Update instagram_post example to crewAI 0.30.11

instagram_post/.env.example

@@ -1,3 +1,5 @@
 SERPER_API_KEY=KEY # https://serper.dev/ (free tier)
-BROWSERLESS_API_KEY=KEY # https://www.browserless.io/ (free tier)
-MODEL='openhermes'
+BROWSERLESS_API_KEY=KEY # https://www.browserless.io/ (no more free tier)
+SCRAPINGANT_API_KEY= # https://scrapingant.com/ (free tier) (if not set will fallback to BROWSERLESS_API_KEY)
+MODEL='openhermes'
+

instagram_post/agents.py

@@ -3,9 +3,9 @@
 from crewai import Agent
 from tools.browser_tools import BrowserTools
 from tools.search_tools import SearchTools
-from langchain.agents import load_tools
+from langchain_community.agent_toolkits.load_tools import load_tools
 
-from langchain.llms import Ollama
+from langchain_community.llms import Ollama
 
 class MarketingAnalysisAgents:
 	def __init__(self):

instagram_post/main.py

@@ -13,8 +13,14 @@
 print("## Welcome to the marketing Crew")
 print('-------------------------------')
 product_website = input("What is the product website you want a marketing strategy for?\n")
-product_details = input("Any extra details about the product and or the instagram post you want?\n")
+if not product_website:
+	print("## You gave an empty value, no worries, we will use the default one")
+	product_website = "https://heycurio.com/product/gabbo"
 
+product_details =  input("Any extra details about the product and or the instagram post you want?\n")
+if not product_details:
+	print("## You gave an empty value, no worries, we will use the default one")
+	product_details = "Gabbo is robot toy built for children to help them disconnect from the digital world and connect to the real world."
 
 # Create Agents
 product_competitor_agent = agents.product_competitor_agent()

instagram_post/tasks.py

@@ -18,6 +18,7 @@ def product_analysis(self, agent, product_website, product_details):
 			Keep in mind, attention to detail is crucial for
 			a comprehensive analysis. It's currenlty 2024.
 			"""),
+			expected_output='A paragraph containing the features and the benefifts of the product.',
 			agent=agent
 		)
 
@@ -32,6 +33,7 @@ def competitor_analysis(self, agent, product_website, product_details):
 			Your final report MUST include BOTH all context about {product_website}
 			and a detailed comparison to whatever competitor they have competitors.
 			"""),
+			expected_output='A paragraph containing the description of the competitiors.',
 			agent=agent
 		)
 
@@ -49,6 +51,7 @@ def campaign_development(self, agent, product_website, product_details):
 			Your final answer MUST be ideas that will resonate with the audience and
 			also include ALL context you have about the product and the customer.
 			"""),
+			expected_output='A paragraph containing the strategy to sell the product.',
 			agent=agent
 		)
 
@@ -70,6 +73,7 @@ def instagram_ad_copy(self, agent):
 			Your final answer MUST be 3 options for an ad copy for instagram that
 			not only informs but also excites and persuades the audience.
 			"""),
+			expected_output='A paragraph containing the text of an engaging story in instagram.',
 			agent=agent
 		)
 
@@ -95,6 +99,7 @@ def take_photograph_task(self, agent, copy, product_website, product_details):
 			Your final answer must be 3 options of photographs, each with 1 paragraph
 			describing the photograph exactly like the examples provided above.
 			"""),
+			expected_output='A prompt for midjourney that will generate an impactful image to sell the product.',
 			agent=agent
 		)
 
@@ -117,5 +122,6 @@ def review_photo(self, agent, product_website, product_details):
 			Your final answer must be 3 reviewed options of photographs,
 			each with 1 paragraph description following the examples provided above.
 			"""),
+			expected_output='A paragraph containing a review of the photo used to sell the product.',
 			agent=agent
 		)

instagram_post/tools/browser_tools.py

@@ -3,21 +3,28 @@
 
 import requests
 from crewai import Agent, Task
-from langchain.tools import tool
 from unstructured.partition.html import partition_html
-
-from langchain.llms import Ollama
+from langchain_community.llms import Ollama
+from langchain_core.tools import tool
 
 class BrowserTools():
 
   @tool("Scrape website content")
-  def scrape_and_summarize_website(website):
+  def scrape_and_summarize_website(url):
     """Useful to scrape and summarize a website content, just pass a string with
     only the full url, no need for a final slash `/`, eg: https://google.com or https://clearbit.com/about-us"""
-    url = f"https://chrome.browserless.io/content?token={os.environ['BROWSERLESS_API_KEY']}"
-    payload = json.dumps({"url": website})
-    headers = {'cache-control': 'no-cache', 'content-type': 'application/json'}
-    response = requests.request("POST", url, headers=headers, data=payload)
+    # Check if SCRAPINGANT_API_KEY is defined and has a non-empty value
+    scrapingant_api_key = os.environ.get('SCRAPINGANT_API_KEY')
+    if scrapingant_api_key:
+      # Use the ScrapingAnt API if the key is available
+      scraping_url = f"https://api.scrapingant.com/v2/general?x-api-key={scrapingant_api_key}&url={url}"
+    else:
+       # Otherwise, use the Browserless API
+        browserless_api_key = os.environ['BROWSERLESS_API_KEY']
+        scraping_url = f"https://chrome.browserless.io/content?token={browserless_api_key}"
+    payload = json.dumps({"url": url})
+    headers = {'Cache-Control': 'no-cache', 'Content-Type': 'application/json'}
+    response = requests.request("POST", scraping_url, headers=headers, data=payload)
     elements = partition_html(text=response.text)
     content = "\n\n".join([str(el) for el in elements])
     content = [content[i:i + 8000] for i in range(0, len(content), 8000)]
@@ -32,9 +39,10 @@ def scrape_and_summarize_website(website):
           llm=Ollama(model=os.environ['MODEL']),
           allow_delegation=False)
       task = Task(
+          expected_output="A long summary of the product features and description.",
           agent=agent,
           description=
-          f'Analyze and make a LONG summary the content bellow, make sure to include the ALL relevant information in the summary, return only the summary nothing else.\n\nCONTENT\n----------\n{chunk}'
+          f'Analyze and make a LONG summary the content below, make sure to include the ALL relevant information in the summary, return only the summary nothing else.\n\nCONTENT\n----------\n{chunk}'
       )
       summary = task.execute()
       summaries.append(summary)

instagram_post/tools/search_tools.py

@@ -2,7 +2,7 @@
 import os
 
 import requests
-from langchain.tools import tool
+from langchain_core.tools import tool
 
 
 class SearchTools():