Fix mypy

evo_researcher/autonolas/research.py

@@ -1076,11 +1076,11 @@ def fetch_additional_information(
     research_chain = (
         research_prompt |
         ChatOpenAI(
-            model_name=engine,
+            model=engine,
             temperature=temperature,
             max_tokens=max_compl_tokens,
             n=1, 
-            request_timeout=120,
+            timeout=120,
         ) |
         StrOutputParser()
     )
@@ -1175,7 +1175,7 @@ def make_prediction(
 
     prediction_prompt = ChatPromptTemplate.from_template(template=PREDICTION_PROMPT)
 
-    llm = ChatOpenAI(model_name=engine, temperature=temperature)
+    llm = ChatOpenAI(model=engine, temperature=temperature)
     formatted_messages = prediction_prompt.format_messages(user_prompt=prompt, additional_information=additional_information, timestamp=formatted_time_utc)
     generation = llm.generate([formatted_messages], logprobs=True, top_logprobs=5)
 

evo_researcher/benchmark/utils.py

@@ -18,8 +18,8 @@ class Market(BaseModel):
     p_yes: float
     volume: float
     is_resolved: bool
-    resolution: str | None
-    outcomePrices: list[float] | None
+    resolution: str | None = None
+    outcomePrices: list[float] | None = None
 
     @validator("outcomePrices", pre=True)
     def _validate_outcome_prices(cls, value: list[float] | None) -> list[float] | None:
@@ -55,8 +55,8 @@ def binary_answer(self) -> bool:
 
 
 class Prediction(BaseModel):
-    evaluation: t.Optional[EvalautedQuestion]
-    outcome_prediction: t.Optional[OutcomePrediction]
+    evaluation: t.Optional[EvalautedQuestion] = None
+    outcome_prediction: t.Optional[OutcomePrediction] = None
 
     time: t.Optional[float] = None
     cost: t.Optional[float] = None

evo_researcher/functions/evaluate_question.py

@@ -38,7 +38,7 @@ def evaluate_question(
     """
     Evaluate if the question is actually answerable.
     """
-    llm = ChatOpenAI(model_name=engine, temperature=0.0)
+    llm = ChatOpenAI(model=engine, temperature=0.0)
 
     prompt = ChatPromptTemplate.from_template(template=prompt_template)
     messages = prompt.format_messages(question=question)

evo_researcher/functions/generate_subqueries.py

@@ -15,7 +15,7 @@ def generate_subqueries(query: str, limit: int) -> list[str]:
 
     subquery_generation_chain = (
         subquery_generation_prompt |
-        ChatOpenAI(model_name="gpt-4-1106-preview") |
+        ChatOpenAI(model="gpt-4-1106-preview") |
         CommaSeparatedListOutputParser()
     )
 

evo_researcher/functions/grade_info.py

@@ -70,7 +70,7 @@ def grade_info(question: str, information: str) -> str:
     planning_prompt = ChatPromptTemplate.from_template(template=grading_planning_prompt_template)
     formatting_prompt = ChatPromptTemplate.from_template(template=grading_format_prompt_template)
 
-    llm = ChatOpenAI(model_name="gpt-4-1106-preview", temperature=0)
+    llm = ChatOpenAI(model="gpt-4-1106-preview", temperature=0)
 
     planning_chain = (
         planning_prompt |

evo_researcher/functions/prepare_report.py

@@ -22,7 +22,7 @@ def prepare_summary(goal: str, content: str, model: str, trim_content_to_tokens:
 
     research_evaluation_chain = (
         evaluation_prompt |
-        ChatOpenAI(model_name=model) |
+        ChatOpenAI(model=model) |
         StrOutputParser()
     )
 
@@ -60,7 +60,7 @@ def prepare_report(goal: str, scraped: list[str], model: str) -> str:
 
     research_evaluation_chain = (
         evaluation_prompt |
-        ChatOpenAI(model_name=model) |
+        ChatOpenAI(model=model) |
         StrOutputParser()
     )
 

evo_researcher/functions/rephrase_question.py

@@ -35,7 +35,7 @@ def rephrase_question(
     open_ended_question: What is the color of the sky?
     """
     tokenizer = tiktoken.encoding_for_model(engine)
-    llm = ChatOpenAI(model_name=engine, temperature=0.0)
+    llm = ChatOpenAI(model=engine, temperature=0.0)
 
     prompt = ChatPromptTemplate.from_template(template=QUESTION_REPHRASE_PROMPT)
     messages = prompt.format_messages(question=question)

evo_researcher/functions/rerank_results.py

@@ -19,7 +19,7 @@ def rerank_results(results: list[str], goal: str) -> list[str]:
 
     rerank_results_chain = (
         rerank_results_prompt |
-        ChatOpenAI(model_name="gpt-4-1106-preview") |
+        ChatOpenAI(model="gpt-4-1106-preview") |
         CommaSeparatedListOutputParser()
     )
 

evo_researcher/functions/rerank_subqueries.py

@@ -17,7 +17,7 @@ def rerank_subqueries(queries: list[str], goal: str) -> list[str]:
 
     rerank_results_chain = (
         rerank_results_prompt |
-        ChatOpenAI(model_name="gpt-4-1106-preview") |
+        ChatOpenAI(model="gpt-4-1106-preview") |
         StrOutputParser()
     )
 

evo_researcher/functions/summarize.py

@@ -7,7 +7,7 @@
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 
 def summarize(objective: str, content: str) -> str:
-    llm = ChatOpenAI(temperature = 0, model_name = "gpt-3.5-turbo-16k-0613")
+    llm = ChatOpenAI(temperature = 0, model="gpt-3.5-turbo-16k-0613")
 
     map_template = """
     The following is a set of documents