From 3dbaedf049af327082167e2ea6a56aff011c5554 Mon Sep 17 00:00:00 2001 From: vizsatiz Date: Sat, 16 Aug 2025 13:24:56 +0530 Subject: [PATCH 1/4] Add support for vertex ai --- flo_ai/flo_ai/builder/agent_builder.py | 15 +- flo_ai/flo_ai/llm/__init__.py | 2 + flo_ai/flo_ai/llm/vertexai_llm.py | 22 ++ flo_ai/poetry.lock | 474 ++++++++++++++++++++++++- flo_ai/pyproject.toml | 1 + 5 files changed, 506 insertions(+), 8 deletions(-) create mode 100644 flo_ai/flo_ai/llm/vertexai_llm.py diff --git a/flo_ai/flo_ai/builder/agent_builder.py b/flo_ai/flo_ai/builder/agent_builder.py index 50ffeb83..9b08ada8 100644 --- a/flo_ai/flo_ai/builder/agent_builder.py +++ b/flo_ai/flo_ai/builder/agent_builder.py @@ -2,7 +2,7 @@ import yaml from flo_ai.models.agent import Agent from flo_ai.models.base_agent import ReasoningPattern -from flo_ai.llm import BaseLLM, OpenAI, Anthropic, Gemini, OllamaLLM +from flo_ai.llm import BaseLLM, OpenAI, Anthropic, Gemini, OllamaLLM, VertexAI from flo_ai.tool.base_tool import Tool from flo_ai.formatter.yaml_format_parser import FloYamlParser from pydantic import BaseModel @@ -124,7 +124,7 @@ def from_yaml( # Configure LLM based on model settings if 'model' in agent_config and base_llm is None: base_url = agent_config.get('base_url', None) - model_config = agent_config['model'] + model_config: dict = agent_config['model'] provider = model_config.get('provider', 'openai').lower() model_name = model_config.get('name') @@ -139,6 +139,17 @@ def from_yaml( builder.with_llm(Gemini(model=model_name, base_url=base_url)) elif provider == 'ollama': builder.with_llm(OllamaLLM(model=model_name, base_url=base_url)) + elif provider == 'vertexai': + project = model_config.get('project') + location = model_config.get('location', 'asia-south1') + builder.with_llm( + VertexAI( + model=model_name, + project=project, + location=location, + base_url=base_url, + ) + ) else: raise ValueError(f'Unsupported model provider: {provider}') else: diff --git a/flo_ai/flo_ai/llm/__init__.py b/flo_ai/flo_ai/llm/__init__.py index 29768237..1e38a34b 100644 --- a/flo_ai/flo_ai/llm/__init__.py +++ b/flo_ai/flo_ai/llm/__init__.py @@ -4,6 +4,7 @@ from .ollama_llm import OllamaLLM from .gemini_llm import Gemini from .openai_vllm import OpenAIVLLM +from .vertexai_llm import VertexAI __all__ = [ 'BaseLLM', @@ -13,4 +14,5 @@ 'Gemini', 'OpenAIVLLM', 'ImageMessage', + 'VertexAI', ] diff --git a/flo_ai/flo_ai/llm/vertexai_llm.py b/flo_ai/flo_ai/llm/vertexai_llm.py new file mode 100644 index 00000000..36821334 --- /dev/null +++ b/flo_ai/flo_ai/llm/vertexai_llm.py @@ -0,0 +1,22 @@ +from typing import Optional +from google import genai +from flo_ai.llm.gemini_llm import GeminiLLM + + +class VertexAI(GeminiLLM): + def __init__( + self, + model: str = 'gemini-2.5-flash', + temperature: float = 0.7, + api_key: Optional[str] = None, + base_url: str = None, + project: str = None, + location: str = None, + **kwargs, + ): + super().__init__(model, api_key, temperature, **kwargs) + self.client = ( + genai.Client(project=project, location=location, vertexai=True) + if self.api_key + else genai.Client() + ) diff --git a/flo_ai/poetry.lock b/flo_ai/poetry.lock index baae925b..5daba1c5 100644 --- a/flo_ai/poetry.lock +++ b/flo_ai/poetry.lock @@ -831,6 +831,23 @@ files = [ {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"}, ] +[[package]] +name = "docstring-parser" +version = "0.17.0" +description = "Parse Python docstrings in reST, Google and Numpydoc format" +optional = false +python-versions = ">=3.8" +groups = ["main"] +files = [ + {file = "docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708"}, + {file = "docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912"}, +] + +[package.extras] +dev = ["pre-commit (>=2.16.0) ; python_version >= \"3.9\"", "pydoctor (>=25.4.0)", "pytest"] +docs = ["pydoctor (>=25.4.0)"] +test = ["pytest"] + [[package]] name = "exceptiongroup" version = "1.3.0" @@ -1097,6 +1114,42 @@ gitdb = ">=4.0.1,<5" doc = ["sphinx (>=7.1.2,<7.2)", "sphinx-autodoc-typehints", "sphinx_rtd_theme"] test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock ; python_version < \"3.8\"", "mypy", "pre-commit", "pytest (>=7.3.1)", "pytest-cov", "pytest-instafail", "pytest-mock", "pytest-sugar", "typing-extensions ; python_version < \"3.11\""] +[[package]] +name = "google-api-core" +version = "2.25.1" +description = "Google API client core library" +optional = false +python-versions = ">=3.7" +groups = ["main"] +files = [ + {file = "google_api_core-2.25.1-py3-none-any.whl", hash = "sha256:8a2a56c1fef82987a524371f99f3bd0143702fecc670c72e600c1cda6bf8dbb7"}, + {file = "google_api_core-2.25.1.tar.gz", hash = "sha256:d2aaa0b13c78c61cb3f4282c464c046e45fbd75755683c9c525e6e8f7ed0a5e8"}, +] + +[package.dependencies] +google-auth = 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"sphinx-remove-toctrees"] +test = ["pytest", "pytest-cov", "scipy-doctest"] + [[package]] name = "six" version = "1.17.0" @@ -3427,7 +3890,6 @@ files = [ {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"}, {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"}, ] -markers = {main = "extra == \"vizualize\""} [[package]] name = "smmap" @@ -4004,4 +4466,4 @@ vizualize = ["matplotlib", "networkx"] [metadata] lock-version = "2.1" python-versions = ">=3.10,<4.0" -content-hash = "df6ba1cd5dc10e0b8c7ece2f2a9eed0e41c76928760a0a5c51df13919d4e68ce" +content-hash = "dcf3d63c0346f6c835e36784bd6d76b6bb810d36056fd9d8a4a816a3b6814283" diff --git a/flo_ai/pyproject.toml b/flo_ai/pyproject.toml index 80c7ee1f..c7e758a8 100644 --- a/flo_ai/pyproject.toml +++ b/flo_ai/pyproject.toml @@ -20,6 +20,7 @@ matplotlib = { version = "^3.7.0", optional = true } networkx = { version = "^3.0", optional = true } anthropic = "^0.57.1" aiohttp = "^3.12.14" +google-cloud-aiplatform = "^1.109.0" [tool.poetry.extras] vizualize = ["matplotlib", "networkx"] From 91fe406058a42d0528c58bdff0792638389d6995 Mon Sep 17 00:00:00 2001 From: vizsatiz Date: Sat, 16 Aug 2025 13:26:19 +0530 Subject: [PATCH 2/4] Fix for creating vertexai client --- flo_ai/flo_ai/llm/vertexai_llm.py | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/flo_ai/flo_ai/llm/vertexai_llm.py b/flo_ai/flo_ai/llm/vertexai_llm.py index 36821334..48e57c05 100644 --- a/flo_ai/flo_ai/llm/vertexai_llm.py +++ b/flo_ai/flo_ai/llm/vertexai_llm.py @@ -15,8 +15,4 @@ def __init__( **kwargs, ): super().__init__(model, api_key, temperature, **kwargs) - self.client = ( - genai.Client(project=project, location=location, vertexai=True) - if self.api_key - else genai.Client() - ) + self.client = genai.Client(project=project, location=location, vertexai=True) From 6e7cacae9f58480891c8c56830ad7bbc6a5d0d09 Mon Sep 17 00:00:00 2001 From: vizsatiz Date: Sat, 16 Aug 2025 21:59:37 +0530 Subject: [PATCH 3/4] Added vertexai usage example --- flo_ai/examples/vertexai_agent_example.py | 319 ++++++++++++++++++++++ flo_ai/flo_ai/llm/vertexai_llm.py | 9 +- 2 files changed, 325 insertions(+), 3 deletions(-) create mode 100644 flo_ai/examples/vertexai_agent_example.py diff --git a/flo_ai/examples/vertexai_agent_example.py b/flo_ai/examples/vertexai_agent_example.py new file mode 100644 index 00000000..38c01c18 --- /dev/null +++ b/flo_ai/examples/vertexai_agent_example.py @@ -0,0 +1,319 @@ +#!/usr/bin/env python3 +""" +Example demonstrating VertexAI LLM usage with different agent configurations. +This example shows how to use Google's VertexAI through the Gemini API +for conversational agents, tool usage, and structured output. +""" + +import asyncio +import os +from flo_ai.builder.agent_builder import AgentBuilder +from flo_ai.llm.vertexai_llm import VertexAI +from flo_ai.models.agent import Agent as ToolAgent +from flo_ai.models.base_agent import ReasoningPattern +from flo_ai.tool.base_tool import Tool +from flo_ai.models.agent_error import AgentError + + +async def create_tools(): + """Create a set of tools for the VertexAI agent to use""" + + # Calculator tool + async def calculate(operation: str, x: float, y: float) -> float: + operations = { + 'add': lambda: x + y, + 'subtract': lambda: x - y, + 'multiply': lambda: x * y, + 'divide': lambda: x / y if y != 0 else 'Cannot divide by zero', + } + if operation not in operations: + raise ValueError(f'Unknown operation: {operation}') + return operations[operation]() + + calculator_tool = Tool( + name='calculate', + description='Perform basic calculations (add, subtract, multiply, divide)', + function=calculate, + parameters={ + 'operation': { + 'type': 'string', + 'description': 'The operation to perform (add, subtract, multiply, divide)', + }, + 'x': {'type': 'number', 'description': 'First number'}, + 'y': {'type': 'number', 'description': 'Second number'}, + }, + ) + + # Weather tool (mock implementation) + async def get_weather(city: str, country: str = None) -> str: + location = f'{city}, {country}' if country else city + # This would normally call a weather API + return f"Currently in {location}, it's sunny and warm with a temperature of 24Ā°C (75Ā°F)." + + weather_tool = Tool( + name='get_weather', + description='Get the current weather for a city', + function=get_weather, + parameters={ + 'city': {'type': 'string', 'description': 'The city to get weather for'}, + 'country': { + 'type': 'string', + 'description': 'The country of the city (optional)', + 'required': False, + }, + }, + ) + + return [calculator_tool, weather_tool] + + +async def example_vertexai_conversational(): + """Test VertexAI with simple conversational agent""" + + # Initialize VertexAI LLM + # You'll need to set up proper Google Cloud credentials + vertexai_llm = VertexAI( + model='gemini-2.5-flash', + temperature=0.7, + project=os.getenv('GOOGLE_CLOUD_PROJECT'), # Your GCP project ID + location=os.getenv('GOOGLE_CLOUD_LOCATION', 'us-central1'), # GCP region + ) + + # Create a simple conversational agent with VertexAI + agent = ( + AgentBuilder() + .with_name('VertexAI Assistant') + .with_prompt('You are a helpful AI assistant powered by Google VertexAI.') + .with_llm(vertexai_llm) + .with_retries(2) + .build() + ) + + # Test the agent with various questions + test_queries = [ + 'What is the capital of France?', + 'Explain quantum computing in simple terms.', + 'What are the benefits of using cloud computing?', + ] + + print('\n=== VertexAI Conversational Agent ===') + for query in test_queries: + print(f'\nQuery: {query}') + try: + response = await agent.run(query) + print(f'Response: {response}') + except Exception as e: + print(f'Error: {e}') + print('-' * 80) + + +async def example_vertexai_tool_agent(): + """Test VertexAI with tool-using agent""" + + # Initialize VertexAI LLM + vertexai_llm = VertexAI( + model='gemini-2.5-flash', + temperature=0.7, + project=os.getenv('GOOGLE_CLOUD_PROJECT'), + location=os.getenv('GOOGLE_CLOUD_LOCATION', 'us-central1'), + ) + + # Create tools + tools = await create_tools() + + # Create a tool-using agent with VertexAI + agent = ( + AgentBuilder() + .with_name('VertexAI Tool Assistant') + .with_prompt("""You are a helpful assistant that can perform calculations and get weather information. + Use the available tools to provide accurate responses. When asked about calculations, + use the calculate tool. When asked about weather, use the get_weather tool.""") + .with_llm(vertexai_llm) + .with_tools(tools) + .with_reasoning(ReasoningPattern.REACT) + .with_retries(2) + .build() + ) + + # Test cases that require tool usage + test_queries = [ + 'What is 25 multiplied by 4?', + "What's the weather like in Tokyo?", + 'Calculate 100 divided by 8, then tell me the weather in Paris, France', + 'If I have 15 apples and give away 7, how many do I have left?', + ] + + print('\n=== VertexAI Tool Agent ===') + for query in test_queries: + print(f'\nQuery: {query}') + try: + response = await agent.run(query) + print(f'Response: {response}') + except Exception as e: + print(f'Error: {e}') + print('-' * 80) + + +async def example_vertexai_structured_output(): + """Test VertexAI with structured output""" + + # Define output schema for structured responses + analysis_schema = { + 'type': 'object', + 'properties': { + 'sentiment': { + 'type': 'string', + 'description': 'The overall sentiment (positive, negative, neutral)', + 'enum': ['positive', 'negative', 'neutral'], + }, + 'confidence': { + 'type': 'number', + 'description': 'Confidence score between 0 and 1', + 'minimum': 0, + 'maximum': 1, + }, + 'key_topics': { + 'type': 'array', + 'items': {'type': 'string'}, + 'description': 'Main topics discussed in the text', + }, + 'summary': {'type': 'string', 'description': 'Brief summary of the text'}, + }, + 'required': ['sentiment', 'confidence', 'key_topics', 'summary'], + } + + # Initialize VertexAI LLM + vertexai_llm = VertexAI( + model='gemini-2.5-flash', + temperature=0.3, # Lower temperature for more consistent structured output + project=os.getenv('GOOGLE_CLOUD_PROJECT'), + location=os.getenv('GOOGLE_CLOUD_LOCATION', 'us-central1'), + ) + + # Create an agent with structured output + agent = ( + AgentBuilder() + .with_name('VertexAI Text Analyzer') + .with_prompt("""You are a text analysis assistant that analyzes sentiment and extracts key information. + Provide structured analysis of the given text.""") + .with_llm(vertexai_llm) + .with_output_schema(analysis_schema) + .build() + ) + + # Test texts for analysis + test_texts = [ + "I absolutely love this new product! It's innovative, well-designed, and has exceeded all my expectations. The customer service was also fantastic.", + "The service was okay, nothing special. It worked as expected but didn't really impress me. Could be better.", + 'This is terrible! The product broke after just one day and customer support was completely unhelpful. Very disappointed.', + ] + + print('\n=== VertexAI Structured Output ===') + for i, text in enumerate(test_texts, 1): + print(f'\nTest {i}: {text[:50]}...') + try: + response = await agent.run(f'Analyze this text: "{text}"') + print(f'Analysis: {response}') + except Exception as e: + print(f'Error: {e}') + print('-' * 80) + + +async def example_vertexai_error_handling(): + """Test VertexAI error handling and retries""" + + # Create a tool that might fail to test error handling + async def flaky_service(query: str) -> str: + if 'error' in query.lower(): + raise ValueError('Service temporarily unavailable') + return f'Successfully processed: {query}' + + flaky_tool = Tool( + name='flaky_service', + description='A service that might fail occasionally', + function=flaky_service, + parameters={'query': {'type': 'string', 'description': 'The query to process'}}, + ) + + # Initialize VertexAI LLM + vertexai_llm = VertexAI( + model='gemini-2.5-flash', + temperature=0.7, + project=os.getenv('GOOGLE_CLOUD_PROJECT'), + location=os.getenv('GOOGLE_CLOUD_LOCATION', 'us-central1'), + ) + + # Create agent with error handling + agent = ToolAgent( + name='VertexAI Error Handler', + system_prompt="""You are a helpful assistant that uses external services. + If a service fails, try to provide helpful information about what went wrong.""", + llm=vertexai_llm, + tools=[flaky_tool], + max_retries=3, + ) + + test_queries = [ + 'Process this successful query', + 'Process this error query', # This will trigger the error + ] + + print('\n=== VertexAI Error Handling ===') + for query in test_queries: + print(f'\nQuery: {query}') + try: + response = await agent.run(query) + print(f'Response: {response}') + except AgentError as e: + print(f'Agent error: {str(e)}') + if e.original_error: + print(f'Original error: {str(e.original_error)}') + except Exception as e: + print(f'Unexpected error: {e}') + print('-' * 80) + + +async def main(): + """Main function to run all VertexAI examples""" + + # Check for required environment variables + project = os.getenv('GOOGLE_CLOUD_PROJECT') + if not project: + print('āš ļø GOOGLE_CLOUD_PROJECT environment variable not set.') + print( + ' Please set it to your Google Cloud project ID to run VertexAI examples.' + ) + print(' Example: export GOOGLE_CLOUD_PROJECT=your-project-id') + return + + print('šŸš€ Running VertexAI LLM Examples') + print('=' * 50) + + try: + # Run conversational example + await example_vertexai_conversational() + + # Run tool agent example + await example_vertexai_tool_agent() + + # Run structured output example + await example_vertexai_structured_output() + + # Run error handling example + await example_vertexai_error_handling() + + print('\nāœ… All VertexAI examples completed successfully!') + + except Exception as e: + print(f'\nāŒ Error running examples: {e}') + print('\nMake sure you have:') + print('1. Set GOOGLE_CLOUD_PROJECT environment variable') + print( + '2. Configured Google Cloud authentication (gcloud auth application-default login)' + ) + print('3. Enabled Vertex AI API in your Google Cloud project') + raise e + + +if __name__ == '__main__': + asyncio.run(main()) diff --git a/flo_ai/flo_ai/llm/vertexai_llm.py b/flo_ai/flo_ai/llm/vertexai_llm.py index 48e57c05..2f1c883c 100644 --- a/flo_ai/flo_ai/llm/vertexai_llm.py +++ b/flo_ai/flo_ai/llm/vertexai_llm.py @@ -1,9 +1,10 @@ from typing import Optional from google import genai -from flo_ai.llm.gemini_llm import GeminiLLM +from flo_ai.llm.gemini_llm import Gemini +from flo_ai.llm.base_llm import BaseLLM -class VertexAI(GeminiLLM): +class VertexAI(Gemini): def __init__( self, model: str = 'gemini-2.5-flash', @@ -14,5 +15,7 @@ def __init__( location: str = None, **kwargs, ): - super().__init__(model, api_key, temperature, **kwargs) + # Initialize only the BaseLLM part to avoid Gemini's client creation + BaseLLM.__init__(self, model, api_key, temperature, **kwargs) + # Create VertexAI-specific client self.client = genai.Client(project=project, location=location, vertexai=True) From 56a042090aa79dee6a790ab3a8c39d18905dbf05 Mon Sep 17 00:00:00 2001 From: vizsatiz Date: Sat, 16 Aug 2025 22:41:09 +0530 Subject: [PATCH 4/4] Updating readme --- README.md | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/README.md b/README.md index 24dc995d..c6a715ef 100644 --- a/README.md +++ b/README.md @@ -65,6 +65,7 @@ Flo AI is a Python framework that makes building production-ready AI agents and - [OpenAI](#openai) - [Anthropic Claude](#anthropic-claude) - [Google Gemini](#google-gemini) + - [Google VertexAI](#google-vertexai) - [Ollama (Local)](#ollama-local) - [šŸ“Š Output Formatting](#-output-formatting) - [šŸ”„ Error Handling](#-error-handling) @@ -702,6 +703,23 @@ llm: Gemini = Gemini( ) ``` +### Google VertexAI +```python +from flo_ai.llm import VertexAI + +llm: VertexAI = VertexAI( + model='gemini-2.5-flash', # or gemini-2.5-pro + temperature=0.7, + project='your-gcp-project-id', # or set GOOGLE_CLOUD_PROJECT env var + location='us-central1' # or set GOOGLE_CLOUD_LOCATION env var +) +``` + +**Prerequisites for VertexAI:** +- Set up Google Cloud project with Vertex AI API enabled +- Configure authentication: `gcloud auth application-default login` +- Set environment variables: `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` + ### Ollama (Local) ```python from flo_ai.llm import Ollama @@ -764,6 +782,8 @@ Check out the `examples/` directory for comprehensive examples: - `multi_tool_example.py` - Multi-tool agent examples - `cot_agent_example.py` - Chain of Thought reasoning - `usage.py` and `usage_claude.py` - Provider-specific examples +- `vertexai_agent_example.py` - Google VertexAI integration examples +- `ollama_agent_example.py` - Local Ollama model examples ## šŸš€ Advanced Features