migrate back to openai with gpt3.5

agents/article_evaluator.py

@@ -1,5 +1,5 @@
 from crewai import Agent
-from llms.gemini import gemini
+from llms.gpt import llm
 
 article_evaluator = Agent(
     role="Recommended Article Evaluator",
@@ -14,5 +14,5 @@ article_evaluator = Agent(
         "incremental learning once the user completes reading the articles."
     ),
     allow_delegation=False,
-    llm=gemini
+    llm=llm
 )

agents/curiosity_catalyst.py

@@ -1,5 +1,5 @@
 from crewai import Agent
-from llms.gemini import gemini
+from llms.gpt import llm
 from tools.scrape_website import scrape_tool
 
 curiosity_catalyst = Agent(
@@ -12,5 +12,5 @@ curiosity_catalyst = Agent(
     "for reading the articles."
   ),
   allow_delegation=False,
-  llm=gemini
+  llm=llm
 )

agents/learning_curator.py

@@ -1,7 +1,7 @@
 from crewai import Agent
 from tools.scrape_website import scrape_tool
 from tools.search_web import search_tool
-from llms.gemini import gemini
+from llms.gpt import llm
 
 learning_curator = Agent(
     role="Personal Learning Curator",
@@ -14,5 +14,5 @@ learning_curator = Agent(
     ),
     allow_delegation=False,
     tools=[scrape_tool, search_tool],
-    llm=gemini
+    llm=llm
 )

agents/learning_profiler.py

@@ -1,6 +1,6 @@
 from crewai import Agent
 from tools.scrape_website import scrape_tool
-from llms.gemini import gemini
+from llms.gpt import llm
 
 learning_profiler = Agent(
     role="Personal Learning Profiler",
@@ -12,5 +12,5 @@ learning_profiler = Agent(
       "The profile you build gives a high level overview of what interests that the user has. "
     ),
     allow_delegation=False,
-    llm=gemini
+    llm=llm
 )

crew/article_suggestion.py

@@ -7,20 +7,28 @@ from tasks.create_learning_profile import learning_profile_task
 from tasks.new_article_suggestion import article_suggestion_task
 from tasks.evaluate_articles import evaluation_task
 from tasks.create_article_pitch import article_pitch_task
-from llms.gemini import gemini
+from llms.gpt import llm
 
 article_recommendation_crew = Crew(
-    agents=[learning_profiler, learning_curator, article_evaluator, curiosity_catalyst],
-    tasks=[learning_profile_task, article_suggestion_task, evaluation_task, article_pitch_task],
+    agents=[learning_profiler, learning_curator,
+            article_evaluator, curiosity_catalyst],
+    tasks=[learning_profile_task, article_suggestion_task,
+           evaluation_task, article_pitch_task],
     verbose=True,
     memory=True,
-    manager_llm=gemini,
+    manager_llm=llm,
     embedder={
-            "provider": "google",
-            "config":{
-                "model": 'models/embedding-001',
-                "task_type": "retrieval_document",
-                "title": "Embeddings for Embedchain"
-            }
+        "provider": "openai",
+        "config": {
+                    "model": 'text-embedding-3-small'
         }
+    }
+    # embedder={
+    #         "provider": "google",
+    #         "config":{
+    #             "model": 'models/embedding-001',
+    #             "task_type": "retrieval_document",
+    #             "title": "Embeddings for Embedchain"
+    #         }
+    #     }
 )

llms/gemini.py

@@ -1,4 +1,3 @@
 from langchain_google_genai import ChatGoogleGenerativeAI
-import os
 
-gemini=ChatGoogleGenerativeAI(model="gemini-1.5-flash",verbose=True)
+llm=ChatGoogleGenerativeAI(model="gemini-1.5-flash",verbose=True)

llms/gpt.py

@@ -0,0 +1,3 @@
+from langchain_openai import ChatOpenAI
+
+llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0.5)

requirements.txt

@@ -3,3 +3,4 @@ crewai
 crewai_tools
 langchain_community
 langchain_google_genai
+langchain_openai