Create main.py

main.py

@@ -0,0 +1,78 @@
+import os
+from dotenv import load_dotenv
+from crewai import Agent, Task, Crew
+from langchain.agents import Tool
+from langchain_community.tools.tavily_search import TavilySearchResults
+
+load_dotenv()
+os.environ["OPENAI_API_KEY"] = os.getenv('OPENAI_API_KEY')
+os.environ["OPENAI_MODEL_NAME"] = 'gpt-3.5-turbo'
+os.environ["TAVILY_API_KEY"] =os.getenv("TAVILY_API_KEY")
+
+def setup_agents_and_tasks():
+    tavily_tool = Tool(
+        name="Intermediate Answer",
+        func=TavilySearchResults().run,
+        description="Useful for search-based queries",
+    )
+
+    sales_rep_agent = Agent(
+        role="Sales Representative",
+        goal="Identify high-value leads that match our ideal customer profile",
+        backstory=(
+            "As a part of the dynamic sales team at AI LOVES HR, "
+            "your mission is to scour the digital landscape for potential leads."
+        ),
+        allow_delegation=False,
+        verbose=True
+    )
+
+    lead_sales_rep_agent = Agent(
+        role="Lead Sales Representative",
+        goal="Nurture leads with personalized, compelling communications",
+        backstory=(
+            "Within the vibrant ecosystem of AI Loves HR's sales department, "
+            "you stand out as the bridge between potential clients and the solutions they need."
+        ),
+        allow_delegation=False,
+        verbose=True
+    )
+
+    lead_profiling_task = Task(
+        description=(
+            "Conduct an in-depth analysis of {lead_name}, a company in the {industry} sector "
+            "that recently showed interest in our solutions. "
+            "Utilize all available data sources to compile a detailed profile."
+        ),
+        expected_output=(
+            "A comprehensive report on {lead_name}, including company background, "
+            "key personnel, recent milestones, and identified needs."
+        ),
+        tools=[tavily_tool],
+        agent=sales_rep_agent,
+    )
+
+    personalized_outreach_task = Task(
+        description=(
+            "Using the insights gathered from the lead profiling report on {lead_name}, "
+            "craft a personalized outreach campaign aimed at {key_decision_maker}."
+        ),
+        expected_output=(
+            "A series of personalized email drafts tailored to {lead_name}, "
+            "specifically targeting {key_decision_maker}."
+        ),
+        tools=[tavily_tool],
+        agent=lead_sales_rep_agent
+    )
+
+    crew = Crew(
+        agents=[sales_rep_agent, lead_sales_rep_agent],
+        tasks=[lead_profiling_task, personalized_outreach_task],
+        verbose=2,
+        memory=True
+    )
+
+    return crew
+
+def kickoff_crew(crew, inputs):
+    return crew.kickoff(inputs=inputs)