chat

app.py

@@ -5,11 +5,36 @@ from ocr_script import ocr_tesseract_only
 #     # chamar seu OCR aqui e retornar texto
 #     return "texto extraído"
 
+def respond(message, history, user_id):
+    return "mock response"
+    # pydantic_history = convert_to_pydantic_history(history)
+    # tools_instance = SearchingTools()
+    # deps = SearchAgentDeps(tools=tools_instance)
+    # agent_config = start_convo(user_input=str(message), messages_history=pydantic_history)
+    # result = agent_config.run_sync(
+    #     str(message),
+    #     deps=deps,
+    #     usage_limits=usage_limits,
+    #     message_history=pydantic_history,
+    # )
+    return result.output
+
 with gr.Blocks() as demo:
-    gr.Markdown("## Text OCR Tesseract only")
-    with gr.Row():
-        img_in = gr.Image(label="Imagem (png, jpg, jpeg)", type="pil")  # ou "filepath"/"numpy"
-        txt_out = gr.Textbox(label="Texto OCR", lines=12)
-    img_in.change(fn=ocr_tesseract_only, inputs=img_in, outputs=txt_out)
+    with gr.Tabs():
+        with gr.Tab("Text OCR Tesseract only"):
+            with gr.Row():
+                img_in = gr.Image(label="Imagem (png, jpg, jpeg)", type="pil")  # ou "filepath"/"numpy"
+                txt_out = gr.Textbox(label="Texto OCR", lines=12)
+            img_in.change(fn=ocr_tesseract_only, inputs=img_in, outputs=txt_out)
+
 
-demo.launch()
+        with gr.Tab("Chat"):
+            user_id = gr.State(str(uuid.uuid4()))
+            chat = gr.ChatInterface(
+                fn=lambda m,h: respond(m,h,user_id.value),
+                type="messages",
+                title="Chat with AI Agent with Access to Extracted Data",
+                save_history=True,
+            )
+            chat.render()
+#demo.launch()