cumulative subtask context
This commit is contained in:
mudler
5
.env
5
.env
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DEBUG=true
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MODELS_PATH=/models
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GALLERIES=[{"name":"model-gallery", "url":"github:go-skynet/model-gallery/index.yaml"}, {"url": "github:go-skynet/model-gallery/huggingface.yaml","name":"huggingface"}]
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# 30b setup
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PRELOAD_MODELS=[{"id":"huggingface@thebloke/gplatty-30b-ggml/gplatty-30b.ggmlv3.q2_k.bin","name":"gpt-4","overrides":{"context_size":4096,"mmap":true,"f16":true,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95}}},{"id":"model-gallery@stablediffusion"},{"id":"model-gallery@voice-en-us-kathleen-low"},{"url":"github:go-skynet/model-gallery/base.yaml","name":"all-MiniLM-L6-v2","overrides":{"embeddings":true,"backend":"huggingface-embeddings","parameters":{"model":"all-MiniLM-L6-v2"}}},{"id":"huggingface@thebloke/gplatty-30b-ggml/gplatty-30b.ggmlv3.q2_k.bin","name":"functions","overrides":{"context_size":4096,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"template":{"chat":"","completion":""},"roles":{"assistant":"ASSISTANT:","system":"SYSTEM:","assistant_function_call":"FUNCTION_CALL:","function":"FUNCTION CALL RESULT:"},"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95},"function":{"disable_no_action":true},"mmap":true,"f16":true}}]
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# 13b setup
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# PRELOAD_MODELS=[{"id":"huggingface@thebloke/wizardlm-13b-v1.0-uncensored-ggml/wizardlm-13b-v1.0-uncensored.ggmlv3.q4_k_m.bin","name":"gpt-4","overrides":{"context_size":2048,"mmap":true,"f16":true,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95}}},{"id":"model-gallery@stablediffusion"},{"id":"model-gallery@voice-en-us-kathleen-low"},{"url":"github:go-skynet/model-gallery/base.yaml","name":"all-MiniLM-L6-v2","overrides":{"embeddings":true,"backend":"huggingface-embeddings","parameters":{"model":"all-MiniLM-L6-v2"}}},{"id":"huggingface@thebloke/wizardlm-13b-v1.0-uncensored-ggml/wizardlm-13b-v1.0-uncensored.ggmlv3.q4_0.bin","name":"functions","overrides":{"context_size":2048,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"template":{"chat":"","completion":""},"roles":{"assistant":"ASSISTANT:","system":"SYSTEM:","assistant_function_call":"FUNCTION_CALL:","function":"FUNCTION CALL RESULT:"},"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95},"function":{"disable_no_action":true},"mmap":true,"f16":true}}]
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#PRELOAD_MODELS_CONFIG=/config/preload-models.yaml
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# 30b superhot setup
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PRELOAD_MODELS=[{"id":"huggingface@thebloke/gplatty-30b-superhot-8k-ggml/gplatty-30b-superhot-8k.ggmlv3.q2_k.bin","name":"gpt-4","overrides":{"context_size":8192,"mmap":true,"f16":true,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95,"rope_freq_scale":0.25}}},{"id":"model-gallery@stablediffusion"},{"id":"model-gallery@voice-en-us-kathleen-low"},{"url":"github:go-skynet/model-gallery/base.yaml","name":"all-MiniLM-L6-v2","overrides":{"embeddings":true,"backend":"huggingface-embeddings","parameters":{"model":"all-MiniLM-L6-v2"}}},{"id":"huggingface@thebloke/gplatty-30b-superhot-8k-ggml/gplatty-30b-superhot-8k.ggmlv3.q2_k.bin","name":"functions","overrides":{"context_size":8192,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"template":{"chat":"","completion":""},"roles":{"assistant":"ASSISTANT:","system":"SYSTEM:","assistant_function_call":"FUNCTION_CALL:","function":"FUNCTION CALL RESULT:"},"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95,"rope_freq_scale":0.25},"function":{"disable_no_action":true},"mmap":true,"f16":true}}]
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#PRELOAD_MODELS=[{"id":"huggingface@thebloke/gplatty-30b-superhot-8k-ggml/gplatty-30b-superhot-8k.ggmlv3.q2_k.bin","name":"gpt-4","overrides":{"context_size":8192,"mmap":true,"f16":true,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95,"rope_freq_scale":0.25}}},{"id":"model-gallery@stablediffusion"},{"id":"model-gallery@voice-en-us-kathleen-low"},{"url":"github:go-skynet/model-gallery/base.yaml","name":"all-MiniLM-L6-v2","overrides":{"embeddings":true,"backend":"huggingface-embeddings","parameters":{"model":"all-MiniLM-L6-v2"}}},{"id":"huggingface@thebloke/gplatty-30b-superhot-8k-ggml/gplatty-30b-superhot-8k.ggmlv3.q2_k.bin","name":"functions","overrides":{"context_size":8192,"mirostat":2,"mirostat_tau":5,"mirostat_eta":0.1,"template":{"chat":"","completion":""},"roles":{"assistant":"ASSISTANT:","system":"SYSTEM:","assistant_function_call":"FUNCTION_CALL:","function":"FUNCTION CALL RESULT:"},"parameters":{"temperature":0.1,"top_k":40,"top_p":0.95,"rope_freq_scale":0.25},"function":{"disable_no_action":true},"mmap":true,"f16":true}}]
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OPENAI_API_KEY=sk---
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OPENAI_API_BASE=http://api:8080
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IMAGE_PATH=/tmp
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11
README.md
11
README.md
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# microAGI
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<h1 align="center">
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<br>
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<img height="300" src="https://github.com/mudler/microAGI/assets/2420543/7717fafb-de72-4a2d-a47a-229fc64b5716"> <br>
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μAGI (microAGI)
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<br>
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</h1>
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From the [LocalAI](https://localai.io) author, microAGI. 100% Local AI assistant.
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Note: this is a fun project, not a serious one. Be warned!
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## What is microAGI?
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## What is μAGI?
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It is a dead simple experiment to show how to tie the various LocalAI functionalities to create a virtual assistant that can do tasks. It is simple on purpose, trying to be minimalistic and easy to understand and customize.
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@@ -57,5 +62,5 @@ Under the hood LocalAI converts functions to llama.cpp BNF grammars. While OpenA
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Run docker-compose with main.py checked-out:
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```bash
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docker-compose run -v main.py:/app/main.py -i --rm microAGI
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docker-compose run -v main.py:/app/main.py -i --rm microagi
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```
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9
main.py
9
main.py
@@ -285,12 +285,19 @@ def evaluate(user_input, conversation_history = [],re_evaluate=False, agent_acti
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# First we check if it's an object
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if isinstance(function_results, dict) and function_results.get("subtasks") and len(function_results["subtasks"]) > 0:
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# cycle subtasks and execute functions
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subtask_result=""
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for subtask in function_results["subtasks"]:
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logger.info("==> subtask: ")
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logger.info(subtask)
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#ctr="Context: "+user_input+"\nThought: "+action["reasoning"]+ "\nRequest: "+subtask["reasoning"]
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cr="Context: "+user_input+"\nRequest: "+subtask["reasoning"]
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cr="Context: "+user_input+"\n"
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if subtask_result != "":
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# Include cumulative results of previous subtasks
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# TODO: this grows context, maybe we should use a different approach or summarize
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cr+="Subtask results: "+subtask_result+"\n"
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cr+="Request: "+subtask["reasoning"]
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subtask_response, function_results = process_functions(cr, subtask["function"],agent_actions=agent_actions)
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subtask_result+=process_history(subtask_response)
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responses.extend(subtask_response)
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if re_evaluate:
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## Better output or this infinite loops..
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