Update app.py
Browse files
app.py
CHANGED
@@ -5,13 +5,12 @@ import asyncio
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import json
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# Replace with your Modal API endpoint URL
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MODAL_API_ENDPOINT = "https://blastingneurons--collective-hive-backend-orchestrate-hive-api.modal.run"
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# Helper function to format chat history for Gradio's 'messages' type
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def format_chat_history_for_gradio(log_entries: list[dict]) -> list[dict]:
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formatted_messages = []
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for entry in log_entries:
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# Default to 'System' if agent name is not found
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role = entry.get("agent", "System")
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content = entry.get("text", "")
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formatted_messages.append({"role": role, "content": content})
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@@ -20,13 +19,11 @@ def format_chat_history_for_gradio(log_entries: list[dict]) -> list[dict]:
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async def call_modal_backend(problem_input: str, complexity: int):
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full_chat_history = []
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# Initialize all outputs with default values for the first yield
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current_status = "Connecting to Hive..."
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current_solution = ""
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current_confidence = ""
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current_minority_opinions = ""
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# First yield to clear previous state and show connecting message
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yield (
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current_status,
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format_chat_history_for_gradio([]),
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@@ -36,17 +33,16 @@ async def call_modal_backend(problem_input: str, complexity: int):
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)
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try:
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async with httpx.AsyncClient(timeout=600.0) as client:
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# Make sure to send complexity if your Modal backend expects it
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async with client.stream("POST", MODAL_API_ENDPOINT, json={"problem": problem_input, "complexity": complexity}) as response:
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response.raise_for_status()
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buffer = ""
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async for chunk in response.aiter_bytes():
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buffer += chunk.decode('utf-8')
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while "\n" in buffer:
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line, buffer = buffer.split("\n", 1)
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if not line.strip(): continue
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try:
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data = json.loads(line)
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event_type = data.get("event")
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@@ -55,23 +51,21 @@ async def call_modal_backend(problem_input: str, complexity: int):
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current_status = data["data"]
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elif event_type == "chat_update":
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full_chat_history.append(data["data"])
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current_status = "In Progress..."
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elif event_type == "final_solution":
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current_status = "Solution Complete!"
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current_solution = data["solution"]
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current_confidence = data["confidence"]
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current_minority_opinions = data["minority_opinions"]
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# Yield final state and then return to end the generator
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yield (
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current_status,
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format_chat_history_for_gradio(full_chat_history + [{"
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current_solution,
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current_confidence,
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current_minority_opinions
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)
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return
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# Yield the current state of all outputs after processing each event
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yield (
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current_status,
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format_chat_history_for_gradio(full_chat_history),
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@@ -82,27 +76,25 @@ async def call_modal_backend(problem_input: str, complexity: int):
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except json.JSONDecodeError as e:
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print(f"JSON Decode Error: {e} in line: {line}")
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# Handle incomplete JSON chunks, perhaps buffer and process when a full line is received
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# For robustness, you might yield an error status here too
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current_status = f"Error decoding: {e}"
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yield (current_status, format_chat_history_for_gradio(full_chat_history), current_solution, current_confidence, current_minority_opinions)
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except Exception as e:
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print(f"Error processing event: {e}, Data: {data}")
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current_status = f"
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yield (current_status, format_chat_history_for_gradio(full_chat_history), current_solution, current_confidence, current_minority_opinions)
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return # Exit on critical error
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except httpx.HTTPStatusError as e:
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current_status = f"HTTP Error: {e.response.status_code}
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print(current_status)
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except httpx.RequestError as e:
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current_status = f"Request Error: Could not connect to Modal backend: {e}"
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print(current_status)
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except Exception as e:
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current_status = f"An unexpected error occurred: {e}"
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print(current_status)
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# Final yield in case of errors or unexpected termination
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yield (current_status, format_chat_history_for_gradio(full_chat_history), current_solution, current_confidence, current_minority_opinions)
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import json
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# Replace with your Modal API endpoint URL
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MODAL_API_ENDPOINT = "https://blastingneurons--collective-hive-backend-orchestrate-hive-api.modal.run"
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# Helper function to format chat history for Gradio's 'messages' type
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def format_chat_history_for_gradio(log_entries: list[dict]) -> list[dict]:
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formatted_messages = []
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for entry in log_entries:
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role = entry.get("agent", "System")
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content = entry.get("text", "")
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formatted_messages.append({"role": role, "content": content})
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async def call_modal_backend(problem_input: str, complexity: int):
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full_chat_history = []
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current_status = "Connecting to Hive..."
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current_solution = ""
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current_confidence = ""
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current_minority_opinions = ""
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yield (
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current_status,
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format_chat_history_for_gradio([]),
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)
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try:
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async with httpx.AsyncClient(timeout=600.0) as client:
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async with client.stream("POST", MODAL_API_ENDPOINT, json={"problem": problem_input, "complexity": complexity}) as response:
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response.raise_for_status()
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buffer = ""
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async for chunk in response.aiter_bytes():
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buffer += chunk.decode('utf-8')
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while "\n" in buffer:
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line, buffer = buffer.split("\n", 1)
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if not line.strip(): continue
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try:
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data = json.loads(line)
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event_type = data.get("event")
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current_status = data["data"]
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elif event_type == "chat_update":
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full_chat_history.append(data["data"])
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current_status = "In Progress..."
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elif event_type == "final_solution":
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current_status = "Solution Complete!"
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current_solution = data["solution"]
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current_confidence = data["confidence"]
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current_minority_opinions = data["minority_opinions"]
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yield (
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current_status,
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format_chat_history_for_gradio(full_chat_history + [{"role": "System", "content": "Final solution synthesized."}]),
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current_solution,
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current_confidence,
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current_minority_opinions
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)
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return
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yield (
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current_status,
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format_chat_history_for_gradio(full_chat_history),
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except json.JSONDecodeError as e:
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print(f"JSON Decode Error: {e} in line: {line}")
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current_status = f"Error decoding: {e}"
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yield (current_status, format_chat_history_for_gradio(full_chat_history), current_solution, current_confidence, current_minority_opinions)
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# Do not return here if you want to keep trying to parse subsequent chunks
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except Exception as e:
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print(f"Error processing event: {e}, Data: {data}")
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current_status = f"An internal error occurred: {e}"
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yield (current_status, format_chat_history_for_gradio(full_chat_history), current_solution, current_confidence, current_minority_opinions)
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return # Exit on critical error
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except httpx.HTTPStatusError as e:
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current_status = f"HTTP Error from Modal backend: {e.response.status_code}"
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print(current_status)
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except httpx.RequestError as e:
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current_status = f"Request Error: Could not connect to Modal backend: {e}"
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print(current_status)
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except Exception as e:
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current_status = f"An unexpected error occurred during API call: {e}"
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print(current_status)
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yield (current_status, format_chat_history_for_gradio(full_chat_history), current_solution, current_confidence, current_minority_opinions)
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