diff --git a/gestell-crew/.env.sample b/gestell-crew/.env.sample new file mode 100644 index 000000000..f50557d65 --- /dev/null +++ b/gestell-crew/.env.sample @@ -0,0 +1,2 @@ +OPENAI_API_KEY="sk-..." +GESTELL_API_KEY="gestell-...-..." \ No newline at end of file diff --git a/gestell-crew/.gitignore b/gestell-crew/.gitignore new file mode 100644 index 000000000..3ca612b38 --- /dev/null +++ b/gestell-crew/.gitignore @@ -0,0 +1,4 @@ +files +__pycache__ +agent +db \ No newline at end of file diff --git a/gestell-crew/.python-version b/gestell-crew/.python-version new file mode 100644 index 000000000..2c0733315 --- /dev/null +++ b/gestell-crew/.python-version @@ -0,0 +1 @@ +3.11 diff --git a/gestell-crew/README.md b/gestell-crew/README.md new file mode 100644 index 000000000..c22ebad40 --- /dev/null +++ b/gestell-crew/README.md @@ -0,0 +1,58 @@ +# Gestell Crew Orchestration Guide + +In this guide, you’ll learn how to use the Gestell MCP Server to create Crew Agents that: + +1. Create and configure a new collection +2. Upload documents into your collection +3. Navigate table categories in the Gestell Console +4. Use an AI agent to research your collection and generate summaries + +View a video walkthrough of this end-to-end orchestration on [Gestell’s YouTube channel](https://youtu.be/V73zXKUuQHc). + +## Why use Gestell? + +Gestell is an ETL for AI search and reasoning. Connect any unstructured data source and Gestell will enable at-scale, efficient and accurate search and reasoning for your application. No need for complex and costly processing and RAG pipelines – simply instruct Gestell in natural language and get production-scale databases setup instantly. + +### Advantages + +- Ease: Add Gestell to your CrewAI implementation in just a few lines of code to get your unstructured datasets integrated to your Crew +- Scale: Process massive unstructured databases with best-in-class performance +- Simplicity: No need for complex RAG or agentic search architectures - simply instruct in natural language how you want your data structured +- Customization: Create specific categories tailored to your business workflows using natural language instructions. Extract features, overlay concepts, and build specialized knowledge bases + +### How Gestell Works with CrewAI + +CrewAI excels at orchestrating AI agents to tackle complex tasks, while Gestell transforms raw data into AI-ready, structured information. Together, they create a powerful system where: + +1. Context Delivery: Gestell's search and reasoning platform provides CrewAI agents with richer, more accurate context for decision-making +2. Specialized Knowledge Bases: Create domain-specific knowledge structures that CrewAI agents can efficiently query and reason with +3. Scalable Reasoning: As your data grows, Gestell's ETL pipeline ensures your CrewAI implementation maintains high performance without degradation +4. Seamless Integration: The integration process is straightforward, allowing you to focus on building your AI application rather than wrestling with data preparation +5. End-to-End Solution: From data ingestion to agent execution, get a complete workflow that handles the complexity of unstructured data and multi-agent coordination + +## Running The Examples + +- You need `node` installed and `uv` installed + +- You also need a Gestell API Key which you can get from the [Gestell Platform](https://platform.gestell.ai) + +- Copy the `.env.sample` file to `.env` and fill in the values + +### Usage + +```bash +# Edit src/download.py to download the wikipedia files you want to download +uv run src/download.py +# NOTE: If you don't want wikipedia articles +# You can also put video, audio, or any other file in `files/`. Gestell will process it for you. + +# After you have items in `files/`, start the document analysis and collection creation Crew +uv run src/create.py + +# Review the status of documents being processed on https://platform.gestell.ai +# Once all documents are processed, run the research Crew +uv run src/research.py + +# You will be given a research report in `agent/research_report.md` +cat agent/research_report.md +``` diff --git a/gestell-crew/config/crew.yaml b/gestell-crew/config/crew.yaml new file mode 100644 index 000000000..67d6983b9 --- /dev/null +++ b/gestell-crew/config/crew.yaml @@ -0,0 +1,36 @@ +collection_planner_agent: + role: > + Document Collection Planner + goal: > + Organize and manage document collections efficiently + backstory: > + You are an expert in document management and organization. Your role is to + analyze, categorize, and structure document collections to make them easily + searchable and accessible. You understand document relationships and can + create intuitive organizational systems. + +document_analyzer_agent: + role: > + Document Analysis Specialist + goal: > + Extract meaningful insights and information from documents + backstory: > + You specialize in analyzing document contents to identify key information, + patterns, and relationships. Your expertise helps in understanding the + context and significance of documents within a collection. You're skilled at + summarizing, categorizing, and extracting structured data from various + document formats. + +research_agent: + role: > + Research Specialist + goal: > + Conduct thorough research and generate comprehensive reports + backstory: > + You are an expert researcher with a keen eye for detail and a talent for + synthesizing information from multiple sources. Your ability to analyze, + interpret, and present complex information in a clear and concise manner + makes you invaluable for generating high-quality research reports. You excel + at identifying key insights, drawing connections between different pieces + of information, and presenting findings in an organized, professional format. + diff --git a/gestell-crew/config/task.yaml b/gestell-crew/config/task.yaml new file mode 100644 index 000000000..2aa49c798 --- /dev/null +++ b/gestell-crew/config/task.yaml @@ -0,0 +1,74 @@ +analyze_document_task: + description: > + Analyze all provided documents in the directory and extract key information, including: + - Main topics and themes + - Key entities (people, places, organizations) + - Important dates and events + - Relationships between entities + - Any specific requirements or actions needed + + Provide concise and clear markdown that segments summaries of each document. + Make sure to provide the **exact** file path when summarizing each document. + expected_output: > + A concise GFM markdown analysis of each document including all key information. + This is to be used as input for the collection creation task. + output_file: "agent/analysis.md" + +create_collection_task: + description: > + Create a collection based on the provided analysis from the analyzed document task. + + Ensure that the instructions are comprehensive and based off of the analysis provided. + You are only allowed to create **table** categories, any other category is not allowed. + + - Tables must have bullet point list of what each column should contain + - All instructions should be clear concise bullet points + expected_output: > + Provide a concise GFM markdown summary of what the collection is about. + After running the createCollection tool, make sure to explicitly state the collection id. + output_file: "agent/collection.md" + +upload_document_task: + description: > + After a collection has been created. Upload all documents to the collection just created. + + To upload a document you are required to do the following: + - You are required to provide the **exact** path to the tool for the "file" field. + - You are required to provide the "name" field with an extension. + - Additional instructions are NOT needed for each file uploaded and should be an empty string. + expected_output: > + A concise GFM markdown list confirmation of successful upload including: + - List of uploaded documents + - Any warnings or issues encountered + - Summary of the upload process + output_file: "agent/upload_summary.md" + +research_task: + description: > + Analyze the collection and then conduct research and generate a comprehensive GFM markdown report. + + Identify the types of questions to ask using the file provided. As well as to retrieve the collection id. + + Use the searchCollectionSimple and promptCollectionSimple tool calls to research the collection. + The prompt field should be used to ask questions about the collection. + + The report should be well-structured and include: + - Executive summary of key findings + - Main topics and themes from the documents + - Important data points and statistics + - Key insights and recommendations + - Any relevant quotes or references + + Format the report using GitHub Flavored Markdown with proper: + - Headers and subheaders + - Bullet points and numbered lists + - Tables for data comparison + - Code blocks for any technical details + - Links to sources where applicable + + Keep the language clear, concise, and professional. + expected_output: > + A well-formatted GFM markdown report that provides a comprehensive overview + of the research findings, ready for sharing and collaboration. + output_file: "agent/research_report.md" + diff --git a/gestell-crew/pyproject.toml b/gestell-crew/pyproject.toml new file mode 100644 index 000000000..0bf8dc6e5 --- /dev/null +++ b/gestell-crew/pyproject.toml @@ -0,0 +1,12 @@ +[project] +name = "gestell-crew" +version = "1.0.0" +description = "Gestell CrewAI Example Workflow" +readme = "README.md" +authors = [{ name = "Chris Cates", email = "hello@chriscates.ca" }] +requires-python = ">=3.11" +dependencies = [ + "crewai-tools[mcp]>=0.45.0", + "mcp>=1.9.0", + "python-dotenv>=1.1.0", +] diff --git a/gestell-crew/src/__init__.py b/gestell-crew/src/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/gestell-crew/src/create.py b/gestell-crew/src/create.py new file mode 100644 index 000000000..a6b0ff047 --- /dev/null +++ b/gestell-crew/src/create.py @@ -0,0 +1,7 @@ +from crewai_tools import MCPServerAdapter +from src.gestell_mcp import server_params +from src.crews.create import GestellCreateCrew + +with MCPServerAdapter(server_params) as tools: + result = GestellCreateCrew(tools=tools).crew().kickoff() + print(result) diff --git a/gestell-crew/src/crews/__init__.py b/gestell-crew/src/crews/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/gestell-crew/src/crews/create.py b/gestell-crew/src/crews/create.py new file mode 100644 index 000000000..61e174915 --- /dev/null +++ b/gestell-crew/src/crews/create.py @@ -0,0 +1,86 @@ +from crewai import Agent, Crew, Process, Task +from crewai.project import CrewBase, agent, crew, task +from typing import List, Optional +from crewai.tools import BaseTool +from pathlib import Path +from crewai_tools import DirectoryReadTool, PDFSearchTool + +files_dir = Path.cwd() / "files" + + +@CrewBase +class GestellCreateCrew: + """Gestell Crew to Create a Collection and Upload Documents""" + + agents_config = "../../config/crew.yaml" + tasks_config = "../../config/task.yaml" + + def __init__(self, tools: Optional[List[BaseTool]] = None): + """Initialize crew with custom tools""" + super().__init__() + self.tools = tools or [] + + @agent + def document_analyzer_agent(self) -> Agent: + return Agent( + config=self.agents_config["document_analyzer_agent"], + allow_delegation=False, + verbose=True, + llm="gpt-4.1-mini", + ) + + @agent + def collection_planner_agent(self) -> Agent: + return Agent( + config=self.agents_config["collection_planner_agent"], + allow_delegation=False, + verbose=True, + llm="gpt-4.1-mini", + ) + + @task + def analyze_document_task(self) -> Task: + return Task( + config=self.tasks_config["analyze_document_task"], + agent=self.document_analyzer_agent(), + tools=[DirectoryReadTool(directory=str(files_dir)), PDFSearchTool()], + ) + + @task + def create_collection_task(self) -> Task: + create_collection_tools = [ + tool + for tool in self.tools + if hasattr(tool, "name") + and tool.name + in ["createCollection", "listOrganizations", "listCollections"] + ] + return Task( + config=self.tasks_config["create_collection_task"], + agent=self.collection_planner_agent(), + tools=create_collection_tools, + ) + + @task + def upload_document_task(self) -> Task: + upload_doc_tool = [ + tool + for tool in self.tools + if hasattr(tool, "name") + and tool.name in ["uploadDocument", "listCollections", "listDocuments"] + ] + return Task( + config=self.tasks_config["upload_document_task"], + agent=self.document_analyzer_agent(), + tools=upload_doc_tool, + ) + + @crew + def crew(self) -> Crew: + """Creates the GestellCrew""" + return Crew( + agents=self.agents, + tasks=self.tasks, + process=Process.sequential, + verbose=True, + ) diff --git a/gestell-crew/src/crews/research.py b/gestell-crew/src/crews/research.py new file mode 100644 index 000000000..e40dc26bd --- /dev/null +++ b/gestell-crew/src/crews/research.py @@ -0,0 +1,45 @@ +from crewai import Agent, Crew, Process, Task +from crewai.project import CrewBase, agent, crew, task +from typing import List, Optional +from crewai.tools import BaseTool + + +@CrewBase +class GestellResearchCrew: + """Gestell Crew to Conduct Research""" + + agents_config = "../../config/crew.yaml" + tasks_config = "../../config/task.yaml" + + def __init__(self, tools: Optional[List[BaseTool]] = None): + """Initialize crew with custom tools""" + super().__init__() + # Use provided tools or default to empty list + self.tools = tools or [] + + @agent + def research_agent(self) -> Agent: + return Agent( + config=self.agents_config["research_agent"], + allow_delegation=False, + verbose=True, + tools=self.tools, + llm="gpt-4.1-mini", + ) + + @task + def research_task(self) -> Task: + return Task( + config=self.tasks_config["research_task"], + agent=self.research_agent(), + ) + + @crew + def crew(self) -> Crew: + """Creates the GestellCrew""" + return Crew( + agents=self.agents, + tasks=self.tasks, + process=Process.sequential, + verbose=True, + ) diff --git a/gestell-crew/src/download.py b/gestell-crew/src/download.py new file mode 100644 index 000000000..fc09544c3 --- /dev/null +++ b/gestell-crew/src/download.py @@ -0,0 +1,51 @@ +import os +from typing import List +import requests + +URLS: List[str] = [ + "https://en.wikipedia.org/wiki/Babylon", + "https://en.wikipedia.org/wiki/Mesopotamia", + "https://en.wikipedia.org/wiki/Achaemenid_Empire", +] + + +def download_wikipedia_pdf(title: str, output_dir: str) -> None: + """ + Download the Wikipedia page with the given title as a PDF and save it. + + :param title: The title of the Wikipedia page to download. + :param output_dir: Directory where the PDF file will be saved. + """ + endpoint = f"https://en.wikipedia.org/api/rest_v1/page/pdf/{title}" + response = requests.get(endpoint, stream=True) + response.raise_for_status() + + os.makedirs(output_dir, exist_ok=True) + filepath = os.path.join(output_dir, f"{title}.pdf") + with open(filepath, "wb") as pdf_file: + for chunk in response.iter_content(chunk_size=8192): + pdf_file.write(chunk) + + +def extract_title_from_url(url: str) -> str: + """ + Extract the page title from a Wikipedia URL. + + :param url: Full URL of the Wikipedia page. + :return: The page title suitable for the PDF-API endpoint. + """ + if "/wiki/" not in url: + raise ValueError(f"Invalid Wikipedia URL: {url}") + return url.split("/wiki/")[1].split("?", 1)[0] + + +def main() -> None: + output_dir = "files" + for url in URLS: + title = extract_title_from_url(url) + download_wikipedia_pdf(title, output_dir) + print(f"✔ Saved: {os.path.join(output_dir, title)}.pdf") + + +if __name__ == "__main__": + main() diff --git a/gestell-crew/src/gestell_mcp.py b/gestell-crew/src/gestell_mcp.py new file mode 100644 index 000000000..7a2484a62 --- /dev/null +++ b/gestell-crew/src/gestell_mcp.py @@ -0,0 +1,11 @@ +from os import getenv +from dotenv import load_dotenv +from mcp import StdioServerParameters + +load_dotenv() + +server_params = StdioServerParameters( + command="npx", + args=["-y", "@gestell/mcp@latest"], + env={"GESTELL_API_KEY": getenv("GESTELL_API_KEY")}, +) diff --git a/gestell-crew/src/research.py b/gestell-crew/src/research.py new file mode 100644 index 000000000..fb950ba57 --- /dev/null +++ b/gestell-crew/src/research.py @@ -0,0 +1,23 @@ +from crewai_tools import MCPServerAdapter, FileReadTool +from src.gestell_mcp import server_params +from src.crews.research import GestellResearchCrew +from pathlib import Path + +collection_file = Path.cwd() / "agent/collection.md" + +with MCPServerAdapter(server_params) as tools: + filtered_tools = [ + tool + for tool in tools + if hasattr(tool, "name") + and tool.name in ["promptCollectionSimple", "searchCollectionSimple"] + ] + + result = ( + GestellResearchCrew( + tools=filtered_tools + [FileReadTool(file_path=str(collection_file))] + ) + .crew() + .kickoff() + ) + print(result) diff --git a/gestell-crew/uv.lock b/gestell-crew/uv.lock new file mode 100644 index 000000000..54475c89b --- /dev/null +++ b/gestell-crew/uv.lock @@ -0,0 +1,3941 @@ +version = 1 +requires-python = ">=3.11" +resolution-markers = [ + 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