Closed jaygdesai closed 1 month ago
Hey @jaygdesai, this looks like a Llama 3.1 issue, I've noticed that it can put double quotes around the numeric parameters:
"parameters": {\n "a": "232",\n "b": "32"\n }
That should be:
"parameters": {\n "a": 232,\n "b": 32\n }.
I've found that I need to add an example to the assistant's system_message, going from this:
assistant = ConversableAgent(
name="Assistant",
system_message="You are a helpful AI assistant. "
"You can help with simple calculations. "
"Return 'TERMINATE' when the task is done.",
llm_config={"config_list": config_list},
)
to this:
assistant = ConversableAgent(
name="Assistant",
system_message="""You are a helpful AI assistant.
You can help with simple calculations.
Example of the return JSON is:
{
"parameter_1_name": 100.00,
"parameter_2_name": "ABC",
"parameter_3_name": "DEF",
}.
Another example of the return JSON is:
{
"parameter_1_name": "GHI",
"parameter_2_name": "ABC",
"parameter_3_name": "DEF",
"parameter_4_name": 123.00,
}.
Return 'TERMINATE' when the task is done.""",
llm_config={"config_list": config_list},
)
Can you try that?
If that still results in strings for the numeric values try converting strings to integers in your calculation functions.
@jaygdesai I think it will be interesting to look into what tools
config is getting passed to LLM. It may not be making clear to LLM the type of parameters. If that is the case, you should use typing to ensure that parameter types are well defined in tools config that get passed to LLM. LLM should honor the function signature.
Hey @jaygdesai, this looks like a Llama 3.1 issue, I've noticed that it can put double quotes around the numeric parameters:
"parameters": {\n "a": "232",\n "b": "32"\n }
That should be: "parameters": {\n "a": 232,\n "b": 32\n }.I've found that I need to add an example to the assistant's system_message, going from this:
assistant = ConversableAgent( name="Assistant", system_message="You are a helpful AI assistant. " "You can help with simple calculations. " "Return 'TERMINATE' when the task is done.", llm_config={"config_list": config_list}, )
to this:
assistant = ConversableAgent( name="Assistant", system_message="""You are a helpful AI assistant. You can help with simple calculations. Example of the return JSON is: { "parameter_1_name": 100.00, "parameter_2_name": "ABC", "parameter_3_name": "DEF", }. Another example of the return JSON is: { "parameter_1_name": "GHI", "parameter_2_name": "ABC", "parameter_3_name": "DEF", "parameter_4_name": 123.00, }. Return 'TERMINATE' when the task is done.""", llm_config={"config_list": config_list}, )
Can you try that?
If that still results in strings for the numeric values try converting strings to integers in your calculation functions.
When I tried suggested approach, I still got following reply.
User (to Assistant):
What is (44232 + 13312 / (232 - 32)) * 5?
--------------------------------------------------------------------------------
>>>>>>>> USING AUTO REPLY...
---------------------------------------------------------------------------
BadRequestError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/autogen/oai/groq.py](https://localhost:8080/#) in create(self, params)
154 try:
--> 155 response = client.chat.completions.create(**groq_params)
156 except Exception as e:
12 frames
BadRequestError: Error code: 400 - {'error': {'message': "Failed to call a function. Please adjust your prompt. See 'failed_generation' for more details.", 'type': 'invalid_request_error', 'code': 'tool_use_failed', 'failed_generation': '<tool-use>\n{\n\t"tool_calls": [\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "add",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "44232",\n\t\t\t\t\t"b": "13312 / (232 - 32)"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t},\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "subtract",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "232",\n\t\t\t\t\t"b": "32"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t},\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "divide",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "13312",\n\t\t\t\t\t"b": "200"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t},\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "multiply",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "44232 + 66.2",\n\t\t\t\t\t"b": "5"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t}\n\t]\n}\n</tool-use>'}}
During handling of the above exception, another exception occurred:
RuntimeError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/autogen/oai/groq.py](https://localhost:8080/#) in create(self, params)
155 response = client.chat.completions.create(**groq_params)
156 except Exception as e:
--> 157 raise RuntimeError(f"Groq exception occurred: {e}")
158 else:
159
RuntimeError: Groq exception occurred: Error code: 400 - {'error': {'message': "Failed to call a function. Please adjust your prompt. See 'failed_generation' for more details.", 'type': 'invalid_request_error', 'code': 'tool_use_failed', 'failed_generation': '<tool-use>\n{\n\t"tool_calls": [\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "add",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "44232",\n\t\t\t\t\t"b": "13312 / (232 - 32)"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t},\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "subtract",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "232",\n\t\t\t\t\t"b": "32"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t},\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "divide",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "13312",\n\t\t\t\t\t"b": "200"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t},\n\t\t{\n\t\t\t"id": "pending",\n\t\t\t"type": "function",\n\t\t\t"function": {\n\t\t\t\t"name": "multiply",\n\t\t\t\t"parameters": {\n\t\t\t\t\t"a": "44232 + 66.2",\n\t\t\t\t\t"b": "5"\n\t\t\t\t}\n\t\t\t},\n\t\t\t"parameters": {}\n\t\t}\n\t]\n}\n</tool-use>'}}
And when I reverted to my previous assistant initialization and changed function parameters to accept str, I get following error:
User (to Assistant):
What is (44232 + 13312 / (232 - 32)) * 5?
--------------------------------------------------------------------------------
>>>>>>>> USING AUTO REPLY...
---------------------------------------------------------------------------
BadRequestError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/autogen/oai/groq.py](https://localhost:8080/#) in create(self, params)
154 try:
--> 155 response = client.chat.completions.create(**groq_params)
156 except Exception as e:
12 frames
BadRequestError: Error code: 400 - {'error': {'message': "Failed to call a function. Please adjust your prompt. See 'failed_generation' for more details.", 'type': 'invalid_request_error', 'code': 'tool_use_failed', 'failed_generation': '<tool-use>\n{\n "tool_calls": [\n {\n "id": "pending",\n "type": "function",\n "function": {\n "name": "add",\n "parameters": {\n "a": "44232",\n "b": "5390"\n }\n }\n }\n ]\n}\n</tool-use>'}}
During handling of the above exception, another exception occurred:
RuntimeError Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/autogen/oai/groq.py](https://localhost:8080/#) in create(self, params)
155 response = client.chat.completions.create(**groq_params)
156 except Exception as e:
--> 157 raise RuntimeError(f"Groq exception occurred: {e}")
158 else:
159
RuntimeError: Groq exception occurred: Error code: 400 - {'error': {'message': "Failed to call a function. Please adjust your prompt. See 'failed_generation' for more details.", 'type': 'invalid_request_error', 'code': 'tool_use_failed', 'failed_generation': '<tool-use>\n{\n "tool_calls": [\n {\n "id": "pending",\n "type": "function",\n "function": {\n "name": "add",\n "parameters": {\n "a": "44232",\n "b": "5390"\n }\n }\n }\n ]\n}\n</tool-use>'}}
In above case, function definitions were changed to:
def add(a: str, b: str) -> int:
ai = int(a)
bi = int(b)
return ai + bi
def subtract(a: str, b: str) -> int:
ai = int(a)
bi = int(b)
return ai - bi
def multiply(a: str, b: str) -> int:
ai = int(a)
bi = int(b)
return ai * bi
def divide(a: str, b: str) -> int:
ai = int(a)
bi = int(b)
return ai / bi
@jaygdesai I think it will be interesting to look into what
tools
config is getting passed to LLM. It may not be making clear to LLM the type of parameters. If that is the case, you should use typing to ensure that parameter types are well defined in tools config that get passed to LLM. LLM should honor the function signature.
Can you let me know how to view tool config passed to LLM from AutoGen. Also, in function definitions I have already included types of parameters.
Hey @jaygdesai, if you're able to put a breakpoint at this line in groq.py, have a look at the groq_params
and you'll see everything that's going to groq.
If you can't put a breakpoint in there, try adding a line before it with: print(groq_params)
Feel free to post it here as well.
@jaygdesai in addition to what @marklysze suggested, you can also print agent.function_map
to see what function details are getting passed.
I recently run the code again. No error! Most likely, correction in llama / groq layers. I think it is a challenge to predict the behaviour with API calls to any hosted LLM, where LLM implementation/version may be changing. Something tested today, may not be valid tomorrow. It would be great if companies provide check-pointed LLMs (for inference) so that application developers can try different prompts to get their implemention right and can product similar results in production.
Closing the issue as the bug is not reproduced.
When I execute this (from documentation, but with Groq model): chat_result = user_proxy.initiate_chat(assistant, message="What is (44232 + 13312 / (232 - 32)) * 5?")
I get following reply:
User (to Assistant):
What is (44232 + 13312 / (232 - 32)) * 5?
12 frames BadRequestError: Error code: 400 - {'error': {'message': "Failed to call a function. Please adjust your prompt. See 'failed_generation' for more details.", 'type': 'invalid_request_error', 'code': 'tool_use_failed', 'failed_generation': '\n{\n "tool_calls": [\n {\n "id": "pending",\n "type": "function",\n "function": {\n "name": "subtract",\n "parameters": {\n "a": "232",\n "b": "32"\n }\n }\n }\n ]\n}\n '}}
During handling of the above exception, another exception occurred:
RuntimeError Traceback (most recent call last) /usr/local/lib/python3.10/dist-packages/autogen/oai/groq.py in create(self, params) 155 response = client.chat.completions.create(**groq_params) 156 except Exception as e: --> 157 raise RuntimeError(f"Groq exception occurred: {e}") 158 else: 159
RuntimeError: Groq exception occurred: Error code: 400 - {'error': {'message': "Failed to call a function. Please adjust your prompt. See 'failed_generation' for more details.", 'type': 'invalid_request_error', 'code': 'tool_use_failed', 'failed_generation': '\n{\n "tool_calls": [\n {\n "id": "pending",\n "type": "function",\n "function": {\n "name": "subtract",\n "parameters": {\n "a": "232",\n "b": "32"\n }\n }\n }\n ]\n}\n '}}
It identifies the call correctly. However, fails to execute. My code is able to call with Cohere (and hopefully OpenAI (But haven't tried)). But, Groq gives above message.
Is there anything I am missing?
Steps to reproduce
Screenshots and logs
No response
Additional Information
Package Version
absl-py 1.4.0 accelerate 0.32.1 aiohttp 3.9.5 aiosignal 1.3.1 alabaster 0.7.16 albumentations 1.3.1 altair 4.2.2 annotated-types 0.7.0 anyio 3.7.1 argon2-cffi 23.1.0 argon2-cffi-bindings 21.2.0 array_record 0.5.1 arviz 0.15.1 astropy 5.3.4 astunparse 1.6.3 async-timeout 4.0.3 atpublic 4.1.0 attrs 23.2.0 audioread 3.0.1 autograd 1.6.2 Babel 2.15.0 backcall 0.2.0 beautifulsoup4 4.12.3 bidict 0.23.1 bigframes 1.11.1 bleach 6.1.0 blinker 1.4 blis 0.7.11 blosc2 2.0.0 bokeh 3.3.4 bqplot 0.12.43 branca 0.7.2 build 1.2.1 CacheControl 0.14.0 cachetools 5.4.0 catalogue 2.0.10 certifi 2024.7.4 cffi 1.16.0 chardet 5.2.0 charset-normalizer 3.3.2 chex 0.1.86 clarabel 0.9.0 click 8.1.7 click-plugins 1.1.1 cligj 0.7.2 cloudpathlib 0.18.1 cloudpickle 2.2.1 cmake 3.27.9 cmdstanpy 1.2.4 colorcet 3.1.0 colorlover 0.3.0 colour 0.1.5 community 1.0.0b1 confection 0.1.5 cons 0.4.6 contextlib2 21.6.0 contourpy 1.2.1 cryptography 43.0.0 cuda-python 12.2.1 cudf-cu12 24.4.1 cufflinks 0.17.3 cupy-cuda12x 12.2.0 cvxopt 1.3.2 cvxpy 1.5.2 cycler 0.12.1 cymem 2.0.8 Cython 3.0.10 dask 2023.8.1 datascience 0.17.6 db-dtypes 1.2.0 dbus-python 1.2.18 debugpy 1.6.6 decorator 4.4.2 defusedxml 0.7.1 diskcache 5.6.3 distributed 2023.8.1 distro 1.7.0 dlib 19.24.4 dm-tree 0.1.8 docker 7.1.0 docstring_parser 0.16 docutils 0.18.1 dopamine_rl 4.0.9 duckdb 0.10.3 earthengine-api 0.1.412 easydict 1.13 ecos 2.0.14 editdistance 0.6.2 eerepr 0.0.4 en-core-web-sm 3.7.1 entrypoints 0.4 et-xmlfile 1.1.0 etils 1.7.0 etuples 0.3.9 exceptiongroup 1.2.2 fastai 2.7.15 fastcore 1.5.54 fastdownload 0.0.7 fastjsonschema 2.20.0 fastprogress 1.0.3 fastrlock 0.8.2 filelock 3.15.4 fiona 1.9.6 firebase-admin 5.3.0 FLAML 2.1.2 Flask 2.2.5 flatbuffers 24.3.25 flax 0.8.4 folium 0.14.0 fonttools 4.53.1 frozendict 2.4.4 frozenlist 1.4.1 fsspec 2023.6.0 future 0.18.3 gast 0.6.0 gcsfs 2023.6.0 GDAL 3.6.4 gdown 5.1.0 geemap 0.33.1 gensim 4.3.3 geocoder 1.38.1 geographiclib 2.0 geopandas 0.13.2 geopy 2.3.0 gin-config 0.5.0 glob2 0.7 google 2.0.3 google-ai-generativelanguage 0.6.6 google-api-core 2.19.1 google-api-python-client 2.137.0 google-auth 2.27.0 google-auth-httplib2 0.2.0 google-auth-oauthlib 1.2.1 google-cloud-aiplatform 1.59.0 google-cloud-bigquery 3.25.0 google-cloud-bigquery-connection 1.15.4 google-cloud-bigquery-storage 2.25.0 google-cloud-bigtable 2.25.0 google-cloud-core 2.4.1 google-cloud-datastore 2.19.0 google-cloud-firestore 2.16.1 google-cloud-functions 1.16.4 google-cloud-iam 2.15.1 google-cloud-language 2.13.4 google-cloud-pubsub 2.22.0 google-cloud-resource-manager 1.12.4 google-cloud-storage 2.8.0 google-cloud-translate 3.15.4 google-colab 1.0.0 google-crc32c 1.5.0 google-generativeai 0.7.2 google-pasta 0.2.0 google-resumable-media 2.7.1 googleapis-common-protos 1.63.2 googledrivedownloader 0.4 graphviz 0.20.3 greenlet 3.0.3 groq 0.9.0 grpc-google-iam-v1 0.13.1 grpcio 1.64.1 grpcio-status 1.48.2 gspread 6.0.2 gspread-dataframe 3.3.1 gym 0.25.2 gym-notices 0.0.8 h11 0.14.0 h5netcdf 1.3.0 h5py 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