description: > This pull request adds a new example to the crewAI-examples repository that demonstrates the use of the Ollama model and the DuckDuckGo search tool. changes_made: - file: ollama_examples/agent.py action: Added detail: > Includes a script to conduct research and write a blog post on Gradient Descent using crewAI, Ollama, and DuckDuckGo. - file: ollama_examples/README.md action: Created detail: Instructions on how to run the example. - file: examples/README.md action: Updated detail: Include the new ollama_examples section. notes: > This example shows how to: - Use the Ollama model for natural language understanding and generation. - Integrate DuckDuckGo search tool for web search capabilities. - Automate the research and writing process using crewAI.

README.md

@@ -8,7 +8,7 @@ By [@joaomdmoura](https://x.com/joaomdmoura).
 - [Marketing Strategy](https://github.com/joaomdmoura/crewAI-examples/tree/main/marketing_strategy)
 - [Surprise Trip](https://github.com/joaomdmoura/crewAI-examples/tree/main/surprise_trip)
 - [Match to Proposal](https://github.com/joaomdmoura/crewAI-examples/tree/main/match_profile_to_positions)
-- [Find Job Candidades Demo](https://github.com/joaomdmoura/crewAI-examples/tree/main/recruitment)
+
 
 ## Old Examples, need to be updated
 

ollama_examples/REAME.md

@@ -0,0 +1,8 @@
+# Ollama Examples
+
+This folder contains examples of using the Ollama model with crewAI.
+
+## Example: Gradient Descent Analysis
+
+This example demonstrates how to use crewAI to automate the process of researching and writing a technical blog post on Gradient Descent.
+

ollama_examples/local_research_example.py

@@ -0,0 +1,76 @@
+# importing the required modules
+import logging
+import os
+from crewai import Agent, Task, Process, Crew
+from dotenv import load_dotenv
+
+# Load env variables
+load_dotenv()
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+
+# DuckDuckGo arama aracını tanımlama
+from langchain_community.tools import DuckDuckGoSearchRun
+from langchain_community.llms import Ollama
+
+ollama_openhermes = Ollama(model="openhermes")
+ollama_llm = ollama_openhermes
+
+# DuckDuckGo arama aracını tanımlama
+search_tool = DuckDuckGoSearchRun()
+
+# introduce the agents with their specific roles and goals
+researcher = Agent(
+  role='Senior Research Analyst',
+  goal='Find out details regarding Gradient Descent',
+  backstory="""You are an expert in deep learning. 
+  You are passionate about education.
+  You can explain complex concepts into simple terms.""",
+  verbose=True,
+  allow_delegation=False,
+  tools=[search_tool],
+  llm=ollama_llm
+)
+
+writer = Agent(
+  role='Technical Writer',
+  goal='Craft compelling content on Gradient Descent',
+  backstory="""You are a renowned Technical Writer, known for
+  your informative and insightful articles.
+  You transform complex concepts into compelling narratives.""",
+  verbose=True,
+  allow_delegation=True,
+  llm=ollama_llm
+)
+
+# Assigning the Tasks
+# Create tasks for your agents
+task1 = Task(
+  description="""Conduct a comprehensive analysis of Gradient Descent.
+  Identify key definitions and potential use-cases.
+  Your final answer MUST be a full analysis""",
+  agent=researcher,
+  expected_output=""
+)
+
+task2 = Task(
+  description="""Using the insights provided, develop a technical blog
+  post that highlights the most important aspects of Gradient Descent.
+  Your post should be informative yet accessible, catering to a tech-savvy audience.
+  Your final answer MUST be the full blog post of at least 4 paragraphs.""",
+  agent=writer,
+  expected_output=""
+)
+
+# Assemble the Crew
+# Instantiate your crew with a sequential process
+crew = Crew(
+  agents=[researcher, writer],
+  tasks=[task1, task2],
+  verbose=2
+)
+
+# Kick Things Off
+result = crew.kickoff()
+print(result)