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examples : server chat mode with llama2 (#2400)
* add: server chat mode with llama2 * fix: remove the unnecessary last \n
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examples/server-llama2-13B.sh
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examples/server-llama2-13B.sh
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#!/bin/bash
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set -e
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cd "$(dirname "$0")/.." || exit
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# Specify the model you want to use here:
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MODEL="${MODEL:-./models/llama-2-13b-chat.ggmlv3.q5_K_M.bin}"
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PROMPT_TEMPLATE=${PROMPT_TEMPLATE:-./prompts/chat-system.txt}
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# Adjust to the number of CPU cores you want to use.
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N_THREAD="${N_THREAD:-12}"
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# Note: you can also override the generation options by specifying them on the command line:
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GEN_OPTIONS="${GEN_OPTIONS:---ctx_size 4096 --batch-size 1024}"
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# shellcheck disable=SC2086 # Intended splitting of GEN_OPTIONS
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./server $GEN_OPTIONS \
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--model "$MODEL" \
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--threads "$N_THREAD" \
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--rope-freq-scale 1.0 \
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"$@"
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# I used this to test the model with mps, but omitted it from the general purpose. If you want to use it, just specify it on the command line.
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# -ngl 1 \
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109
examples/server/chat-llama2.sh
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examples/server/chat-llama2.sh
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#!/bin/bash
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API_URL="${API_URL:-http://127.0.0.1:8080}"
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CHAT=(
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"Hello, Assistant."
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"Hello. How may I help you today?"
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)
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INSTRUCTION="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions."
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trim() {
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shopt -s extglob
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set -- "${1##+([[:space:]])}"
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printf "%s" "${1%%+([[:space:]])}"
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}
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trim_trailing() {
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shopt -s extglob
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printf "%s" "${1%%+([[:space:]])}"
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}
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format_prompt() {
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if [[ "${#CHAT[@]}" -eq 0 ]]; then
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echo -n "[INST] <<SYS>>\n${INSTRUCTION}\n<</SYS>>"
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else
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LAST_INDEX=$(( ${#CHAT[@]} - 1 ))
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echo -n "${CHAT[$LAST_INDEX]}\n[INST] $1 [/INST]"
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fi
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}
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tokenize() {
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curl \
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--silent \
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--request POST \
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--url "${API_URL}/tokenize" \
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--header "Content-Type: application/json" \
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--data-raw "$(jq -ns --arg content "$1" '{content:$content}')" \
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| jq '.tokens[]'
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}
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N_KEEP=$(tokenize "[INST] <<SYS>>\n${INSTRUCTION}\n<</SYS>>" | wc -l)
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chat_completion() {
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PROMPT="$(trim_trailing "$(format_prompt "$1")")"
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DATA="$(echo -n "$PROMPT" | jq -Rs --argjson n_keep $N_KEEP '{
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prompt: .,
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temperature: 0.2,
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top_k: 40,
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top_p: 0.9,
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n_keep: $n_keep,
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n_predict: 1024,
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stop: ["[INST]"],
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stream: true
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}')"
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# Create a temporary file to hold the Python output
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TEMPFILE=$(mktemp)
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exec 3< <(curl \
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--silent \
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--no-buffer \
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--request POST \
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--url "${API_URL}/completion" \
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--header "Content-Type: application/json" \
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--data-raw "${DATA}")
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python -c "
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import json
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import sys
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answer = ''
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while True:
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line = sys.stdin.readline()
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if not line:
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break
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if line.startswith('data: '):
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json_content = line[6:].strip()
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content = json.loads(json_content)['content']
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sys.stdout.write(content)
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sys.stdout.flush()
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answer += content
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answer = answer.rstrip('\n')
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# Write the answer to the temporary file
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with open('$TEMPFILE', 'w') as f:
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f.write(answer)
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" <&3
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exec 3<&-
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# Read the answer from the temporary file
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ANSWER=$(cat $TEMPFILE)
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# Clean up the temporary file
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rm $TEMPFILE
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printf "\n"
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CHAT+=("$1" "$(trim "$ANSWER")")
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}
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while true; do
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echo -en "\033[0;32m" # Green color
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read -r -e -p "> " QUESTION
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echo -en "\033[0m" # Reset color
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chat_completion "${QUESTION}"
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done
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