llama_index.llms.maritalk"
+
+[tool.llamahub.class_authors]
+Maritalk = "rodrigo-f-nogueira"
+
+[tool.mypy]
+disallow_untyped_defs = true
+# Remove venv skip when integrated with pre-commit
+exclude = ["_static", "build", "examples", "notebooks", "venv"]
+ignore_missing_imports = true
+python_version = "3.8"
+
+[tool.poetry]
+authors = ["Your Name <you@example.com>"]
+description = "llama-index llms maritalk integration"
+license = "MIT"
+name = "llama-index-llms-maritalk"
+packages = [{include = "llama_index/"}]
+readme = "README.md"
+version = "0.1.0"
+
+[tool.poetry.dependencies]
+python = ">=3.8.1,<3.12"
+llama-index-core = "^0.10.0"
+
+[tool.poetry.group.dev.dependencies]
+black = {extras = ["jupyter"], version = "<=23.9.1,>=23.7.0"}
+codespell = {extras = ["toml"], version = ">=v2.2.6"}
+ipython = "8.10.0"
+jupyter = "^1.0.0"
+mypy = "0.991"
+pre-commit = "3.2.0"
+pylint = "2.15.10"
+pytest = "7.2.1"
+pytest-mock = "3.11.1"
+ruff = "0.0.292"
+tree-sitter-languages = "^1.8.0"
+types-Deprecated = ">=0.1.0"
+types-PyYAML = "^6.0.12.12"
+types-protobuf = "^4.24.0.4"
+types-redis = "4.5.5.0"
+types-requests = "2.28.11.8"  # TODO: unpin when mypy>0.991
+types-setuptools = "67.1.0.0"