Merge pull request #32 from valory-xyz/chore/modify-prompt

Update prompt

.gitignore

@@ -36,4 +36,8 @@ agent/
 
 ethereum_private_key.txt
 keys.json
-market_maker/
+market_maker/
+fetched_service/
+keys_json/
+market_approval_server/market_approval_server.log
+market_approval_server/server_config.json

market_identification_prompt.txt

@@ -1,18 +1,17 @@
-Based on the following news snippets under "INPUT", formulate 5 prediction market questions with clear, objective
-outcomes that can be verified on specific dates and leave no room for interpretation or subjectivity.
-Avoid incorporating questions that could potentially encourage unethical behavior or violence. Feel
-free to use the same event with different dates as necessary. Every question should be resolvable in a 
-random day between 1st and the 31st of August 2023, with a requirement that all questions
-be resolvable in a different day of the month.
+Based on the following news snippets under INPUT, formulate 5 prediction market questions with clear, objective
+outcomes that can be verified on a specific date and leave no room for interpretation or subjectivity.
+Avoid incorporating questions that could potentially encourage unethical behavior or violence.
+Every question must be related to an event happening on or by {event_day}. The answer to the question
+must be unknown until that day, but it must be known after that day.
 Your questions should follow a structure similar to this:
-"Will VERIFIABLE_BINARY_OUTCOME_OR_PREDICTION occur on SPECIFIC_DAY_OF_AUGUST_2023".
+"Will VERIFIABLE_BINARY_OUTCOME_OR_PREDICTION occur on {event_day}".
 Your output must follow the output format detailed under "OUTPUT FORMAT".
 
 INPUT
 {input_news}
 
 OUTPUT_FORMAT
-* Your output response must be only a single JSON array to be parsed by Python's "json.loads()".
+* Your output response must be only a single JSON array to be parsed by Python "json.loads()".
 * All of the date strings should be represented in YYYY-MM-DD format.
 * Each entry of the JSON array must be a JSON object containing the fields:
     - question: The binary question to open a prediction market.

packages/packages.json

@@ -3,10 +3,10 @@
         "contract/valory/conditional_tokens/0.1.0": "bafybeig5vtn7bzpegfrzehdgeezqcnox3xlb5i54ehnqndazhcfh3bkdcq",
         "contract/valory/fpmm_deterministic_factory/0.1.0": "bafybeig4ztnqgyaespzlcmcom56nvmi4c4paddsxsjsh5q7olnylu3z7ou",
         "contract/valory/realtio/0.1.0": "bafybeihoj7w5dqdyo6ds2rdmi326cvl5wuc7xp6yms7lwks35m4nqypk4q",
-        "skill/valory/market_creation_manager_abci/0.1.0": "bafybeichgshhxeigjb46pyfbeokdkiwrc4jongf225bcwopkw7ka2azuda",
-        "skill/valory/market_maker_abci/0.1.0": "bafybeig4hmaqu3hka6ynblqvms6jpq4qbn6ofc2rdocwbxpeobyhyccwe4",
-        "agent/valory/market_maker/0.1.0": "bafybeicbjdxea7y5dndpsekx5rtovdzyjf4vsex5f5gy3urcgjx2lnmiou",
-        "service/valory/market_maker/0.1.0": "bafybeiawlstpxj2fjkeu2izza7xniynmfhmfqbow4vsnol5wbbuznwuof4",
+        "skill/valory/market_creation_manager_abci/0.1.0": "bafybeibaovti3jrf5syhtffkgnj34agk4decoiybeufh4yb6qpvvtqycve",
+        "skill/valory/market_maker_abci/0.1.0": "bafybeibidkqzpqpx4cd2kil4f53ag32v4xyotxz5fn55iorgl7ylwdhcga",
+        "agent/valory/market_maker/0.1.0": "bafybeib4yddbk7kutldwubejzaqbscut7liwkwoncgepydaqbr3w7ztfaa",
+        "service/valory/market_maker/0.1.0": "bafybeigfi7bvtbqvvruherltjunkdlhsyxl3nlehno5nrbhvfgp4hizhhe",
         "contract/valory/wxdai/0.1.0": "bafybeie3c5enerf54jt75xc62mbzck4kjqxpjx2mzo6v4rrz4dmcy4xdgy",
         "skill/valory/market_validation_abci/0.1.0": "bafybeifyfwynotmzg6wypbzbwsfnrplhjhumfx32dm2j3ddasp7ygrfoqa"
     },

packages/valory/agents/market_maker/aea-config.yaml

@@ -36,9 +36,9 @@ protocols:
 skills:
 - valory/abstract_abci:0.1.0:bafybeiamr3cwetayz6lr72buhq6iviabtboj4hhpq47tlumimxolvvqjcy
 - valory/abstract_round_abci:0.1.0:bafybeiaseziuvbzh3trjggl5hx2tv3fduqrpiwiyksudaf6nvuxmwrg74i
-- valory/market_maker_abci:0.1.0:bafybeig4hmaqu3hka6ynblqvms6jpq4qbn6ofc2rdocwbxpeobyhyccwe4
+- valory/market_maker_abci:0.1.0:bafybeibidkqzpqpx4cd2kil4f53ag32v4xyotxz5fn55iorgl7ylwdhcga
 - valory/registration_abci:0.1.0:bafybeibafy7qmcvvzaykimy3mbqdwtcuajmbghqilaa7zwkh6wla33cfce
-- valory/market_creation_manager_abci:0.1.0:bafybeichgshhxeigjb46pyfbeokdkiwrc4jongf225bcwopkw7ka2azuda
+- valory/market_creation_manager_abci:0.1.0:bafybeibaovti3jrf5syhtffkgnj34agk4decoiybeufh4yb6qpvvtqycve
 - valory/market_validation_abci:0.1.0:bafybeifyfwynotmzg6wypbzbwsfnrplhjhumfx32dm2j3ddasp7ygrfoqa
 - valory/reset_pause_abci:0.1.0:bafybeialcwck7fahrr23jckv5qjwg3cdq4ai2ihyjsofnbj44jzyl4cjmm
 - valory/termination_abci:0.1.0:bafybeifqsogqiar4yook5bu3j6z66dbdcizey7dr3e5oxeocdjijvfbaja
@@ -128,38 +128,24 @@ models:
       log_dir: ${str:/logs}
   params:
     args:
-      market_identification_prompt: ${str:You are an LLM inside a multi-agent system.
-        Your task is to propose a collection of prediction market\nquestions based
-        on your input. Your input is under the label \"INPUT\". You must follow the
-        instructions\nunder \"INSTRUCTIONS\". You must provide your response in the
-        format specified under \"OUTPUT_FORMAT\".\n\nINSTRUCTIONS\n* Read the input
-        under the label \"INPUT\" delimited by three backticks.\n* The \"INPUT\" specifies
-        a list of recent news headlines, their date, and short descriptions.\n* Based
-        on the \"INPUT\" and your training data, you must provide a list of binary
-        questions, valid\n    answers and resolution dates to create prediction markets.\n*
-        Each market must satisfy the following conditions;\n    - The outcome of the
-        market is unknown at the present date.\n    - The outcome of the market must
-        be known by its resolution date.\n    - The outcome of the market must be
-        related to a deterministic, measurable or verifiable fact.\n    - Questions
-        whose answer is known at the present date are invalid.\n    - Questions whose
-        answer is subjective or opinionated are invalid.\n    - Questions with relative
-        dates are invalid.\n    - Questions about moral values, subjective opinions,
-        and not facts are invalid.\n    - Questions in which none of the answers are
-        valid will resolve as invalid.\n    - Questions with multiple valid answers
-        are invalid.\n    - Questions must not incentivize committing an immoral violent
-        action.\n    - The dates in the question need to be in YYYY-MM-DD format.\n*
-        The created markets must be different and not overlap semantically.\n* You
-        must provide your response in the format specified under \"OUTPUT_FORMAT\".\n*
-        Do not include any other contents in your response.\n\nINPUT\n{input_news}\n\nOUTPUT_FORMAT\n*
-        Your output response must be only a single JSON array to be parsed by Python\'s
-        \"json.loads()\".\n* The JSON array must be of length 5.\n* All of the date
-        strings should be represented in YYYY-MM-DD format.\n* Each entry of the JSON
-        array must be a JSON object containing the fields;\n    - question; The binary
-        question to open a prediction market.\n    - answers; The possible answers
-        to the question.\n    - resolution_date; The resolution date for the outcome
-        of the market to be verified.\n    - topic; One word description of the topic
-        of the news and it should be one of; {topics}.\n* Output only the JSON object.
-        Do not include any other contents in your response.}
+      market_identification_prompt: ${str:Based on the following news snippets under
+        INPUT, formulate 5 prediction market questions with clear, objective\noutcomes
+        that can be verified on a specific date and leave no room for interpretation
+        or subjectivity.\nAvoid incorporating questions that could potentially encourage
+        unethical behavior or violence.\nEvery question must be related to an event
+        happening on or by {event_day}. The answer to the question\nmust be unknown
+        until that day, but it must be known after that day.\nYour questions should
+        follow a structure similar to this;\n\"Will VERIFIABLE_BINARY_OUTCOME_OR_PREDICTION
+        occur on {event_day}\".\nYour output must follow the output format detailed
+        under \"OUTPUT FORMAT\".\n\nINPUT\n{input_news}\n\nOUTPUT_FORMAT\n* Your output
+        response must be only a single JSON array to be parsed by Python \"json.loads()\".\n*
+        All of the date strings should be represented in YYYY-MM-DD format.\n* Each
+        entry of the JSON array must be a JSON object containing the fields;\n - question;
+        The binary question to open a prediction market.\n - answers; The possible
+        answers to the question.\n - resolution_date; The resolution date for the
+        outcome of the market to be verified.\n - topic; One word description of the
+        topic of the news and it should be one of; {topics}.\n* Output only the JSON
+        object. Do not include any other contents in your response.}
       num_markets: ${int:1}
       market_approval_server_url: ${str:http://127.0.0.1:5000}
       market_approval_server_api_key: ${str:api_key}

packages/valory/services/market_maker/service.yaml

@@ -7,7 +7,7 @@ license: Apache-2.0
 fingerprint:
   README.md: bafybeibwz3af6326msp4h3kqehijvmyhaytvyfbo3o2npc2w4b6zrg6pfq
 fingerprint_ignore_patterns: []
-agent: valory/market_maker:0.1.0:bafybeicbjdxea7y5dndpsekx5rtovdzyjf4vsex5f5gy3urcgjx2lnmiou
+agent: valory/market_maker:0.1.0:bafybeib4yddbk7kutldwubejzaqbscut7liwkwoncgepydaqbr3w7ztfaa
 number_of_agents: 1
 deployment:
   agent:
@@ -23,38 +23,24 @@ models:
       log_dir: /logs
   params:
     args:
-      market_identification_prompt: ${MARKET_IDENTIFICATION_PROMPT:str:You are an
-        LLM inside a multi-agent system. Your task is to propose a collection of prediction
-        market\nquestions based on your input. Your input is under the label \"INPUT\".
-        You must follow the instructions\nunder \"INSTRUCTIONS\". You must provide
-        your response in the format specified under \"OUTPUT_FORMAT\".\n\nINSTRUCTIONS\n*
-        Read the input under the label \"INPUT\" delimited by three backticks.\n*
-        The \"INPUT\" specifies a list of recent news headlines, their date, and short
-        descriptions.\n* Based on the \"INPUT\" and your training data, you must provide
-        a list of binary questions, valid\n    answers and resolution dates to create
-        prediction markets.\n* Each market must satisfy the following conditions;\n    -
-        The outcome of the market is unknown at the present date.\n    - The outcome
-        of the market must be known by its resolution date.\n    - The outcome of
-        the market must be related to a deterministic, measurable or verifiable fact.\n    -
-        Questions whose answer is known at the present date are invalid.\n    - Questions
-        whose answer is subjective or opinionated are invalid.\n    - Questions with
-        relative dates are invalid.\n    - Questions about moral values, subjective
-        opinions, and not facts are invalid.\n    - Questions in which none of the
-        answers are valid will resolve as invalid.\n    - Questions with multiple
-        valid answers are invalid.\n    - Questions must not incentivize committing
-        an immoral violent action.\n    - The dates in the question need to be in
-        YYYY-MM-DD format.\n* The created markets must be different and not overlap
-        semantically.\n* You must provide your response in the format specified under
-        \"OUTPUT_FORMAT\".\n* Do not include any other contents in your response.\n\nINPUT\n{input_news}\n\nOUTPUT_FORMAT\n*
-        Your output response must be only a single JSON array to be parsed by Python\'s
-        \"json.loads()\".\n* The JSON array must be of length 5.\n* All of the date
-        strings should be represented in YYYY-MM-DD format.\n* Each entry of the JSON
-        array must be a JSON object containing the fields;\n    - question; The binary
-        question to open a prediction market.\n    - answers; The possible answers
-        to the question.\n    - resolution_date; The resolution date for the outcome
-        of the market to be verified.\n    - topic; One word description of the topic
-        of the news and it should be one of; {topics}.\n* Output only the JSON object.
-        Do not include any other contents in your response.}
+      market_identification_prompt: ${MARKET_IDENTIFICATION_PROMPT:str:Based on the
+        following news snippets under INPUT, formulate 5 prediction market questions
+        with clear, objective\noutcomes that can be verified on a specific date and
+        leave no room for interpretation or subjectivity.\nAvoid incorporating questions
+        that could potentially encourage unethical behavior or violence.\nEvery question
+        must be related to an event happening on or by {event_day}. The answer to
+        the question\nmust be unknown until that day, but it must be known after that
+        day.\nYour questions should follow a structure similar to this;\n\"Will VERIFIABLE_BINARY_OUTCOME_OR_PREDICTION
+        occur on {event_day}\".\nYour output must follow the output format detailed
+        under \"OUTPUT FORMAT\".\n\nINPUT\n{input_news}\n\nOUTPUT_FORMAT\n* Your output
+        response must be only a single JSON array to be parsed by Python \"json.loads()\".\n*
+        All of the date strings should be represented in YYYY-MM-DD format.\n* Each
+        entry of the JSON array must be a JSON object containing the fields;\n - question;
+        The binary question to open a prediction market.\n - answers; The possible
+        answers to the question.\n - resolution_date; The resolution date for the
+        outcome of the market to be verified.\n - topic; One word description of the
+        topic of the news and it should be one of; {topics}.\n* Output only the JSON
+        object. Do not include any other contents in your response.}
       num_markets: ${NUM_MARKETS:int:1}
       market_approval_server_url: ${MARKET_APPROVAL_SERVER_URL:str:http://127.0.0.1:5000}
       market_approval_server_api_key: ${MARKET_APPROVAL_SERVER_API_KEY:str:api_key}

packages/valory/skills/market_creation_manager_abci/behaviours.py

@@ -269,9 +269,14 @@ def _get_llm_response(self) -> Generator[None, None, Optional[dict]]:
             date = article["publishedAt"]
             input_news += f"- ({date}) {title}\n  {content}\n\n"
 
+        event_day = self._get_event_day()
         topics = ", ".join(self.params.topics)
         prompt_template = self.params.market_identification_prompt
-        prompt_values = {"input_news": input_news, "topics": topics}
+        prompt_values = {
+            "input_news": input_news,
+            "topics": topics,
+            "event_day": event_day,
+        }
 
         self.context.logger.info(
             f"Sending LLM request...\nprompt_template={prompt_template}\nprompt_values={prompt_values}"
@@ -333,6 +338,27 @@ def _get_llm_response(self) -> Generator[None, None, Optional[dict]]:
             return None
         return valid_responses[0]
 
+    def _get_event_day(self) -> str:
+        # Get the current date
+        n = self.synchronized_data.markets_created
+        today = datetime.datetime.now().date()
+
+        # Set the target year and month
+        target_year = 2023
+        target_month = 8
+        minimum_days_until_event = self.params.minimum_market_time + 1
+
+        # Calculate the start_date in August (at least today + 2 days)
+        start_date = max(
+            datetime.date(target_year, target_month, 1),
+            today + datetime.timedelta(days=minimum_days_until_event),
+        )
+        end_date = datetime.date(target_year, target_month, 31)
+        days_difference = abs((end_date - start_date).days)
+        event_day = start_date + datetime.timedelta(n % (days_difference + 1))
+
+        return event_day.strftime("%-d %B %Y")
+
     def _do_llm_request(
         self,
         llm_message: LlmMessage,

packages/valory/skills/market_creation_manager_abci/skill.yaml

@@ -8,7 +8,7 @@ aea_version: '>=1.0.0, <2.0.0'
 fingerprint:
   .gitignore: bafybeihdfdezgtr3s2lzq5y3oaitfrdy4u4pehionju2bdez35wcjgqx6y
   __init__.py: bafybeibkyjt4covc4yhd22aw7kav45zozk3exdv344emt3lilln64soaxm
-  behaviours.py: bafybeifs3qwjzxaj6aofcydsp4gdhlejkp2adji6tqof7vymfvumqh3rze
+  behaviours.py: bafybeicvgjl3efqzc3yb5przgeui3qetsv3htjjeessr5gz37b66xy4voy
   dialogues.py: bafybeicmaufkl7vdomnfciv7lw4536ssld7x4uemdapuhsyvfpd4ncibza
   fsm_specification.yaml: bafybeiay4aepnfdkcsriajxqige65bsszrujin57riubflm7dyw2keapoi
   handlers.py: bafybeietxjfli2i57kb7heoy772rcq2znusl36gg7jjj5g3pddw7egny3q

packages/valory/skills/market_maker_abci/skill.yaml

@@ -23,7 +23,7 @@ skills:
 - valory/abstract_round_abci:0.1.0:bafybeiaseziuvbzh3trjggl5hx2tv3fduqrpiwiyksudaf6nvuxmwrg74i
 - valory/registration_abci:0.1.0:bafybeibafy7qmcvvzaykimy3mbqdwtcuajmbghqilaa7zwkh6wla33cfce
 - valory/reset_pause_abci:0.1.0:bafybeialcwck7fahrr23jckv5qjwg3cdq4ai2ihyjsofnbj44jzyl4cjmm
-- valory/market_creation_manager_abci:0.1.0:bafybeichgshhxeigjb46pyfbeokdkiwrc4jongf225bcwopkw7ka2azuda
+- valory/market_creation_manager_abci:0.1.0:bafybeibaovti3jrf5syhtffkgnj34agk4decoiybeufh4yb6qpvvtqycve
 - valory/market_validation_abci:0.1.0:bafybeifyfwynotmzg6wypbzbwsfnrplhjhumfx32dm2j3ddasp7ygrfoqa
 - valory/termination_abci:0.1.0:bafybeifqsogqiar4yook5bu3j6z66dbdcizey7dr3e5oxeocdjijvfbaja
 - valory/transaction_settlement_abci:0.1.0:bafybeiacwr7p4nhhufoey7uz2jqkegrlykdrmc7mm3rzkvh2mslu66gyle

run_service.sh

@@ -2,6 +2,7 @@
 
 # Load env vars
 export $(grep -v '^#' .env | xargs)
+
 export MARKET_IDENTIFICATION_PROMPT=$(sed -e ':a' -e 'N' -e '$!ba' \
   -e 's/"/\\"/g' \
   -e "s/'/\\\'/g" \
@@ -14,7 +15,7 @@ make clean
 autonomy packages lock
 autonomy push-all
 
-autonomy fetch --local --service valory/market_maker && cd market_maker
+autonomy fetch --local --service valory/market_maker --alias fetched_service && cd fetched_service
 
 # Build the image
 autonomy build-image