Parameterize setup and chat; continue to build out prototype

Makefile

@@ -5,6 +5,7 @@ ENV=dev
 
 help:
 	echo "make build          | build the SAM project"
+	echo "make serve          | run the SAM server locally"
 	echo "make clean          | remove all installed dependencies and build artifacts"
 	echo "make deps           | install all dependencies"
 	echo "make link           | create hard links to allow for hot reloading of a built project"

python/src/handlers/chat.py

@@ -1,17 +1,19 @@
-from langchain.vectorstores import Weaviate
+import base64
 import json
 import setup
 
 def handler(event, context):
-  params = event.get("queryStringParameters", {})
-  query = params.get("query")
+  question = event.get("body", "")
+  if event.get("isBase64Encoded", False):
+    question = base64.b64decode(question)
 
-  CLIENT = setup.connect()
-  index_name = "Work"
-  text_key = "title"
+  params = event.get("queryStringParameters", {})
+  index_name = params.get("index", "Work")
+  text_key = params.get("text_key", "title")
+  attributes = params.get("attributes", "identifier,title").split(",")
 
-  weaviate = Weaviate(CLIENT, index_name, text_key)
-  result = weaviate.similarity_search_by_text(query=query, additional="certainty")
+  weaviate = setup.weaviate_vector_store(index_name=index_name, text_key=text_key, attributes=attributes)
+  result = weaviate.similarity_search_by_text(query=question, additional="certainty")
 
   return {
     "statusCode": 200,

python/src/setup.py

@@ -1,17 +1,29 @@
+from langchain.chat_models import AzureChatOpenAI
+from langchain.vectorstores import Weaviate
+from typing import List
+import openai
 import os
 import weaviate
 
-def connect():
+def openai_chat_client():
+  deployment = os.getenv("AZURE_OPENAI_LLM_DEPLOYMENT_ID")
+  resource = os.getenv("AZURE_OPENAI_RESOURCE_NAME")
+  api_key = os.getenv("AZURE_OPENAI_API_KEY")
+
+  return AzureChatOpenAI(deployment_name=deployment)
+
+def weaviate_vector_store(index_name: str, text_key: str, attributes: List[str] = []):
   weaviate_url = os.environ['WEAVIATE_URL']
   weaviate_api_key = os.environ['WEAVIATE_API_KEY']
   openai_api_key = os.environ['AZURE_OPENAI_API_KEY']
 
   auth_config = weaviate.AuthApiKey(api_key=weaviate_api_key)
 
-  return weaviate.Client(
+  client = weaviate.Client(
       url=weaviate_url,
       auth_client_secret=auth_config,
       additional_headers={
           "X-OpenAI-Api-Key": openai_api_key
       }
-  )
+  )
+  return Weaviate(client=client, index_name=index_name, text_key=text_key, attributes=attributes)

template.yaml

@@ -564,12 +564,12 @@ Resources:
           WEAVIATE_API_KEY: !Ref WeaviateApiKey
           WEAVIATE_URL: !Ref WeaviateUrl
       Events:
-        GetApiGet:
+        PostApi:
           Type: HttpApi
           Properties:
             ApiId: !Ref dcApi
             Path: /chat
-            Method: GET
+            Method: POST
   defaultFunction:
     Type: AWS::Serverless::Function
     Properties: