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Merge pull request #210 from valory-xyz/feat/tool-param-component
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feat: add tool params
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@richardblythman
richardblythman authored Apr 24, 2024
2 parents a823a98 + 0db6879 commit 80051bd
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Showing 16 changed files with 113 additions and 109 deletions.
4 changes: 3 additions & 1 deletion packages/napthaai/customs/prediction_request_rag/component.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -7,10 +7,12 @@ license: Apache-2.0
aea_version: '>=1.0.0, <2.0.0'
fingerprint:
__init__.py: bafybeibt7f7crtwvmkg7spy3jhscmlqltvyblzp32g6gj44v7tlo5lycuq
prediction_request_rag.py: bafybeie4rafsx7m7mfkdgd2n2ovfm3gwk5ybjr5cz6s7r3oz545ag2wwuy
prediction_request_rag.py: bafybeibtvuddvbhjlyd4sbk7rwz4mcsr4hiigfgrpdhzwa6vn6bhb6fboy
fingerprint_ignore_patterns: []
entry_point: prediction_request_rag.py
callable: run
params:
default_model: claude-3-sonnet-20240229
dependencies:
google-api-python-client:
version: ==2.95.0
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35 changes: 16 additions & 19 deletions packages/napthaai/customs/prediction_request_rag/prediction_request_rag.py
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Original file line number Diff line number Diff line change
Expand Up @@ -222,8 +222,6 @@ def embeddings(self, model, input):
"prediction-request-rag",
]
ALLOWED_MODELS = list(LLM_SETTINGS.keys())
DEFAULT_MODEL = "claude-3-haiku-20240307"
TOOL_TO_ENGINE = {tool: DEFAULT_MODEL for tool in ALLOWED_TOOLS}
DEFAULT_NUM_URLS = defaultdict(lambda: 3)
DEFAULT_NUM_QUERIES = defaultdict(lambda: 3)
NUM_URLS_PER_QUERY = 5
Expand Down Expand Up @@ -299,11 +297,11 @@ def count_tokens(text: str, model: str) -> int:

def multi_queries(
prompt: str,
engine: str,
model: str,
num_queries: int,
counter_callback: Optional[Callable[[int, int, str], None]] = None,
temperature: Optional[float] = LLM_SETTINGS[DEFAULT_MODEL]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS[DEFAULT_MODEL]["default_max_tokens"],
temperature: Optional[float] = LLM_SETTINGS["gpt-4-0125-preview"]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS["gpt-4-0125-preview"]["default_max_tokens"],
) -> List[str]:
"""Generate multiple queries for fetching information from the web."""
url_query_prompt = URL_QUERY_PROMPT.format(
Expand All @@ -316,7 +314,7 @@ def multi_queries(
]

response = client.completions(
model=engine,
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
Expand All @@ -325,7 +323,7 @@ def multi_queries(
counter_callback(
input_tokens=response.usage.prompt_tokens,
output_tokens=response.usage.completion_tokens,
model=engine,
model=model,
token_counter=count_tokens,
)
queries = parser_query_response(response.content, num_queries=num_queries)
Expand Down Expand Up @@ -539,15 +537,15 @@ def recursive_character_text_splitter(text, max_tokens, overlap):

def fetch_additional_information(
prompt: str,
engine: str,
model: str,
google_api_key: Optional[str],
google_engine_id: Optional[str],
counter_callback: Optional[Callable[[int, int, str], None]] = None,
source_links: Optional[List[str]] = None,
num_urls: Optional[int] = DEFAULT_NUM_URLS,
num_queries: Optional[int] = DEFAULT_NUM_QUERIES,
temperature: Optional[float] = LLM_SETTINGS[DEFAULT_MODEL]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS[DEFAULT_MODEL]["default_max_tokens"],
temperature: Optional[float] = LLM_SETTINGS["gpt-4-0125-preview"]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS["gpt-4-0125-preview"]["default_max_tokens"],
) -> Tuple[str, Callable[[int, int, str], None]]:
"""Fetch additional information to help answer the user prompt."""

Expand All @@ -556,7 +554,7 @@ def fetch_additional_information(
try:
queries, counter_callback = multi_queries(
prompt=prompt,
engine=engine,
model=model,
num_queries=num_queries,
counter_callback=counter_callback,
temperature=temperature,
Expand Down Expand Up @@ -674,14 +672,13 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:
kwargs["api_keys"], kwargs["llm_provider"], embedding_provider="openai"
):
tool = kwargs["tool"]
model = kwargs.get("model", TOOL_TO_ENGINE[tool])
prompt = extract_question(kwargs["prompt"])
engine = kwargs.get("model", TOOL_TO_ENGINE[tool])
print(f"ENGINE: {engine}")
model = kwargs.get("model")
print(f"MODEL: {model}")
max_tokens = kwargs.get(
"max_tokens", LLM_SETTINGS[engine]["default_max_tokens"]
"max_tokens", LLM_SETTINGS[model]["default_max_tokens"]
)
temperature = kwargs.get("temperature", LLM_SETTINGS[engine]["temperature"])
temperature = kwargs.get("temperature", LLM_SETTINGS[model]["temperature"])
num_urls = kwargs.get("num_urls", DEFAULT_NUM_URLS[tool])
num_queries = kwargs.get("num_queries", DEFAULT_NUM_QUERIES[tool])
counter_callback = kwargs.get("counter_callback", None)
Expand All @@ -699,7 +696,7 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:

additional_information, counter_callback = fetch_additional_information(
prompt=prompt,
engine=engine,
model=model,
google_api_key=google_api_key,
google_engine_id=google_engine_id,
counter_callback=counter_callback,
Expand All @@ -723,7 +720,7 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:
]

response = client.completions(
model=engine,
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
Expand All @@ -733,7 +730,7 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:
counter_callback(
input_tokens=response.usage.prompt_tokens,
output_tokens=response.usage.completion_tokens,
model=engine,
model=model,
token_counter=count_tokens,
)

Expand Down
4 changes: 3 additions & 1 deletion packages/napthaai/customs/prediction_request_rag_cohere/component.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -8,10 +8,12 @@ license: Apache-2.0
aea_version: '>=1.0.0, <2.0.0'
fingerprint:
__init__.py: bafybeiekjzoy2haayvkiwhb2u2epflpqxticud34mma3gdhfzgu36lxwiq
prediction_request_rag_cohere.py: bafybeidt7vvlrapi2y4b4ytqqi2s2ro5oi5xfc62a2rftkwbat2fmw5hme
prediction_request_rag_cohere.py: bafybeig4oq3tdjuz2la2pz232u5m7347q7gplu5pw4vebbxteuiqw6hh3u
fingerprint_ignore_patterns: []
entry_point: prediction_request_rag_cohere.py
callable: run
params:
default_model: cohere/command-r-plus
dependencies:
google-api-python-client:
version: ==2.95.0
Expand Down
35 changes: 16 additions & 19 deletions packages/napthaai/customs/prediction_request_rag_cohere/prediction_request_rag_cohere.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -192,8 +192,6 @@ def embeddings(self, model, input):
"prediction-request-rag-cohere",
]
ALLOWED_MODELS = list(LLM_SETTINGS.keys())
DEFAULT_MODEL = "cohere/command-r-plus"
TOOL_TO_ENGINE = {tool: DEFAULT_MODEL for tool in ALLOWED_TOOLS}
DEFAULT_NUM_URLS = defaultdict(lambda: 3)
DEFAULT_NUM_QUERIES = defaultdict(lambda: 3)
NUM_URLS_PER_QUERY = 5
Expand Down Expand Up @@ -274,11 +272,11 @@ def count_tokens(text: str, model: str) -> int:

def multi_queries(
prompt: str,
engine: str,
model: str,
num_queries: int,
counter_callback: Optional[Callable[[int, int, str], None]] = None,
temperature: Optional[float] = LLM_SETTINGS[DEFAULT_MODEL]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS[DEFAULT_MODEL]["default_max_tokens"],
temperature: Optional[float] = LLM_SETTINGS["cohere/command-r-plus"]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS["cohere/command-r-plus"]["default_max_tokens"],
) -> List[str]:
"""Generate multiple queries for fetching information from the web."""
url_query_prompt = URL_QUERY_PROMPT.format(
Expand All @@ -291,7 +289,7 @@ def multi_queries(
]

response = client.completions(
model=engine,
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
Expand All @@ -300,7 +298,7 @@ def multi_queries(
counter_callback(
input_tokens=response.usage.prompt_tokens,
output_tokens=response.usage.completion_tokens,
model=engine,
model=model,
token_counter=count_tokens,
)
queries = parser_query_response(response.content, num_queries=num_queries)
Expand Down Expand Up @@ -514,15 +512,15 @@ def recursive_character_text_splitter(text, max_tokens, overlap):

def fetch_additional_information(
prompt: str,
engine: str,
model: str,
google_api_key: Optional[str],
google_engine_id: Optional[str],
counter_callback: Optional[Callable[[int, int, str], None]] = None,
source_links: Optional[List[str]] = None,
num_urls: Optional[int] = DEFAULT_NUM_URLS,
num_queries: Optional[int] = DEFAULT_NUM_QUERIES,
temperature: Optional[float] = LLM_SETTINGS[DEFAULT_MODEL]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS[DEFAULT_MODEL]["default_max_tokens"],
temperature: Optional[float] = LLM_SETTINGS["cohere/command-r-plus"]["temperature"],
max_tokens: Optional[int] = LLM_SETTINGS["cohere/command-r-plus"]["default_max_tokens"],
) -> Tuple[str, Callable[[int, int, str], None]]:
"""Fetch additional information to help answer the user prompt."""

Expand All @@ -531,7 +529,7 @@ def fetch_additional_information(
try:
queries, counter_callback = multi_queries(
prompt=prompt,
engine=engine,
model=model,
num_queries=num_queries,
counter_callback=counter_callback,
temperature=temperature,
Expand Down Expand Up @@ -648,14 +646,13 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:
kwargs["api_keys"], kwargs["llm_provider"], embedding_provider="openai"
):
tool = kwargs["tool"]
model = kwargs.get("model", TOOL_TO_ENGINE[tool])
model = kwargs.get("model")
prompt = extract_question(kwargs["prompt"])
engine = kwargs.get("model", TOOL_TO_ENGINE[tool])
print(f"ENGINE: {engine}")
print(f"MODEL: {model}")
max_tokens = kwargs.get(
"max_tokens", LLM_SETTINGS[engine]["default_max_tokens"]
"max_tokens", LLM_SETTINGS[model]["default_max_tokens"]
)
temperature = kwargs.get("temperature", LLM_SETTINGS[engine]["temperature"])
temperature = kwargs.get("temperature", LLM_SETTINGS[model]["temperature"])
num_urls = kwargs.get("num_urls", DEFAULT_NUM_URLS[tool])
num_queries = kwargs.get("num_queries", DEFAULT_NUM_QUERIES[tool])
counter_callback = kwargs.get("counter_callback", None)
Expand All @@ -673,7 +670,7 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:

additional_information, counter_callback = fetch_additional_information(
prompt=prompt,
engine=engine,
model=model,
google_api_key=google_api_key,
google_engine_id=google_engine_id,
counter_callback=counter_callback,
Expand All @@ -697,7 +694,7 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:
]

response = client.completions(
model=engine,
model=model,
messages=messages,
temperature=temperature,
max_tokens=max_tokens,
Expand All @@ -707,7 +704,7 @@ def run(**kwargs) -> Tuple[Optional[str], Any, Optional[Dict[str, Any]], Any]:
counter_callback(
input_tokens=response.usage.prompt_tokens,
output_tokens=response.usage.completion_tokens,
model=engine,
model=model,
token_counter=count_tokens,
)

Expand Down
4 changes: 3 additions & 1 deletion packages/napthaai/customs/prediction_request_reasoning/component.yaml
View file
Original file line number Diff line number Diff line change
Expand Up @@ -7,10 +7,12 @@ license: Apache-2.0
aea_version: '>=1.0.0, <2.0.0'
fingerprint:
__init__.py: bafybeib36ew6vbztldut5xayk5553rylrq7yv4cpqyhwc5ktvd4cx67vwu
prediction_request_reasoning.py: bafybeibyncgeeyrlcqhdbsdzzama7aah44jzedqo3zcplvuc45goykwjli
prediction_request_reasoning.py: bafybeidiabgnlc453spgrdn7rhhl2xc3aa6zqeukkw2bthndbugtjf6bya
fingerprint_ignore_patterns: []
entry_point: prediction_request_reasoning.py
callable: run
params:
default_model: claude-3-sonnet-20240229
dependencies:
google-api-python-client:
version: ==2.95.0
Expand Down
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