Merge pull request #34 from beautiful-code/supabase_connect

.env.example

@@ -1,11 +1,16 @@
 OPENAI_API_KEY=""
-OPENAI_MODEL="gpt-3.5-turbo"
+OPENAI_MODEL="gpt-4o-mini"
 GOOGLE_API_KEY=""
 
 LANGCHAIN_TRACING_V2=true
 LANGCHAIN_API_KEY=""
 LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
-LANGCHAIN_PROJECT="growthy-agents"
+LANGCHAIN_PROJECT="customer_agent"
 
-TAVILY_API_KEY=""
 ENV="local"
+
+SUPABASE_URL_STAGING=""
+SUPABASE_KEY_STAGING=""
+
+SUPABASE_URL_PROD=""
+SUPABASE_KEY_PROD=""

app/lib/supabase_client.py

@@ -0,0 +1,26 @@
+from pydantic import UUID4
+from supabase import create_client
+import os
+
+FEEDBACK_TABLE_NAME = "llm_feedback"
+
+
+class SupabaseClient:
+    def __init__(self):
+        url = os.environ.get("SUPABASE_URL")
+        key = os.environ.get("SUPABASE_KEY")
+        self.client = create_client(url, key)
+
+    def post_feedback(self, run_id: UUID4, metric_type: str, metric_score: float, sub_workflow: str):
+        try:
+            response = self.client.table(FEEDBACK_TABLE_NAME).insert({
+                "run_id": str(run_id),
+                "sub_workflow": sub_workflow,
+                "metric_type": metric_type,
+                "metric_score": metric_score,
+            }).execute()
+            print("Response: ", response)
+            return response
+        except Exception as exception:
+            print("Exception: ", exception)
+            return exception

{tests → app/tests}/til_test.py

@@ -1,5 +1,5 @@
 import pytest
-from growthy_agents.crew.til import TilCrew  # type: ignore
+from app.workflows.til.analyse_til import TilCrew  # type: ignore
 
 
 examples = [

{ui → app/ui}/course_learn_suggest_expectations.py

@@ -1,7 +1,7 @@
 import streamlit as st
-from workflows.courses.suggest_expectations import SuggestExpectations, Inputs as ExpectationsInputs, Expectation
+from app.workflows.courses.suggest_expectations import SuggestExpectations, Inputs as ExpectationsInputs, Expectation
 from streamlit_extras.stylable_container import stylable_container
-from workflows.courses.expectation_revision import ExpectationRevision
+from app.workflows.courses.expectation_revision import ExpectationRevision
 
 
 

{ui → app/ui}/til_feedback.py

@@ -1,9 +1,9 @@
 import streamlit as st
 from dotenv import load_dotenv
-from workflows.til.analyse_til import TilCrew
-from workflows.til.analyse_til_v2 import AnalyseTilV2
+from app.workflows.til.analyse_til import TilCrew
+from app.workflows.til.analyse_til_v2 import AnalyseTilV2
 from streamlit_extras.capture import stdout
-from workflows.utils.feedback import Feedback
+from app.workflows.utils.feedback import Feedback
 
 load_dotenv()
 

{workflows → app/workflows}/utils/feedback.py

@@ -1,6 +1,7 @@
 from pydantic import BaseModel, UUID4
 from typing import List, Optional
 from langsmith import Client
+from app.lib.supabase_client import SupabaseClient
 
 class Feedback(BaseModel):
     metric_type: Optional[str]
@@ -32,12 +33,17 @@ class NewFeedback(BaseModel):
         run_id = inputs["run_id"]
         sub_workflow = inputs["sub_workflow"]
 
-        # make a call to supabase
-        self._post_to_supbase()
-
+        self._post_to_supbase(run_id, sub_workflow)
         self._post_to_langsmith(run_id)
 
-    def _post_to_supbase(self):
+    def _post_to_supbase(self, run_id: UUID4, sub_worfklow: str):
+        client = SupabaseClient()
+        client.post_feedback(
+            run_id= run_id,
+            sub_workflow= sub_worfklow,
+            metric_score=self.metric_score,
+            metric_type=self.metric_type
+        )
         return
 
     def _post_to_langsmith(self, run_id: UUID4):

endpoints.py

@@ -1,27 +1,37 @@
 from dotenv import load_dotenv
 load_dotenv()
 
-from .workflows.til.suggest_headlines_v2 import SuggestHeadlinesV2, Response as SuggestHeadlinesResponse
-from .workflows.til.rewrite_til_v2 import RewriteTilV2, Response as RewriteTilResponse
-from .workflows.courses.expectation_revision import ExpectationRevision, Inputs as ExpectationRevisionInputs, Response as ExpectationRevisionResponse
-from .workflows.courses.suggest_check_question import SuggestCheckQuestion, Inputs as SuggestCheckQuestionInputs, Response as SuggestCheckQuestionResponse
-from .workflows.courses.suggest_expectations import SuggestExpectations, Inputs as SuggestExpectationsInputs, Expectation, Response as SuggestExpectationsResponse
-from .workflows.til.analyse_til import TilCrew, TilFeedbackResponse
-from .workflows.til.analyse_til_v2 import AnalyseTilV2, TilV2FeedbackResponse
-from .workflows.utils.feedback import Feedback, post_feedback, NewFeedback
-from .utils.endpoints_utils import CreateTilInputs
+from app.workflows.til.suggest_headlines_v2 import SuggestHeadlinesV2, Response as SuggestHeadlinesResponse
+from app.workflows.til.rewrite_til_v2 import RewriteTilV2, Response as RewriteTilResponse
+from app.workflows.courses.expectation_revision import ExpectationRevision, Inputs as ExpectationRevisionInputs, Response as ExpectationRevisionResponse
+from app.workflows.courses.suggest_check_question import SuggestCheckQuestion, Inputs as SuggestCheckQuestionInputs, Response as SuggestCheckQuestionResponse
+from app.workflows.courses.suggest_expectations import SuggestExpectations, Inputs as SuggestExpectationsInputs, Expectation, Response as SuggestExpectationsResponse
+from app.workflows.til.analyse_til import TilCrew, TilFeedbackResponse
+from app.workflows.til.analyse_til_v2 import AnalyseTilV2, TilV2FeedbackResponse
+from app.workflows.utils.feedback import Feedback, post_feedback, NewFeedback
+from app.utils.endpoints_utils import CreateTilInputs
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import UUID4
 from tempenv import TemporaryEnvironment
 from typing import List
+import os
 import uvicorn
 
 
-LANGSMITH_STAGING_PROJECT = "customer_agent"
-LANGSMITH_PROD_PROJECT = "growthy-agents"
-LANGSMITH_STAGING_MODEL = "gpt-4o-mini"
-LANGSMITH_PROD_MODEL = "gpt-4o"
+STAGING_ENV_CONFIG = {
+  "LANGCHAIN_PROJECT": "customer_agent",
+  "OPENAI_MODEL": "gpt-4o-mini",
+  "SUPABASE_URL": os.environ["SUPABASE_URL_STAGING"],
+  "SUPABASE_KEY": os.environ["SUPABASE_KEY_STAGING"]
+}
+
+PROD_ENV_CONFIG = {
+  "LANGCHAIN_PROJECT": "growthy-agents-prod",
+  "OPENAI_MODEL": "gpt-4o",
+  "SUPABASE_URL": os.environ["SUPABASE_URL_PROD"],
+  "SUPABASE_KEY": os.environ["SUPABASE_KEY_PROD"]
+}
 
 description = """
  API helps you do awesome stuff. 🚀
@@ -73,7 +83,7 @@ async def capture_feedback(run_id: UUID4, feedback: Feedback) -> str:
 
 @app.post("/staging/til_feedback", tags=["til_feedback", "staging"])
 async def staging_til_feedback_kickoff(content: List[str]) -> TilFeedbackResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         separator = "\n* "
         content[0] = "* " + content[0]
         inputs = {"content": separator.join(content)}
@@ -83,7 +93,7 @@ async def staging_til_feedback_kickoff(content: List[str]) -> TilFeedbackRespons
 
 @app.post("/staging/til_feedback/{run_id}/feedback", tags=["til_feedback", "staging"])
 async def staging_capture_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         post_feedback(run_id=run_id, feedback=feedback)
         return "ok"
 
@@ -96,12 +106,12 @@ def til_v2_analyze_logic(content) -> TilV2FeedbackResponse:
 
 @app.post("/v2/til_feedback", tags=["til_feedback"])
 async def til_v2_feedback_kickoff(content: List[str]) -> TilV2FeedbackResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         return til_v2_analyze_logic(content)
 
 @app.post("/v2/til_feedback/{run_id}/feedback", tags=["til_feedback"])
 async def capture_til_v2_feedback(run_id: UUID4, feedback: NewFeedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         feedback.post({"run_id": run_id, "sub_workflow": "til_analysis"})
         return "ok"
 
@@ -109,20 +119,20 @@ async def capture_til_v2_feedback(run_id: UUID4, feedback: NewFeedback) -> str:
 
 @app.post("/staging/v2/til_feedback", tags=["til_feedback", "staging"])
 async def staging_til_v2_feedback_kickoff(content: List[str]) -> TilV2FeedbackResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         return til_v2_analyze_logic(content)
 
 
 @app.post("/staging/v2/til_feedback/{run_id}/feedback", tags=["til_feedback", "staging"])
 async def staging_capture_til_v2_feedback(run_id: UUID4, feedback: NewFeedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_MODEL, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         feedback.post({"run_id": run_id, "sub_workflow": "til_analysis"})
         return "ok"
 
 
 @app.post("/v2/til_rewrite", tags=["til_readability"])
 async def til_v2_rewrite_kickoff(content: List[str]) -> RewriteTilResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         inputs = CreateTilInputs(content)
         result = RewriteTilV2().kickoff(inputs)
         return result
@@ -130,14 +140,14 @@ async def til_v2_rewrite_kickoff(content: List[str]) -> RewriteTilResponse:
 
 @app.post("/v2/til_rewrite/{run_id}/feedback", tags=["til_readability"])
 async def capture_til_v2_rewrite_feedback(run_id: UUID4, feedback: NewFeedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         feedback.post({"run_id": run_id, "sub_workflow": "til_understandability"})
         return "ok"
 
 
 @app.post("/staging/v2/til_rewrite", tags=["til_readability", "staging"])
 async def staging_til_v2_rewrite_kickoff(content: List[str]) -> RewriteTilResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         inputs = CreateTilInputs(content)
         result = RewriteTilV2().kickoff(inputs)
         return result
@@ -145,14 +155,14 @@ async def staging_til_v2_rewrite_kickoff(content: List[str]) -> RewriteTilRespon
 
 @app.post("/staging/v2/til_rewrite/{run_id}/feedback", tags=["til_readability", "staging"])
 async def staging_capture_til_v2_rewrite_feedback(run_id: UUID4, feedback: NewFeedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         feedback.post({"run_id": run_id, "sub_workflow": "til_understandability"})
         return "ok"
 
 
 @app.post("/v2/til_headlines", tags=["til_headlines"])
 async def til_v2_suggest_headlines(content: List[str]) -> SuggestHeadlinesResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         inputs = CreateTilInputs(content)
         result = SuggestHeadlinesV2().kickoff(inputs)
         return result
@@ -160,14 +170,14 @@ async def til_v2_suggest_headlines(content: List[str]) -> SuggestHeadlinesRespon
 
 @app.post("/v2/til_headlines/{run_id}/feedback", tags=["til_headlines"])
 async def capture_til_v2_headlines(run_id: UUID4, feedback: NewFeedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         feedback.post({"run_id": run_id, "sub_workflow": "til_headline"})
         return "ok"
 
 
 @app.post("/staging/v2/til_headlines", tags=["til_headlines", "staging"])
 async def staging_til_v2_suggest_headlines(content: List[str]) -> SuggestHeadlinesResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         inputs = CreateTilInputs(content)
         result = SuggestHeadlinesV2().kickoff(inputs)
         return result
@@ -175,7 +185,7 @@ async def staging_til_v2_suggest_headlines(content: List[str]) -> SuggestHeadlin
 
 @app.post("/staging/v2/til_headlines/{run_id}/feedback", tags=["til_headlines", "staging"])
 async def staging_capture_til_v2_headlines(run_id: UUID4, feedback: NewFeedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_MODEL, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         feedback.post({"run_id": run_id, "sub_workflow": "til_headline"})
         return "ok"
 
@@ -203,25 +213,25 @@ def course_learn_suggest_expectations_feedback_logic(run_id: UUID4, feedback: Fe
 
 @app.post("/course_learn/suggest_expectations", tags=["course_learn"])
 async def course_learn_suggest_expectations(inputs: SuggestExpectationsInputs) -> SuggestExpectationsResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         return course_learn_suggest_expectations_logic(inputs)
 
 
 @app.post("/staging/course_learn/suggest_expectations", tags=["course_learn", "staging"])
 async def staging_course_learn_suggest_expectations(inputs: SuggestExpectationsInputs) -> SuggestExpectationsResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         return course_learn_suggest_expectations_logic(inputs)
 
 
 @app.post("/course_learn/suggest_expectations/{run_id}/feedback", tags=["course_learn"])
 async def capture_suggest_expectations_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         return course_learn_suggest_expectations_feedback_logic(run_id, feedback)
 
 
 @app.post("/staging/course_learn/suggest_expectations/{run_id}/feedback", tags=["course_learn", "staging"])
 async def staging_capture_suggest_expectations_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         return course_learn_suggest_expectations_feedback_logic(run_id, feedback)
 
 
@@ -237,13 +247,13 @@ def course_learn_expectation_revision_logic(inputs: ExpectationRevisionInputs) -
 
 @app.post("/course_learn/expectation_revision", tags=["course_learn"])
 async def course_learn_expectation_revision(inputs: ExpectationRevisionInputs) -> ExpectationRevisionResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         return course_learn_expectation_revision_logic(inputs)
 
 
 @app.post("/staging/course_learn/expectation_revision", tags=["course_learn", "staging"])
 async def staging_course_learn_expectation_revision(inputs: ExpectationRevisionInputs) -> ExpectationRevisionResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         return course_learn_expectation_revision_logic(inputs)
 
 
@@ -256,13 +266,13 @@ def capture_expectation_revision_feedback_logic(run_id: UUID4, feedback: Feedbac
 
 @app.post("/course_learn/expectation_revision/{run_id}/feedback", tags=["course_learn"])
 async def capture_expectation_revision_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         return capture_expectation_revision_feedback_logic(run_id, feedback)
 
 
 @app.post("/staging/course_learn/expectation_revision/{run_id}/feedback", tags=["course_learn", "staging"])
 async def staging_capture_expectation_revision_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         return capture_expectation_revision_feedback_logic(run_id, feedback)
 
 
@@ -279,13 +289,13 @@ def course_learn_suggest_check_question_logic(inputs: SuggestCheckQuestionInputs
 
 @app.post("/course_learn/suggest_check_question", tags=["course_learn"])
 async def course_learn_suggest_check_question(inputs: SuggestCheckQuestionInputs) -> SuggestCheckQuestionResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         return course_learn_suggest_check_question_logic(inputs)
 
 
 @app.post("/staging/course_learn/suggest_check_question", tags=["course_learn", "staging"])
 async def staging_course_learn_suggest_check_question(inputs: SuggestCheckQuestionInputs) -> SuggestCheckQuestionResponse:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         return course_learn_suggest_check_question_logic(inputs)
 
 
@@ -298,26 +308,26 @@ def course_learn_suggest_check_question_feedback_logic(run_id: UUID4, feedback:
 
 @app.post("/course_learn/suggest_check_question/{run_id}/feedback", tags=["course_learn"])
 async def course_learn_suggest_check_question_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         return course_learn_suggest_check_question_feedback_logic(run_id, feedback)
 
 
 @app.post("/staging/course_learn/suggest_check_question/{run_id}/feedback", tags=["course_learn", "staging"])
 async def staging_course_learn_suggest_check_question_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         return course_learn_suggest_check_question_feedback_logic(run_id, feedback)
 
 
 @app.post("/llm_feedback/{run_id}/feedback", tags=["llm_feedback"])
 async def capture_llm_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
+    with TemporaryEnvironment(PROD_ENV_CONFIG):
         post_feedback(run_id=run_id, feedback=feedback)
         return "ok"
 
 
 @app.post("/staging/llm_feedback/{run_id}/feedback", tags=["llm_feedback", "staging"])
 async def staging_capture_llm_feedback(run_id: UUID4, feedback: Feedback) -> str:
-    with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_STAGING_PROJECT, "OPENAI_MODEL": LANGSMITH_STAGING_MODEL}):
+    with TemporaryEnvironment(STAGING_ENV_CONFIG):
         post_feedback(run_id=run_id, feedback=feedback)
         return "ok"
 

requirements.txt

@@ -3,8 +3,10 @@ asyncio
 crewai
 crewai_tools
 fastapi
+fastapi[standard]
 fastapi_cors
 langchain_community
+fastapi[standard]
 langchain_google_genai
 langchain_openai
 langchainhub
@@ -19,6 +21,7 @@ semanticscholar
 streamlit
 streamlit-extras
 streamlit_router
+supabase
 tavily-python
 tempenv
 unstructured

ui_main.py

@@ -1,7 +1,7 @@
 from dotenv import load_dotenv
 from streamlit_extras.stylable_container import stylable_container
-from ui.til_feedback import feedback_main
-from ui.course_learn_suggest_expectations import course_suggester_main
+from app.ui.til_feedback import feedback_main
+from app.ui.course_learn_suggest_expectations import course_suggester_main
 import math
 import streamlit as st
 import subprocess
@@ -48,7 +48,7 @@ def show_main_page():
         '''
     st.markdown(page_bg_img, unsafe_allow_html=True)
 
-    css = load_css("ui/main.css")
+    css = load_css("app/ui/main.css")
 
     st.markdown(f"<style>{css}</style>", unsafe_allow_html=True)