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LiteLLM compatible #10

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Merged
changbenjamin merged 1 commit into from
Nov 24, 2025
+1,736 −1,558
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LiteLLM compatible #10

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4 changes: 2 additions & 2 deletions robin/analyses.py
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Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@ async def data_analysis(

# Step 1: Gating, MFI and statistical analysis
analysis_step = Step(
name="job-futurehouse-data-analysis-crow-high",
name=configuration.agent_settings.data_analysis_agent,
prompt_template=analysis_prompt,
cot_prompt=False,
input_files={data_path: "flow_250508/"}, # change this to your input folder
Expand All @@ -65,7 +65,7 @@ async def data_analysis(

# Step 2: Consensus Analysis
consensus_step = Step(
name="job-futurehouse-data-analysis-crow-high",
name=configuration.agent_settings.data_analysis_agent,
prompt_template=consensus_prompt,
cot_prompt=False,
input_files={
Expand Down
15 changes: 7 additions & 8 deletions robin/assays.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ async def generate_assay_queries(
A dictionary of queries for the literature search, where keys and values
are the query strings.
"""
logger.info("\n\nStep 1: Formulating relevant queries for literature search...")
logger.info("Step 1: Formulating relevant queries for literature search...")

assay_literature_system_message = (
configuration.prompts.assay_literature_system_message.format(
Expand Down Expand Up @@ -87,7 +87,7 @@ async def experimental_assay_lit_review(
Returns:
A string containing the summarized literature review.
"""
logger.info("\n\nStep 2: Conducting literature search with Edison platform...")
logger.info("Step 2: Conducting literature search with Edison platform...")

assay_lit_review = await call_platform(
queries=experimental_assay_queries_dict,
Expand Down Expand Up @@ -122,7 +122,7 @@ async def propose_experimental_assay(
Returns:
A list of formatted strings, where each string represents a proposed assay.
"""
logger.info("\n\nStep 3: Generating ideas for relevant experimental assays...")
logger.info("Step 3: Generating ideas for relevant experimental assays...")

assay_proposal_system_message = (
configuration.prompts.assay_proposal_system_message.format(
Expand Down Expand Up @@ -165,7 +165,7 @@ async def propose_experimental_assay(

await f.write(f"Assay Candidate {i + 1}:\n")
await f.write(f"{strategy}\n")
await f.write(f"{reasoning}\n\n")
await f.write(f"{reasoning}")

logger.info(f"Successfully exported to {assay_list_export_file}")

Expand All @@ -188,7 +188,7 @@ async def experimental_assay_detailed_reports(
Returns:
A dictionary containing the raw results from the platform call.
"""
logger.info("\n\nStep 4: Detailed investigation and evaluation for each assay...")
logger.info("Step 4: Detailed investigation and evaluation for each assay...")

def create_assay_hypothesis_queries(assay_idea_list: list[str]) -> dict[str, str]:
assay_hypothesis_system_prompt = (
Expand Down Expand Up @@ -247,7 +247,7 @@ async def select_top_experimental_assay(
Returns:
The name (hypothesis) of the top-ranked experimental assay.
"""
logger.info("\n\nStep 5: Selecting the top experimental assay...")
logger.info("Step 5: Selecting the top experimental assay...")

assay_hypothesis_df = pd.DataFrame(assay_hypotheses["results"])
assay_hypothesis_df["index"] = assay_hypothesis_df.index
Expand All @@ -271,7 +271,7 @@ async def select_top_experimental_assay(

await run_comparisons(
pairs_list=assay_pairs_list,
client=configuration.llm_client,
client=configuration.llm_judge,
system_prompt=assay_ranking_system_prompt,
ranking_prompt_format=assay_ranking_prompt_format,
assay_hypothesis_df=assay_hypothesis_df,
Expand Down Expand Up @@ -353,7 +353,6 @@ async def experimental_assay(configuration: RobinConfiguration) -> str:
The synthesized candidate generation goal, or None if the process fails.
"""
logger.info("Starting selection of a relevant experimental assay.")
logger.info("————————————————————————————————————————————————————")

# Step 1: Generate queries for Crow
experimental_assay_queries_dict = await generate_assay_queries(configuration)
Expand Down
33 changes: 13 additions & 20 deletions robin/candidates.py
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ async def generate_candidate_queries(
Returns:
A dictionary of queries for the literature search.
"""
logger.info("\n\nStep 1: Formulating relevant queries for literature search...")
logger.info("Step 1: Formulating relevant queries for literature search...")

candidate_query_generation_system_message = (
configuration.prompts.candidate_query_generation_system_message.format(
Expand Down Expand Up @@ -112,7 +112,7 @@ async def candidate_lit_review(
Returns:
A string containing the summarized literature review.
"""
logger.info("\n\nStep 2: Conducting literature search with Edison platform...")
logger.info("Step 2: Conducting literature search with Edison platform...")

run_folder_name = str(configuration.run_folder_name)

Expand Down Expand Up @@ -157,7 +157,7 @@ async def propose_therapeutic_candidates( # noqa: PLR0912
A list of formatted strings, each representing a proposed candidate.
"""
logger.info(
f"\n\nStep 3: Generating {configuration.num_candidates} ideas for therapeutic"
f"Step 3: Generating {configuration.num_candidates} ideas for therapeutic"
" candidates..."
)

Expand Down Expand Up @@ -199,19 +199,12 @@ async def propose_therapeutic_candidates( # noqa: PLR0912
Message(role="user", content=candidate_generation_user_message),
]

if "claude" in configuration.llm_name:
candidate_generation_result = await configuration.llm_client.call_single(
messages,
timeout=600,
temperature=1,
max_tokens=32000,
reasoning_effort="high",
)
else:
candidate_generation_result = await configuration.llm_client.call_single(
messages,
temperature=1,
)
candidate_generation_result = await configuration.llm_client.call_single(
messages,
timeout=600,
temperature=1,
reasoning_effort="high",
)

llm_raw_output = cast(str, candidate_generation_result.text)
candidate_ideas_json = []
Expand Down Expand Up @@ -301,7 +294,7 @@ async def propose_therapeutic_candidates( # noqa: PLR0912
await f.write(f"Therapeutic Candidate {i + 1}:\n")
await f.write(f"{parts[0]}\n") # Candidate
await f.write(f"{parts[1]}\n") # Hypothesis
await f.write(f"{parts[2]}\n\n") # Reasoning
await f.write(f"{parts[2]}") # Reasoning

logger.info(f"Successfully exported to {export_file}")
return candidate_idea_list
Expand All @@ -320,7 +313,7 @@ async def candidate_detailed_reports(
candidate_idea_list: The list of proposed candidate strings.
experimental_insights: Optional insights from experimental data analysis.
"""
logger.info("\n\nStep 4: Detailed investigation and evaluation for candidates...")
logger.info("Step 4: Detailed investigation and evaluation for candidates...")
run_folder_name = str(configuration.run_folder_name)

def create_therapeutic_candidate_queries(
Expand Down Expand Up @@ -380,7 +373,7 @@ async def rank_therapeutic_candidates( # noqa: PLR0912
configuration: The RobinConfiguration object for the run.
experimental_insights: Optional insights from experimental data analysis.
"""
logger.info("\n\nStep 5: Ranking the strength of the therapeutic candidates...")
logger.info("Step 5: Ranking the strength of the therapeutic candidates...")

run_folder_name = str(configuration.run_folder_name)
hypotheses_folder = (
Expand Down Expand Up @@ -412,7 +405,7 @@ async def rank_therapeutic_candidates( # noqa: PLR0912

await run_comparisons(
pairs_list=pairs_list,
client=configuration.llm_client,
client=configuration.llm_judge,
system_prompt=system_prompt,
ranking_prompt_format=prompt_format,
assay_hypothesis_df=candidate_information_df,
Expand Down
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