add secret key

Summarization.py

@@ -1,51 +1,52 @@
-# Warning control
-import warnings
-warnings.filterwarnings('ignore')
-
-from typing import List
-import json
-from pydantic import BaseModel
-# from langchain_community.llms import HuggingFaceHub
-from langchain_huggingface import HuggingFaceEndpoint
-from crewai import Agent, Task, Crew
-
-import os
-from dotenv import load_dotenv, find_dotenv
-_ = load_dotenv(find_dotenv()) # read local .env file
-hf_api_key = os.environ['HF_API_KEY']
-
-llm = HuggingFaceEndpoint(
-    repo_id="HuggingFaceH4/zephyr-7b-beta",
-    huggingfacehub_api_token=hf_api_key,
-    task="text-generation"
-)
-
-editor = Agent(
-    role="Editor",
-    goal="Extract the summary of user requirements based on the chat between user and Graphic designer. Chat: {chat}",
-    backstory="You're working as an Editor"
-              "You are provided with chat between user and graphic designer. Chat: {chat}."
-              "Extract the summary of user requirements from the chat",
-    llm=llm,
-    allow_delegation=False,
-	verbose=False
-)
-
-
-summary = Task(
-    description=(
-        "Provide the summary of user requirements based on the chat between user and Graphic designer. Chat: {chat}"
-    ),
-    expected_output="Summary of user requirements. output only summary",
-    agent=editor,
-)
-
-crew = Crew(
-    agents=[editor],
-    tasks=[summary],
-    verbose=False
-)
-
-def Summarizer(chat, userDefinedQuestions=None):
-    result = crew.kickoff(inputs={"chat": chat})
+# Warning control
+import warnings
+warnings.filterwarnings('ignore')
+
+from typing import List
+import json
+from pydantic import BaseModel
+# from langchain_community.llms import HuggingFaceHub
+from langchain_huggingface import HuggingFaceEndpoint
+from crewai import Agent, Task, Crew
+
+import os
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv()) # read local .env file
+# hf_api_key = os.environ['HF_API_KEY']
+hf_api_key = os.getenv('HF_API_KEY')
+
+llm = HuggingFaceEndpoint(
+    repo_id="HuggingFaceH4/zephyr-7b-beta",
+    huggingfacehub_api_token=hf_api_key,
+    task="text-generation"
+)
+
+editor = Agent(
+    role="Editor",
+    goal="Extract the summary of user requirements based on the chat between user and Graphic designer. Chat: {chat}",
+    backstory="You're working as an Editor"
+              "You are provided with chat between user and graphic designer. Chat: {chat}."
+              "Extract the summary of user requirements from the chat",
+    llm=llm,
+    allow_delegation=False,
+	verbose=False
+)
+
+
+summary = Task(
+    description=(
+        "Provide the summary of user requirements based on the chat between user and Graphic designer. Chat: {chat}"
+    ),
+    expected_output="Summary of user requirements. output only summary",
+    agent=editor,
+)
+
+crew = Crew(
+    agents=[editor],
+    tasks=[summary],
+    verbose=False
+)
+
+def Summarizer(chat, userDefinedQuestions=None):
+    result = crew.kickoff(inputs={"chat": chat})
     return result