Add application file

Dockerfile

@@ -7,6 +7,15 @@ WORKDIR /code
 ## Copy the current directory contents in the container at /code
 COPY ./requirements.txt /code/requirements.txt
 
+COPY ./agents.py /code/agents.py
+
+COPY ./tasks.py /code/tasks.py
+
+COPY ./tools/search_tools.py /code/tools/search_tools.py
+
+
+
+
 ## Install the requirements.txt
 RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
 

agents.py

@@ -0,0 +1,60 @@
+import os
+from crewai import Agent
+from textwrap import dedent
+from langchain_groq import ChatGroq
+from tools.search_tools import SearchTools
+from dotenv import load_dotenv
+
+# Load environment variables
+dotenv_path = os.path.join(os.path.dirname(__file__), '.env')
+load_dotenv(dotenv_path)
+
+class SneakerAgents:
+    def __init__(self, search_tools):
+        groq_key = os.getenv("GROQ_API_KEY")
+        if not groq_key:
+            raise ValueError("GROQ_API_KEY environment variable is not set.")
+        
+        self.LLaMA = ChatGroq(
+            model_name="llama3-8b-8192",
+            temperature=0.7,
+            groq_api_key=groq_key,
+            verbose=True
+        )
+        self.search_tools = search_tools
+        
+    def sneaker_expert(self):
+        return Agent(
+            role="Sneaker Expert",
+            backstory=dedent(
+                """With a keen eye for hype and a pulse on the sneaker market, I've spent years navigating the world of reselling. 
+                I'm well-versed in spotting potential grails, deciphering hype from bricks, and understanding what drives resale value. 
+                From limited-edition drops to coveted collaborations, I can help you identify the next big thing and make informed decisions."""
+            ),
+            goal=dedent(
+                """I'm here to equip you with the knowledge to conquer the resell market. 
+                Tell me about a specific sneaker, and I'll analyze its potential: current market price, estimated resale value, 
+                factors influencing resell rating (hype, brand, scarcity), and any unique features that could impact its value."""
+            ),
+            tools=[self.search_tools.search_internet],
+            verbose=True,
+            llm=self.LLaMA
+        )
+
+    def resale_expert(self):
+        return Agent(
+            role="Resale Value Expert",
+            backstory=dedent(
+                """I'm a data-driven expert on the ever-fluctuating sneaker resale market. 
+                I leverage market trends, historical data, and brand insights to predict a sneaker's potential resale value. 
+                From analyzing hype levels to identifying deadstock opportunities, I can help you navigate the complexities of reselling."""
+            ),
+            goal=dedent(
+                """Let's talk about the resell potential of a specific sneaker. 
+                I'll analyze market data, brand history, and hype levels to provide an estimated resale value and rating. 
+                Additionally, I can help you identify potential risks like fufu (counterfeit) sneakers and suggest strategies to maximize your resale profit."""
+            ),
+            tools=[self.search_tools.search_internet],
+            verbose=True,
+            llm=self.LLaMA
+        )

tasks.py

@@ -0,0 +1,48 @@
+from crewai import Task
+from textwrap import dedent
+from datetime import datetime, timedelta
+
+class SneakerTasks:
+    def __init__(self):
+        self.tip_section = "If you do your BEST WORK, I'll give you a $10,000 commission!"
+
+    def suggest_and_fetch_upcoming_shoes(self, agent, brand, gender):
+        current_date = datetime.now().date()
+        suggestion_date = current_date + timedelta(days=30)  # Suggesting shoes to be released within 30 days
+        release_date = current_date + timedelta(days=30)  # Assuming upcoming releases within the next 30 days
+
+        return Task(
+            description=dedent(
+                f"""
+                **Task**: Suggest New Shoes and Fetch Upcoming Release Information
+                **Description**: Identify and suggest eupcoming {brand} {gender} sneaker releases from {current_date} to {suggestion_date}, 
+                and gather information about upcoming {brand} sneaker releases expected by {release_date}.
+
+                **Parameters**: 
+                - Brand: {brand}
+                - Gender: {gender}
+
+                **Note**: {self.tip_section}
+                """
+            ),
+            agent=agent,
+            expected_output=f"List of upcoming releases for {brand} {gender} sneakers within the next {suggestion_date} days , with insights on potential hot sellers and the current hype surrounding them.."
+        )
+
+    def estimate_resale_value(self, agent, brand):
+        return Task(
+            description=dedent(
+                f"""
+                **Task**: Estimate Sneaker Resale Value
+                **Description**: Analyze and estimate the resale value of {brand} sneakers based on market trends, 
+                    historical data, and anticipated demand.
+
+                **Parameters**: 
+                - Brand: {brand}
+
+                **Note**: {self.tip_section}
+                """
+            ),
+            agent=agent,
+            expected_output=f"Estimated resale value for {brand} sneakers,along with a breakdown of the factors affecting their value, such as brand popularity, rarity, and current market trends."
+        )

tools/search_tools.py

@@ -0,0 +1,37 @@
+import json
+import os
+
+import requests
+from langchain.tools import tool
+
+
+class SearchTools():
+
+    @tool("Search the internet")
+    def search_internet(query):
+        """Useful to search the internet
+        about a a given topic and return relevant results"""
+        top_result_to_return = 10
+        url = "https://google.serper.dev/search"
+        payload = json.dumps({"q": query})
+        headers = {
+            'X-API-KEY': os.environ['SERPER_API_KEY'],
+            'content-type': 'application/json'
+        }
+        response = requests.request("POST", url, headers=headers, data=payload)
+        # check if there is an organic key
+        if 'organic' not in response.json():
+            return "Sorry, I couldn't find anything about that, there could be an error with you serper api key."
+        else:
+            results = response.json()['organic']
+            string = []
+            for result in results[:top_result_to_return]:
+                try:
+                    string.append('\n'.join([
+                        f"Title: {result['title']}", f"Link: {result['link']}",
+                        f"Snippet: {result['snippet']}", "\n-----------------"
+                    ]))
+                except KeyError:
+                    next
+
+            return '\n'.join(string)