new

app.py

@@ -1,67 +1,58 @@
-import os
-
-import openai
-import gradio as gr
-
-openai.api_key = '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'
-#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
-
-def clean_textbox(*args):
-    n = len(args)
-    return [""] * n
-
-
-class ChatGPT:
-    def __init__(self):
-        self.messages = [{'role': 'system', 'content': "You are now a very useful maid assistant! If you have a question you can't answer, please reply with As a classy, I can't answer this question"}]
-
-    def reset(self, *args):
-        self.messages = [{'role': 'system', 'content': "You are now a very useful maid assistant! If you have a question you can't answer, please reply with As a classy, I can't answer this question"}]
-        return clean_textbox(*args)
-
-    def chat(self, prompt):
-        self.messages.append({"role": "user", "content": prompt})
-        completion = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=self.messages,
-            temperature=0.7
-        )
-        res_msg = completion.choices[0].message["content"].strip()
-        self.messages.append({"role": "assistant", "content": res_msg})
-        return res_msg
-
-
-if __name__ == '__main__':
-    my_chatgpt = ChatGPT()
-    with gr.Blocks(title="POULTA INC ChatGPT") as demo:
-        gr.Markdown('''
-        # ChatGPT
-                ''')
-        with gr.Row():
-            with gr.Column(scale=9):
-                prompt = gr.Text(label='ChatGPT_Prompt', show_label=False, lines=3,
-                                 placeholder='ChatGPT Prompt')
-                res = gr.Text(label='ChatGPT_result', show_label=False, lines=3,
-                              placeholder='chatgpt results')
-
-            with gr.Column(scale=1):
-                btn_gen = gr.Button(value="send", variant='primary')
-                btn_clear = gr.Button(value="restart chat")
-
-        gr.Examples([
-            ["What is Poulta Inc?"],
-            ["what is Poulta inc doing?"],
-            ["Poulta inc Bring real-time central monitoring to your farms"]],
-            inputs=[prompt],
-            outputs=[res],
-            fn=my_chatgpt.chat,
-            cache_examples=False)
-
-        btn_gen.click(fn=my_chatgpt.chat, inputs=prompt,
-                      outputs=res)
-        btn_clear.click(fn=my_chatgpt.reset,
-                        inputs=[prompt, res],
-                        outputs=[prompt, res])
-
-    demo.queue()
-    demo.launch()
+import streamlit as st
+from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
+from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
+from clarifai_grpc.grpc.api.status import status_code_pb2
+
+# Function to make API call and get text completion
+def get_text_completion(raw_text):
+    PAT = '9b209aadda08410caf0b6d815b57e080'
+    USER_ID = 'openai'
+    APP_ID = 'chat-completion'
+    MODEL_ID = 'GPT-4'
+    MODEL_VERSION_ID = '5d7a50b44aec4a01a9c492c5a5fcf387'
+    
+    channel = ClarifaiChannel.get_grpc_channel()
+    stub = service_pb2_grpc.V2Stub(channel)
+    metadata = (('authorization', 'Key ' + PAT),)
+    
+    userDataObject = resources_pb2.UserAppIDSet(user_id=USER_ID, app_id=APP_ID)
+    
+    post_model_outputs_response = stub.PostModelOutputs(
+        service_pb2.PostModelOutputsRequest(
+            user_app_id=userDataObject,
+            model_id=MODEL_ID,
+            version_id=MODEL_VERSION_ID,
+            inputs=[
+                resources_pb2.Input(
+                    data=resources_pb2.Data(
+                        text=resources_pb2.Text(
+                            raw=raw_text
+                        )
+                    )
+                )
+            ]
+        ),
+        metadata=metadata
+    )
+    
+    if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
+        raise Exception(f"Post model outputs failed, status: {post_model_outputs_response.status.description}")
+    
+    output = post_model_outputs_response.outputs[0]
+    
+    return output.data.text.raw
+
+# Streamlit app
+def main():
+    st.title("Text Completion App")
+    
+    # Get user input
+    raw_text = st.text_area("Enter text:", "i need to know about narcotics pemishment")
+    
+    # Perform text completion when button is clicked
+    if st.button("Complete Text"):
+        completion_result = get_text_completion(raw_text)
+        st.success("Completion:\n{}".format(completion_result))
+
+if __name__ == "__main__":
+    main()