add env

.env.example

@@ -0,0 +1,11 @@
+OPENAI_API_KEY=""
+OPENAI_MODEL="gpt-3.5-turbo"
+GOOGLE_API_KEY=""
+
+LANGCHAIN_TRACING_V2=true
+LANGCHAIN_API_KEY=""
+LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
+LANGCHAIN_PROJECT="growthy-agents"
+
+TAVILY_API_KEY=""
+ENV="local"

README.md

@@ -1,5 +1,5 @@
 ---
-title: ArticleRecommender
+title: AI Workflows
 app_file: test.py
 sdk: streamlit
 sdk_version: 1.35.0

crew/til.py

@@ -5,10 +5,11 @@ from langchain_core.output_parsers import JsonOutputParser
 from langchain_openai import ChatOpenAI
 from typing import List
 import pprint
+import os
 
 HIGH_IMPACT_THRESHOLD = 8
 LOW_IMPACT_THRESHOLD = 7
-OPENAI_MODEL = "gpt-4o"
+# OPENAI_MODEL = "gpt-4o"
 # OPENAI_MODEL = "gpt-3.5-turbo"
 
 class TilCrew:
@@ -85,8 +86,16 @@ class TilCrew:
         ])
         print("Prompt: ")
         pprint.pp(feedback_prompt, width=80)
-        llm = ChatOpenAI(model=OPENAI_MODEL, temperature=0.2)
-        analysis_chain = feedback_prompt | llm | feedback_parser
+        llm = ChatOpenAI(model=os.environ['OPENAI_MODEL'], temperature=0.2)
+        analysis_chain = (feedback_prompt | llm | feedback_parser).with_config({
+            "tags": ["til"], "run_name": "Analysing TIL",
+            "metadata" : {
+                "versoin": "v1.0.0",
+                "growth_activity": "til",
+                "env": os.environ["ENV"],
+                "model": os.environ["OPENAI_MODEL"],
+            }
+        })
 
         return analysis_chain
 

test.py

@@ -1,3 +1,6 @@
+from dotenv import load_dotenv
+load_dotenv()
+
 from crew.til import TilCrew
 import streamlit as st
 from streamlit_extras.capture import stdout