Merge pull request #195 from raspawar/raspawar/nvidia_integration

NVIDIA NIM CrewAI Integration

nvidia_models/intro/.env.example

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+NVIDIA_API_KEY=
+MODEL=meta/llama-3.1-8b-instruct

nvidia_models/intro/.gitignore

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+.env
+.DS_Store
+__pycache__
+.venv
+poetry.lock
+.ruff_cache

nvidia_models/intro/Makefile

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+.PHONY: all format lint test tests integration_tests help
+
+# Default target executed when no arguments are given to make.
+all: help
+
+install: ## Install the poetry environment and dependencies
+	poetry install --no-root
+
+clean: ## Clean up cache directories and build artifacts
+	find . -type d -name "__pycache__" -exec rm -rf {} +
+	find . -type d -name "*.pyc" -exec rm -rf {} +
+	find . -type d -name ".ruff_cache" -exec rm -rf {} +
+	find . -type d -name ".pytest_cache" -exec rm -rf {} +
+	find . -type d -name ".coverage" -exec rm -rf {} +
+	rm -rf dist/
+	rm -rf build/
+
+######################
+# LINTING AND FORMATTING
+######################
+
+# Define a variable for Python and notebook files.
+PYTHON_FILES=.
+MYPY_CACHE=.mypy_cache
+lint: ## Run code quality tools
+	poetry run ruff check $(PYTHON_FILES)
+	poetry run ruff format $(PYTHON_FILES) --check
+
+format: ## Format code using ruff
+	poetry run ruff format $(PYTHON_FILES)
+	poetry run ruff check $(PYTHON_FILES) --fix
+
+######################
+# HELP
+######################
+
+help:
+	@echo '----'
+	@echo 'format                       - run code formatters'
+	@echo 'lint                         - run linters'

nvidia_models/intro/README.md

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+# AI Crew using NVIDIA NIM Endpoint
+
+## Introduction
+This is a simple example using the CrewAI framework with an NVIDIA endpoint and langchain-nvidia-ai-endpoints integration.
+
+## Running the Script
+This example uses the Azure OpenAI API to call a model. 
+
+- **Configure Environment**: Set NVIDIA_API_KEY to appropriate api key.
+                             Set MODEL to select appropriate model
+- **Install Dependencies**: Run `make install`.
+- **Execute the Script**: Run `python main.py` to see a list of recommended changes to this document.
+
+## Details & Explanation
+- **Running the Script**: Execute `python main.py`. The script will leverage the CrewAI framework to process the specified file and return a list of changes.

nvidia_models/intro/main.py

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+import logging
+import os
+from typing import Any, Dict, List, Optional, Union
+
+import litellm
+from crewai import LLM, Agent, Crew, Process, Task
+from crewai.utilities.exceptions.context_window_exceeding_exception import (
+    LLMContextLengthExceededException,
+)
+from dotenv import load_dotenv
+from langchain_nvidia_ai_endpoints import ChatNVIDIA
+
+load_dotenv()
+
+
+class nvllm(LLM):
+    def __init__(
+        self,
+        llm: ChatNVIDIA,
+        model_str: str,
+        timeout: Optional[Union[float, int]] = None,
+        temperature: Optional[float] = None,
+        top_p: Optional[float] = None,
+        n: Optional[int] = None,
+        stop: Optional[Union[str, List[str]]] = None,
+        max_completion_tokens: Optional[int] = None,
+        max_tokens: Optional[int] = None,
+        presence_penalty: Optional[float] = None,
+        frequency_penalty: Optional[float] = None,
+        logit_bias: Optional[Dict[int, float]] = None,
+        response_format: Optional[Dict[str, Any]] = None,
+        seed: Optional[int] = None,
+        logprobs: Optional[bool] = None,
+        top_logprobs: Optional[int] = None,
+        base_url: Optional[str] = None,
+        api_version: Optional[str] = None,
+        api_key: Optional[str] = None,
+        callbacks: List[Any] = None,
+        **kwargs,
+    ):
+        self.model = model_str
+        self.timeout = timeout
+        self.temperature = temperature
+        self.top_p = top_p
+        self.n = n
+        self.stop = stop
+        self.max_completion_tokens = max_completion_tokens
+        self.max_tokens = max_tokens
+        self.presence_penalty = presence_penalty
+        self.frequency_penalty = frequency_penalty
+        self.logit_bias = logit_bias
+        self.response_format = response_format
+        self.seed = seed
+        self.logprobs = logprobs
+        self.top_logprobs = top_logprobs
+        self.base_url = base_url
+        self.api_version = api_version
+        self.api_key = api_key
+        self.callbacks = callbacks
+        self.kwargs = kwargs
+        self.llm = llm
+
+        if callbacks is None:
+            self.callbacks = callbacks = []
+
+        self.set_callbacks(callbacks)
+
+    def call(self, messages: List[Dict[str, str]], callbacks: List[Any] = None) -> str:
+        if callbacks is None:
+            callbacks = []
+        if callbacks and len(callbacks) > 0:
+            self.set_callbacks(callbacks)
+
+        try:
+            params = {
+                "model": self.llm.model,
+                "input": messages,
+                "timeout": self.timeout,
+                "temperature": self.temperature,
+                "top_p": self.top_p,
+                "n": self.n,
+                "stop": self.stop,
+                "max_tokens": self.max_tokens or self.max_completion_tokens,
+                "presence_penalty": self.presence_penalty,
+                "frequency_penalty": self.frequency_penalty,
+                "logit_bias": self.logit_bias,
+                "response_format": self.response_format,
+                "seed": self.seed,
+                "logprobs": self.logprobs,
+                "top_logprobs": self.top_logprobs,
+                "api_key": self.api_key,
+                **self.kwargs,
+            }
+
+            response = self.llm.invoke(**params)
+            return response.content
+        except Exception as e:
+            if not LLMContextLengthExceededException(str(e))._is_context_limit_error(
+                str(e)
+            ):
+                logging.error(f"LiteLLM call failed: {str(e)}")
+
+            raise  # Re-raise the exception after logging
+
+    def set_callbacks(self, callbacks: List[Any]):
+        callback_types = [type(callback) for callback in callbacks]
+        for callback in litellm.success_callback[:]:
+            if type(callback) in callback_types:
+                litellm.success_callback.remove(callback)
+
+        for callback in litellm._async_success_callback[:]:
+            if type(callback) in callback_types:
+                litellm._async_success_callback.remove(callback)
+
+        litellm.callbacks = callbacks
+
+
+model = os.environ.get("MODEL", "meta/llama-3.1-8b-instruct")
+llm = ChatNVIDIA(model=model)
+default_llm = nvllm(model_str="nvidia_nim/" + model, llm=llm)
+
+os.environ["NVIDIA_NIM_API_KEY"] = os.environ.get("NVIDIA_API_KEY")
+
+# Create a researcher agent
+researcher = Agent(
+    role="Senior Researcher",
+    goal="Discover groundbreaking technologies",
+    verbose=True,
+    llm=default_llm,
+    backstory=(
+        "A curious mind fascinated by cutting-edge innovation and the potential "
+        "to change the world, you know everything about tech."
+    ),
+)
+
+# Task for the researcher
+research_task = Task(
+    description="Identify the next big trend in AI",
+    agent=researcher,  # Assigning the task to the researcher
+    expected_output="Data Insights",
+)
+
+
+# Instantiate your crew
+tech_crew = Crew(
+    agents=[researcher],
+    tasks=[research_task],
+    process=Process.sequential,  # Tasks will be executed one after the other
+)
+
+# Begin the task execution
+tech_crew.kickoff()

nvidia_models/intro/pyproject.toml

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+[tool.poetry]
+name = "nvidia-intro-crewai-example"
+version = "0.1.0"
+description = ""
+authors = ["raspawar <[email protected]>"]
+
+[tool.poetry.dependencies]
+python = ">=3.10.0,<3.12"
+python-dotenv = "1.0.0"
+litellm = "^1.52.10"
+langchain-nvidia-ai-endpoints = "^0.3.5"
+crewai = "^0.80.0"
+
+[tool.pyright]
+# https://github.com/microsoft/pyright/blob/main/docs/configuration.md
+useLibraryCodeForTypes = true
+exclude = [".cache"]
+
+[tool.ruff.lint]
+select = [
+    "E",     # pycodestyle
+    "F",     # pyflakes
+    "I",     # isort
+    "B",     # flake8-bugbear
+    "C4",    # flake8-comprehensions
+    "ARG",   # flake8-unused-arguments
+    "SIM",   # flake8-simplify
+    "T201",  # print
+]
+ignore = [
+    "W291",  # trailing whitespace
+    "W292",  # no newline at end of file
+    "W293",  # blank line contains whitespace
+]
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"

nvidia_models/intro/scripts/check_pydantic.sh

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+#!/bin/bash
+#
+# This script searches for lines starting with "import pydantic" or "from pydantic"
+# in tracked files within a Git repository.
+#
+# Usage: ./scripts/check_pydantic.sh /path/to/repository
+
+# Check if a path argument is provided
+if [ $# -ne 1 ]; then
+  echo "Usage: $0 /path/to/repository"
+  exit 1
+fi
+
+repository_path="$1"
+
+# Search for lines matching the pattern within the specified repository
+result=$(git -C "$repository_path" grep -E '^import pydantic|^from pydantic')
+
+# Check if any matching lines were found
+if [ -n "$result" ]; then
+  echo "ERROR: The following lines need to be updated:"
+  echo "$result"
+  echo "Please replace the code with an import from langchain_core.pydantic_v1."
+  echo "For example, replace 'from pydantic import BaseModel'"
+  echo "with 'from langchain_core.pydantic_v1 import BaseModel'"
+  exit 1
+fi

nvidia_models/intro/scripts/lint_imports.sh

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+#!/bin/bash
+
+set -eu
+
+# Initialize a variable to keep track of errors
+errors=0
+
+# make sure not importing from langchain or langchain_experimental
+git --no-pager grep '^from langchain\.' . && errors=$((errors+1))
+git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1))
+
+# Decide on an exit status based on the errors
+if [ "$errors" -gt 0 ]; then
+    exit 1
+else
+    exit 0
+fi

nvidia_models/marketing_strategy/.env.example

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+SERPER_API_KEY=
+NVIDIA_API_KEY=
+MODEL=meta/llama-3.1-8b-instruct

nvidia_models/marketing_strategy/.gitignore

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+.env
+.DS_Store
+__pycache__
+.venv
+poetry.lock
+.ruff_cache

nvidia_models/marketing_strategy/Makefile

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+.PHONY: all format lint test tests integration_tests help
+
+# Default target executed when no arguments are given to make.
+all: help
+
+install: ## Install the poetry environment and dependencies
+	poetry install --no-root
+
+clean: ## Clean up cache directories and build artifacts
+	find . -type d -name "__pycache__" -exec rm -rf {} +
+	find . -type d -name "*.pyc" -exec rm -rf {} +
+	find . -type d -name ".ruff_cache" -exec rm -rf {} +
+	find . -type d -name ".pytest_cache" -exec rm -rf {} +
+	find . -type d -name ".coverage" -exec rm -rf {} +
+	rm -rf dist/
+	rm -rf build/
+
+######################
+# LINTING AND FORMATTING
+######################
+
+# Define a variable for Python and notebook files.
+PYTHON_FILES=.
+MYPY_CACHE=.mypy_cache
+lint: ## Run code quality tools
+	poetry run ruff check $(PYTHON_FILES)
+	poetry run ruff format $(PYTHON_FILES) --check
+
+format: ## Format code using ruff
+	poetry run ruff format $(PYTHON_FILES)
+	poetry run ruff check $(PYTHON_FILES) --fix
+
+######################
+# HELP
+######################
+
+help:
+	@echo '----'
+	@echo 'format                       - run code formatters'
+	@echo 'lint                         - run linters'