workflows(til_v2): create new feedback endpoints

* create specific endpoints for each til sub-workflow
* create new feedback class NewFeedback

endpoints.py

@@ -8,7 +8,7 @@ from .workflows.courses.suggest_check_question import SuggestCheckQuestion, Inpu
 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
+from .workflows.utils.feedback import Feedback, post_feedback, NewFeedback
 from .utils.endpoints_utils import CreateTilInputs
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
@@ -99,6 +99,13 @@ async def til_v2_feedback_kickoff(content: List[str]) -> TilV2FeedbackResponse:
     with TemporaryEnvironment({"LANGCHAIN_PROJECT": LANGSMITH_PROD_PROJECT, "OPENAI_MODEL": LANGSMITH_PROD_MODEL}):
         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}):
+        feedback.post({"run_id": run_id, "sub_workflow": "til_analysis"})
+        return "ok"
+
+
 
 @app.post("/staging/v2/til_feedback", tags=["til_feedback", "staging"])
 async def staging_til_v2_feedback_kickoff(content: List[str]) -> TilV2FeedbackResponse:
@@ -106,6 +113,13 @@ async def staging_til_v2_feedback_kickoff(content: List[str]) -> TilV2FeedbackRe
         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}):
+        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}):
@@ -114,6 +128,13 @@ async def til_v2_rewrite_kickoff(content: List[str]) -> RewriteTilResponse:
         return result
 
 
+@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}):
+        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}):
@@ -122,6 +143,13 @@ async def staging_til_v2_rewrite_kickoff(content: List[str]) -> RewriteTilRespon
         return result
 
 
+@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}):
+        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}):
@@ -130,6 +158,13 @@ async def til_v2_suggest_headlines(content: List[str]) -> SuggestHeadlinesRespon
         return result
 
 
+@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}):
+        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}):
@@ -138,6 +173,15 @@ async def staging_til_v2_suggest_headlines(content: List[str]) -> SuggestHeadlin
         return result
 
 
+@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}):
+        feedback.post({"run_id": run_id, "sub_workflow": "til_headline"})
+        return "ok"
+
+
+
+
 # Course Learn
 def course_learn_suggest_expectations_logic(inputs) -> SuggestExpectationsResponse:
     print("Inputs: ", inputs)

workflows/utils/feedback.py

@@ -20,3 +20,33 @@ def post_feedback(run_id: UUID4, feedback: Feedback):
         source_info={"content": feedback.feedback_on},
         type="api",
     )
+
+## fields of inputs dict: run_id, sub_workflow
+class NewFeedback(BaseModel):
+    metric_type: str
+    metric_score: float
+    original_content: Optional[str]
+    modified_content: Optional[str]
+
+    def post(self, inputs={}):
+        run_id = inputs["run_id"]
+        sub_workflow = inputs["sub_workflow"]
+
+        # make a call to supabase
+        self._post_to_supbase()
+
+        self._post_to_langsmith(run_id)
+
+    def _post_to_supbase(self):
+        return
+
+    def _post_to_langsmith(self, run_id: UUID4):
+        client = Client()
+        client.create_feedback(
+            str(run_id),
+            key=self.metric_type,
+            score=self.metric_score,
+            source_info={"original_content": self.original_content, "modified_content": self.modified_content},
+            type="api",
+        )
+