Create app.py

app.py

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+import gradio as gr
+import cohere
+import os
+import re
+import uuid
+from functools import partial
+
+
+
+cohere_api_key = os.getenv("COHERE_API_KEY")
+co = cohere.Client(cohere_api_key)
+
+def trigger_example(example):
+    chat, updated_history = generate_response(example)
+    return chat, updated_history
+        
+def generate_response(user_message, history=None):
+    global cid
+    
+    if history is None:
+        history = []
+        
+    history.append(user_message)
+     
+    stream = co.chat_stream(message=user_message, conversation_id=cid, model='command-r', connectors=[], temperature=0.3)
+    
+    output = ""
+    for idx, response in enumerate(stream):
+        if response.event_type == "text-generation":
+            output += response.text
+        
+        if idx == 0:
+            history.append(" " + output)
+        else:
+            history[-1] = output
+
+        chat = [
+            (history[i].strip(), history[i + 1].strip())
+            for i in range(0, len(history) - 1, 2)
+        ]
+        
+        yield chat, history
+
+    return chat, history
+    
+
+def clear_chat():
+    global cid
+    cid = str(uuid.uuid4())
+    return [], []
+
+
+examples = [
+"Get a quick overview of current market condition of solar panels",
+"Gather business intelligence on the Chinese markets",
+"Summarize recent news about the North American tech job market",
+"Give me a rundown of AI startups in the productivity space",
+"Write a python code to reverse a string",
+"Write a children's story about a polar bear who goes to the market to buy a new coat",
+"Create a list of unusual excuses people might use to get out of a work meeting",
+"Explain the relativity theory in french"
+]
+
+title = """<h1 align="center">Cohere for AI Command R</h1>"""
+custom_css = """
+#logo-img {
+    display: block;
+    margin-left: auto;
+    margin-right: auto;
+}
+#chat-message {
+    font-size: 14px;
+    min-height: 300px;
+}
+"""
+
+with gr.Blocks(analytics_enabled=False, css=custom_css) as demo:
+    #gr.HTML(title)
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Image("cmdr.png", elem_id="logo-img", show_label=False)
+        with gr.Column(scale=3):
+            gr.Markdown("""Command R is a large language model with open weights optimized for various use cases 
+            including reasoning, summarization, and question answering. Command R is capable of multilingual generation 
+            evaluated in 10 languages and highly performant RAG capabilities. 
+            <br/><br/>
+            **Model**: [c4ai-command-r-v01](https://huggingface.co/CohereForAI/c4ai-command-r-v01)
+            <br/> 
+            **Developed by**: [Cohere](https://cohere.com/) and [Cohere for AI](https://cohere.com/research)
+            <br/>
+            **License**: CC-BY-NC, requires also adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy)
+            """
+            )
+            
+    with gr.Column():
+        with gr.Row():
+            chatbot = gr.Chatbot(show_label=False)
+        
+        with gr.Row():
+            user_message = gr.Textbox(lines=1, placeholder="Ask anything ...", label="Input", show_label=False)
+
+      
+        with gr.Row():
+            submit_button = gr.Button("Submit")
+            clear_button = gr.Button("Clear chat")
+
+                        
+        history = gr.State([])
+        cid = str(uuid.uuid4())
+
+        
+        user_message.submit(fn=generate_response, inputs=[user_message, history], outputs=[chatbot, history])
+
+        submit_button.click(fn=generate_response, inputs=[user_message, history], outputs=[chatbot, history])
+        clear_button.click(fn=clear_chat, inputs=None, outputs=[chatbot, history])
+
+        with gr.Row():
+            gr.Examples(
+                examples=examples,
+                inputs=[user_message],
+                cache_examples=False,
+                fn=trigger_example,
+                outputs=[chatbot],
+            )
+
+if __name__ == "__main__":
+    demo.launch(share=True)