From dd9d67e7b32d15875bd4b1a8e50d2b637db9f537 Mon Sep 17 00:00:00 2001
From: ascender1729 <pavankumar.dubasi2019@gmail.com>
Date: Fri, 16 May 2025 21:55:55 +0530
Subject: [PATCH 1/5] fix: Update 4o_mini_demo.py to use GPT-4o-mini model
- Replace Ollama local models with OpenAI GPT-4o-mini
- Resolve context spam and extraneous output issues
- Improve output formatting for medical coding diagnosis
- Closes #771
---
examples/4o_mini_demo.py | 249 +++++++++++++++++++++++++++++++++++++++
1 file changed, 249 insertions(+)
create mode 100644 examples/4o_mini_demo.py
diff --git a/examples/4o_mini_demo.py b/examples/4o_mini_demo.py
new file mode 100644
index 00000000..04f54140
--- /dev/null
+++ b/examples/4o_mini_demo.py
@@ -0,0 +1,249 @@
+"""
+- For each diagnosis, pull lab results,
+- egfr
+- for each diagnosis, pull lab ranges,
+- pull ranges for diagnosis
+
+- if the diagnosis is x, then the lab ranges should be a to b
+- train the agents, increase the load of input
+- medical history sent to the agent
+- setup rag for the agents
+- run the first agent -> kidney disease -> don't know the stage -> stage 2 -> lab results -> indicative of stage 3 -> the case got elavated ->
+- how to manage diseases and by looking at correlating lab, docs, diagnoses
+- put docs in rag ->
+- monitoring, evaluation, and treatment
+- can we confirm for every diagnosis -> monitoring, evaluation, and treatment, specialized for these things
+- find diagnosis -> or have diagnosis, -> for each diagnosis are there evidence of those 3 things
+- swarm of those 4 agents, ->
+- fda api for healthcare for commerically available papers
+-
+
+"""
+
+from datetime import datetime
+
+from swarms import Agent, AgentRearrange, create_file_in_folder
+
+
+chief_medical_officer = Agent(
+ agent_name="Chief Medical Officer",
+ system_prompt="""You are the Chief Medical Officer coordinating a team of medical specialists for viral disease diagnosis.
+ Your responsibilities include:
+ - Gathering initial patient symptoms and medical history
+ - Coordinating with specialists to form differential diagnoses
+ - Synthesizing different specialist opinions into a cohesive diagnosis
+ - Ensuring all relevant symptoms and test results are considered
+ - Making final diagnostic recommendations
+ - Suggesting treatment plans based on team input
+ - Identifying when additional specialists need to be consulted
+ - For each diferrential diagnosis provide minimum lab ranges to meet that diagnosis or be indicative of that diagnosis minimum and maximum
+
+ Format all responses with clear sections for:
+ - Initial Assessment (include preliminary ICD-10 codes for symptoms)
+ - Differential Diagnoses (with corresponding ICD-10 codes)
+ - Specialist Consultations Needed
+ - Recommended Next Steps
+
+
+ """,
+ model_name="gpt-4o-mini",
+ max_loops=1,
+)
+
+virologist = Agent(
+ agent_name="Virologist",
+ system_prompt="""You are a specialist in viral diseases. For each case, provide:
+
+ Clinical Analysis:
+ - Detailed viral symptom analysis
+ - Disease progression timeline
+ - Risk factors and complications
+
+ Coding Requirements:
+ - List relevant ICD-10 codes for:
+ * Confirmed viral conditions
+ * Suspected viral conditions
+ * Associated symptoms
+ * Complications
+ - Include both:
+ * Primary diagnostic codes
+ * Secondary condition codes
+
+ Document all findings using proper medical coding standards and include rationale for code selection.""",
+ model_name="gpt-4o-mini",
+ max_loops=1,
+)
+
+internist = Agent(
+ agent_name="Internist",
+ system_prompt="""You are an Internal Medicine specialist responsible for comprehensive evaluation.
+
+ For each case, provide:
+
+ Clinical Assessment:
+ - System-by-system review
+ - Vital signs analysis
+ - Comorbidity evaluation
+
+ Medical Coding:
+ - ICD-10 codes for:
+ * Primary conditions
+ * Secondary diagnoses
+ * Complications
+ * Chronic conditions
+ * Signs and symptoms
+ - Include hierarchical condition category (HCC) codes where applicable
+
+ Document supporting evidence for each code selected.""",
+ model_name="gpt-4o-mini",
+ max_loops=1,
+)
+
+medical_coder = Agent(
+ agent_name="Medical Coder",
+ system_prompt="""You are a certified medical coder responsible for:
+
+ Primary Tasks:
+ 1. Reviewing all clinical documentation
+ 2. Assigning accurate ICD-10 codes
+ 3. Ensuring coding compliance
+ 4. Documenting code justification
+
+ Coding Process:
+ - Review all specialist inputs
+ - Identify primary and secondary diagnoses
+ - Assign appropriate ICD-10 codes
+ - Document supporting evidence
+ - Note any coding queries
+
+ Output Format:
+ 1. Primary Diagnosis Codes
+ - ICD-10 code
+ - Description
+ - Supporting documentation
+ 2. Secondary Diagnosis Codes
+ - Listed in order of clinical significance
+ 3. Symptom Codes
+ 4. Complication Codes
+ 5. Coding Notes""",
+ model_name="gpt-4o-mini",
+ max_loops=1,
+)
+
+synthesizer = Agent(
+ agent_name="Diagnostic Synthesizer",
+ system_prompt="""You are responsible for creating the final diagnostic and coding assessment.
+
+ Synthesis Requirements:
+ 1. Integrate all specialist findings
+ 2. Reconcile any conflicting diagnoses
+ 3. Verify coding accuracy and completeness
+
+ Final Report Sections:
+ 1. Clinical Summary
+ - Primary diagnosis with ICD-10
+ - Secondary diagnoses with ICD-10
+ - Supporting evidence
+ 2. Coding Summary
+ - Complete code list with descriptions
+ - Code hierarchy and relationships
+ - Supporting documentation
+ 3. Recommendations
+ - Additional testing needed
+ - Follow-up care
+ - Documentation improvements needed
+
+ Include confidence levels and evidence quality for all diagnoses and codes.""",
+ model_name="gpt-4o-mini",
+ max_loops=1,
+)
+
+# Create agent list
+agents = [
+ chief_medical_officer,
+ virologist,
+ internist,
+ medical_coder,
+ synthesizer,
+]
+
+# Define diagnostic flow
+flow = f"""{chief_medical_officer.agent_name} -> {virologist.agent_name} -> {internist.agent_name} -> {medical_coder.agent_name} -> {synthesizer.agent_name}"""
+
+# Create the swarm system
+diagnosis_system = AgentRearrange(
+ name="Medical-coding-diagnosis-swarm",
+ description="Comprehensive medical diagnosis and coding system",
+ agents=agents,
+ flow=flow,
+ max_loops=1,
+ output_type="all",
+)
+
+
+def generate_coding_report(diagnosis_output: str) -> str:
+ """
+ Generate a structured medical coding report from the diagnosis output.
+ """
+ timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
+ report = f"""# Medical Diagnosis and Coding Report
+ Generated: {timestamp}
+
+ ## Clinical Summary
+ {diagnosis_output}
+
+ ## Coding Summary
+ ### Primary Diagnosis Codes
+ [Extracted from synthesis]
+
+ ### Secondary Diagnosis Codes
+ [Extracted from synthesis]
+
+ ### Symptom Codes
+ [Extracted from synthesis]
+
+ ### Procedure Codes (if applicable)
+ [Extracted from synthesis]
+
+ ## Documentation and Compliance Notes
+ - Code justification
+ - Supporting documentation references
+ - Any coding queries or clarifications needed
+
+ ## Recommendations
+ - Additional documentation needed
+ - Suggested follow-up
+ - Coding optimization opportunities
+ """
+ return report
+
+
+if __name__ == "__main__":
+ # Example patient case
+ patient_case = """
+ Patient: 45-year-old White Male
+
+ Lab Results:
+ - egfr
+ - 59 ml / min / 1.73
+ - non african-american
+
+ """
+
+ # Add timestamp to the patient case
+ case_info = f"Timestamp: {datetime.now()}\nPatient Information: {patient_case}"
+
+ # Run the diagnostic process
+ diagnosis = diagnosis_system.run(case_info)
+
+ # Generate coding report
+ coding_report = generate_coding_report(diagnosis)
+
+ # Create reports
+ create_file_in_folder(
+ "reports", "medical_diagnosis_report.md", diagnosis
+ )
+ create_file_in_folder(
+ "reports", "medical_coding_report.md", coding_report
+ )
From 6698bd3c8b6ff01b11eadd774950c9bebc63fecb Mon Sep 17 00:00:00 2001
From: ascender1729 <pavankumar.dubasi2019@gmail.com>
Date: Sat, 17 May 2025 01:42:31 +0530
Subject: [PATCH 2/5] fix: Update ollama_demo.py to use LiteLLM format
- Update model configuration to use LiteLLM format (ollama/llama3.2)
- Standardize model handling with 4o_mini_demo.py
- Improve output formatting and consistency
- Fix context spam issues
---
examples/ollama_demo.py | 13 +++++--------
1 file changed, 5 insertions(+), 8 deletions(-)
diff --git a/examples/ollama_demo.py b/examples/ollama_demo.py
index 4d1d41ef..bf369a56 100644
--- a/examples/ollama_demo.py
+++ b/examples/ollama_demo.py
@@ -24,9 +24,6 @@ from datetime import datetime
from swarms import Agent, AgentRearrange, create_file_in_folder
-from swarm_models import OllamaModel
-
-model = OllamaModel(model_name="llama3.2")
chief_medical_officer = Agent(
agent_name="Chief Medical Officer",
@@ -49,7 +46,7 @@ chief_medical_officer = Agent(
""",
- llm=model,
+ model_name="ollama/llama3.2",
max_loops=1,
)
@@ -73,7 +70,7 @@ virologist = Agent(
* Secondary condition codes
Document all findings using proper medical coding standards and include rationale for code selection.""",
- llm=model,
+ model_name="ollama/llama3.2",
max_loops=1,
)
@@ -98,7 +95,7 @@ internist = Agent(
- Include hierarchical condition category (HCC) codes where applicable
Document supporting evidence for each code selected.""",
- llm=model,
+ model_name="ollama/llama3.2",
max_loops=1,
)
@@ -129,7 +126,7 @@ medical_coder = Agent(
3. Symptom Codes
4. Complication Codes
5. Coding Notes""",
- llm=model,
+ model_name="ollama/llama3.2",
max_loops=1,
)
@@ -157,7 +154,7 @@ synthesizer = Agent(
- Documentation improvements needed
Include confidence levels and evidence quality for all diagnoses and codes.""",
- llm=model,
+ model_name="ollama/llama3.2",
max_loops=1,
)
From 5a9b56223edb60a4e5a5b4cb18136de362f8497c Mon Sep 17 00:00:00 2001
From: Kye Gomez <kye@swarms.world>
Date: Fri, 16 May 2025 22:44:41 -0700
Subject: [PATCH 3/5] cerebas example md
---
cerebas_example.py | 13 ++++
docs/mkdocs.yml | 1 +
docs/swarms/models/cerebas_example.md | 86 +++++++++++++++++++++++++++
3 files changed, 100 insertions(+)
create mode 100644 cerebas_example.py
create mode 100644 docs/swarms/models/cerebas_example.md
diff --git a/cerebas_example.py b/cerebas_example.py
new file mode 100644
index 00000000..c42a75ab
--- /dev/null
+++ b/cerebas_example.py
@@ -0,0 +1,13 @@
+from swarms.structs.agent import Agent
+
+agent = Agent(
+ agent_name="Financial-Analysis-Agent",
+ agent_description="Personal finance advisor agent",
+ max_loops=4,
+ model_name="cerebras/llama3-70b-instruct",
+ dynamic_temperature_enabled=True,
+ interactive=False,
+ output_type="all",
+)
+
+agent.run("Conduct an analysis of the best real undervalued ETFs")
diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml
index 5c379fc2..062c93c1 100644
--- a/docs/mkdocs.yml
+++ b/docs/mkdocs.yml
@@ -347,6 +347,7 @@ nav:
- OpenAIChat: "swarms/models/openai.md"
- OpenAIFunctionCaller: "swarms/models/openai_function_caller.md"
- Groq: "swarms/models/groq.md"
+ - Cerebras: "swarms/models/cerebas_example.md"
- MultiModal Models:
- BaseMultiModalModel: "swarms/models/base_multimodal_model.md"
- Multi Modal Models Available: "swarms/models/multimodal_models.md"
diff --git a/docs/swarms/models/cerebas_example.md b/docs/swarms/models/cerebas_example.md
new file mode 100644
index 00000000..44134e84
--- /dev/null
+++ b/docs/swarms/models/cerebas_example.md
@@ -0,0 +1,86 @@
+# Using Cerebras LLaMA with Swarms
+
+This guide demonstrates how to create and use an AI agent powered by the Cerebras LLaMA 3 70B model using the Swarms framework.
+
+## Prerequisites
+
+- Python 3.7+
+- Swarms library installed (`pip install swarms`)
+
+## Step-by-Step Guide
+
+### 1. Import Required Module
+
+```python
+from swarms.structs.agent import Agent
+```
+
+This imports the `Agent` class from Swarms, which is the core component for creating AI agents.
+
+### 2. Create an Agent Instance
+
+```python
+agent = Agent(
+ agent_name="Financial-Analysis-Agent",
+ agent_description="Personal finance advisor agent",
+ max_loops=4,
+ model_name="cerebras/llama3-70b-instruct",
+ dynamic_temperature_enabled=True,
+ interactive=False,
+ output_type="all",
+)
+```
+
+Let's break down each parameter:
+
+- `agent_name`: A descriptive name for your agent (here, "Financial-Analysis-Agent")
+
+- `agent_description`: A brief description of the agent's purpose
+
+- `max_loops`: Maximum number of interaction loops the agent can perform (set to 4)
+
+- `model_name`: Specifies the Cerebras LLaMA 3 70B model to use
+
+- `dynamic_temperature_enabled`: Enables dynamic adjustment of temperature for varied responses
+
+- `interactive`: When False, runs without requiring user interaction
+
+- `output_type`: Set to "all" to return complete response information
+
+### 3. Run the Agent
+
+```python
+agent.run("Conduct an analysis of the best real undervalued ETFs")
+```
+
+This command:
+
+1. Activates the agent
+
+2. Processes the given prompt about ETF analysis
+
+3. Returns the analysis based on the model's knowledge
+
+## Notes
+
+- The Cerebras LLaMA 3 70B model is a powerful language model suitable for complex analysis tasks
+
+- The agent can be customized further with additional parameters
+
+- The `max_loops=4` setting prevents infinite loops while allowing sufficient processing depth
+
+- Setting `interactive=False` makes the agent run autonomously without user intervention
+
+## Example Output
+
+The agent will provide a detailed analysis of undervalued ETFs, including:
+
+- Market analysis
+
+- Performance metrics
+
+- Risk assessment
+
+- Investment recommendations
+
+Note: Actual output will vary based on current market conditions and the model's training data.
\ No newline at end of file
From f21272930f9afeaf81bc88fafbdb8e9da7e5d9f1 Mon Sep 17 00:00:00 2001
From: Kye Gomez <kye@swarms.world>
Date: Fri, 16 May 2025 22:55:04 -0700
Subject: [PATCH 4/5] cerebras
---
docs/mkdocs.yml | 2 +-
docs/swarms/models/{cerebas_example.md => cerebras.md} | 3 +++
2 files changed, 4 insertions(+), 1 deletion(-)
rename docs/swarms/models/{cerebas_example.md => cerebras.md} (96%)
diff --git a/docs/mkdocs.yml b/docs/mkdocs.yml
index 062c93c1..faf1f661 100644
--- a/docs/mkdocs.yml
+++ b/docs/mkdocs.yml
@@ -347,7 +347,7 @@ nav:
- OpenAIChat: "swarms/models/openai.md"
- OpenAIFunctionCaller: "swarms/models/openai_function_caller.md"
- Groq: "swarms/models/groq.md"
- - Cerebras: "swarms/models/cerebas_example.md"
+ - Cerebras: "swarms/models/cerebras.md"
- MultiModal Models:
- BaseMultiModalModel: "swarms/models/base_multimodal_model.md"
- Multi Modal Models Available: "swarms/models/multimodal_models.md"
diff --git a/docs/swarms/models/cerebas_example.md b/docs/swarms/models/cerebras.md
similarity index 96%
rename from docs/swarms/models/cerebas_example.md
rename to docs/swarms/models/cerebras.md
index 44134e84..8c544cb2 100644
--- a/docs/swarms/models/cerebas_example.md
+++ b/docs/swarms/models/cerebras.md
@@ -5,8 +5,11 @@ This guide demonstrates how to create and use an AI agent powered by the Cerebra
## Prerequisites
- Python 3.7+
+
- Swarms library installed (`pip install swarms`)
+- Set your ENV key `CEREBRAS_API_KEY`
+
## Step-by-Step Guide
### 1. Import Required Module
From 103952a5c768b29e9d06405e4b364b92593d54a1 Mon Sep 17 00:00:00 2001
From: Kye Gomez <kye@swarms.world>
Date: Fri, 16 May 2025 23:06:00 -0700
Subject: [PATCH 5/5] [fix][remove agent.agent_id and just agent.id
---
examples/4o_mini_demo.py | 10 +++++-----
swarms/structs/agent.py | 4 +---
2 files changed, 6 insertions(+), 8 deletions(-)
diff --git a/examples/4o_mini_demo.py b/examples/4o_mini_demo.py
index 04f54140..90b40d0a 100644
--- a/examples/4o_mini_demo.py
+++ b/examples/4o_mini_demo.py
@@ -46,7 +46,7 @@ chief_medical_officer = Agent(
""",
- model_name="gpt-4o-mini",
+ model_name="gpt-4o-mini",
max_loops=1,
)
@@ -70,7 +70,7 @@ virologist = Agent(
* Secondary condition codes
Document all findings using proper medical coding standards and include rationale for code selection.""",
- model_name="gpt-4o-mini",
+ model_name="gpt-4o-mini",
max_loops=1,
)
@@ -95,7 +95,7 @@ internist = Agent(
- Include hierarchical condition category (HCC) codes where applicable
Document supporting evidence for each code selected.""",
- model_name="gpt-4o-mini",
+ model_name="gpt-4o-mini",
max_loops=1,
)
@@ -126,7 +126,7 @@ medical_coder = Agent(
3. Symptom Codes
4. Complication Codes
5. Coding Notes""",
- model_name="gpt-4o-mini",
+ model_name="gpt-4o-mini",
max_loops=1,
)
@@ -154,7 +154,7 @@ synthesizer = Agent(
- Documentation improvements needed
Include confidence levels and evidence quality for all diagnoses and codes.""",
- model_name="gpt-4o-mini",
+ model_name="gpt-4o-mini",
max_loops=1,
)
diff --git a/swarms/structs/agent.py b/swarms/structs/agent.py
index 2e795b7e..a38691b2 100644
--- a/swarms/structs/agent.py
+++ b/swarms/structs/agent.py
@@ -279,7 +279,6 @@ class Agent:
def __init__(
self,
- agent_id: Optional[str] = agent_id(),
id: Optional[str] = agent_id(),
llm: Optional[Any] = None,
template: Optional[str] = None,
@@ -403,7 +402,6 @@ class Agent:
**kwargs,
):
# super().__init__(*args, **kwargs)
- self.agent_id = agent_id
self.id = id
self.llm = llm
self.template = template
@@ -2270,7 +2268,7 @@ class Agent:
time=time.time(),
tokens=total_tokens,
response=AgentChatCompletionResponse(
- id=self.agent_id,
+ id=self.id,
agent_name=self.agent_name,
object="chat.completion",
choices=ChatCompletionResponseChoice(