fix build

Dockerfile

@@ -15,8 +15,7 @@ RUN apt-get update && \
     xargs -r -a /app/packages.txt apt-get install -y && \
     rm -rf /var/lib/apt/lists/* && \
     pip install --no-cache-dir -r $HOME/app/requirements.txt && \
-    pip install llama-cpp-python \
-    --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu
+    pip install llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu
 
 EXPOSE 7860
 CMD streamlit run app.py \

README.md

@@ -1,11 +1,23 @@
 ---
 title: Naomi
-emoji: 🏆
-colorFrom: blue
+emoji: 👧🏻
+colorFrom: pink
 colorTo: gray
 sdk: docker
 pinned: false
 license: mit
+hf_oath: true
+
+models:
+- bartowski/Meta-Llama-3.1-8B-Instruct-GGUF Meta-Llama-3.1-8B-Instruct-Q3_K_XL.gguf
+tags:
+- text
+- llm
+- meta
+- instruct
+preload_from_hub:
+- bartowski/Meta-Llama-3.1-8B-Instruct-GGUF Meta-Llama-3.1-8B-Instruct-Q3_K_XL.gguf
+
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

agent.py

@@ -0,0 +1,153 @@
+"""
+This script defines the Naomi class, which utilizes the Llama model for chatbot interactions.
+It includes methods for responding to user input while maintaining a chat history.
+
+Keyword arguments:
+    - kwargs: Additional keyword arguments for candidate information.
+
+Return:
+    - An instance of the Naomi class, capable of handling chatbot interactions.
+"""
+
+
+import time
+from uuid import uuid4
+from llama_cpp import Llama
+from llama_cpp.llama_tokenizer import LlamaHFTokenizer
+
+# default decoding params initiation
+SEED = 42
+
+MODEL_CARD = "bartowski/Meta-Llama-3.1-8B-Instruct-GGUF"
+MODEL_PATH = "Meta-Llama-3.1-8B-Instruct-Q3_K_XL.gguf"
+base_model_id = "meta-llama/Llama-3.1-8B-Instruct"
+
+new_chat_template = """{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 Jul 2024" %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+    {#- System message + builtin tools #}
+    {{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+    {%- if builtin_tools is defined or tools is not none %}
+        {{- "Environment: ipython\n" }}
+    {%- endif %}
+    {%- if builtin_tools is defined %}
+        {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
+    {%- endif %}
+    {%- if tools is not none and not tools_in_user_message %}
+        {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+        {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+        {{- "Do not use variables.\n\n" }}
+        {%- for t in tools %}
+            {{- t | tojson(indent=4) }}
+            {{- "\n\n" }}
+        {%- endfor %}
+    {%- endif %}
+    {{- system_message }}
+    {{- "<|eot_id|>" }}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- '{"name": "' + tool_call.name + '", ' }}
+            {{- '"parameters": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- "}" }}
+        {%- endif %}
+        {%- if builtin_tools is defined %}
+            {#- This means we're in ipython mode #}
+            {{- "<|eom_id|>" }}
+        {%- else %}
+            {{- "<|eot_id|>" }}
+        {%- endif %}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}"""
+
+datetime_format = '%Y-%m-%d %H:%M:%S'
+
+from datetime import datetime
+
+class Naomi:
+    def __init__(self, **kwargs):
+        self.session_id = uuid4().hex
+        self.candidate = kwargs
+
+        # load the model
+        self.model = Llama.from_pretrained(
+	        repo_id=MODEL_CARD,
+	        filename=MODEL_PATH,
+            tokenizer=LlamaHFTokenizer.from_pretrained(base_model_id)
+        )
+
+        self.model.tokenizer_.hf_tokenizer.chat_template = new_chat_template
+        # load the agents prompts
+        self.chat_history = self.model.tokenizer_.hf_tokenizer.apply_chat_template(
+        )
+
+        self.timestamps = []
+
+    def invoke(self, history, **kwargs):
+        """ Invoked during stream. """
+        # user msg handling
+        self.timestamps += [datetime.now().strftime(datetime_format)]
+        format_user_input = self.model.tokenizer_.hf_tokenizer.apply_chat_template(history[-1], tokenize=False, add_generation_prompt=False)
+        self.chat_history += format_user_input
+        # agent msg results + clean
+        response = self.model(self.chat_history, **kwargs)
+        output = "".join(response['choices'][0]['text'].split('\n\n')[1:])
+        # update history
+        self.timestamps += [datetime.now().strftime(datetime_format)]
+        self.chat_history += self.model.tokenizer_.hf_tokenizer.apply_chat_template([{'role': 'assistant', 'content': output}], tokenize=False, add_generation_prompt=False)
+        return output
+
+    def respond(self, history, **kwargs):
+        """ Generator that yields responses in chat sessions. """
+        response = self.invoke(history, **kwargs)
+        for word in response.split():
+            yield word + " "
+            time.sleep(0.05)