Complete the code to start streaming the AI model's response.
response = model.generate(input_text, stream=[1])Setting stream=True enables the model to send partial outputs as they are generated, allowing streaming responses.
Complete the code to process each chunk of the streamed response.
for chunk in response.[1](): print(chunk)
The iter() method allows iterating over streamed chunks from the response.
Fix the error in the code to correctly handle streaming output.
response = model.generate(input_text, stream=True) for chunk in response.[1]: print(chunk)
The iter() method must be called with parentheses to get an iterator for streaming.
Fill both blanks to create a dictionary of tokens and their counts from streamed text.
token_counts = {}
for chunk in response.[1]():
for token in chunk.split():
token_counts[token] = token_counts.get(token, 0) [2] 1Use iter() to loop over streamed chunks, and + to increment token counts.
Fill all three blanks to collect streamed text chunks and join them into a full response string.
chunks = [] for chunk in response.[1](): chunks.[2](chunk) full_response = [3].join(chunks)
Use iter() to loop, append to add chunks to the list, and "" (empty string) to join chunks without spaces.