Update app.py

app.py

@@ -1,4 +1,4 @@
-from typing import Any, Tuple
+from typing import Any, List, Tuple
 import gradio as gr
 from langchain_openai import OpenAIEmbeddings
 from langchain_community.vectorstores import Chroma
@@ -13,7 +13,7 @@ import openai
 
 openai.api_key = "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"
 
-def add_text(history, text: str):
+def add_text(history: List[Tuple[str, str]], text: str) -> List[Tuple[str, str]]:
     if not text:
         raise gr.Error("Enter text")
     history.append((text, ""))
@@ -32,7 +32,7 @@ class MyApp:
             self.chain = self.build_chain(file)
         return self.chain
 
-    def process_file(self, file: str) -> Image:
+    def process_file(self, file) -> Image.Image:
         loader = PyMuPDFLoader(file.name)
         self.documents = loader.load()
         pattern = r"/([^/]+)$"
@@ -47,7 +47,7 @@ class MyApp:
         image = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
         return image
 
-    def build_chain(self, file: str) -> str:
+    def build_chain(self, file) -> str:
         embeddings = OpenAIEmbeddings(openai_api_key=self.OPENAI_API_KEY)
         pdfsearch = Chroma.from_documents(
             self.documents,
@@ -78,14 +78,14 @@ def get_response(history, query, file):
         history[-1][-1] += char
         yield history, "", source_texts_str
 
-def render_file(file) -> Image:
+def render_file(file) -> Image.Image:
     doc = fitz.open(file.name)
     page = doc[0]
     pix = page.get_pixmap(dpi=150)
     image = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
     return image
 
-def purge_chat_and_render_first(file) -> Tuple[Image, list]:
+def purge_chat_and_render_first(file) -> Tuple[Image.Image, list]:
     app.chat_history = []
     doc = fitz.open(file.name)
     page = doc[0]